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2020 – today
- 2026
[c11]Jinjian Liu, Yichuan Wang, Xinxi Lyu, Rulin Shao, Joseph E. Gonzalez, Matei Zaharia, Sewon Min:
DS SERVE: A Framework for Efficient and Scalable Neural Retrieval. AAAI 2026: 41631-41633- [i27]Jinjian Liu, Yichuan Wang, Xinxi Lyu, Rulin Shao, Joseph E. Gonzalez, Matei Zaharia, Sewon Min:
DS SERVE: A Framework for Efficient and Scalable Neural Retrieval. CoRR abs/2602.22224 (2026) - 2025
- [c10]Mingda Chen, Yang Li, Karthik Padthe, Rulin Shao, Alicia Yi Sun, Luke Zettlemoyer, Gargi Ghosh, Wen-tau Yih:
Improving Factuality with Explicit Working Memory. ACL (1) 2025: 11199-11213 - [c9]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al.:
Language models scale reliably with over-training and on downstream tasks. ICLR 2025 - [c8]Pei Chen, Hongye Jin, Cheng-Che Lee, Rulin Shao, Jingfeng Yang, Mingyu Zhao, Zhaoyu Zhang, Qin Lu, Kaiwen Men, Ning Xie, Huasheng Li, Bing Yin, Han Li, Lingyun Wang:
LongLeader: A Comprehensive Leaderboard for Large Language Models in Long-context Scenarios. NAACL (Long Papers) 2025: 8734-8750 - [i26]Xindi Wu, Mengzhou Xia, Rulin Shao, Zhiwei Deng, Pang Wei Koh, Olga Russakovsky:
ICONS: Influence Consensus for Vision-Language Data Selection. CoRR abs/2501.00654 (2025) - [i25]Chien-Yu Lin, Keisuke Kamahori, Yiyu Liu, Xiaoxiang Shi, Madhav Mahesh Kashyap
, Yile Gu, Rulin Shao, Zihao Ye, Kan Zhu, Stephanie Wang, Arvind Krishnamurthy, Rohan Kadekodi, Luis Ceze, Baris Kasikci:
TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval. CoRR abs/2502.20969 (2025) - [i24]Rulin Shao, Rui Qiao, Varsha Kishore, Niklas Muennighoff, Xi Victoria Lin, Daniela Rus, Bryan Kian Hsiang Low, Sewon Min, Wen-tau Yih, Pang Wei Koh, Luke Zettlemoyer:
ReasonIR: Training Retrievers for Reasoning Tasks. CoRR abs/2504.20595 (2025) - [i23]Rulin Shao, Shuyue Stella Li, Rui Xin, Scott Geng, Yiping Wang, Sewoong Oh, Simon Shaolei Du, Nathan Lambert, Sewon Min, Ranjay Krishna, Yulia Tsvetkov, Hannaneh Hajishirzi, Pang Wei Koh, Luke Zettlemoyer:
Spurious Rewards: Rethinking Training Signals in RLVR. CoRR abs/2506.10947 (2025) - [i22]Xinxi Lyu, Michael Duan, Rulin Shao, Pang Wei Koh, Sewon Min:
Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks. CoRR abs/2507.01297 (2025) - [i21]Xilun Chen, Ilia Kulikov, Vincent-Pierre Berges, Barlas Oguz, Rulin Shao, Gargi Ghosh, Jason Weston, Wen-tau Yih:
Learning to Reason for Factuality. CoRR abs/2508.05618 (2025) - [i20]Zhepei Wei, Xiao Yang, Kai Sun, Jiaqi Wang, Rulin Shao, Sean Chen, Mohammad Kachuee, Teja Gollapudi, Tony Liao, Nicolas Scheffer, Rakesh Wanga, Anuj Kumar, Yu Meng, Wen-tau Yih, Xin Luna Dong:
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning. CoRR abs/2509.25760 (2025) - [i19]Shicheng Liu, Kai Sun, Lisheng Fu, Xilun Chen, Xinyuan Zhang, Zhaojiang Lin, Rulin Shao, Yue Liu, Anuj Kumar, Wen-tau Yih, Xin Luna Dong:
SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning. CoRR abs/2510.01832 (2025) - [i18]Rulin Shao, Akari Asai, Shannon Zejiang Shen, Hamish Ivison, Varsha Kishore, Jingming Zhuo, Xinran Zhao, Molly Park, Samuel G. Finlayson, David A. Sontag, Tyler Murray, Sewon Min, Pradeep Dasigi, Luca Soldaini, Faeze Brahman, Wen-tau Yih, Tongshuang Wu, Luke Zettlemoyer, Yoon Kim, Hannaneh Hajishirzi, Pang Wei Koh:
DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research. CoRR abs/2511.19399 (2025) - [i17]Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, David Graham, David Heineman, Dirk Groeneveld, Faeze Brahman, Finbarr Timbers, Hamish Ivison, Jacob Morrison, Jake Poznanski, Kyle Lo, Luca Soldaini, Matt Jordan, Mayee F. Chen, Michael Noukhovitch, Nathan Lambert, Pete Walsh, Pradeep Dasigi, Robert Berry, Saumya Malik, Saurabh Shah, Scott Geng, Shane Arora, Shashank Gupta, Taira Anderson, Teng Xiao, Tyler Murray, Tyler Romero, Victoria Graf, Akari Asai, Akshita Bhagia, Alexander Wettig, Alisa Liu, Aman Rangapur, Chloe Anastasiades, Costa Huang, Dustin Schwenk, Harsh Trivedi, Ian Magnusson, Jaron Lochner, Jiacheng Liu, Lester James V. Miranda, Maarten Sap, Malia Morgan, Michael Schmitz, Michal Guerquin, Michael Wilson, Regan Huff, Ronan Le Bras, Rui Xin, Rulin Shao, Sam Skjonsberg, Shannon Zejiang Shen, Shuyue Stella Li, Tucker Wilde, Valentina Pyatkin, William Merrill, Yapei Chang, Yuling Gu, Zhiyuan Zeng, Ashish Sabharwal, Luke Zettlemoyer, Pang Wei Koh, Ali Farhadi, Noah A. Smith, Hannaneh Hajishirzi:
Olmo 3. CoRR abs/2512.13961 (2025) - 2024
- [c7]Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin, Yu Cheng, Qifan Wang, Lifu Huang:
Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning. ACL (Findings) 2024: 15271-15342 - [c6]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar Guha, Sedrick Scott Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee F. 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, Alex Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar:
DataComp-LM: In search of the next generation of training sets for language models. NeurIPS 2024 - [c5]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. NeurIPS 2024 - [i16]Zhiyang Xu, Chao Feng, Rulin Shao, Trevor Ashby, Ying Shen, Di Jin, Yu Cheng, Qifan Wang, Lifu Huang:
Vision-Flan: Scaling Human-Labeled Tasks in Visual Instruction Tuning. CoRR abs/2402.11690 (2024) - [i15]Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Jenia Jitsev, Alexandros G. Dimakis, Gabriel Ilharco, Shuran Song, Thomas Kollar, Yair Carmon, Achal Dave, Reinhard Heckel, Niklas Muennighoff, Ludwig Schmidt:
Language models scale reliably with over-training and on downstream tasks. CoRR abs/2403.08540 (2024) - [i14]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 F. 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) - [i13]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) - [i12]Jingyuan Qi, Zhiyang Xu, Rulin Shao, Yang Chen, Di Jin, Yu Cheng, Qifan Wang, Lifu Huang:
RoRA-VLM: Robust Retrieval-Augmented Vision Language Models. CoRR abs/2410.08876 (2024) - [i11]Akari Asai, Jacqueline He, Rulin Shao, Weijia Shi, Amanpreet Singh, Joseph Chee Chang, Kyle Lo, Luca Soldaini, Sergey Feldman, Mike D'Arcy, David Wadden, Matt Latzke, Minyang Tian, Pan Ji, Shengyan Liu, Hao Tong, Bohao Wu, Yanyu Xiong, Luke Zettlemoyer, Graham Neubig, Daniel S. Weld, Doug Downey, Wen-tau Yih, Pang Wei Koh, Hannaneh Hajishirzi:
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs. CoRR abs/2411.14199 (2024) - [i10]Mingda Chen, Yang Li, Karthik Padthe, Rulin Shao, Alicia Sun, Luke Zettlemoyer, Gargi Gosh, Wen-tau Yih:
Improving Factuality with Explicit Working Memory. CoRR abs/2412.18069 (2024) - 2023
- [c4]Rohan Pandey, Rulin Shao, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment. ACL (1) 2023: 5444-5455 - [c3]Dacheng Li, Hongyi Wang, Rulin Shao, Han Guo, Eric P. Xing, Hao Zhang:
MPCFORMER: Fast, Performant and Provate Transformer Inference with MPC. ICLR 2023 - [c2]Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt:
VisIT-Bench: A Dynamic Benchmark for Evaluating Instruction-Following Vision-and-Language Models. NeurIPS 2023 - [i9]Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt:
VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use. CoRR abs/2308.06595 (2023) - [i8]Dacheng Li, Rulin Shao, Anze Xie, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica, Xuezhe Ma, Hao Zhang:
LightSeq: Sequence Level Parallelism for Distributed Training of Long Context Transformers. CoRR abs/2310.03294 (2023) - 2022
- [j1]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
On the Adversarial Robustness of Vision Transformers. Trans. Mach. Learn. Res. 2022 (2022) - [c1]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
Robust Text CAPTCHAs Using Adversarial Examples. IEEE Big Data 2022: 1495-1504 - [i7]Dacheng Li, Rulin Shao, Hongyi Wang, Han Guo, Eric P. Xing, Hao Zhang:
MPCFormer: fast, performant and private Transformer inference with MPC. CoRR abs/2211.01452 (2022) - [i6]Rohan Pandey, Rulin Shao, Paul Pu Liang, Ruslan Salakhutdinov, Louis-Philippe Morency:
Cross-modal Attention Congruence Regularization for Vision-Language Relation Alignment. CoRR abs/2212.10549 (2022) - 2021
- [i5]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
Robust Text CAPTCHAs Using Adversarial Examples. CoRR abs/2101.02483 (2021) - [i4]Rulin Shao, Zhouxing Shi, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
On the Adversarial Robustness of Visual Transformers. CoRR abs/2103.15670 (2021) - [i3]Rulin Shao, Jinfeng Yi, Pin-Yu Chen, Cho-Jui Hsieh:
How and When Adversarial Robustness Transfers in Knowledge Distillation? CoRR abs/2110.12072 (2021)
2010 – 2019
- 2019
- [i2]Rulin Shao, Hui Liu, Dianbo Liu:
Privacy Preserving Stochastic Channel-Based Federated Learning with Neural Network Pruning. CoRR abs/1910.02115 (2019) - [i1]Rulin Shao, Hongyu He, Hui Liu, Dianbo Liu:
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving. CoRR abs/1910.11160 (2019)
Coauthor Index
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last updated on 2026-03-31 00:32 CEST by the dblp team
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