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Lichan Hong
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Publications
- 2024
- [i29]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) - [i28]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) - [i27]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) - 2023
- [c63]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 - [c62]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 - [c61]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 - [c60]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 - [c59]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 - [c58]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 - [c57]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 - [c56]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 - [i26]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) - [i25]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) - [i24]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) - [i23]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) - [i22]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) - [i21]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) - [i20]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) - [i19]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) - [i18]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) - [i17]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) - 2022
- [c55]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 - [c54]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 - [c53]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 - [i16]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) - [i15]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) - 2021
- [c52]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. AISTATS 2021: 928-936 - [c51]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Ting Chen, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi (Jay) Kang, Evan Ettinger:
Self-supervised Learning for Large-scale Item Recommendations. CIKM 2021: 4321-4330 - [c50]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Learning to Embed Categorical Features without Embedding Tables for Recommendation. KDD 2021: 840-850 - [c49]Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi:
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. NeurIPS 2021: 29335-29347 - [c48]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. WSDM 2021: 76-84 - [c47]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems. WWW 2021: 1785-1797 - [c46]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. WWW 2021: 2220-2231 - [i14]Hussein Hazimeh, Zhe Zhao, Aakanksha Chowdhery, Maheswaran Sathiamoorthy, Yihua Chen, Rahul Mazumder, Lichan Hong, Ed H. Chi:
DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning. CoRR abs/2106.03760 (2021) - 2020
- [c45]Ji Yang, Xinyang Yi, Derek Zhiyuan Cheng, Lichan Hong, Yang Li, Simon Xiaoming Wang, Taibai Xu, Ed H. Chi:
Mixed Negative Sampling for Learning Two-tower Neural Networks in Recommendations. WWW (Companion Volume) 2020: 441-447 - [c44]Jiaqi Ma, Zhe Zhao, Xinyang Yi, Ji Yang, Minmin Chen, Jiaxi Tang, Lichan Hong, Ed H. Chi:
Off-policy Learning in Two-stage Recommender Systems. WWW 2020: 463-473 - [c43]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. WWW (Companion Volume) 2020: 562-566 - [i13]Wang-Cheng Kang, Derek Zhiyuan Cheng, Ting Chen, Xinyang Yi, Dong Lin, Lichan Hong, Ed H. Chi:
Learning Multi-granular Quantized Embeddings for Large-Vocab Categorical Features in Recommender Systems. CoRR abs/2002.08530 (2020) - [i12]Jiaqi Ma, Xinyang Yi, Weijing Tang, Zhe Zhao, Lichan Hong, Ed H. Chi, Qiaozhu Mei:
Learning-to-Rank with Partitioned Preference: Fast Estimation for the Plackett-Luce Model. CoRR abs/2006.05067 (2020) - [i11]Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng, Felix X. Yu, Aditya Krishna Menon, Lichan Hong, Ed H. Chi, Steve Tjoa, Jieqi Kang, Evan Ettinger:
Self-supervised Learning for Deep Models in Recommendations. CoRR abs/2007.12865 (2020) - [i10]Yuyan Wang, Zhe Zhao, Bo Dai, Christopher Fifty, Dong Lin, Lichan Hong, Ed H. Chi:
Small Towers Make Big Differences. CoRR abs/2008.05808 (2020) - [i9]Zhe Chen, Yuyan Wang, Dong Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H. Chi, Claire Cui:
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems. CoRR abs/2008.07032 (2020) - [i8]Ruoxi Wang, Rakesh Shivanna, Derek Zhiyuan Cheng, Sagar Jain, Dong Lin, Lichan Hong, Ed H. Chi:
DCN-M: Improved Deep & Cross Network for Feature Cross Learning in Web-scale Learning to Rank Systems. CoRR abs/2008.13535 (2020) - [i7]Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Ting Chen, Lichan Hong, Ed H. Chi:
Deep Hash Embedding for Large-Vocab Categorical Feature Representations. CoRR abs/2010.10784 (2020) - [i6]Yin Zhang, Derek Zhiyuan Cheng, Tiansheng Yao, Xinyang Yi, Lichan Hong, Ed H. Chi:
A Model of Two Tales: Dual Transfer Learning Framework for Improved Long-tail Item Recommendation. CoRR abs/2010.15982 (2020) - 2019
- [c42]Jiaqi Ma, Zhe Zhao, Jilin Chen, Ang Li, Lichan Hong, Ed H. Chi:
SNR: Sub-Network Routing for Flexible Parameter Sharing in Multi-Task Learning. AAAI 2019: 216-223 - [c41]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson:
Efficient Training on Very Large Corpora via Gramian Estimation. ICLR (Poster) 2019 - [c40]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. KDD 2019: 2212-2220 - [c39]Zhe Zhao, Lichan Hong, Li Wei, Jilin Chen, Aniruddh Nath, Shawn Andrews, Aditee Kumthekar, Maheswaran Sathiamoorthy, Xinyang Yi, Ed H. Chi:
Recommending what video to watch next: a multitask ranking system. RecSys 2019: 43-51 - [c38]Xinyang Yi, Ji Yang, Lichan Hong, Derek Zhiyuan Cheng, Lukasz Heldt, Aditee Kumthekar, Zhe Zhao, Li Wei, Ed H. Chi:
Sampling-bias-corrected neural modeling for large corpus item recommendations. RecSys 2019: 269-277 - [i5]Alex Beutel, Jilin Chen, Tulsee Doshi, Hai Qian, Li Wei, Yi Wu, Lukasz Heldt, Zhe Zhao, Lichan Hong, Ed H. Chi, Cristos Goodrow:
Fairness in Recommendation Ranking through Pairwise Comparisons. CoRR abs/1903.00780 (2019) - 2018
- [j6]Amy X. Zhang, Jilin Chen, Wei Chai, Jinjun Xu, Lichan Hong, Ed H. Chi:
Evaluation and Refinement of Clustered Search Results with the Crowd. ACM Trans. Interact. Intell. Syst. 8(2): 14:1-14:28 (2018) - [c37]Jiaqi Ma, Zhe Zhao, Xinyang Yi, Jilin Chen, Lichan Hong, Ed H. Chi:
Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts. KDD 2018: 1930-1939 - [i4]Walid Krichene, Nicolas Mayoraz, Steffen Rendle, Li Zhang, Xinyang Yi, Lichan Hong, Ed H. Chi, John R. Anderson:
Efficient Training on Very Large Corpora via Gramian Estimation. CoRR abs/1807.07187 (2018) - 2016
- [c35]Shuo Chang, Peng Dai, Lichan Hong, Cheng Sheng, Tianjiao Zhang, Ed H. Chi:
AppGrouper: Knowledge-based Interactive Clustering Tool for App Search Results. IUI 2016: 348-358 - 2015
- [c33]Zhe Zhao, Zhiyuan Cheng, Lichan Hong, Ed Huai-hsin Chi:
Improving User Topic Interest Profiles by Behavior Factorization. WWW 2015: 1406-1416 - 2012
- [i1]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Who is Authoritative? Understanding Reputation Mechanisms in Quora. CoRR abs/1204.3724 (2012) - 2011
- [c32]Brent J. Hecht, Lichan Hong, Bongwon Suh, Ed H. Chi:
Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles. CHI 2011: 237-246 - [c31]Lichan Hong, Gregorio Convertino, Ed H. Chi:
Language Matters In Twitter: A Large Scale Study. ICWSM 2011 - [c30]Sharoda A. Paul, Lichan Hong, Ed H. Chi:
Is Twitter a Good Place for Asking Questions? A Characterization Study. ICWSM 2011 - 2010
- [c29]Gregorio Convertino, Sanjay Kairam, Lichan Hong, Bongwon Suh, Ed H. Chi:
Designing a cross-channel information management tool for workers in enterprise task forces. AVI 2010: 103-110 - [c28]Lichan Hong, Gregorio Convertino, Bongwon Suh, Ed H. Chi, Sanjay Kairam:
FeedWinnower: layering structures over collections of information streams. CHI 2010: 947-950 - [c27]Bongwon Suh, Lichan Hong, Peter Pirolli, Ed H. Chi:
Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network. SocialCom/PASSAT 2010: 177-184 - [c26]Michael S. Bernstein, Bongwon Suh, Lichan Hong, Jilin Chen, Sanjay Kairam, Ed H. Chi:
Eddi: interactive topic-based browsing of social status streams. UIST 2010: 303-312 - 2009
- [c24]Lichan Hong, Ed H. Chi:
Annotate once, appear anywhere: collective foraging for snippets of interest using paragraph fingerprinting. CHI 2009: 1791-1794 - [c23]Les Nelson, Christoph Held, Peter Pirolli, Lichan Hong, Diane J. Schiano, Ed H. Chi:
With a little help from my friends: examining the impact of social annotations in sensemaking tasks. CHI 2009: 1795-1798 - [c22]Gregorio Convertino, Lichan Hong, Les Nelson, Peter Pirolli, Ed H. Chi:
Activity Awareness and Social Sensemaking 2.0: Design of a Task Force Workspace. HCI (16) 2009: 128-137 - [c21]Les Nelson, Gregorio Convertino, Peter Pirolli, Lichan Hong, Ed H. Chi:
Impact on Performance and Process by a Social Annotation System: A Social Reading Experiment. HCI (16) 2009: 270-278 - 2008
- [c20]Lichan Hong, Ed Huai-hsin Chi, Raluca Budiu, Peter Pirolli, Les Nelson:
SparTag.us: a low cost tagging system for foraging of web content. AVI 2008: 65-72 - 2007
- [j5]Ed Huai-hsin Chi, Lichan Hong, Julie Heiser, Stuart K. Card, Michelle Gumbrecht:
ScentIndex and ScentHighlights: productive reading techniques for conceptually reorganizing subject indexes and highlighting passages. Inf. Vis. 6(1): 32-47 (2007) - [c19]Ed Huai-hsin Chi, Michelle Gumbrecht, Lichan Hong:
Visual Foraging of Highlighted Text: An Eye-Tracking Study. HCI (3) 2007: 589-598 - 2006
- [c17]Ed H. Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
Scentindex: Conceptually Reorganizing Subject Indexes for Reading. IEEE VAST 2006: 159-166 - 2005
- [c16]Lichan Hong, Ed Huai-hsin Chi, Stuart K. Card:
Annotating 3D electronic books. CHI Extended Abstracts 2005: 1463-1466 - [c15]Ed Huai-hsin Chi, Lichan Hong, Michelle Gumbrecht, Stuart K. Card:
ScentHighlights: highlighting conceptually-related sentences during reading. IUI 2005: 272-274 - 2004
- [c14]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a 3D electronic smart book. AVI 2004: 303-307 - [c13]Stuart K. Card, Lichan Hong, Jock D. Mackinlay, Ed Huai-hsin Chi:
3Book: a scalable 3D virtual book. CHI Extended Abstracts 2004: 1095-1098 - [c12]Ed Huai-hsin Chi, Lichan Hong, Julie Heiser, Stuart K. Card:
eBooks with indexes that reorganize conceptually. CHI Extended Abstracts 2004: 1223-1226
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last updated on 2024-03-26 21:44 CET by the dblp team
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