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ORCIDPercy Liang
Person information
- affiliation: Stanford University, Computer Science Department
- award (2019): Presidential Early Career Award for Scientists and Engineers
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Books and Theses
- 2011
[b1]Percy Liang:
Learning Dependency-Based Compositional Semantics. University of California, Berkeley, USA, 2011
Journal Articles
- 2022
- [j10]Pang Wei Koh
, Jacob Steinhardt, Percy Liang:
Stronger data poisoning attacks break data sanitization defenses. Mach. Learn. 111(1): 1-47 (2022) - [j9]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. Trans. Mach. Learn. Res. 2022 (2022) - 2020
- [j8]Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H. Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Andrew Wolfe, Abby Wray, Yuchen Zhang, Alexander Zotov:
Task-Oriented Dialogue as Dataflow Synthesis. Trans. Assoc. Comput. Linguistics 8: 556-571 (2020) - 2019
- [j7]Kensen Shi, Jacob Steinhardt, Percy Liang:
FrAngel: component-based synthesis with control structures. Proc. ACM Program. Lang. 3(POPL): 73:1-73:29 (2019) - 2018
- [j6]Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang:
Generating Sentences by Editing Prototypes. Trans. Assoc. Comput. Linguistics 6: 437-450 (2018) - [j5]Fereshte Khani, Noah D. Goodman, Percy Liang:
Planning, Inference, and Pragmatics in Sequential Language Games. Trans. Assoc. Comput. Linguistics 6: 543-555 (2018) - 2016
- [j4]Percy Liang:
Learning executable semantic parsers for natural language understanding. Commun. ACM 59(9): 68-76 (2016) - 2015
- [j3]Jonathan Berant, Percy Liang:
Imitation Learning of Agenda-based Semantic Parsers. Trans. Assoc. Comput. Linguistics 3: 545-558 (2015) - 2014
- [j2]Percy Liang:
Talking to computers in natural language. XRDS 21(1): 18-21 (2014) - 2013
- [j1]Percy Liang, Michael I. Jordan, Dan Klein:
Learning Dependency-Based Compositional Semantics. Comput. Linguistics 39(2): 389-446 (2013)
Conference and Workshop Papers
- 2024
- [c192]Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah:
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. AAAI 2024: 22021-22030 - 2023
- [c191]Nelson F. Liu, Ananya Kumar, Percy Liang, Robin Jia:
Are Sample-Efficient NLP Models More Robust? ACL (2) 2023: 1689-1709 - [c190]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. ACL (Findings) 2023: 7479-7498 - [c189]John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang:
Backpack Language Models. ACL (1) 2023: 9103-9125 - [c188]Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis:
Contrastive Decoding: Open-ended Text Generation as Optimization. ACL (1) 2023: 12286-12312 - [c187]Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang:
Do Question Answering Modeling Improvements Hold Across Benchmarks? ACL (1) 2023: 13186-13218 - [c186]Nelson F. Liu, Tianyi Zhang, Percy Liang:
Evaluating Verifiability in Generative Search Engines. EMNLP (Findings) 2023: 7001-7025 - [c185]Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh:
No, to the Right: Online Language Corrections for Robotic Manipulation via Shared Autonomy. HRI 2023: 93-101 - [c184]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. ICLR 2023 - [c183]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Study on Representation Learning. ICLR 2023 - [c182]Steven Cao, Percy Liang, Gregory Valiant:
One-sided Matrix Completion from Two Observations Per Row. ICML 2023: 3599-3624 - [c181]Yann Dubois, Tatsunori Hashimoto, Percy Liang:
Evaluating Self-Supervised Learning via Risk Decomposition. ICML 2023: 8779-8820 - [c180]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. ICML 2023: 10800-10834 - [c179]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? ICML 2023: 29971-30004 - [c178]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Beidi Chen, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU. ICML 2023: 31094-31116 - [c177]Jue Wang, Yucheng Lu, Binhang Yuan, Beidi Chen, Percy Liang, Christopher De Sa, Christopher Ré, Ce Zhang:
CocktailSGD: Fine-tuning Foundation Models over 500Mbps Networks. ICML 2023: 36058-36076 - [c176]Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Richard James, Jure Leskovec, Percy Liang, Mike Lewis, Luke Zettlemoyer, Wen-Tau Yih:
Retrieval-Augmented Multimodal Language Modeling. ICML 2023: 39755-39769 - [c175]Yann Dubois, Chen Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. NeurIPS 2023 - [c174]Qian Huang, Hongyu Ren, Peng Chen, Gregor Krzmanc, Daniel Zeng, Percy Liang, Jure Leskovec:
PRODIGY: Enabling In-context Learning Over Graphs. NeurIPS 2023 - [c173]Qian Huang, Eric Zelikman, Sarah Chen, Yuhuai Wu, Gregory Valiant, Percy Liang:
Lexinvariant Language Models. NeurIPS 2023 - [c172]Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Fei-Fei Li, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-to-Image Models. NeurIPS 2023 - [c171]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models. NeurIPS 2023 - [c170]Connor Toups, Rishi Bommasani, Kathleen Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. NeurIPS 2023 - [c169]Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu:
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. NeurIPS 2023 - [c168]Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang:
Data Selection for Language Models via Importance Resampling. NeurIPS 2023 - [c167]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. Robotics: Science and Systems 2023 - [c166]Joon Sung Park, Joseph C. O'Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein:
Generative Agents: Interactive Simulacra of Human Behavior. UIST 2023: 2:1-2:22 - 2022
- [c165]Michihiro Yasunaga, Jure Leskovec, Percy Liang:
LinkBERT: Pretraining Language Models with Document Links. ACL (1) 2022: 8003-8016 - [c164]Mina Lee, Percy Liang, Qian Yang:
CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities. CHI 2022: 388:1-388:19 - [c163]John Hewitt, Christopher D. Manning, Percy Liang:
Truncation Sampling as Language Model Desmoothing. EMNLP (Findings) 2022: 3414-3427 - [c162]Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec:
GreaseLM: Graph REASoning Enhanced Language Models. ICLR 2022 - [c161]Ananya Kumar, Aditi Raghunathan, Robbie Matthew Jones, Tengyu Ma, Percy Liang:
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution. ICLR 2022 - [c160]Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto:
Large Language Models Can Be Strong Differentially Private Learners. ICLR 2022 - [c159]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c158]Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma:
An Explanation of In-context Learning as Implicit Bayesian Inference. ICLR 2022 - [c157]Kendrick Shen, Robbie M. Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang:
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. ICML 2022: 19847-19878 - [c156]Chris Donahue, John Thickstun, Percy Liang:
Melody transcription via generative pre-training. ISMIR 2022: 485-492 - [c155]Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant:
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. NeurIPS 2022 - [c154]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? NeurIPS 2022 - [c153]Yann Dubois, Stefano Ermon, Tatsunori B. Hashimoto, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. NeurIPS 2022 - [c152]Xiang Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. NeurIPS 2022 - [c151]Yuhuai Wu, Felix Li, Percy Liang:
Insights into Pre-training via Simpler Synthetic Tasks. NeurIPS 2022 - [c150]Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec:
Deep Bidirectional Language-Knowledge Graph Pretraining. NeurIPS 2022 - [c149]Binhang Yuan, Yongjun He, Jared Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang:
Decentralized Training of Foundation Models in Heterogeneous Environments. NeurIPS 2022 - [c148]Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan:
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift. UAI 2022: 1041-1051 - [c147]Joon Sung Park, Lindsay Popowski, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein:
Social Simulacra: Creating Populated Prototypes for Social Computing Systems. UIST 2022: 74:1-74:18 - 2021
- [c146]Xiang Lisa Li, Percy Liang:
Prefix-Tuning: Optimizing Continuous Prompts for Generation. ACL/IJCNLP (1) 2021: 4582-4597 - [c145]Siddharth Karamcheti, Megha Srivastava, Percy Liang, Dorsa Sadigh:
LILA: Language-Informed Latent Actions. CoRL 2021: 1379-1390 - [c144]John Hewitt, Kawin Ethayarajh, Percy Liang, Christopher D. Manning:
Conditional probing: measuring usable information beyond a baseline. EMNLP (1) 2021: 1626-1639 - [c143]Michihiro Yasunaga, Jure Leskovec, Percy Liang:
LM-Critic: Language Models for Unsupervised Grammatical Error Correction. EMNLP (1) 2021: 7752-7763 - [c142]Fereshte Khani, Percy Liang:
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately. FAccT 2021: 196-205 - [c141]Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang:
Selective Classification Can Magnify Disparities Across Groups. ICLR 2021 - [c140]Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang:
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness. ICLR 2021 - [c139]Jared Quincy Davis, Albert Gu, Krzysztof Choromanski, Tri Dao, Christopher Ré, Chelsea Finn, Percy Liang:
Catformer: Designing Stable Transformers via Sensitivity Analysis. ICML 2021: 2489-2499 - [c138]Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran S. Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML 2021: 5637-5664 - [c137]Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn:
Just Train Twice: Improving Group Robustness without Training Group Information. ICML 2021: 6781-6792 - [c136]Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn:
Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices. ICML 2021: 6925-6935 - [c135]John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt:
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. ICML 2021: 7721-7735 - [c134]Sang Michael Xie, Tengyu Ma, Percy Liang:
Composed Fine-Tuning: Freezing Pre-Trained Denoising Autoencoders for Improved Generalization. ICML 2021: 11424-11435 - [c133]Michihiro Yasunaga, Percy Liang:
Break-It-Fix-It: Unsupervised Learning for Program Repair. ICML 2021: 11941-11952 - [c132]Rodrigo Castellon, Chris Donahue, Percy Liang:
Codified audio language modeling learns useful representations for music information retrieval. ISMIR 2021: 88-96 - [c131]Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, Jure Leskovec:
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering. NAACL-HLT 2021: 535-546 - [c130]Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang:
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality. NAACL-HLT 2021: 4362-4379 - [c129]Yu Gu, Sue Kase, Michelle Vanni, Brian M. Sadler, Percy Liang, Xifeng Yan, Yu Su:
Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases. WWW 2021: 3477-3488 - 2020
- [c128]Shikhar Murty, Pang Wei Koh, Percy Liang:
ExpBERT: Representation Engineering with Natural Language Explanations. ACL 2020: 2106-2113 - [c127]Chris Donahue, Mina Lee, Percy Liang:
Enabling Language Models to Fill in the Blanks. ACL 2020: 2492-2501 - [c126]Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang:
Robust Encodings: A Framework for Combating Adversarial Typos. ACL 2020: 2752-2765 - [c125]Jesse Mu, Percy Liang, Noah D. Goodman:
Shaping Visual Representations with Language for Few-Shot Classification. ACL 2020: 4823-4830 - [c124]Amita Kamath, Robin Jia, Percy Liang:
Selective Question Answering under Domain Shift. ACL 2020: 5684-5696 - [c123]Benjamin Newman, John Hewitt, Percy Liang, Christopher D. Manning:
The EOS Decision and Length Extrapolation. BlackboxNLP@EMNLP 2020: 276-291 - [c122]John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher D. Manning:
RNNs can generate bounded hierarchical languages with optimal memory. EMNLP (1) 2020: 1978-2010 - [c121]Stephen Mussmann, Robin Jia, Percy Liang:
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks. EMNLP (Findings) 2020: 3400-3413 - [c120]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection via Proxy: Efficient Data Selection for Deep Learning. ICLR 2020 - [c119]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Strategies for Pre-training Graph Neural Networks. ICLR 2020 - [c118]Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Neural Networks. ICLR 2020 - [c117]Fereshte Khani, Percy Liang:
Feature Noise Induces Loss Discrepancy Across Groups. ICML 2020: 5209-5219 - [c116]Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang:
Concept Bottleneck Models. ICML 2020: 5338-5348 - [c115]Ananya Kumar, Tengyu Ma, Percy Liang:
Understanding Self-Training for Gradual Domain Adaptation. ICML 2020: 5468-5479 - [c114]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Understanding and Mitigating the Tradeoff between Robustness and Accuracy. ICML 2020: 7909-7919 - [c113]Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang:
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. ICML 2020: 8346-8356 - [c112]Megha Srivastava, Tatsunori B. Hashimoto, Percy Liang:
Robustness to Spurious Correlations via Human Annotations. ICML 2020: 9109-9119 - [c111]Michihiro Yasunaga, Percy Liang:
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback. ICML 2020: 10799-10808 - [c110]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. NeurIPS 2020 - [c109]Ray Li, Percy Liang, Stephen Mussmann:
A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree. SODA 2020: 102-121 - 2019
- [c108]Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson, Percy Liang:
Inferring Multidimensional Rates of Aging from Cross-Sectional Data. AISTATS 2019: 97-107 - [c107]Yuchen Zhang, Percy Liang:
Defending against Whitebox Adversarial Attacks via Randomized Discretization. AISTATS 2019: 684-693 - [c106]John Hewitt, Percy Liang:
Designing and Interpreting Probes with Control Tasks. EMNLP/IJCNLP (1) 2019: 2733-2743 - [c105]Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang:
Certified Robustness to Adversarial Word Substitutions. EMNLP/IJCNLP (1) 2019: 4127-4140 - [c104]Yonatan Oren, Shiori Sagawa, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Language Modeling. EMNLP/IJCNLP (1) 2019: 4226-4236 - [c103]Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, David L. Dill:
Learning a SAT Solver from Single-Bit Supervision. ICLR (Poster) 2019 - [c102]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. NAACL-HLT (1) 2019: 1689-1701 - [c101]He He, Nanyun Peng, Percy Liang:
Pun Generation with Surprise. NAACL-HLT (1) 2019: 1734-1744 - [c100]Ananya Kumar, Percy Liang, Tengyu Ma:
Verified Uncertainty Calibration. NeurIPS 2019: 3787-3798 - [c99]Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang:
On the Accuracy of Influence Functions for Measuring Group Effects. NeurIPS 2019: 5255-5265 - [c98]Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, John C. Duchi, Percy Liang:
Unlabeled Data Improves Adversarial Robustness. NeurIPS 2019: 11190-11201 - [c97]Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, Percy Liang:
SPoC: Search-based Pseudocode to Code. NeurIPS 2019: 11883-11894 - 2018
- [c96]Arun Tejasvi Chaganty, Stephen Mussmann, Percy Liang:
The price of debiasing automatic metrics in natural language evalaution. ACL (1) 2018: 643-653 - [c95]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. ACL (2) 2018: 784-789 - [c94]Braden Hancock, Paroma Varma, Stephanie Wang, Martin Bringmann, Percy Liang, Christopher Ré:
Training Classifiers with Natural Language Explanations. ACL (1) 2018: 1884-1895 - [c93]Stephen Mussmann, Percy Liang:
Generalized Binary Search For Split-Neighborly Problems. AISTATS 2018: 1561-1569 - [c92]Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning, Dan Jurafsky, Percy Liang:
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts. EMNLP 2018: 82-92 - [c91]Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer:
QuAC: Question Answering in Context. EMNLP 2018: 2174-2184 - [c90]He He, Derek Chen, Anusha Balakrishnan, Percy Liang:
Decoupling Strategy and Generation in Negotiation Dialogues. EMNLP 2018: 2333-2343 - [c89]Panupong Pasupat, Tian-Shun Jiang, Evan Zheran Liu, Kelvin Guu, Percy Liang:
Mapping natural language commands to web elements. EMNLP 2018: 4970-4976 - [c88]Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, Tianlin Shi, Percy Liang:
Reinforcement Learning on Web Interfaces using Workflow-Guided Exploration. ICLR (Poster) 2018 - [c87]Aditi Raghunathan, Jacob Steinhardt, Percy Liang:
Certified Defenses against Adversarial Examples. ICLR (Poster) 2018 - [c86]Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang:
Fairness Without Demographics in Repeated Loss Minimization. ICML 2018: 1934-1943 - [c85]Stephen Mussmann, Percy Liang:
On the Relationship between Data Efficiency and Error for Uncertainty Sampling. ICML 2018: 3671-3679 - [c84]Juncen Li, Robin Jia, He He, Percy Liang:
Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer. NAACL-HLT 2018: 1865-1874 - [c83]Stephen Mussmann, Percy Liang:
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss. NeurIPS 2018: 6955-6964 - [c82]Tatsunori B. Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang:
A Retrieve-and-Edit Framework for Predicting Structured Outputs. NeurIPS 2018: 10073-10083 - [c81]Aditi Raghunathan, Jacob Steinhardt, Percy Liang:
Semidefinite relaxations for certifying robustness to adversarial examples. NeurIPS 2018: 10900-10910 - [c80]Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang:
Active learning of points-to specifications. PLDI 2018: 678-692 - [c79]Vatsal Sharan, Sham M. Kakade, Percy Liang, Gregory Valiant:
Prediction with a short memory. STOC 2018: 1074-1087 - 2017
- [c78]Sida I. Wang, Samuel Ginn, Percy Liang, Christopher D. Manning:
Naturalizing a Programming Language via Interactive Learning. ACL (1) 2017: 929-938 - [c77]Kelvin Guu, Panupong Pasupat, Evan Zheran Liu, Percy Liang:
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood. ACL (1) 2017: 1051-1062 - [c76]He He, Anusha Balakrishnan, Mihail Eric, Percy Liang:
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. ACL (1) 2017: 1766-1776 - [c75]Yuchen Zhang, Percy Liang, Moses Charikar:
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. COLT 2017: 1980-2022 - [c74]Arun Tejasvi Chaganty, Ashwin Paranjape, Percy Liang, Christopher D. Manning:
Importance sampling for unbiased on-demand evaluation of knowledge base population. EMNLP 2017: 1038-1048 - [c73]Yuchen Zhang, Panupong Pasupat, Percy Liang:
Macro Grammars and Holistic Triggering for Efficient Semantic Parsing. EMNLP 2017: 1214-1223 - [c72]Robin Jia, Percy Liang:
Adversarial Examples for Evaluating Reading Comprehension Systems. EMNLP 2017: 2021-2031 - [c71]Pang Wei Koh, Percy Liang:
Understanding Black-box Predictions via Influence Functions. ICML 2017: 1885-1894 - [c70]Daniel Selsam, Percy Liang, David L. Dill:
Developing Bug-Free Machine Learning Systems With Formal Mathematics. ICML 2017: 3047-3056 - [c69]Tianlin Shi, Andrej Karpathy, Linxi Fan, Jonathan Hernandez, Percy Liang:
World of Bits: An Open-Domain Platform for Web-Based Agents. ICML 2017: 3135-3144 - [c68]Yuchen Zhang, Percy Liang, Martin J. Wainwright:
Convexified Convolutional Neural Networks. ICML 2017: 4044-4053 - [c67]Vatsal Sharan, Sham M. Kakade, Percy Liang, Gregory Valiant:
Learning Overcomplete HMMs. NIPS 2017: 940-949 - [c66]Jacob Steinhardt, Pang Wei Koh, Percy Liang:
Certified Defenses for Data Poisoning Attacks. NIPS 2017: 3517-3529 - [c65]Tatsunori B. Hashimoto, Percy Liang, John C. Duchi:
Unsupervised Transformation Learning via Convex Relaxations. NIPS 2017: 6875-6883 - [c64]Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang:
Synthesizing program input grammars. PLDI 2017: 95-110 - 2016
- [c63]Arun Tejasvi Chaganty, Percy Liang:
How Much is 131 Million Dollars? Putting Numbers in Perspective with Compositional Descriptions. ACL (1) 2016 - [c62]Robin Jia, Percy Liang:
Data Recombination for Neural Semantic Parsing. ACL (1) 2016 - [c61]Fereshte Khani, Martin C. Rinard, Percy Liang:
Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings. ACL (1) 2016 - [c60]Reginald Long, Panupong Pasupat, Percy Liang:
Simpler Context-Dependent Logical Forms via Model Projections. ACL (1) 2016 - [c59]Panupong Pasupat, Percy Liang:
Inferring Logical Forms From Denotations. ACL (1) 2016 - [c58]Sida I. Wang, Percy Liang, Christopher D. Manning:
Learning Language Games through Interaction. ACL (1) 2016 - [c57]Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang:
SQuAD: 100, 000+ Questions for Machine Comprehension of Text. EMNLP 2016: 2383-2392 - [c56]Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang:
Estimation from Indirect Supervision with Linear Moments. ICML 2016: 2568-2577 - [c55]Jacob Steinhardt, Percy Liang:
Unsupervised Risk Estimation Using Only Conditional Independence Structure. NIPS 2016: 3657-3665 - 2015
- [c54]Dipendra Kumar Misra, Kejia Tao, Percy Liang, Ashutosh Saxena:
Environment-Driven Lexicon Induction for High-Level Instructions. ACL (1) 2015: 992-1002 - [c53]Yushi Wang, Jonathan Berant, Percy Liang:
Building a Semantic Parser Overnight. ACL (1) 2015: 1332-1342 - [c52]Panupong Pasupat, Percy Liang:
Compositional Semantic Parsing on Semi-Structured Tables. ACL (1) 2015: 1470-1480 - [c51]Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang:
Tensor Factorization via Matrix Factorization. AISTATS 2015 - [c50]Tianlin Shi, Jacob Steinhardt, Percy Liang:
Learning Where to Sample in Structured Prediction. AISTATS 2015 - [c49]Kelvin Guu, John Miller, Percy Liang:
Traversing Knowledge Graphs in Vector Space. EMNLP 2015: 318-327 - [c48]Jacob Steinhardt, Percy Liang:
Reified Context Models. ICML 2015: 1043-1052 - [c47]Jacob Steinhardt, Percy Liang:
Learning Fast-Mixing Models for Structured Prediction. ICML 2015: 1063-1072 - [c46]Sida Wang, Arun Tejasvi Chaganty, Percy Liang:
Estimating Mixture Models via Mixtures of Polynomials. NIPS 2015: 487-495 - [c45]Jacob Steinhardt, Percy Liang:
Learning with Relaxed Supervision. NIPS 2015: 2827-2835 - [c44]Keenon Werling, Arun Tejasvi Chaganty, Percy Liang, Christopher D. Manning:
On-the-Job Learning with Bayesian Decision Theory. NIPS 2015: 3465-3473 - [c43]Volodymyr Kuleshov, Percy Liang:
Calibrated Structured Prediction. NIPS 2015: 3474-3482 - 2014
- [c42]Panupong Pasupat, Percy Liang:
Zero-shot Entity Extraction from Web Pages. ACL (1) 2014: 391-401 - [c41]Jonathan Berant, Percy Liang:
Semantic Parsing via Paraphrasing. ACL (1) 2014: 1415-1425 - [c40]Vignesh Ramanathan, Armand Joulin, Percy Liang, Li Fei-Fei:
Linking People in Videos with "Their" Names Using Coreference Resolution. ECCV (1) 2014: 95-110 - [c39]Jacob Steinhardt, Percy Liang:
Filtering with Abstract Particles. ICML 2014: 727-735 - [c38]Jacob Steinhardt, Percy Liang:
Adaptivity and Optimism: An Improved Exponentiated Gradient Algorithm. ICML 2014: 1593-1601 - [c37]Arun Tejasvi Chaganty, Percy Liang:
Estimating Latent-Variable Graphical Models using Moments and Likelihoods. ICML 2014: 1872-1880 - [c36]Stefan Wager, William Fithian, Sida Wang, Percy Liang:
Altitude Training: Strong Bounds for Single-Layer Dropout. NIPS 2014: 100-108 - [c35]Roy Frostig, Sida Wang, Percy Liang, Christopher D. Manning:
Simple MAP Inference via Low-Rank Relaxations. NIPS 2014: 3077-3085 - [c34]Sida I. Wang, Roy Frostig, Percy Liang, Christopher D. Manning:
Relaxations for inference in restricted Boltzmann machines. ICLR (Workshop) 2014 - 2013
- [c33]Sida Wang, Mengqiu Wang, Stefan Wager, Percy Liang, Christopher D. Manning:
Feature Noising for Log-Linear Structured Prediction. EMNLP 2013: 1170-1179 - [c32]Jonathan Berant, Andrew Chou, Roy Frostig, Percy Liang:
Semantic Parsing on Freebase from Question-Answer Pairs. EMNLP 2013: 1533-1544 - [c31]Rahul Sharma, Saurabh Gupta, Bharath Hariharan, Alex Aiken, Percy Liang, Aditya V. Nori:
A Data Driven Approach for Algebraic Loop Invariants. ESOP 2013: 574-592 - [c30]Vignesh Ramanathan, Percy Liang, Li Fei-Fei:
Video Event Understanding Using Natural Language Descriptions. ICCV 2013: 905-912 - [c29]Arun Tejasvi Chaganty, Percy Liang:
Spectral Experts for Estimating Mixtures of Linear Regressions. ICML (3) 2013: 1040-1048 - [c28]Stefan Wager, Sida Wang, Percy Liang:
Dropout Training as Adaptive Regularization. NIPS 2013: 351-359 - 2012
- [c27]Daniel J. Hsu, Sham M. Kakade, Percy Liang:
Identifiability and Unmixing of Latent Parse Trees. NIPS 2012: 1520-1528 - 2011
- [c26]Percy Liang, Michael I. Jordan, Dan Klein:
Learning Dependency-Based Compositional Semantics. ACL 2011: 590-599 - [c25]Percy Liang, Mayur Naik:
Scaling abstraction refinement via pruning. PLDI 2011: 590-601 - [c24]Percy Liang, Omer Tripp, Mayur Naik:
Learning minimal abstractions. POPL 2011: 31-42 - 2010
- [c23]Dave Golland, Percy Liang, Dan Klein:
A Game-Theoretic Approach to Generating Spatial Descriptions. EMNLP 2010: 410-419 - [c22]Gabor Angeli, Percy Liang, Dan Klein:
A Simple Domain-Independent Probabilistic Approach to Generation. EMNLP 2010: 502-512 - [c21]Percy Liang, Michael I. Jordan, Dan Klein:
Learning Programs: A Hierarchical Bayesian Approach. ICML 2010: 639-646 - [c20]Percy Liang, Nati Srebro:
On the Interaction between Norm and Dimensionality: Multiple Regimes in Learning. ICML 2010: 647-654 - [c19]Percy Liang, Michael I. Jordan, Dan Klein:
Type-Based MCMC. HLT-NAACL 2010: 573-581 - [c18]Percy Liang, Omer Tripp, Mayur Naik, Mooly Sagiv:
A dynamic evaluation of the precision of static heap abstractions. OOPSLA 2010: 411-427 - 2009
- [c17]Percy Liang, Michael I. Jordan, Dan Klein:
Learning Semantic Correspondences with Less Supervision. ACL/IJCNLP 2009: 91-99 - [c16]Percy Liang, Michael I. Jordan, Dan Klein:
Learning from measurements in exponential families. ICML 2009: 641-648 - [c15]Percy Liang, Dan Klein:
Online EM for Unsupervised Models. HLT-NAACL 2009: 611-619 - [c14]Percy Liang, Francis R. Bach, Guillaume Bouchard, Michael I. Jordan:
Asymptotically Optimal Regularization in Smooth Parametric Models. NIPS 2009: 1132-1140 - 2008
- [c13]Aria Haghighi, Percy Liang, Taylor Berg-Kirkpatrick, Dan Klein:
Learning Bilingual Lexicons from Monolingual Corpora. ACL 2008: 771-779 - [c12]Percy Liang, Dan Klein:
Analyzing the Errors of Unsupervised Learning. ACL 2008: 879-887 - [c11]Percy Liang, Michael I. Jordan:
An asymptotic analysis of generative, discriminative, and pseudolikelihood estimators. ICML 2008: 584-591 - [c10]Percy Liang, Hal Daumé III, Dan Klein:
Structure compilation: trading structure for features. ICML 2008: 592-599 - 2007
- [c9]Percy Liang, Slav Petrov, Michael I. Jordan, Dan Klein:
The Infinite PCFG Using Hierarchical Dirichlet Processes. EMNLP-CoNLL 2007: 688-697 - [c8]Alexandre Bouchard-Côté, Percy Liang, Thomas L. Griffiths, Dan Klein:
A Probabilistic Approach to Diachronic Phonology. EMNLP-CoNLL 2007: 887-896 - [c7]Percy Liang, Michael I. Jordan, Benjamin Taskar:
A permutation-augmented sampler for DP mixture models. ICML 2007: 545-552 - [c6]Alexandre Bouchard-Côté, Percy Liang, Thomas L. Griffiths, Dan Klein:
A Probabilistic Approach to Language Change. NIPS 2007: 169-176 - [c5]Percy Liang, Dan Klein, Michael I. Jordan:
Agreement-Based Learning. NIPS 2007: 913-920 - 2006
- [c4]Percy Liang, Alexandre Bouchard-Côté, Dan Klein, Benjamin Taskar:
An End-to-End Discriminative Approach to Machine Translation. ACL 2006 - [c3]Percy Liang, Benjamin Taskar, Dan Klein:
Alignment by Agreement. HLT-NAACL 2006 - 2005
- [c2]Michael Shilman, Percy Liang, Paul A. Viola:
Learning Non-Generative Grammatical Models for Document Analysis. ICCV 2005: 962-969 - [c1]Percy Liang, Mukund Narasimhan, Michael Shilman, Paul A. Viola:
Efficient Geometric Algorithms for Parsing in Two Dimensions. ICDAR 2005: 1172-1177
Editorship
- 2021
- [e2]Marc'Aurelio Ranzato, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual. 2021 [contents] - 2015
- [e1]Phil Blunsom, Shay B. Cohen, Paramveer S. Dhillon, Percy Liang:
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, VS@NAACL-HLT 2015, June 5, 2015, Denver, Colorado, USA. The Association for Computational Linguistics 2015, ISBN 978-1-941643-46-4 [contents]
Informal and Other Publications
- 2024
- [i191]John Hewitt, Sarah Chen, Lanruo Lora Xie, Edward Adams, Percy Liang, Christopher D. Manning:
Model Editing with Canonical Examples. CoRR abs/2402.06155 (2024) - [i190]Siddharth Karamcheti, Suraj Nair, Ashwin Balakrishna, Percy Liang, Thomas Kollar, Dorsa Sadigh:
Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models. CoRR abs/2402.07865 (2024) - [i189]Rishi Bommasani, Kevin Klyman, Shayne Longpre, Betty Xiong, Sayash Kapoor, Nestor Maslej, Arvind Narayanan, Percy Liang:
Foundation Model Transparency Reports. CoRR abs/2402.16268 (2024) - [i188]Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
A Safe Harbor for AI Evaluation and Red Teaming. CoRR abs/2403.04893 (2024) - [i187]Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
On the Societal Impact of Open Foundation Models. CoRR abs/2403.07918 (2024) - [i186]Elliot Bolton, Abhinav Venigalla, Michihiro Yasunaga, David Hall, Betty Xiong, Tony Lee, Roxana Daneshjou, Jonathan Frankle, Percy Liang, Michael Carbin, Christopher D. Manning:
BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text. CoRR abs/2403.18421 (2024) - 2023
- [i185]Yuchen Cui, Siddharth Karamcheti, Raj Palleti, Nidhya Shivakumar, Percy Liang, Dorsa Sadigh:
"No, to the Right" - Online Language Corrections for Robotic Manipulation via Shared Autonomy. CoRR abs/2301.02555 (2023) - [i184]Tianyi Zhang, Faisal Ladhak, Esin Durmus, Percy Liang, Kathleen R. McKeown, Tatsunori B. Hashimoto:
Benchmarking Large Language Models for News Summarization. CoRR abs/2301.13848 (2023) - [i183]Yann Dubois, Tatsunori Hashimoto, Percy Liang:
Evaluating Self-Supervised Learning via Risk Decomposition. CoRR abs/2302.03068 (2023) - [i182]Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang:
Data Selection for Language Models via Importance Resampling. CoRR abs/2302.03169 (2023) - [i181]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. CoRR abs/2302.11861 (2023) - [i180]Siddharth Karamcheti, Suraj Nair, Annie S. Chen, Thomas Kollar, Chelsea Finn, Dorsa Sadigh, Percy Liang:
Language-Driven Representation Learning for Robotics. CoRR abs/2302.12766 (2023) - [i179]Michael Sun, Ananya Kumar, Divyam Madaan, Percy Liang:
Improving Representational Continuity via Continued Pretraining. CoRR abs/2302.13289 (2023) - [i178]Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y. Fu, Zhiqiang Xie, Beidi Chen, Clark W. Barrett, Joseph E. Gonzalez, Percy Liang, Christopher Ré, Ion Stoica, Ce Zhang:
High-throughput Generative Inference of Large Language Models with a Single GPU. CoRR abs/2303.06865 (2023) - [i177]Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, Percy Liang:
Foundation Models and Fair Use. CoRR abs/2303.15715 (2023) - [i176]Rishi Bommasani, Dilara Soylu, Thomas I. Liao, Kathleen A. Creel, Percy Liang:
Ecosystem Graphs: The Social Footprint of Foundation Models. CoRR abs/2303.15772 (2023) - [i175]Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto:
Whose Opinions Do Language Models Reflect? CoRR abs/2303.17548 (2023) - [i174]Joon Sung Park, Joseph C. O'Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein:
Generative Agents: Interactive Simulacra of Human Behavior. CoRR abs/2304.03442 (2023) - [i173]Nelson F. Liu, Tianyi Zhang, Percy Liang:
Evaluating Verifiability in Generative Search Engines. CoRR abs/2304.09848 (2023) - [i172]Deepak Narayanan, Keshav Santhanam, Peter Henderson, Rishi Bommasani, Tony Lee, Percy Liang:
Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs. CoRR abs/2305.02440 (2023) - [i171]Sang Michael Xie, Hieu Pham, Xuanyi Dong, Nan Du, Hanxiao Liu, Yifeng Lu, Percy Liang, Quoc V. Le, Tengyu Ma, Adams Wei Yu:
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining. CoRR abs/2305.10429 (2023) - [i170]Qian Huang, Hongyu Ren, Peng Chen, Gregor Krzmanc, Daniel Zeng, Percy Liang, Jure Leskovec:
PRODIGY: Enabling In-context Learning Over Graphs. CoRR abs/2305.12600 (2023) - [i169]Hong Liu, Zhiyuan Li, David Hall, Percy Liang, Tengyu Ma:
Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training. CoRR abs/2305.14342 (2023) - [i168]Yann Dubois, Xuechen Li, Rohan Taori, Tianyi Zhang, Ishaan Gulrajani, Jimmy Ba, Carlos Guestrin, Percy Liang, Tatsunori B. Hashimoto:
AlpacaFarm: A Simulation Framework for Methods that Learn from Human Feedback. CoRR abs/2305.14387 (2023) - [i167]Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang:
Lexinvariant Language Models. CoRR abs/2305.16349 (2023) - [i166]John Hewitt, John Thickstun, Christopher D. Manning, Percy Liang:
Backpack Language Models. CoRR abs/2305.16765 (2023) - [i165]Yuhui Zhang, Michihiro Yasunaga, Zhengping Zhou, Jeff Z. HaoChen, James Zou, Percy Liang, Serena Yeung:
Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models. CoRR abs/2305.17311 (2023) - [i164]Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan:
Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment. CoRR abs/2306.03262 (2023) - [i163]Steven Cao, Percy Liang, Gregory Valiant:
One-sided Matrix Completion from Two Observations Per Row. CoRR abs/2306.04049 (2023) - [i162]John Thickstun, David Hall, Chris Donahue, Percy Liang:
Anticipatory Music Transformer. CoRR abs/2306.08620 (2023) - [i161]Eric Zelikman, Qian Huang, Percy Liang, Nick Haber, Noah D. Goodman:
Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness. CoRR abs/2306.10015 (2023) - [i160]Nelson F. Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, Percy Liang:
Lost in the Middle: How Language Models Use Long Contexts. CoRR abs/2307.03172 (2023) - [i159]Connor Toups, Rishi Bommasani, Kathleen A. Creel, Sarah H. Bana, Dan Jurafsky, Percy Liang:
Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes. CoRR abs/2307.05862 (2023) - [i158]Rohith Kuditipudi, John Thickstun, Tatsunori Hashimoto, Percy Liang:
Robust Distortion-free Watermarks for Language Models. CoRR abs/2307.15593 (2023) - [i157]Scott L. Fleming, Alejandro Lozano, William J. Haberkorn, Jenelle A. Jindal, Eduardo Pontes Reis, Rahul Thapa, Louis Blankemeier, Julian Z. Genkins, Ethan Steinberg, Ashwin Nayak, Birju S. Patel, Chia-Chun Chiang, Alison Callahan, Zepeng Huo, Sergios Gatidis, Scott J. Adams, Oluseyi Fayanju, Shreya J. Shah, Thomas Savage, Ethan Goh, Akshay S. Chaudhari, Nima Aghaeepour, Christopher D. Sharp, Michael A. Pfeffer, Percy Liang, Jonathan H. Chen, Keith E. Morse, Emma P. Brunskill, Jason A. Fries, Nigam H. Shah:
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records. CoRR abs/2308.14089 (2023) - [i156]Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou:
Large Language Models as Analogical Reasoners. CoRR abs/2310.01714 (2023) - [i155]Xiang Lisa Li, Vaishnavi Shrivastava, Siyan Li, Tatsunori Hashimoto, Percy Liang:
Benchmarking and Improving Generator-Validator Consistency of Language Models. CoRR abs/2310.01846 (2023) - [i154]Qian Huang, Jian Vora, Percy Liang, Jure Leskovec:
Benchmarking Large Language Models As AI Research Agents. CoRR abs/2310.03302 (2023) - [i153]Rishi Bommasani, Kevin Klyman, Shayne Longpre, Sayash Kapoor, Nestor Maslej, Betty Xiong, Daniel Zhang, Percy Liang:
The Foundation Model Transparency Index. CoRR abs/2310.12941 (2023) - [i152]Tony Lee, Michihiro Yasunaga, Chenlin Meng, Yifan Mai, Joon Sung Park, Agrim Gupta, Yunzhi Zhang, Deepak Narayanan, Hannah Benita Teufel, Marco Bellagente, Minguk Kang, Taesung Park, Jure Leskovec, Jun-Yan Zhu, Li Fei-Fei, Jiajun Wu, Stefano Ermon, Percy Liang:
Holistic Evaluation of Text-To-Image Models. CoRR abs/2311.04287 (2023) - [i151]Vaishnavi Shrivastava, Percy Liang, Ananya Kumar:
Llamas Know What GPTs Don't Show: Surrogate Models for Confidence Estimation. CoRR abs/2311.08877 (2023) - [i150]Chenchen Gu, Xiang Lisa Li, Percy Liang, Tatsunori Hashimoto:
On the Learnability of Watermarks for Language Models. CoRR abs/2312.04469 (2023) - 2022
- [i149]Mina Lee, Percy Liang, Qian Yang:
CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities. CoRR abs/2201.06796 (2022) - [i148]Xikun Zhang, Antoine Bosselut, Michihiro Yasunaga, Hongyu Ren, Percy Liang, Christopher D. Manning, Jure Leskovec:
GreaseLM: Graph REASoning Enhanced Language Models for Question Answering. CoRR abs/2201.08860 (2022) - [i147]Ananya Kumar, Aditi Raghunathan, Robbie Jones, Tengyu Ma, Percy Liang:
Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution. CoRR abs/2202.10054 (2022) - [i146]Michihiro Yasunaga, Jure Leskovec, Percy Liang:
LinkBERT: Pretraining Language Models with Document Links. CoRR abs/2203.15827 (2022) - [i145]Kendrick Shen, Robbie Jones, Ananya Kumar, Sang Michael Xie, Jeff Z. HaoChen, Tengyu Ma, Percy Liang:
Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation. CoRR abs/2204.00570 (2022) - [i144]Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, Tatsunori B. Hashimoto:
Diffusion-LM Improves Controllable Text Generation. CoRR abs/2205.14217 (2022) - [i143]Binhang Yuan, Yongjun He, Jared Quincy Davis, Tianyi Zhang, Tri Dao, Beidi Chen, Percy Liang, Christopher Ré, Ce Zhang:
Decentralized Training of Foundation Models in Heterogeneous Environments. CoRR abs/2206.01288 (2022) - [i142]Jason Wei, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph, Sebastian Borgeaud, Dani Yogatama, Maarten Bosma, Denny Zhou, Donald Metzler, Ed H. Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, William Fedus:
Emergent Abilities of Large Language Models. CoRR abs/2206.07682 (2022) - [i141]Yuhuai Wu, Felix Li, Percy Liang:
Insights into Pre-training via Simpler Synthetic Tasks. CoRR abs/2206.10139 (2022) - [i140]Shibani Santurkar, Yann Dubois, Rohan Taori, Percy Liang, Tatsunori Hashimoto:
Is a Caption Worth a Thousand Images? A Controlled Study for Representation Learning. CoRR abs/2207.07635 (2022) - [i139]Ananya Kumar, Tengyu Ma, Percy Liang, Aditi Raghunathan:
Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift. CoRR abs/2207.08977 (2022) - [i138]Shivam Garg, Dimitris Tsipras, Percy Liang, Gregory Valiant:
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes. CoRR abs/2208.01066 (2022) - [i137]Joon Sung Park, Lindsay Popowski, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein:
Social Simulacra: Creating Populated Prototypes for Social Computing Systems. CoRR abs/2208.04024 (2022) - [i136]Yann Dubois, Tatsunori Hashimoto, Stefano Ermon, Percy Liang:
Improving Self-Supervised Learning by Characterizing Idealized Representations. CoRR abs/2209.06235 (2022) - [i135]Nelson F. Liu, Ananya Kumar, Percy Liang, Robin Jia:
Are Sample-Efficient NLP Models More Robust? CoRR abs/2210.06456 (2022) - [i134]Michihiro Yasunaga, Antoine Bosselut, Hongyu Ren, Xikun Zhang, Christopher D. Manning, Percy Liang, Jure Leskovec:
Deep Bidirectional Language-Knowledge Graph Pretraining. CoRR abs/2210.09338 (2022) - [i133]Yoonho Lee, Annie S. Chen, Fahim Tajwar, Ananya Kumar, Huaxiu Yao, Percy Liang, Chelsea Finn:
Surgical Fine-Tuning Improves Adaptation to Distribution Shifts. CoRR abs/2210.11466 (2022) - [i132]Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis:
Contrastive Decoding: Open-ended Text Generation as Optimization. CoRR abs/2210.15097 (2022) - [i131]John Hewitt, Christopher D. Manning, Percy Liang:
Truncation Sampling as Language Model Desmoothing. CoRR abs/2210.15191 (2022) - [i130]Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda:
Holistic Evaluation of Language Models. CoRR abs/2211.09110 (2022) - [i129]Michihiro Yasunaga, Armen Aghajanyan, Weijia Shi, Rich James, Jure Leskovec, Percy Liang, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih:
Retrieval-Augmented Multimodal Language Modeling. CoRR abs/2211.12561 (2022) - [i128]Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N. Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé III, Emma Pierson, Nihar B. Shah:
How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions? CoRR abs/2211.12966 (2022) - [i127]Rishi Bommasani, Kathleen A. Creel, Ananya Kumar, Dan Jurafsky, Percy Liang:
Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization? CoRR abs/2211.13972 (2022) - [i126]Chris Donahue, John Thickstun, Percy Liang:
Melody transcription via generative pre-training. CoRR abs/2212.01884 (2022) - [i125]Mina Lee, Megha Srivastava, Amelia Hardy, John Thickstun, Esin Durmus, Ashwin Paranjape, Ines Gerard-Ursin, Xiang Lisa Li, Faisal Ladhak, Frieda Rong, Rose E. Wang, Minae Kwon, Joon Sung Park, Hancheng Cao, Tony Lee, Rishi Bommasani, Michael S. Bernstein, Percy Liang:
Evaluating Human-Language Model Interaction. CoRR abs/2212.09746 (2022) - [i124]Rishi Bommasani, Percy Liang:
Trustworthy Social Bias Measurement. CoRR abs/2212.11672 (2022) - [i123]Omar Khattab, Keshav Santhanam, Xiang Lisa Li, David Hall, Percy Liang, Christopher Potts, Matei Zaharia:
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP. CoRR abs/2212.14024 (2022) - 2021
- [i122]Xiang Lisa Li, Percy Liang:
Prefix-Tuning: Optimizing Continuous Prompts for Generation. CoRR abs/2101.00190 (2021) - [i121]Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang:
Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches. CoRR abs/2102.01065 (2021) - [i120]Michihiro Yasunaga, Hongyu Ren, Antoine Bosselut, Percy Liang, Jure Leskovec:
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering. CoRR abs/2104.06378 (2021) - [i119]Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang:
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality. CoRR abs/2106.04102 (2021) - [i118]Michihiro Yasunaga, Percy Liang:
Break-It-Fix-It: Unsupervised Learning for Program Repair. CoRR abs/2106.06600 (2021) - [i117]John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt:
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. CoRR abs/2107.04649 (2021) - [i116]Rodrigo Castellon, Chris Donahue, Percy Liang:
Codified audio language modeling learns useful representations for music information retrieval. CoRR abs/2107.05677 (2021) - [i115]Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn:
Just Train Twice: Improving Group Robustness without Training Group Information. CoRR abs/2107.09044 (2021) - [i114]Fahim Tajwar, Ananya Kumar, Sang Michael Xie, Percy Liang:
No True State-of-the-Art? OOD Detection Methods are Inconsistent across Datasets. CoRR abs/2109.05554 (2021) - [i113]Michihiro Yasunaga, Jure Leskovec, Percy Liang:
LM-Critic: Language Models for Unsupervised Grammatical Error Correction. CoRR abs/2109.06822 (2021) - [i112]John Hewitt, Kawin Ethayarajh, Percy Liang, Christopher D. Manning:
Conditional probing: measuring usable information beyond a baseline. CoRR abs/2109.09234 (2021) - [i111]Xuechen Li, Florian Tramèr, Percy Liang, Tatsunori Hashimoto:
Large Language Models Can Be Strong Differentially Private Learners. CoRR abs/2110.05679 (2021) - [i110]Sang Michael Xie, Aditi Raghunathan, Percy Liang, Tengyu Ma:
An Explanation of In-context Learning as Implicit Bayesian Inference. CoRR abs/2111.02080 (2021) - [i109]Siddharth Karamcheti, Megha Srivastava, Percy Liang, Dorsa Sadigh:
LILA: Language-Informed Latent Actions. CoRR abs/2111.03205 (2021) - [i108]Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang:
Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR abs/2112.05090 (2021) - 2020
- [i107]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Understanding and Mitigating the Tradeoff Between Robustness and Accuracy. CoRR abs/2002.10716 (2020) - [i106]Ananya Kumar, Tengyu Ma, Percy Liang:
Understanding Self-Training for Gradual Domain Adaptation. CoRR abs/2002.11361 (2020) - [i105]Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang:
Robust Encodings: A Framework for Combating Adversarial Typos. CoRR abs/2005.01229 (2020) - [i104]Shikhar Murty, Pang Wei Koh, Percy Liang:
ExpBERT: Representation Engineering with Natural Language Explanations. CoRR abs/2005.01932 (2020) - [i103]Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang:
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. CoRR abs/2005.04345 (2020) - [i102]Chris Donahue, Mina Lee, Percy Liang:
Enabling Language Models to Fill in the Blanks. CoRR abs/2005.05339 (2020) - [i101]Michihiro Yasunaga, Percy Liang:
Graph-based, Self-Supervised Program Repair from Diagnostic Feedback. CoRR abs/2005.10636 (2020) - [i100]Amita Kamath, Robin Jia, Percy Liang:
Selective Question Answering under Domain Shift. CoRR abs/2006.09462 (2020) - [i99]Sang Michael Xie, Tengyu Ma, Percy Liang:
Simplifying Models with Unlabeled Output Data. CoRR abs/2006.16205 (2020) - [i98]Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang:
Concept Bottleneck Models. CoRR abs/2007.04612 (2020) - [i97]Evan Zheran Liu, Ramtin Keramati, Sudarshan Seshadri, Kelvin Guu, Panupong Pasupat, Emma Brunskill, Percy Liang:
Learning Abstract Models for Strategic Exploration and Fast Reward Transfer. CoRR abs/2007.05896 (2020) - [i96]Megha Srivastava, Tatsunori B. Hashimoto, Percy Liang:
Robustness to Spurious Correlations via Human Annotations. CoRR abs/2007.06661 (2020) - [i95]Evan Zheran Liu, Aditi Raghunathan, Percy Liang, Chelsea Finn:
Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning. CoRR abs/2008.02790 (2020) - [i94]Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H. Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Andrew Wolfe, Abby Wray, Yuchen Zhang, Alexander Zotov:
Task-Oriented Dialogue as Dataflow Synthesis. CoRR abs/2009.11423 (2020) - [i93]Stephen Mussmann, Robin Jia, Percy Liang:
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks. CoRR abs/2010.05103 (2020) - [i92]Siddharth Karamcheti, Dorsa Sadigh, Percy Liang:
Learning Adaptive Language Interfaces through Decomposition. CoRR abs/2010.05190 (2020) - [i91]Benjamin Newman, John Hewitt, Percy Liang, Christopher D. Manning:
The EOS Decision and Length Extrapolation. CoRR abs/2010.07174 (2020) - [i90]John Hewitt, Michael Hahn, Surya Ganguli, Percy Liang, Christopher D. Manning:
RNNs can generate bounded hierarchical languages with optimal memory. CoRR abs/2010.07515 (2020) - [i89]Sumanth Dathathri, Krishnamurthy Dvijotham, Alexey Kurakin, Aditi Raghunathan, Jonathan Uesato, Rudy Bunel, Shreya Shankar, Jacob Steinhardt, Ian J. Goodfellow, Percy Liang, Pushmeet Kohli:
Enabling certification of verification-agnostic networks via memory-efficient semidefinite programming. CoRR abs/2010.11645 (2020) - [i88]Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang:
Selective Classification Can Magnify Disparities Across Groups. CoRR abs/2010.14134 (2020) - [i87]Yu Gu, Sue Kase, Michelle Vanni, Brian M. Sadler, Percy Liang, Xifeng Yan, Yu Su:
Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases. CoRR abs/2011.07743 (2020) - [i86]Fereshte Khani, Percy Liang:
Removing Spurious Features can Hurt Accuracy and Affect Groups Disproportionately. CoRR abs/2012.04104 (2020) - [i85]Sang Michael Xie, Ananya Kumar, Robbie Jones, Fereshte Khani, Tengyu Ma, Percy Liang:
In-N-Out: Pre-Training and Self-Training using Auxiliary Information for Out-of-Distribution Robustness. CoRR abs/2012.04550 (2020) - [i84]Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang:
WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR abs/2012.07421 (2020) - 2019
- [i83]Jesse Mu, Percy Liang, Noah D. Goodman:
Shaping Visual Representations with Language for Few-shot Classification. ViGIL@NeurIPS 2019 - [i82]Hatef Monajemi, Riccardo Murri, Eric Jonas, Percy Liang, Victoria Stodden, David L. Donoho:
Ambitious Data Science Can Be Painless. CoRR abs/1901.08705 (2019) - [i81]Yuchen Zhang, Percy Liang:
Defending against Whitebox Adversarial Attacks via Randomized Discretization. CoRR abs/1903.10586 (2019) - [i80]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. CoRR abs/1904.02792 (2019) - [i79]He He, Nanyun Peng, Percy Liang:
Pun Generation with Surprise. CoRR abs/1904.06828 (2019) - [i78]Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec:
Pre-training Graph Neural Networks. CoRR abs/1905.12265 (2019) - [i77]Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang:
On the Accuracy of Influence Functions for Measuring Group Effects. CoRR abs/1905.13289 (2019) - [i76]Yair Carmon, Aditi Raghunathan, Ludwig Schmidt, Percy Liang, John C. Duchi:
Unlabeled Data Improves Adversarial Robustness. CoRR abs/1905.13736 (2019) - [i75]Fereshte Khani, Aditi Raghunathan, Percy Liang:
Maximum Weighted Loss Discrepancy. CoRR abs/1906.03518 (2019) - [i74]Sumith Kulal, Panupong Pasupat, Kartik Chandra, Mina Lee, Oded Padon, Alex Aiken, Percy Liang:
SPoC: Search-based Pseudocode to Code. CoRR abs/1906.04908 (2019) - [i73]Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang:
Adversarial Training Can Hurt Generalization. CoRR abs/1906.06032 (2019) - [i72]Ray Li, Percy Liang, Stephen Mussmann:
A Tight Analysis of Greedy Yields Subexponential Time Approximation for Uniform Decision Tree. CoRR abs/1906.11385 (2019) - [i71]Cody Coleman, Christopher Yeh, Stephen Mussmann, Baharan Mirzasoleiman, Peter Bailis, Percy Liang, Jure Leskovec, Matei Zaharia:
Selection Via Proxy: Efficient Data Selection For Deep Learning. CoRR abs/1906.11829 (2019) - [i70]Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang:
Certified Robustness to Adversarial Word Substitutions. CoRR abs/1909.00986 (2019) - [i69]Yonatan Oren, Shiori Sagawa, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Language Modeling. CoRR abs/1909.02060 (2019) - [i68]John Hewitt, Percy Liang:
Designing and Interpreting Probes with Control Tasks. CoRR abs/1909.03368 (2019) - [i67]Ananya Kumar, Percy Liang, Tengyu Ma:
Verified Uncertainty Calibration. CoRR abs/1909.10155 (2019) - [i66]Jesse Mu, Percy Liang, Noah D. Goodman:
Shaping Visual Representations with Language for Few-shot Classification. CoRR abs/1911.02683 (2019) - [i65]Mina Lee, Tatsunori B. Hashimoto, Percy Liang:
Learning Autocomplete Systems as a Communication Game. CoRR abs/1911.06964 (2019) - [i64]Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization. CoRR abs/1911.08731 (2019) - [i63]Fereshte Khani, Percy Liang:
Noise Induces Loss Discrepancy Across Groups for Linear Regression. CoRR abs/1911.09876 (2019) - 2018
- [i62]Aditi Raghunathan, Jacob Steinhardt, Percy Liang:
Certified Defenses against Adversarial Examples. CoRR abs/1801.09344 (2018) - [i61]Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, David L. Dill:
Learning a SAT Solver from Single-Bit Supervision. CoRR abs/1802.03685 (2018) - [i60]Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, Tianlin Shi, Percy Liang:
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration. CoRR abs/1802.08802 (2018) - [i59]Stephen Mussmann, Percy Liang:
Generalized Binary Search For Split-Neighborly Problems. CoRR abs/1802.09751 (2018) - [i58]Juncen Li, Robin Jia, He He, Percy Liang:
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer. CoRR abs/1804.06437 (2018) - [i57]Braden Hancock, Paroma Varma, Stephanie Wang, Martin Bringmann, Percy Liang, Christopher Ré:
Training Classifiers with Natural Language Explanations. CoRR abs/1805.03818 (2018) - [i56]Fereshte Khani, Noah D. Goodman, Percy Liang:
Planning, Inference and Pragmatics in Sequential Language Games. CoRR abs/1805.11774 (2018) - [i55]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. CoRR abs/1806.03822 (2018) - [i54]Stephen Mussmann, Percy Liang:
On the Relationship between Data Efficiency and Error for Uncertainty Sampling. CoRR abs/1806.06123 (2018) - [i53]Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang:
Fairness Without Demographics in Repeated Loss Minimization. CoRR abs/1806.08010 (2018) - [i52]Arun Tejasvi Chaganty, Stephen Mussmann, Percy Liang:
The price of debiasing automatic metrics in natural language evaluation. CoRR abs/1807.02202 (2018) - [i51]Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nicholas Eriksson, Percy Liang:
Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data. CoRR abs/1807.04709 (2018) - [i50]Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, Luke Zettlemoyer:
QuAC : Question Answering in Context. CoRR abs/1808.07036 (2018) - [i49]Panupong Pasupat, Tian-Shun Jiang, Evan Zheran Liu, Kelvin Guu, Percy Liang:
Mapping Natural Language Commands to Web Elements. CoRR abs/1808.09132 (2018) - [i48]He He, Derek Chen, Anusha Balakrishnan, Percy Liang:
Decoupling Strategy and Generation in Negotiation Dialogues. CoRR abs/1808.09637 (2018) - [i47]Matthew Lamm, Arun Tejasvi Chaganty, Christopher D. Manning, Dan Jurafsky, Percy Liang:
Textual Analogy Parsing: What's Shared and What's Compared among Analogous Facts. CoRR abs/1809.02700 (2018) - [i46]Dorottya Demszky, Kelvin Guu, Percy Liang:
Transforming Question Answering Datasets Into Natural Language Inference Datasets. CoRR abs/1809.02922 (2018) - [i45]Pang Wei Koh, Jacob Steinhardt, Percy Liang:
Stronger Data Poisoning Attacks Break Data Sanitization Defenses. CoRR abs/1811.00741 (2018) - [i44]Aditi Raghunathan, Jacob Steinhardt, Percy Liang:
Semidefinite relaxations for certifying robustness to adversarial examples. CoRR abs/1811.01057 (2018) - [i43]Kensen Shi, Jacob Steinhardt, Percy Liang:
FrAngel: Component-Based Synthesis with Control Structures. CoRR abs/1811.05175 (2018) - [i42]Tatsunori B. Hashimoto, Kelvin Guu, Yonatan Oren, Percy Liang:
A Retrieve-and-Edit Framework for Predicting Structured Outputs. CoRR abs/1812.01194 (2018) - [i41]Stephen Mussmann, Percy Liang:
Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss. CoRR abs/1812.01815 (2018) - 2017
- [i40]Yuchen Zhang, Percy Liang, Moses Charikar:
A Hitting Time Analysis of Stochastic Gradient Langevin Dynamics. CoRR abs/1702.05575 (2017) - [i39]Pang Wei Koh, Percy Liang:
Understanding Black-box Predictions via Influence Functions. CoRR abs/1703.04730 (2017) - [i38]Sida I. Wang, Samuel Ginn, Percy Liang, Christopher D. Manning:
Naturalizing a Programming Language via Interactive Learning. CoRR abs/1704.06956 (2017) - [i37]He He, Anusha Balakrishnan, Mihail Eric, Percy Liang:
Learning Symmetric Collaborative Dialogue Agents with Dynamic Knowledge Graph Embeddings. CoRR abs/1704.07130 (2017) - [i36]Kelvin Guu, Panupong Pasupat, Evan Zheran Liu, Percy Liang:
From Language to Programs: Bridging Reinforcement Learning and Maximum Marginal Likelihood. CoRR abs/1704.07926 (2017) - [i35]Jacob Steinhardt, Pang Wei Koh, Percy Liang:
Certified Defenses for Data Poisoning Attacks. CoRR abs/1706.03691 (2017) - [i34]Daniel Selsam, Percy Liang, David L. Dill:
Developing Bug-Free Machine Learning Systems With Formal Mathematics. CoRR abs/1706.08605 (2017) - [i33]Robin Jia, Percy Liang:
Adversarial Examples for Evaluating Reading Comprehension Systems. CoRR abs/1707.07328 (2017) - [i32]Yuchen Zhang, Panupong Pasupat, Percy Liang:
Macro Grammars and Holistic Triggering for Efficient Semantic Parsing. CoRR abs/1707.07806 (2017) - [i31]Kelvin Guu, Tatsunori B. Hashimoto, Yonatan Oren, Percy Liang:
Generating Sentences by Editing Prototypes. CoRR abs/1709.08878 (2017) - [i30]Vatsal Sharan, Sham M. Kakade, Percy Liang, Gregory Valiant:
Learning Overcomplete HMMs. CoRR abs/1711.02309 (2017) - [i29]Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang:
Active Learning of Points-To Specifications. CoRR abs/1711.03239 (2017) - 2016
- [i28]Percy Liang:
Learning Executable Semantic Parsers for Natural Language Understanding. CoRR abs/1603.06677 (2016) - [i27]Sida I. Wang, Arun Tejasvi Chaganty, Percy Liang:
Estimating Mixture Models via Mixtures of Polynomials. CoRR abs/1603.08482 (2016) - [i26]Sida I. Wang, Percy Liang, Christopher D. Manning:
Learning Language Games through Interaction. CoRR abs/1606.02447 (2016) - [i25]Robin Jia, Percy Liang:
Data Recombination for Neural Semantic Parsing. CoRR abs/1606.03622 (2016) - [i24]Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang:
SQuAD: 100, 000+ Questions for Machine Comprehension of Text. CoRR abs/1606.05250 (2016) - [i23]Jacob Steinhardt, Percy Liang:
Unsupervised Risk Estimation Using Only Conditional Independence Structure. CoRR abs/1606.05313 (2016) - [i22]Reginald Long, Panupong Pasupat, Percy Liang:
Simpler Context-Dependent Logical Forms via Model Projections. CoRR abs/1606.05378 (2016) - [i21]Fereshte Khani, Martin C. Rinard, Percy Liang:
Unanimous Prediction for 100% Precision with Application to Learning Semantic Mappings. CoRR abs/1606.06368 (2016) - [i20]Panupong Pasupat, Percy Liang:
Inferring Logical Forms From Denotations. CoRR abs/1606.06900 (2016) - [i19]Osbert Bastani, Rahul Sharma, Alex Aiken, Percy Liang:
Synthesizing Program Input Grammars. CoRR abs/1608.01723 (2016) - [i18]Aditi Raghunathan, Roy Frostig, John C. Duchi, Percy Liang:
Estimation from Indirect Supervision with Linear Moments. CoRR abs/1608.03100 (2016) - [i17]Arun Tejasvi Chaganty, Percy Liang:
How Much is 131 Million Dollars? Putting Numbers in Perspective with Compositional Descriptions. CoRR abs/1609.00070 (2016) - [i16]Yuchen Zhang, Percy Liang, Martin J. Wainwright:
Convexified Convolutional Neural Networks. CoRR abs/1609.01000 (2016) - [i15]Sham M. Kakade, Percy Liang, Vatsal Sharan, Gregory Valiant:
Prediction with a Short Memory. CoRR abs/1612.02526 (2016) - 2015
- [i14]Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang:
Simultaneous diagonalization: the asymmetric, low-rank, and noisy settings. CoRR abs/1501.06318 (2015) - [i13]Volodymyr Kuleshov, Arun Tejasvi Chaganty, Percy Liang:
Tensor Factorization via Matrix Factorization. CoRR abs/1501.07320 (2015) - [i12]Jacob Steinhardt, Percy Liang:
Reified Context Models. CoRR abs/1502.06665 (2015) - [i11]Jacob Steinhardt, Percy Liang:
Learning Fast-Mixing Models for Structured Prediction. CoRR abs/1502.06668 (2015) - [i10]Kelvin Guu, John Miller, Percy Liang:
Traversing Knowledge Graphs in Vector Space. CoRR abs/1506.01094 (2015) - [i9]Keenon Werling, Arun Tejasvi Chaganty, Percy Liang, Christopher D. Manning:
On-the-Job Learning with Bayesian Decision Theory. CoRR abs/1506.03140 (2015) - [i8]Panupong Pasupat, Percy Liang:
Compositional Semantic Parsing on Semi-Structured Tables. CoRR abs/1508.00305 (2015) - 2014
- [i7]Stefan Wager, William Fithian, Sida Wang, Percy Liang:
Altitude Training: Strong Bounds for Single-Layer Dropout. CoRR abs/1407.3289 (2014) - [i6]Jacob Steinhardt, Stefan Wager, Percy Liang:
The Statistics of Streaming Sparse Regression. CoRR abs/1412.4182 (2014) - 2013
- [i5]Arun Tejasvi Chaganty, Percy Liang:
Spectral Experts for Estimating Mixtures of Linear Regressions. CoRR abs/1306.3729 (2013) - [i4]Stefan Wager, Sida Wang, Percy Liang:
Dropout Training as Adaptive Regularization. CoRR abs/1307.1493 (2013) - [i3]Percy Liang:
Lambda Dependency-Based Compositional Semantics. CoRR abs/1309.4408 (2013) - 2012
- [i2]Daniel J. Hsu, Sham M. Kakade, Percy Liang:
Identifiability and Unmixing of Latent Parse Trees. CoRR abs/1206.3137 (2012) - 2011
- [i1]Percy Liang, Michael I. Jordan, Dan Klein:
Learning Dependency-Based Compositional Semantics. CoRR abs/1109.6841 (2011)
Coauthor Index
Tatsunori B. Hashimoto
aka: Tatsunori Hashimoto
aka: Tatsunori Hashimoto
[j9] [j6] [c188] [c183] [c181] [c180] [c179] [c175] [c160] [c159] [c153] [c152] [c118] [c112] [c108] [c104] [c102] [c86] [c82] [c65] [i184] [i183] [i181] [i177] [i175] [i168] [i158] [i155] [i150] [i144] [i142] [i140] [i136] [i132] [i130] [i111] [i108] [i96] [i80] [i69] [i65] [i64] [i53] [i51] [i42] [i31]
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last updated on 2024-04-14 03:50 CEST by the dblp team
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