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ORCIDJulian J. McAuley
Julian John McAuley
Person information
- affiliation: University of California, San Diego, Department of Computer Science and Engineering, CA, USA
- affiliation: Stanford University, InfoLab, CA, USA
- affiliation: NICTA, Canberra, Australia
- affiliation: Australian National University, Research School of Information Sciences and Engineering, Australia
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2020 – today
- 2025
[j17]Shuyang Li
, Bodhisattwa Prasad Majumder, Julian J. McAuley:
Self-Supervised Bot Play for Transcript-Free Conversational Critiquing with Rationales. Trans. Recomm. Syst. 3(1): 7:1-7:20 (2025)- 2024
- [j16]Yashar Deldjoo, Fatemeh Nazary, Arnau Ramisa, Julian J. McAuley, Giovanni Pellegrini, Alejandro Bellogín, Tommaso Di Noia:
A Review of Modern Fashion Recommender Systems. ACM Comput. Surv. 56(4): 87:1-87:37 (2024) - [j15]Lina Yao, Julian J. McAuley, Xianzhi Wang, Dietmar Jannach:
Special Issue on Responsible Recommender Systems Part 1. ACM Trans. Intell. Syst. Technol. 15(4): 72:1-72:3 (2024) - [j14]Zhe Liu, Yun Li, Lina Yao, Julian J. McAuley, Sam Dixon:
Rethink, Revisit, Revise: A Spiral Reinforced Self-Revised Network for Zero-Shot Learning. IEEE Trans. Neural Networks Learn. Syst. 35(1): 657-669 (2024) - [c203]Yu Wang, Zexue He, Zhankui He, Hao Xu, Julian J. McAuley:
Deciphering Compatibility Relationships with Textual Descriptions via Extraction and Explanation. AAAI 2024: 9133-9141 - [c202]Zeyuan Zhang, Tanmay Laud, Zihang He, Xiaojie Chen, Xinshuang Liu, Zhouhang Xie, Julian J. McAuley, Zhankui He:
RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface. AAAI 2024: 23856-23858 - [c201]Canwen Xu, Yichong Xu, Shuohang Wang, Yang Liu, Chenguang Zhu, Julian J. McAuley:
Small Models are Valuable Plug-ins for Large Language Models. ACL (Findings) 2024: 283-294 - [c200]Zhouhang Xie, Bodhisattwa Prasad Majumder, Mengjie Zhao, Yoshinori Maeda, Keiichi Yamada, Hiromi Wakaki, Julian J. McAuley:
Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning. ACL (Findings) 2024: 13207-13219 - [c199]Jianing Wang, Junda Wu, Yupeng Hou, Yao Liu, Ming Gao, Julian J. McAuley:
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment. ACL (Findings) 2024: 13492-13510 - [c198]Junda Wu, Tong Yu, Xiang Chen, Haoliang Wang, Ryan A. Rossi, Sungchul Kim, Anup B. Rao, Julian J. McAuley:
DeCoT: Debiasing Chain-of-Thought for Knowledge-Intensive Tasks in Large Language Models via Causal Intervention. ACL (1) 2024: 14073-14087 - [c197]Yupeng Hou, Junjie Zhang, Zihan Lin, Hongyu Lu, Ruobing Xie, Julian J. McAuley, Wayne Xin Zhao:
Large Language Models are Zero-Shot Rankers for Recommender Systems. ECIR (2) 2024: 364-381 - [c196]Tianyang Liu, Canwen Xu, Julian J. McAuley:
RepoBench: Benchmarking Repository-Level Code Auto-Completion Systems. ICLR 2024 - [c195]Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Zichao Yang, Eric P. Xing, Zhiting Hu:
Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding. ICML 2024 - [c194]Paarth Neekhara, Shehzeen Samarah Hussain, Rafael Valle, Boris Ginsburg, Rishabh Ranjan, Shlomo Dubnov, Farinaz Koushanfar, Julian J. McAuley:
SelfVC: Voice Conversion With Iterative Refinement using Self Transformations. ICML 2024 - [c193]Zachary Novack, Julian J. McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan:
DITTO: Diffusion Inference-Time T-Optimization for Music Generation. ICML 2024 - [c192]Yu Wang, Yifan Gao, Xiusi Chen, Haoming Jiang, Shiyang Li, Jingfeng Yang, Qingyu Yin, Zheng Li, Xian Li, Bing Yin, Jingbo Shang, Julian J. McAuley:
MEMORYLLM: Towards Self-Updatable Large Language Models. ICML 2024 - [c191]Junda Wu, Cheng-Chun Chang, Tong Yu, Zhankui He, Jianing Wang, Yupeng Hou, Julian J. McAuley:
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation. KDD 2024: 3391-3401 - [c190]Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano:
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). KDD 2024: 6448-6458 - [c189]Narges Tabari, Aniket Anand Deshmukh, Wang-Cheng Kang, Hamed Zamani, Rashmi Gangadharaiah, Julian J. McAuley, George Karypis:
First Workshop on Generative AI for Recommender Systems and Personalization. KDD 2024: 6737-6738 - [c188]Canwen Xu, Corby Rosset, Ethan C. Chau, Luciano Del Corro, Shweti Mahajan, Julian J. McAuley, Jennifer Neville, Ahmed Awadallah, Nikhil Rao:
Automatic Pair Construction for Contrastive Post-training. NAACL-HLT (Findings) 2024: 149-162 - [c187]Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff, Julian J. McAuley:
Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation. NAACL-HLT 2024: 1490-1504 - [c186]Petros Karypis, Julian J. McAuley, George Karypis:
Extending Input Contexts of Language Models through Training on Segmented Sequences. NAACL-HLT (Findings) 2024: 3040-3052 - [c185]Yu Xia, Tong Yu, Zhankui He, Handong Zhao, Julian J. McAuley, Shuai Li:
Aligning as Debiasing: Causality-Aware Alignment via Reinforcement Learning with Interventional Feedback. NAACL-HLT 2024: 4684-4695 - [c184]Brendan Andrew Duncan, Surya Kallumadi, Taylor Berg-Kirkpatrick, Julian J. McAuley:
MAWI Rec: Leveraging Severe Weather Data in Recommendation. RecSys 2024: 850-854 - [c183]Zhouhang Xie, Junda Wu, Hyunsik Jeon, Zhankui He, Harald Steck, Rahul Jha, Dawen Liang, Nathan Kallus, Julian J. McAuley:
Neighborhood-Based Collaborative Filtering for Conversational Recommendation. RecSys 2024: 1045-1050 - [c182]Yashar Deldjoo, Julian J. McAuley, Scott Sanner, Pablo Castells, Shuai Zhang, Enrico Palumbo:
The 1st International Workshop on Risks, Opportunities, and Evaluation of Generative Models in Recommendation (ROEGEN). RecSys 2024: 1250-1252 - [c181]Huimin Zeng, Zhankui He, Zhenrui Yue, Julian J. McAuley, Dong Wang:
Fair Sequential Recommendation without User Demographics. SIGIR 2024: 395-404 - [c180]Jessica Maria Echterhoff, Aditya Melkote, Sujen Kancherla, Julian J. McAuley:
Avoiding Decision Fatigue with AI-Assisted Decision-Making. UMAP 2024: 1-11 - [c179]Jessica Maria Echterhoff, An Yan, Kyungtae Han, Amr Abdelraouf, Rohit Gupta, Julian J. McAuley:
Driving through the Concept Gridlock: Unraveling Explainability Bottlenecks in Automated Driving. WACV 2024: 7331-7340 - [c178]Zhenrui Yue, Yueqi Wang, Zhankui He, Huimin Zeng, Julian J. McAuley, Dong Wang:
Linear Recurrent Units for Sequential Recommendation. WSDM 2024: 930-938 - [c177]Jiarui Jin, Zexue He, Mengyue Yang, Weinan Zhang, Yong Yu, Jun Wang, Julian J. McAuley:
InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization. WWW 2024: 1350-1361 - [c176]Noveen Sachdeva, Lequn Wang, Dawen Liang, Nathan Kallus, Julian J. McAuley:
Off-Policy Evaluation for Large Action Spaces via Policy Convolution. WWW 2024: 3576-3585 - [c175]Junjie Zhang, Yupeng Hou, Ruobing Xie, Wenqi Sun, Julian J. McAuley, Wayne Xin Zhao, Leyu Lin, Ji-Rong Wen:
AgentCF: Collaborative Learning with Autonomous Language Agents for Recommender Systems. WWW 2024: 3679-3689 - [i195]Zachary Novack, Julian J. McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan:
DITTO: Diffusion Inference-Time T-Optimization for Music Generation. CoRR abs/2401.12179 (2024) - [i194]Jiarui Jin, Zexue He, Mengyue Yang, Weinan Zhang, Yong Yu, Jun Wang, Julian J. McAuley:
InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization. CoRR abs/2401.12553 (2024) - [i193]Sejoon Oh, Berk Ustun, Julian J. McAuley, Srijan Kumar:
FINEST: Stabilizing Recommendations by Rank-Preserving Fine-Tuning. CoRR abs/2402.03481 (2024) - [i192]Yu Wang, Xiusi Chen, Jingbo Shang, Julian J. McAuley:
MEMORYLLM: Towards Self-Updatable Large Language Models. CoRR abs/2402.04624 (2024) - [i191]Jianing Wang, Junda Wu, Yupeng Hou, Yao Liu, Ming Gao, Julian J. McAuley:
InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment. CoRR abs/2402.08785 (2024) - [i190]Noveen Sachdeva, Benjamin Coleman, Wang-Cheng Kang, Jianmo Ni, Lichan Hong, Ed H. Chi, James Caverlee, Julian J. McAuley, Derek Zhiyuan Cheng:
How to Train Data-Efficient LLMs. CoRR abs/2402.09668 (2024) - [i189]Chengkai Huang, Tong Yu, Kaige Xie, Shuai Zhang, Lina Yao, Julian J. McAuley:
Foundation Models for Recommender Systems: A Survey and New Perspectives. CoRR abs/2402.11143 (2024) - [i188]Yakun Chen, Kaize Shi, Zhangkai Wu, Juan Chen, Xianzhi Wang, Julian J. McAuley, Guandong Xu, Shui Yu:
A Temporally Disentangled Contrastive Diffusion Model for Spatiotemporal Imputation. CoRR abs/2402.11558 (2024) - [i187]Yu Wang, Zeyuan Zhang, Julian J. McAuley, Zexue He:
LVCHAT: Facilitating Long Video Comprehension. CoRR abs/2402.12079 (2024) - [i186]Zexue He, Leonid Karlinsky, Donghyun Kim, Julian J. McAuley, Dmitry Krotov, Rogério Feris:
CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory. CoRR abs/2402.13449 (2024) - [i185]Zeyuan Zhang, Tanmay Laud, Zihang He, Xiaojie Chen, Xinshuang Liu, Zhouhang Xie, Julian J. McAuley, Zhankui He:
RecWizard: A Toolkit for Conversational Recommendation with Modular, Portable Models and Interactive User Interface. CoRR abs/2402.15591 (2024) - [i184]Guangyi Liu, Yu Wang, Zeyu Feng, Qiyu Wu, Liping Tang, Yuan Gao, Zhen Li, Shuguang Cui, Julian J. McAuley, Eric P. Xing, Zichao Yang, Zhiting Hu:
Generating, Reconstructing, and Representing Discrete and Continuous Data: Generalized Diffusion with Learnable Encoding-Decoding. CoRR abs/2402.19009 (2024) - [i183]Anton Lozhkov, Raymond Li, Loubna Ben Allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman Jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian J. McAuley, Han Hu, Torsten Scholak, Sébastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, et al.:
StarCoder 2 and The Stack v2: The Next Generation. CoRR abs/2402.19173 (2024) - [i182]Jessica Maria Echterhoff, Yao Liu, Abeer Alessa, Julian J. McAuley, Zexue He:
Cognitive Bias in High-Stakes Decision-Making with LLMs. CoRR abs/2403.00811 (2024) - [i181]Yupeng Hou, Jiacheng Li, Zhankui He, An Yan, Xiusi Chen, Julian J. McAuley:
Bridging Language and Items for Retrieval and Recommendation. CoRR abs/2403.03952 (2024) - [i180]Junda Wu, Cheng-Chun Chang, Tong Yu, Zhankui He, Jianing Wang, Yupeng Hou, Julian J. McAuley:
CoRAL: Collaborative Retrieval-Augmented Large Language Models Improve Long-tail Recommendation. CoRR abs/2403.06447 (2024) - [i179]Xiaoyu Liu, Paiheng Xu, Junda Wu, Jiaxin Yuan, Yifan Yang, Yuhang Zhou, Fuxiao Liu, Tianrui Guan, Haoliang Wang, Tong Yu, Julian J. McAuley, Wei Ai, Furong Huang:
Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey. CoRR abs/2403.09606 (2024) - [i178]Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff, Julian J. McAuley:
Evaluating Large Language Models as Generative User Simulators for Conversational Recommendation. CoRR abs/2403.09738 (2024) - [i177]Zhouhang Xie, Bodhisattwa Prasad Majumder, Mengjie Zhao, Yoshinori Maeda, Keiichi Yamada, Hiromi Wakaki, Julian J. McAuley:
Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning. CoRR abs/2403.15737 (2024) - [i176]Yashar Deldjoo, Zhankui He, Julian J. McAuley, Anton Korikov, Scott Sanner, Arnau Ramisa, René Vidal, Maheswaran Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano:
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys). CoRR abs/2404.00579 (2024) - [i175]Yu Xia, Rui Wang, Xu Liu, Mingyan Li, Tong Yu, Xiang Chen, Julian J. McAuley, Shuai Li:
Beyond Chain-of-Thought: A Survey of Chain-of-X Paradigms for LLMs. CoRR abs/2404.15676 (2024) - [i174]An Yan, Zhengyuan Yang, Junda Wu, Wanrong Zhu, Jianwei Yang, Linjie Li, Kevin Lin, Jianfeng Wang, Julian J. McAuley, Jianfeng Gao, Lijuan Wang:
List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs. CoRR abs/2404.16375 (2024) - [i173]Zhiyu Zoey Chen, Jing Ma, Xinlu Zhang, Nan Hao, An Yan, Armineh Nourbakhsh, Xianjun Yang, Julian J. McAuley, Linda R. Petzold, William Yang Wang:
A Survey on Large Language Models for Critical Societal Domains: Finance, Healthcare, and Law. CoRR abs/2405.01769 (2024) - [i172]Zhankui He, Zhouhang Xie, Harald Steck, Dawen Liang, Rahul Jha, Nathan Kallus, Julian J. McAuley:
Reindex-Then-Adapt: Improving Large Language Models for Conversational Recommendation. CoRR abs/2405.12119 (2024) - [i171]Se-eun Yoon, Hyunsik Jeon, Julian J. McAuley:
Imagery as Inquiry: Exploring A Multimodal Dataset for Conversational Recommendation. CoRR abs/2405.14142 (2024) - [i170]Yu Wang, Ruihan Wu, Zexue He, Xiusi Chen, Julian J. McAuley:
Large Scale Knowledge Washing. CoRR abs/2405.16720 (2024) - [i169]Zihan Liu, Yupeng Hou, Julian J. McAuley:
Multi-Behavior Generative Recommendation. CoRR abs/2405.16871 (2024) - [i168]Zachary Novack, Julian J. McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan:
DITTO-2: Distilled Diffusion Inference-Time T-Optimization for Music Generation. CoRR abs/2405.20289 (2024) - [i167]Yueqi Wang, Zhankui He, Zhenrui Yue, Julian J. McAuley, Dong Wang:
Auto-Encoding or Auto-Regression? A Reality Check on Causality of Self-Attention-Based Sequential Recommenders. CoRR abs/2406.02048 (2024) - [i166]Nafis Sadeq, Zhouhang Xie, Byungkyu Kang, Prarit Lamba, Xiang Gao, Julian J. McAuley:
Mitigating Hallucination in Fictional Character Role-Play. CoRR abs/2406.17260 (2024) - [i165]Junda Wu, Zachary Novack, Amit Namburi, Jiaheng Dai, Hao-Wen Dong, Zhouhang Xie, Carol Chen, Julian J. McAuley:
Futga: Towards Fine-grained Music Understanding through Temporally-enhanced Generative Augmentation. CoRR abs/2407.20445 (2024) - [i164]Junda Wu, Xintong Li, Tong Yu, Yu Wang, Xiang Chen, Jiuxiang Gu, Lina Yao, Jingbo Shang, Julian J. McAuley:
CoMMIT: Coordinated Instruction Tuning for Multimodal Large Language Models. CoRR abs/2407.20454 (2024) - [i163]Hyunsik Jeon, Se-eun Yoon, Julian J. McAuley:
Calibration-Disentangled Learning and Relevance-Prioritized Reranking for Calibrated Sequential Recommendation. CoRR abs/2408.02156 (2024) - [i162]Se-eun Yoon, Ahmad Bin Rabiah, Zaid Alibadi, Surya Kallumadi, Julian J. McAuley:
Forecasting Live Chat Intent from Browsing History. CoRR abs/2408.04668 (2024) - [i161]Tingchen Fu, Yupeng Hou, Julian J. McAuley, Rui Yan:
Unlocking Decoding-time Controllability: Gradient-Free Multi-Objective Alignment with Contrastive Prompts. CoRR abs/2408.05094 (2024) - [i160]Anton Korikov, Scott Sanner, Yashar Deldjoo, Zhankui He, Julian J. McAuley, Arnau Ramisa, René Vidal, Mahesh Sathiamoorthy, Atoosa Kasirzadeh, Silvia Milano, Francesco Ricci:
Large Language Model Driven Recommendation. CoRR abs/2408.10946 (2024) - [i159]Ryotaro Shimizu, Yu Wang, Masanari Kimura, Yuki Hirakawa, Takashi Wada, Yuki Saito, Julian J. McAuley:
A Fashion Item Recommendation Model in Hyperbolic Space. CoRR abs/2409.02599 (2024) - 2023
- [j13]Xiaocong Chen, Lina Yao, Julian J. McAuley, Guanglin Zhou, Xianzhi Wang:
Deep reinforcement learning in recommender systems: A survey and new perspectives. Knowl. Based Syst. 264: 110335 (2023) - [j12]Noveen Sachdeva, Julian J. McAuley:
Data Distillation: A Survey. Trans. Mach. Learn. Res. 2023 (2023) - [j11]Yun Li, Zhe Liu, Xiaojun Chang, Julian J. McAuley, Lina Yao:
Diversity-Boosted Generalization-Specialization Balancing for Zero-Shot Learning. IEEE Trans. Multim. 25: 8372-8382 (2023) - [c174]Canwen Xu, Julian J. McAuley:
A Survey on Model Compression and Acceleration for Pretrained Language Models. AAAI 2023: 10566-10575 - [c173]Zhouhang Xie, Sameer Singh, Julian J. McAuley, Bodhisattwa Prasad Majumder:
Factual and Informative Review Generation for Explainable Recommendation. AAAI 2023: 13816-13824 - [c172]Zexue He, An Yan, Amilcare Gentili, Julian J. McAuley, Chun-Nan Hsu:
"Nothing Abnormal": Disambiguating Medical Reports via Contrastive Knowledge Infusion. AAAI 2023: 14232-14240 - [c171]Myeongjun Jang, Bodhisattwa Prasad Majumder, Julian J. McAuley, Thomas Lukasiewicz, Oana-Maria Camburu:
KNOW How to Make Up Your Mind! Adversarially Detecting and Alleviating Inconsistencies in Natural Language Explanations. ACL (2) 2023: 540-553 - [c170]Zexue He, Graeme Blackwood, Rameswar Panda, Julian J. McAuley, Rogério Feris:
Synthetic Pre-Training Tasks for Neural Machine Translation. ACL (Findings) 2023: 8080-8098 - [c169]Weihan Xu, Julian J. McAuley, Shlomo Dubnov, Hao-Wen Dong:
Equipping Pretrained Unconditional Music Transformers with Instrument and Genre Controls. IEEE Big Data 2023: 4512-4517 - [c168]Zhankui He, Zhouhang Xie, Rahul Jha, Harald Steck, Dawen Liang, Yesu Feng, Bodhisattwa Prasad Majumder, Nathan Kallus, Julian J. McAuley:
Large Language Models as Zero-Shot Conversational Recommenders. CIKM 2023: 720-730 - [c167]Zheng Chen, Ziyan Jiang, Fan Yang, Zhankui He, Yupeng Hou, Eunah Cho, Julian J. McAuley, Aram Galstyan, Xiaohua Hu, Jie Yang:
The First Workshop on Personalized Generative AI @ CIKM 2023: Personalization Meets Large Language Models. CIKM 2023: 5267-5270 - [c166]Diego Antognini, Shuyang Li, Boi Faltings, Julian J. McAuley:
Assistive Recipe Editing through Critiquing. EACL 2023: 375-384 - [c165]Canwen Xu, Julian J. McAuley:
A Survey on Dynamic Neural Networks for Natural Language Processing. EACL (Findings) 2023: 2325-2336 - [c164]Nafis Sadeq, Byungkyu Kang, Prarit Lamba, Julian J. McAuley:
Unsupervised Improvement of Factual Knowledge in Language Models. EACL 2023: 2952-2961 - [c163]Ryan Tran, Canwen Xu, Julian J. McAuley:
Spoiler Detection as Semantic Text Matching. EMNLP 2023: 6109-6113 - [c162]Canwen Xu, Daya Guo, Nan Duan, Julian J. McAuley:
Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on Self-Chat Data. EMNLP 2023: 6268-6278 - [c161]Zexue He, Yu Wang, An Yan, Yao Liu, Eric Y. Chang, Amilcare Gentili, Julian J. McAuley, Chun-Nan Hsu:
MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation. EMNLP 2023: 8725-8744 - [c160]Bodhisattwa Prasad Majumder, Zexue He, Julian J. McAuley:
InterFair: Debiasing with Natural Language Feedback for Fair Interpretable Predictions. EMNLP 2023: 9466-9471 - [c159]Hao-Wen Dong, Ke Chen, Shlomo Dubnov, Julian J. McAuley, Taylor Berg-Kirkpatrick:
Multitrack Music Transformer. ICASSP 2023: 1-5 - [c158]An Yan, Yu Wang, Yiwu Zhong, Chengyu Dong, Zexue He, Yujie Lu, William Yang Wang, Jingbo Shang, Julian J. McAuley:
Learning Concise and Descriptive Attributes for Visual Recognition. ICCV 2023: 3067-3077 - [c157]Hao-Wen Dong, Naoya Takahashi, Yuki Mitsufuji, Julian J. McAuley, Taylor Berg-Kirkpatrick:
CLIPSep: Learning Text-queried Sound Separation with Noisy Unlabeled Videos. ICLR 2023 - [c156]Daya Guo, Canwen Xu, Nan Duan, Jian Yin, Julian J. McAuley:
LongCoder: A Long-Range Pre-trained Language Model for Code Completion. ICML 2023: 12098-12107 - [c155]Zachary Novack, Julian J. McAuley, Zachary Chase Lipton, Saurabh Garg:
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. ICML 2023: 26342-26362 - [c154]Jean Erik Delanois, Aditya Ahuja, Giri P. Krishnan, Timothy Tadros, Julian J. McAuley, Maxim Bazhenov:
Improving Robustness of Convolutional Networks Through Sleep-Like Replay. ICMLA 2023: 257-264 - [c153]Jiacheng Li, Zhankui He, Jingbo Shang, Julian J. McAuley:
UCEpic: Unifying Aspect Planning and Lexical Constraints for Generating Explanations in Recommendation. KDD 2023: 1248-1257 - [c152]Jiacheng Li, Ming Wang, Jin Li, Jinmiao Fu, Xin Shen, Jingbo Shang, Julian J. McAuley:
Text Is All You Need: Learning Language Representations for Sequential Recommendation. KDD 2023: 1258-1267 - [c151]Shuchang Liu, Qingpeng Cai, Zhankui He, Bowen Sun, Julian J. McAuley, Dong Zheng, Peng Jiang, Kun Gai:
Generative Flow Network for Listwise Recommendation. KDD 2023: 1524-1534 - [c150]Xiquan Cui, Vachik S. Dave, Yi Su, Khalifeh Al Jadda, Srijan Kumar, Julian J. McAuley, Tao Ye, Stephen D. Guo, Chip Huyen:
3rd Workshop on Online and Adaptive Recommender Systems (OARS). KDD 2023: 5855-5856 - [c149]An Yan, Zhankui He, Jiacheng Li, Tianyang Zhang, Julian John McAuley:
Personalized Showcases: Generating Multi-Modal Explanations for Recommendations. SIGIR 2023: 2251-2255 - [c148]Hao-Wen Dong, Xiaoyu Liu, Jordi Pons, Gautam Bhattacharya, Santiago Pascual, Joan Serrà, Taylor Berg-Kirkpatrick, Julian J. McAuley:
CLIPSonic: Text-to-Audio Synthesis with Unlabeled Videos and Pretrained Language-Vision Models. WASPAA 2023: 1-5 - [c147]Zihao Li, Xianzhi Wang, Chao Yang, Lina Yao, Julian J. McAuley, Guandong Xu:
Exploiting Explicit and Implicit Item relationships for Session-based Recommendation. WSDM 2023: 553-561 - [c146]Canwen Xu, Julian J. McAuley, Penghan Wang:
Mirror: A Natural Language Interface for Data Querying, Summarization, and Visualization. WWW (Companion Volume) 2023: 49-52 - [c145]Brendan Andrew Duncan, Surya Kallumadi, Taylor Berg-Kirkpatrick, Julian J. McAuley:
Jointly modeling products and resource pages for task-oriented recommendation. WWW (Companion Volume) 2023: 432-436 - [c144]Yupeng Hou, Zhankui He, Julian J. McAuley, Wayne Xin Zhao:
Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders. WWW 2023: 1162-1171 - [i158]Noveen Sachdeva, Julian J. McAuley:
Data Distillation: A Survey. CoRR abs/2301.04272 (2023) - [i157]Zachary Novack, Saurabh Garg, Julian J. McAuley, Zachary C. Lipton:
CHiLS: Zero-Shot Image Classification with Hierarchical Label Sets. CoRR abs/2302.02551 (2023) - [i156]Canwen Xu, Julian J. McAuley, Penghan Wang:
Mirror: A Natural Language Interface for Data Querying, Summarization, and Visualization. CoRR abs/2303.08697 (2023) - [i155]