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ORCIDLuke Zettlemoyer
Luke S. Zettlemoyer
Person information
- affiliation: University of Washington, School of Computer Science & Engineering, Seattle, WA, USA
- award (2016): Presidential Early Career Award for Scientists and Engineers
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2020 – today
- 2024
[c218]Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa:
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. ACL (1) 2024: 749-775- [c217]Tomasz Limisiewicz, Terra Blevins, Hila Gonen, Orevaoghene Ahia, Luke Zettlemoyer:
MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling. ACL (1) 2024: 15059-15076 - [c216]Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Evan Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. ACL (1) 2024: 15725-15788 - [c215]Dirk Groeneveld, Iz Beltagy, Evan Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. ACL (1) 2024: 15789-15809 - [c214]Jiawei Ma, Po-Yao Huang, Saining Xie, Shang-Wen Li, Luke Zettlemoyer, Shih-Fu Chang, Wen-Tau Yih, Hu Xu:
MoDE: CLIP Data Experts via Clustering. CVPR 2024: 26344-26353 - [c213]Haoqiang Kang, Terra Blevins, Luke Zettlemoyer:
Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation with Pretrained Language Models. EACL (1) 2024: 1562-1575 - [c212]Yu Meng
, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer:
Representation Deficiency in Masked Language Modeling. ICLR 2024 - [c211]Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
Demystifying CLIP Data. ICLR 2024 - [c210]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Omer Levy, Luke Zettlemoyer, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. ICLR 2024 - [c209]Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Richard James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih:
RA-DIT: Retrieval-Augmented Dual Instruction Tuning. ICLR 2024 - [c208]Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer:
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. ICLR 2024 - [c207]Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, Luke Zettlemoyer:
Detecting Pretraining Data from Large Language Models. ICLR 2024 - [c206]Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Wen-tau Yih, Mike Lewis:
In-Context Pretraining: Language Modeling Beyond Document Boundaries. ICLR 2024 - [c205]Weijia Shi, Xiaochuang Han, Mike Lewis, Yulia Tsvetkov, Luke Zettlemoyer, Wen-tau Yih:
Trusting Your Evidence: Hallucinate Less with Context-aware Decoding. NAACL (Short Papers) 2024: 783-791 - [c204]Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Richard James, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih:
REPLUG: Retrieval-Augmented Black-Box Language Models. NAACL-HLT 2024: 8371-8384 - [i203]Terra Blevins, Tomasz Limisiewicz, Suchin Gururangan, Margaret Li, Hila Gonen, Noah A. Smith, Luke Zettlemoyer:
Breaking the Curse of Multilinguality with Cross-lingual Expert Language Models. CoRR abs/2401.10440 (2024) - [i202]Jiacheng Liu, Sewon Min, Luke Zettlemoyer, Yejin Choi, Hannaneh Hajishirzi:
Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens. CoRR abs/2401.17377 (2024) - [i201]Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo:
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. CoRR abs/2402.00159 (2024) - [i200]Dirk Groeneveld, Iz Beltagy, Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi:
OLMo: Accelerating the Science of Language Models. CoRR abs/2402.00838 (2024) - [i199]Michael Duan, Anshuman Suri, Niloofar Mireshghallah, Sewon Min, Weijia Shi, Luke Zettlemoyer, Yulia Tsvetkov, Yejin Choi, David Evans, Hannaneh Hajishirzi:
Do Membership Inference Attacks Work on Large Language Models? CoRR abs/2402.07841 (2024) - [i198]Haoqiang Kang, Terra Blevins, Luke Zettlemoyer:
Comparing Hallucination Detection Metrics for Multilingual Generation. CoRR abs/2402.10496 (2024) - [i197]Akari Asai, Zexuan Zhong, Danqi Chen, Pang Wei Koh, Luke Zettlemoyer, Hannaneh Hajishirzi, Wen-tau Yih:
Reliable, Adaptable, and Attributable Language Models with Retrieval. CoRR abs/2403.03187 (2024) - [i196]Tomasz Limisiewicz, Terra Blevins, Hila Gonen, Orevaoghene Ahia, Luke Zettlemoyer:
MYTE: Morphology-Driven Byte Encoding for Better and Fairer Multilingual Language Modeling. CoRR abs/2403.10691 (2024) - [i195]Xuezhe Ma, Xiaomeng Yang, Wenhan Xiong, Beidi Chen, Lili Yu, Hao Zhang, Jonathan May, Luke Zettlemoyer, Omer Levy, Chunting Zhou:
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length. CoRR abs/2404.08801 (2024) - [i194]Jiawei Ma, Po-Yao Huang, Saining Xie, Shang-Wen Li, Luke Zettlemoyer, Shih-Fu Chang, Wen-Tau Yih, Hu Xu:
MoDE: CLIP Data Experts via Clustering. CoRR abs/2404.16030 (2024) - [i193]Vasu Sharma, Karthik Padthe, Newsha Ardalani, Kushal Tirumala, Russell Howes, Hu Xu, Po-Yao Huang, Shang-Wen Li, Armen Aghajanyan, Gargi Ghosh, Luke Zettlemoyer:
Text Quality-Based Pruning for Efficient Training of Language Models. CoRR abs/2405.01582 (2024) - [i192]Maciej Kilian, Varun Jampani, Luke Zettlemoyer:
Computational Tradeoffs in Image Synthesis: Diffusion, Masked-Token, and Next-Token Prediction. CoRR abs/2405.13218 (2024) - [i191]Yushi Hu, Weijia Shi, Xingyu Fu, Dan Roth, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Ranjay Krishna:
Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models. CoRR abs/2406.09403 (2024) - [i190]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. CoRR abs/2406.11794 (2024) - [i189]Luxi He, Yangsibo Huang, Weijia Shi, Tinghao Xie, Haotian Liu, Yue Wang, Luke Zettlemoyer, Chiyuan Zhang, Danqi Chen, Peter Henderson:
Fantastic Copyrighted Beasts and How (Not) to Generate Them. CoRR abs/2406.14526 (2024) - [i188]Boyi Wei, Weijia Shi, Yangsibo Huang, Noah A. Smith, Chiyuan Zhang, Luke Zettlemoyer, Kai Li, Peter Henderson:
Evaluating Copyright Takedown Methods for Language Models. CoRR abs/2406.18664 (2024) - [i187]Weijia Shi, Jaechan Lee, Yangsibo Huang, Sadhika Malladi, Jieyu Zhao, Ari Holtzman, Daogao Liu, Luke Zettlemoyer, Noah A. Smith, Chiyuan Zhang:
MUSE: Machine Unlearning Six-Way Evaluation for Language Models. CoRR abs/2407.06460 (2024) - [i186]Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh:
CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation. CoRR abs/2407.07087 (2024) - [i185]Rulin Shao, Jacqueline He, Akari Asai, Weijia Shi, Tim Dettmers, Sewon Min, Luke Zettlemoyer, Pang Wei Koh:
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore. CoRR abs/2407.12854 (2024) - [i184]Xi Victoria Lin, Akshat Shrivastava, Liang Luo, Srinivasan Iyer, Mike Lewis, Gargi Ghosh, Luke Zettlemoyer, Armen Aghajanyan:
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts. CoRR abs/2407.21770 (2024) - [i183]Thao Nguyen, Jeffrey Li, Sewoong Oh, Ludwig Schmidt, Jason Weston, Luke Zettlemoyer, Xian Li:
Better Alignment with Instruction Back-and-Forth Translation. CoRR abs/2408.04614 (2024) - [i182]Hila Gonen, Terra Blevins, Alisa Liu, Luke Zettlemoyer, Noah A. Smith:
Does Liking Yellow Imply Driving a School Bus? Semantic Leakage in Language Models. CoRR abs/2408.06518 (2024) - [i181]Chunting Zhou, Lili Yu, Arun Babu, Kushal Tirumala, Michihiro Yasunaga, Leonid Shamis, Jacob Kahn, Xuezhe Ma, Luke Zettlemoyer, Omer Levy:
Transfusion: Predict the Next Token and Diffuse Images with One Multi-Modal Model. CoRR abs/2408.11039 (2024) - 2023
- [j12]Devendra Singh Sachan, Mike Lewis, Dani Yogatama, Luke Zettlemoyer, Joelle Pineau, Manzil Zaheer:
Questions Are All You Need to Train a Dense Passage Retriever. Trans. Assoc. Comput. Linguistics 11: 600-616 (2023) - [j11]Siddharth Dalmia, Dmytro Okhonko, Mike Lewis, Sergey Edunov, Shinji Watanabe, Florian Metze, Luke Zettlemoyer, Abdelrahman Mohamed:
LegoNN: Building Modular Encoder-Decoder Models. IEEE ACM Trans. Audio Speech Lang. Process. 31: 3112-3126 (2023) - [c203]Suzanna Sia, Anton Belyy, Amjad Almahairi, Madian Khabsa, Luke Zettlemoyer, Lambert Mathias:
Logical Satisfiability of Counterfactuals for Faithful Explanations in NLI. AAAI 2023: 9837-9845 - [c202]Hongjin Su, Weijia Shi, Jungo Kasai, Yizhong Wang, Yushi Hu, Mari Ostendorf, Wen-tau Yih, Noah A. Smith, Luke Zettlemoyer, Tao Yu:
One Embedder, Any Task: Instruction-Finetuned Text Embeddings. ACL (Findings) 2023: 1102-1121 - [c201]Sewon Min, Weijia Shi, Mike Lewis, Xilun Chen, Wen-tau Yih, Hannaneh Hajishirzi, Luke Zettlemoyer:
Nonparametric Masked Language Modeling. ACL (Findings) 2023: 2097-2118 - [c200]Xinxi Lyu, Sewon Min, Iz Beltagy, Luke Zettlemoyer, Hannaneh Hajishirzi:
Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations. ACL (1) 2023: 2304-2317 - [c199]Boshi Wang, Sewon Min, Xiang Deng, Jiaming Shen, You Wu, Luke Zettlemoyer, Huan Sun:
Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters. ACL (1) 2023: 2717-2739 - [c198]Terra Blevins, Hila Gonen, Luke Zettlemoyer:
Prompting Language Models for Linguistic Structure. ACL (1) 2023: 6649-6663 - [c197]Sweta Agrawal, Chunting Zhou, Mike Lewis, Luke Zettlemoyer, Marjan Ghazvininejad:
In-context Examples Selection for Machine Translation. ACL (Findings) 2023: 8857-8873 - [c196]Xinyan Yu, Sewon Min, Luke Zettlemoyer, Hannaneh Hajishirzi:
CREPE: Open-Domain Question Answering with False Presuppositions. ACL (1) 2023: 10457-10480 - [c195]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 - [c194]Mengzhou Xia, Mikel Artetxe, Chunting Zhou, Xi Victoria Lin, Ramakanth Pasunuru, Danqi Chen, Luke Zettlemoyer, Veselin Stoyanov:
Training Trajectories of Language Models Across Scales. ACL (1) 2023: 13711-13738 - [c193]Mikel Artetxe, Vedanuj Goswami, Shruti Bhosale, Angela Fan, Luke Zettlemoyer:
Revisiting Machine Translation for Cross-lingual Classification. EMNLP 2023: 6489-6499 - [c192]Victor Zhong, Weijia Shi, Wen-tau Yih, Luke Zettlemoyer:
RoMQA: A Benchmark for Robust, Multi-evidence, Multi-answer Question Answering. EMNLP (Findings) 2023: 7055-7067 - [c191]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Getting MoRE out of Mixture of Language Model Reasoning Experts. EMNLP (Findings) 2023: 8234-8249 - [c190]Hila Gonen, Srini Iyer, Terra Blevins, Noah A. Smith, Luke Zettlemoyer:
Demystifying Prompts in Language Models via Perplexity Estimation. EMNLP (Findings) 2023: 10136-10148 - [c189]Weijia Shi, Xiaochuang Han, Hila Gonen, Ari Holtzman, Yulia Tsvetkov, Luke Zettlemoyer:
Toward Human Readable Prompt Tuning: Kubrick's The Shining is a good movie, and a good prompt too? EMNLP (Findings) 2023: 10994-11005 - [c188]Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi:
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. EMNLP 2023: 12076-12100 - [c187]Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, Madian Khabsa:
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models. EMNLP 2023: 13142-13152 - [c186]Hu Xu, Saining Xie, Po-Yao Huang, Licheng Yu, Russell Howes, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
CiT: Curation in Training for Effective Vision-Language Data. ICCV 2023: 15134-15143 - [c185]Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Binding Language Models in Symbolic Languages. ICLR 2023 - [c184]Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis:
InCoder: A Generative Model for Code Infilling and Synthesis. ICLR 2023 - [c183]Olga Golovneva, Moya Chen, Spencer Poff, Martin Corredor, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz:
ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning. ICLR 2023 - [c182]Xuezhe Ma, Chunting Zhou, Xiang Kong, Junxian He, Liangke Gui, Graham Neubig, Jonathan May, Luke Zettlemoyer:
Mega: Moving Average Equipped Gated Attention. ICLR 2023 - [c181]Bhargavi Paranjape, Pradeep Dasigi, Vivek Srikumar, Luke Zettlemoyer, Hannaneh Hajishirzi:
AGRO: Adversarial discovery of error-prone Groups for Robust Optimization. ICLR 2023 - [c180]Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu:
Selective Annotation Makes Language Models Better Few-Shot Learners. ICLR 2023 - [c179]Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer:
Scaling Laws for Generative Mixed-Modal Language Models. ICML 2023: 265-279 - [c178]Tim Dettmers, Luke Zettlemoyer:
The case for 4-bit precision: k-bit Inference Scaling Laws. ICML 2023: 7750-7774 - [c177]Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-Tau Yih, Daniel Fried, Sida I. Wang, Tao Yu:
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. ICML 2023: 18319-18345 - [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]Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. NeurIPS 2023 - [c174]Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Eric Hambro, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom:
Toolformer: Language Models Can Teach Themselves to Use Tools. NeurIPS 2023 - [c173]Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. NeurIPS 2023 - [c172]Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis:
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. NeurIPS 2023 - [c171]Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. NeurIPS 2023 - [c170]Benjamin Muller, Belen Alastruey, Prangthip Hansanti, Elahe Kalbassi, Christophe Ropers, Eric Michael Smith, Adina Williams, Luke Zettlemoyer, Pierre Andrews, Marta R. Costa-jussà:
The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages. WMT 2023: 536-550 - [i180]Hu Xu, Saining Xie, Po-Yao Huang, Licheng Yu, Russell Howes, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
CiT: Curation in Training for Effective Vision-Language Data. CoRR abs/2301.02241 (2023) - [i179]Armen Aghajanyan, Lili Yu, Alexis Conneau, Wei-Ning Hsu, Karen Hambardzumyan, Susan Zhang, Stephen Roller, Naman Goyal, Omer Levy, Luke Zettlemoyer:
Scaling Laws for Generative Mixed-Modal Language Models. CoRR abs/2301.03728 (2023) - [i178]Davis Liang, Hila Gonen, Yuning Mao, Rui Hou, Naman Goyal, Marjan Ghazvininejad, Luke Zettlemoyer, Madian Khabsa:
XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models. CoRR abs/2301.10472 (2023) - [i177]Weijia Shi, Sewon Min, Michihiro Yasunaga, Minjoon Seo, Rich James, Mike Lewis, Luke Zettlemoyer, Wen-tau Yih:
REPLUG: Retrieval-Augmented Black-Box Language Models. CoRR abs/2301.12652 (2023) - [i176]Yu Meng, Jitin Krishnan, Sinong Wang, Qifan Wang, Yuning Mao, Han Fang, Marjan Ghazvininejad, Jiawei Han, Luke Zettlemoyer:
Representation Deficiency in Masked Language Modeling. CoRR abs/2302.02060 (2023) - [i175]Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, Thomas Scialom:
Toolformer: Language Models Can Teach Themselves to Use Tools. CoRR abs/2302.04761 (2023) - [i174]Marjan Ghazvininejad, Hila Gonen, Luke Zettlemoyer:
Dictionary-based Phrase-level Prompting of Large Language Models for Machine Translation. CoRR abs/2302.07856 (2023) - [i173]Bhargavi Paranjape, Scott M. Lundberg, Sameer Singh, Hannaneh Hajishirzi, Luke Zettlemoyer, Marco Túlio Ribeiro:
ART: Automatic multi-step reasoning and tool-use for large language models. CoRR abs/2303.09014 (2023) - [i172]Suchin Gururangan, Margaret Li, Mike Lewis, Weijia Shi, Tim Althoff, Noah A. Smith, Luke Zettlemoyer:
Scaling Expert Language Models with Unsupervised Domain Discovery. CoRR abs/2303.14177 (2023) - [i171]Mitchell Wortsman, Tim Dettmers, Luke Zettlemoyer, Ari Morcos, Ali Farhadi, Ludwig Schmidt:
Stable and low-precision training for large-scale vision-language models. CoRR abs/2304.13013 (2023) - [i170]Haoqiang Kang, Terra Blevins, Luke Zettlemoyer:
Translate to Disambiguate: Zero-shot Multilingual Word Sense Disambiguation with Pretrained Language Models. CoRR abs/2304.13803 (2023) - [i169]Lili Yu, Daniel Simig, Colin Flaherty, Armen Aghajanyan, Luke Zettlemoyer, Mike Lewis:
MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers. CoRR abs/2305.07185 (2023) - [i168]Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. CoRR abs/2305.11206 (2023) - [i167]Mikel Artetxe, Vedanuj Goswami, Shruti Bhosale, Angela Fan, Luke Zettlemoyer:
Revisiting Machine Translation for Cross-lingual Classification. CoRR abs/2305.14240 (2023) - [i166]Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi:
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. CoRR abs/2305.14251 (2023) - [i165]Tim Dettmers, Artidoro Pagnoni, Ari Holtzman, Luke Zettlemoyer:
QLoRA: Efficient Finetuning of Quantized LLMs. CoRR abs/2305.14314 (2023) - [i164]Chenglei Si, Weijia Shi, Chen Zhao, Luke Zettlemoyer, Jordan L. Boyd-Graber:
Mixture of Prompt Experts for Generalizable and Interpretable Question Answering. CoRR abs/2305.14628 (2023) - [i163]Weijia Shi, Xiaochuang Han, Mike Lewis, Yulia Tsvetkov, Luke Zettlemoyer, Scott Wen-tau Yih:
Trusting Your Evidence: Hallucinate Less with Context-aware Decoding. CoRR abs/2305.14739 (2023) - [i162]Ari Holtzman, Peter West, Luke Zettlemoyer:
Generative Models as a Complex Systems Science: How can we make sense of large language model behavior? CoRR abs/2308.00189 (2023) - [i161]Sewon Min, Suchin Gururangan, Eric Wallace, Hannaneh Hajishirzi, Noah A. Smith, Luke Zettlemoyer:
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore. CoRR abs/2308.04430 (2023) - [i160]Tianlu Wang, Ping Yu, Xiaoqing Ellen Tan, Sean O'Brien, Ramakanth Pasunuru, Jane Dwivedi-Yu, Olga Golovneva, Luke Zettlemoyer, Maryam Fazel-Zarandi, Asli Celikyilmaz:
Shepherd: A Critic for Language Model Generation. CoRR abs/2308.04592 (2023) - [i159]Xian Li, Ping Yu, Chunting Zhou, Timo Schick, Luke Zettlemoyer, Omer Levy, Jason Weston, Mike Lewis:
Self-Alignment with Instruction Backtranslation. CoRR abs/2308.06259 (2023) - [i158]Benjamin Muller, Belen Alastruey, Prangthip Hansanti, Elahe Kalbassi, Christophe Ropers, Eric Michael Smith, Adina Williams, Luke Zettlemoyer, Pierre Andrews, Marta R. Costa-jussà:
The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages. CoRR abs/2308.16871 (2023) - [i157]Lucas Bandarkar, Davis Liang, Benjamin Muller, Mikel Artetxe, Satya Narayan Shukla, Donald Husa, Naman Goyal, Abhinandan Krishnan, Luke Zettlemoyer, Madian Khabsa:
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants. CoRR abs/2308.16884 (2023) - [i156]Lili Yu, Bowen Shi, Ramakanth Pasunuru, Benjamin Muller, Olga Golovneva, Tianlu Wang, Arun Babu, Binh Tang, Brian Karrer, Shelly Sheynin, Candace Ross, Adam Polyak, Russell Howes, Vasu Sharma, Puxin Xu, Hovhannes Tamoyan, Oron Ashual, Uriel Singer, Shang-Wen Li, Susan Zhang, Richard James, Gargi Ghosh, Yaniv Taigman, Maryam Fazel-Zarandi, Asli Celikyilmaz, Luke Zettlemoyer, Armen Aghajanyan:
Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. CoRR abs/2309.02591 (2023) - [i155]Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer:
Demystifying CLIP Data. CoRR abs/2309.16671 (2023) - [i154]Xi Victoria Lin, Xilun Chen, Mingda Chen, Weijia Shi, Maria Lomeli, Rich James, Pedro Rodriguez, Jacob Kahn, Gergely Szilvasy, Mike Lewis, Luke Zettlemoyer, Scott Yih:
RA-DIT: Retrieval-Augmented Dual Instruction Tuning. CoRR abs/2310.01352 (2023) - [i153]Weijia Shi, Sewon Min, Maria Lomeli, Chunting Zhou, Margaret Li, Xi Victoria Lin, Noah A. Smith, Luke Zettlemoyer, Scott Yih, Mike Lewis:
In-Context Pretraining: Language Modeling Beyond Document Boundaries. CoRR abs/2310.10638 (2023) - [i152]Joel Jang, Seungone Kim, Bill Yuchen Lin, Yizhong Wang, Jack Hessel, Luke Zettlemoyer, Hannaneh Hajishirzi, Yejin Choi, Prithviraj Ammanabrolu:
Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging. CoRR abs/2310.11564 (2023) - [i151]