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Ed H. Chi
Ed Huai-hsin Chi – 紀懷新
Person information
- unicode name: 紀懷新
- affiliation: Google, Mountain View, CA, USA
- affiliation: Palo Alto Research Center (PARC), CA, USA
- affiliation (PhD 1999): University of Minnesota, Computer Science Department, Minneapolis, MN, USA
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2020 – today
- 2024
- [j24]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. J. Mach. Learn. Res. 25: 70:1-70:53 (2024) - [c192]Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed Huai-hsin Chi, Xinyang Yi:
Leveraging LLM Reasoning Enhances Personalized Recommender Systems. ACL (Findings) 2024: 13176-13188 - [c191]Xiao Ma
, Swaroop Mishra
, Ariel Liu
, Sophie Ying Su
, Jilin Chen
, Chinmay Kulkarni
, Heng-Tze Cheng
, Quoc V. Le
, Ed H. Chi:
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CHI Extended Abstracts 2024: 56:1-56:12 - [c190]Michihiro Yasunaga, Xinyun Chen, Yujia Li, Panupong Pasupat, Jure Leskovec, Percy Liang, Ed H. Chi, Denny Zhou:
Large Language Models as Analogical Reasoners. ICLR 2024 - [c189]Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou:
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. ICLR 2024 - [c188]Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. ICML 2024 - [c187]Yi Su
, Haokai Lu
, Yuening Li
, Liang Liu
, Shuchao Bi
, Ed H. Chi
, Minmin Chen
:
Multi-Task Neural Linear Bandit for Exploration in Recommender Systems. KDD 2024: 5723-5730 - [c186]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan Hulikal Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. NAACL-HLT (Findings) 2024: 1051-1066 - [c185]Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng:
SELF-DISCOVER: Large Language Models Self-Compose Reasoning Structures. NeurIPS 2024 - [c184]Nikhil Khani
, Li Wei
, Aniruddh Nath
, Shawn Andrews
, Shuo Yang
, Yang Liu
, Pendo Abbo
, Maciej Kula
, Jarrod Kahn
, Zhe Zhao
, Lichan Hong
, Ed H. Chi:
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. RecSys 2024: 758-761 - [c183]Zhen Zhang, Qingyun Liu, Yuening Li, Sourabh Bansod, Mingyan Gao, Yaping Zhang, Zhe Zhao, Lichan Hong, Ed H. Chi, Shuchao Bi, Liang Liu:
Co-optimize Content Generation and Consumption in a Large Scale Video Recommendation System. RecSys 2024: 762-764 - [c182]Noveen Sachdeva
, Benjamin Coleman
, Wang-Cheng Kang
, Jianmo Ni
, James Caverlee
, Lichan Hong
, Ed H. Chi, Derek Zhiyuan Cheng
:
Improving Data Efficiency for Recommenders and LLMs. RecSys 2024: 790-792 - [c181]Yin Zhang
, Ruoxi Wang
, Xiang Li
, Tiansheng Yao
, Andrew Evdokimov
, Jonathan Valverde
, Yuan Gao
, Jerry Zhang
, Evan Ettinger
, Ed H. Chi
, Derek Zhiyuan Cheng
:
Self-Auxiliary Distillation for Sample Efficient Learning in Google-Scale Recommenders. RecSys 2024: 829-831 - [c180]Yuening Li
, Diego Uribe
, Chuan He
, Jiaxi Tang
, Qingyun Liu
, Junjie Shan
, Ben Most
, Kaushik Kalyan
, Shuchao Bi
, Xinyang Yi
, Lichan Hong
, Ed H. Chi, Liang Liu
:
Short-form Video Needs Long-term Interests: An Industrial Solution for Serving Large User Sequence Models. RecSys 2024: 832-834 - [c179]Jianling Wang
, Haokai Lu
, Yifan Liu
, He Ma
, Yueqi Wang
, Yang Gu
, Shuzhou Zhang
, Ningren Han
, Shuchao Bi
, Lexi Baugher
, Ed H. Chi
, Minmin Chen
:
LLMs for User Interest Exploration in Large-scale Recommendation Systems. RecSys 2024: 872-877 - [c178]Anima Singh
, Trung Vu
, Nikhil Mehta
, Raghunandan H. Keshavan
, Maheswaran Sathiamoorthy
, Yilin Zheng
, Lichan Hong
, Lukasz Heldt
, Li Wei
, Devansh Tandon
, Ed H. Chi, Xinyang Yi
:
Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations. RecSys 2024: 1039-1044 - [c177]Yi Su
, Xiangyu Wang
, Elaine Ya Le
, Liang Liu
, Yuening Li
, Haokai Lu
, Benjamin Lipshitz
, Sriraj Badam
, Lukasz Heldt
, Shuchao Bi
, Ed H. Chi
, Cristos Goodrow
, Su-Lin Wu
, Lexi Baugher
, Minmin Chen
:
Long-Term Value of Exploration: Measurements, Findings and Algorithms. WSDM 2024: 636-644 - [c176]Bo Chang
, Changping Meng
, He Ma
, Shuo Chang
, Yang Gu
, Yajun Peng
, Jingchen Feng
, Yaping Zhang
, Shuchao Bi
, Ed H. Chi
, Minmin Chen
:
Cluster Anchor Regularization to Alleviate Popularity Bias in Recommender Systems. WWW (Companion Volume) 2024: 151-160 - [c175]Jianling Wang
, Haokai Lu
, James Caverlee
, Ed H. Chi
, Minmin Chen
:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. WWW (Companion Volume) 2024: 726-729 - [i91]Pei Zhou, Jay Pujara, Xiang Ren, Xinyun Chen, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou, Swaroop Mishra, Huaixiu Steven Zheng:
Self-Discover: Large Language Models Self-Compose Reasoning Structures. CoRR abs/2402.03620 (2024) - [i90]Yuji Roh, Qingyun Liu, Huan Gui, Zhe Yuan, Yujin Tang, Steven Euijong Whang, Liang Liu, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views. CoRR abs/2402.04644 (2024) - [i89]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) - [i88]Jianling Wang, Haokai Lu, James Caverlee, Ed H. Chi, Minmin Chen:
Large Language Models as Data Augmenters for Cold-Start Item Recommendation. CoRR abs/2402.11724 (2024) - [i87]Zichang Liu, Qingyun Liu, Yuening Li, Liang Liu, Anshumali Shrivastava, Shuchao Bi, Lichan Hong, Ed H. Chi, Zhe Zhao:
Wisdom of Committee: Distilling from Foundation Model to Specialized Application Model. CoRR abs/2402.14035 (2024) - [i86]Yuwei Cao, Nikhil Mehta, Xinyang Yi, Raghunandan H. Keshavan, Lukasz Heldt, Lichan Hong, Ed H. Chi, Maheswaran Sathiamoorthy:
Aligning Large Language Models with Recommendation Knowledge. CoRR abs/2404.00245 (2024) - [i85]Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo, Sriraj Badam, Ed H. Chi, Minmin Chen:
Diversifying by Intent in Recommender Systems. CoRR abs/2405.12327 (2024) - [i84]Jianling Wang, Haokai Lu, Yifan Liu, He Ma, Yueqi Wang, Yang Gu, Shuzhou Zhang, Ningren Han, Shuchao Bi, Lexi Baugher, Ed H. Chi, Minmin Chen:
LLMs for User Interest Exploration: A Hybrid Approach. CoRR abs/2405.16363 (2024) - [i83]Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou:
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR abs/2406.04520 (2024) - [i82]Alicia Tsai, Adam Kraft, Long Jin, Chenwei Cai, Anahita Hosseini, Taibai Xu, Zemin Zhang, Lichan Hong, Ed H. Chi, Xinyang Yi:
Leveraging LLM Reasoning Enhances Personalized Recommender Systems. CoRR abs/2408.00802 (2024) - [i81]Nikhil Khani, Shuo Yang, Aniruddh Nath, Yang Liu, Pendo Abbo, Li Wei, Shawn Andrews, Maciej Kula, Jarrod Kahn, Zhe Zhao, Lichan Hong, Ed H. Chi:
Bridging the Gap: Unpacking the Hidden Challenges in Knowledge Distillation for Online Ranking Systems. CoRR abs/2408.14678 (2024) - [i80]Kiran Vodrahalli, Santiago Ontanon, Nilesh Tripuraneni, Kelvin Xu, Sanil Jain, Rakesh Shivanna, Jeffrey Hui, Nishanth Dikkala, Mehran Kazemi, Bahare Fatemi, Rohan Anil, Ethan Dyer, Siamak Shakeri, Roopali Vij, Harsh Mehta, Vinay V. Ramasesh, Quoc Le, Ed H. Chi, Yifeng Lu, Orhan Firat, Angeliki Lazaridou, Jean-Baptiste Lespiau, Nithya Attaluri, Kate Olszewska:
Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries. CoRR abs/2409.12640 (2024) - [i79]Allen Nie, Yi Su, Bo Chang, Jonathan N. Lee, Ed H. Chi, Quoc V. Le, Minmin Chen:
EVOLvE: Evaluating and Optimizing LLMs For Exploration. CoRR abs/2410.06238 (2024) - [i78]Dong-Ho Lee, Adam Kraft, Long Jin, Nikhil Mehta, Taibai Xu, Lichan Hong, Ed H. Chi, Xinyang Yi:
STAR: A Simple Training-free Approach for Recommendations using Large Language Models. CoRR abs/2410.16458 (2024) - 2023
- [c174]Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei:
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. ACL (Findings) 2023: 13003-13051 - [c173]Qingyun Liu, Zhe Zhao, Liang Liu, Zhen Zhang, Junjie Shan
, Yuening Li
, Shuchao Bi
, Lichan Hong, Ed H. Chi:
Multitask Ranking System for Immersive Feed and No More Clicks: A Case Study of Short-Form Video Recommendation. CIKM 2023: 4709-4716 - [c172]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel:
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) 2023: 127-139 - [c171]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou:
Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR 2023 - [c170]Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi:
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR 2023 - [c169]Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou:
Large Language Models Can Be Easily Distracted by Irrelevant Context. ICML 2023: 31210-31227 - [c168]Jiaxi Tang
, Yoel Drori
, Daryl Chang
, Maheswaran Sathiamoorthy
, Justin Gilmer
, Li Wei
, Xinyang Yi
, Lichan Hong
, Ed H. Chi
:
Improving Training Stability for Multitask Ranking Models in Recommender Systems. KDD 2023: 4882-4893 - [c167]Jianling Wang
, Haokai Lu
, Sai Zhang
, Bart N. Locanthi
, Haoting Wang
, Dylan Greaves
, Benjamin Lipshitz
, Sriraj Badam
, Ed H. Chi
, Cristos J. Goodrow
, Su-Lin Wu
, Lexi Baugher
, Minmin Chen
:
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. KDD 2023: 5082-5091 - [c166]Yin Zhang
, Ruoxi Wang
, Derek Zhiyuan Cheng
, Tiansheng Yao
, Xinyang Yi
, Lichan Hong
, James Caverlee
, Ed H. Chi
:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). KDD 2023: 5608-5617 - [c165]Derek Zhiyuan Cheng
, Dhaval Patel
, Linsey Pang
, Sameep Mehta
, Kexin Xie
, Ed H. Chi
, Wei Liu
, Nitesh V. Chawla
, James Bailey
:
Foundations and Applications in Large-scale AI Models: Pre-training, Fine-tuning, and Prompt-based Learning. KDD 2023: 5853-5854 - [c164]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. NeurIPS 2023 - [c163]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan Hulikal Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Mahesh Sathiamoorthy:
Recommender Systems with Generative Retrieval. NeurIPS 2023 - [c162]Derek Zhiyuan Cheng
, Ruoxi Wang
, Wang-Cheng Kang
, Benjamin Coleman
, Yin Zhang
, Jianmo Ni
, Jonathan Valverde
, Lichan Hong
, Ed H. Chi:
Efficient Data Representation Learning in Google-scale Systems. RecSys 2023: 267-271 - [c161]Xinyang Yi
, Shao-Chuan Wang
, Ruining He
, Hariharan Chandrasekaran
, Charles Wu
, Lukasz Heldt
, Lichan Hong
, Minmin Chen
, Ed H. Chi
:
Online Matching: A Real-time Bandit System for Large-scale Recommendations. RecSys 2023: 403-414 - [c160]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML 2023: 365-376 - [c159]Kaize Ding
, Albert Jiongqian Liang
, Bryan Perozzi
, Ting Chen
, Ruoxi Wang
, Lichan Hong
, Ed H. Chi
, Huan Liu
, Derek Zhiyuan Cheng
:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. SIGIR 2023: 2062-2066 - [c158]Bo Chang
, Alexandros Karatzoglou
, Yuyan Wang
, Can Xu
, Ed H. Chi
, Minmin Chen
:
Latent User Intent Modeling for Sequential Recommenders. WWW (Companion Volume) 2023: 427-431 - [c157]Abhishek Naik
, Bo Chang
, Alexandros Karatzoglou
, Martin Mladenov
, Ed H. Chi
, Minmin Chen
:
Investigating Action-Space Generalization in Reinforcement Learning for Recommendation Systems. WWW (Companion Volume) 2023: 966-972 - [i77]Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed H. Chi, Nathanael Schärli, Denny Zhou:
Large Language Models Can Be Easily Distracted by Irrelevant Context. CoRR abs/2302.00093 (2023) - [i76]Jiaxi Tang, Yoel Drori, Daryl Chang, Maheswaran Sathiamoorthy, Justin Gilmer, Li Wei, Xinyang Yi, Lichan Hong, Ed H. Chi:
Improving Training Stability for Multitask Ranking Models in Recommender Systems. CoRR abs/2302.09178 (2023) - [i75]Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel:
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR abs/2302.11188 (2023) - [i74]Shashank Rajput, Nikhil Mehta, Anima Singh, Raghunandan H. Keshavan, Trung Vu, Lukasz Heldt, Lichan Hong, Yi Tay, Vinh Q. Tran, Jonah Samost, Maciej Kula, Ed H. Chi, Maheswaran Sathiamoorthy:
Recommender Systems with Generative Retrieval. CoRR abs/2305.05065 (2023) - [i73]Wang-Cheng Kang, Jianmo Ni, Nikhil Mehta, Maheswaran Sathiamoorthy, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction. CoRR abs/2305.06474 (2023) - [i72]Yi Su, Xiangyu Wang, Elaine Ya Le, Liang Liu, Yuening Li, Haokai Lu, Benjamin Lipshitz, Sriraj Badam, Lukasz Heldt, Shuchao Bi, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Value of Exploration: Measurements, Findings and Algorithms. CoRR abs/2305.07764 (2023) - [i71]Benjamin Coleman, Wang-Cheng Kang, Matthew Fahrbach, Ruoxi Wang, Lichan Hong, Ed H. Chi, Derek Zhiyuan Cheng:
Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems. CoRR abs/2305.12102 (2023) - [i70]Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel:
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR abs/2305.13535 (2023) - [i69]Konstantina Christakopoulou, Alberto Lalama, Cj Adams, Iris Qu, Yifat Amir, Samer Chucri, Pierce Vollucci, Fabio Soldo, Dina Bseiso, Sarah Scodel, Lucas Dixon, Ed H. Chi, Minmin Chen:
Large Language Models for User Interest Journeys. CoRR abs/2305.15498 (2023) - [i68]Kaize Ding, Albert Jiongqian Liang, Bryan Perozzi, Ting Chen, Ruoxi Wang, Lichan Hong, Ed H. Chi, Huan Liu, Derek Zhiyuan Cheng:
HyperFormer: Learning Expressive Sparse Feature Representations via Hypergraph Transformer. CoRR abs/2305.17386 (2023) - [i67]Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen:
Prompt Tuning Large Language Models on Personalized Aspect Extraction for Recommendations. CoRR abs/2306.01475 (2023) - [i66]Pan Li, Yuyan Wang, Ed H. Chi, Minmin Chen:
Hierarchical Reinforcement Learning for Modeling User Novelty-Seeking Intent in Recommender Systems. CoRR abs/2306.01476 (2023) - [i65]Jianling Wang, Haokai Lu, Sai Zhang, Bart N. Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen:
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. CoRR abs/2306.01720 (2023) - [i64]Anima Singh, Trung Vu, Raghunandan H. Keshavan, Nikhil Mehta, Xinyang Yi, Lichan Hong, Lukasz Heldt, Li Wei, Ed H. Chi, Maheswaran Sathiamoorthy:
Better Generalization with Semantic IDs: A case study in Ranking for Recommendations. CoRR abs/2306.08121 (2023) - [i63]Xinyang Yi, Shao-Chuan Wang, Ruining He, Hariharan Chandrasekaran, Charles Wu, Lukasz Heldt, Lichan Hong, Minmin Chen, Ed H. Chi:
Online Matching: A Real-time Bandit System for Large-scale Recommendations. CoRR abs/2307.15893 (2023) - [i62]Nikhil Mehta, Anima Singh, Xinyang Yi, Sagar Jain, Lichan Hong, Ed H. Chi:
Density Weighting for Multi-Interest Personalized Recommendation. CoRR abs/2308.01563 (2023) - [i61]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) - [i60]Zhe Zhao, Qingyun Liu, Huan Gui, Bang An, Lichan Hong, Ed H. Chi:
Talking Models: Distill Pre-trained Knowledge to Downstream Models via Interactive Communication. CoRR abs/2310.03188 (2023) - [i59]Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen, Heng-Tze Cheng, Ed H. Chi, Quoc V. Le, Denny Zhou:
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models. CoRR abs/2310.06117 (2023) - [i58]Huan Gui, Ruoxi Wang, Ke Yin, Long Jin, Maciej Kula, Taibai Xu, Lichan Hong, Ed H. Chi:
Hiformer: Heterogeneous Feature Interactions Learning with Transformers for Recommender Systems. CoRR abs/2311.05884 (2023) - [i57]Xiao Ma, Swaroop Mishra, Ariel Liu, Sophie Ying Su, Jilin Chen, Chinmay Kulkarni, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi:
Beyond ChatBots: ExploreLLM for Structured Thoughts and Personalized Model Responses. CoRR abs/2312.00763 (2023) - 2022
- [j23]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) - [c156]Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi:
HyperPrompt: Prompt-based Task-Conditioning of Transformers. ICML 2022: 8678-8690 - [c155]Yuyan Wang, Mohit Sharma, Can Xu, Sriraj Badam, Qian Sun, Lee Richardson, Lisa Chung, Ed H. Chi, Minmin Chen:
Surrogate for Long-Term User Experience in Recommender Systems. KDD 2022: 4100-4109 - [c154]Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi:
Improving Multi-Task Generalization via Regularizing Spurious Correlation. NeurIPS 2022 - [c153]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou:
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS 2022 - [c152]Minmin Chen, Can Xu, Vince Gatto, Devanshu Jain, Aviral Kumar, Ed H. Chi:
Off-Policy Actor-critic for Recommender Systems. RecSys 2022: 338-349 - [c151]Furkan Kocayusufoglu, Tao Wu, Anima Singh, Georgios Roumpos, Heng-Tze Cheng, Sagar Jain, Ed H. Chi, Ambuj K. Singh:
Multi-Resolution Attention for Personalized Item Search. WSDM 2022: 508-516 - [c150]Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen:
Learning to Augment for Casual User Recommendation. WWW 2022: 2183-2194 - [c149]Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Li Wei, Ed H. Chi:
Can Small Heads Help? Understanding and Improving Multi-Task Generalization. WWW 2022: 3009-3019 - [c148]Hongyi Wen, Xinyang Yi, Tiansheng Yao, Jiaxi Tang, Lichan Hong, Ed H. Chi:
Distributionally-robust Recommendations for Improving Worst-case User Experience. WWW 2022: 3606-3610 - [i56]Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Kathleen S. Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Agüera y Arcas, Claire Cui, Marian Croak, Ed H. Chi, Quoc Le:
LaMDA: Language Models for Dialog Applications. CoRR abs/2201.08239 (2022) - [i55]Bo Chang, Can Xu, Matthieu Lê, Jingchen Feng, Ya Le, Sriraj Badam, Ed H. Chi, Minmin Chen:
Recency Dropout for Recurrent Recommender Systems. CoRR abs/2201.11016 (2022) - [i54]Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, Denny Zhou:
Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR abs/2201.11903 (2022) - [i53]Kiran Vodrahalli, Rakesh Shivanna, Maheswaran Sathiamoorthy, Sagar Jain, Ed H. Chi:
Algorithms for Efficiently Learning Low-Rank Neural Networks. CoRR abs/2202.00834 (2022) - [i52]Yun He, Huaixiu Steven Zheng, Yi Tay, Jai Prakash Gupta, Yu Du, Vamsi Aribandi, Zhe Zhao, YaGuang Li, Zhao Chen, Donald Metzler, Heng-Tze Cheng, Ed H. Chi:
HyperPrompt: Prompt-based Task-Conditioning of Transformers. CoRR abs/2203.00759 (2022) - [i51]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR abs/2203.11171 (2022) - [i50]Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed H. Chi, Minmin Chen:
Learning to Augment for Casual User Recommendation. CoRR abs/2204.00926 (2022) - [i49]Ziniu Hu, Zhe Zhao, Xinyang Yi, Tiansheng Yao, Lichan Hong, Yizhou Sun, Ed H. Chi:
Improving Multi-Task Generalization via Regularizing Spurious Correlation. CoRR abs/2205.09797 (2022) - [i48]Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi:
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR abs/2205.10625 (2022) - [i47]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) - [i46]Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou:
Rationale-Augmented Ensembles in Language Models. CoRR abs/2207.00747 (2022) - [i45]Konstantina Christakopoulou, Can Xu, Sai Zhang, Sriraj Badam, Trevor Potter, Daniel Li, Hao Wan, Xinyang Yi, Ya Le, Chris Berg, Eric Bencomo Dixon, Ed H. Chi, Minmin Chen:
Reward Shaping for User Satisfaction in a REINFORCE Recommender. CoRR abs/2209.15166 (2022) - [i44]Flavien Prost, Ben Packer, Jilin Chen, Li Wei, Pierre Kremp, Nick Blumm, Susan Wang, Tulsee Doshi, Tonia Osadebe, Lukasz Heldt, Ed H. Chi, Alex Beutel:
Simpson's Paradox in Recommender Fairness: Reconciling differences between per-user and aggregated evaluations. CoRR abs/2210.07755 (2022) - [i43]Mirac Suzgun, Nathan Scales, Nathanael Schärli, Sebastian Gehrmann, Yi Tay, Hyung Won Chung, Aakanksha Chowdhery, Quoc V. Le, Ed H. Chi, Denny Zhou, Jason Wei:
Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them. CoRR abs/2210.09261 (2022) - [i42]Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei:
Scaling Instruction-Finetuned Language Models. CoRR abs/2210.11416 (2022) - [i41]Yin Zhang, Ruoxi Wang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, James Caverlee, Ed H. Chi:
Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN). CoRR abs/2210.14309 (2022) - [i40]Bo Chang, Alexandros Karatzoglou, Yuyan Wang, Can Xu, Ed H. Chi, Minmin Chen:
Latent User Intent Modeling for Sequential Recommenders. CoRR abs/2211.09832 (2022) - 2021
- [c147]Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter