Sheng Shen

According to our database, Sheng Shen authored at least 51 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Efficient and Scalable Large Multimodal Models

Sheng Shen

PhD thesis, 2024

BLIP3-KALE: Knowledge Augmented Large-Scale Dense Captions.

Anas Awadalla, Le Xue, Manli Shu, An Yan, Jun Wang, Senthil Purushwalkam, Sheng Shen, Hannah Lee, Oscar Lo, Jae Sung Park, Etash Kumar Guha, Silvio Savarese, Ludwig Schmidt, Yejin Choi, Caiming Xiong, Ran Xu

CoRR, 2024

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens.

Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Matt Jordan, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt

CoRR, 2024

Enhancing Large Vision Language Models with Self-Training on Image Comprehension.

Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, James Zou, Kai-Wei Chang, Wei Wang

CoRR, 2024

RAFT: Adapting Language Model to Domain Specific RAG.

Tianjun Zhang, Shishir G. Patil, Naman Jain, Sheng Shen, Matei Zaharia, Ion Stoica, Joseph E. Gonzalez

CoRR, 2024

Multitask Vision-Language Prompt Tuning.

Sheng Shen, Shijia Yang, Tianjun Zhang, Bohan Zhai, Joseph E. Gonzalez, Kurt Keutzer, Trevor Darrell

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Enhancing Large Vision Language Models with Self-Training on Image Comprehension.

Yihe Deng, Pan Lu, Fan Yin, Ziniu Hu, Sheng Shen, Quanquan Gu, James Y. Zou, Kai-Wei Chang, Wei Wang

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens.

Anas Awadalla, Le Xue, Oscar Lo, Manli Shu, Hannah Lee, Etash Kumar Guha, Sheng Shen, Mohamed Awadalla, Silvio Savarese, Caiming Xiong, Ran Xu, Yejin Choi, Ludwig Schmidt

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

SqueezeLLM: Dense-and-Sparse Quantization.

Sehoon Kim, Coleman Hooper, Amir Gholami, Zhen Dong, Xiuyu Li, Sheng Shen, Michael W. Mahoney, Kurt Keutzer

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models.

Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

AgentBench: Evaluating LLMs as Agents.

Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Aligning Large Multimodal Models with Factually Augmented RLHF.

Zhiqing Sun, Sheng Shen, Shengcao Cao, Haotian Liu, Chunyuan Li, Yikang Shen, Chuang Gan, Liangyan Gui, Yu-Xiong Wang, Yiming Yang, Kurt Keutzer, Trevor Darrell

Proceedings of the Findings of the Association for Computational Linguistics, 2024

LLM2LLM: Boosting LLMs with Novel Iterative Data Enhancement.

Nicholas Lee, Thanakul Wattanawong, Sehoon Kim, Karttikeya Mangalam, Sheng Shen, Gopala Anumanchipalli, Michael W. Mahoney, Kurt Keutzer, Amir Gholami

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

From Text to Tactic: Evaluating LLMs Playing the Game of Avalon.

Jonathan Light, Min Cai, Sheng Shen, Ziniu Hu

CoRR, 2023

HallE-Switch: Rethinking and Controlling Object Existence Hallucinations in Large Vision Language Models for Detailed Caption.

Bohan Zhai, Shijia Yang, Xiangchen Zhao, Chenfeng Xu, Sheng Shen, Dongdi Zhao, Kurt Keutzer, Manling Li, Tan Yan, Xiangjun Fan

CoRR, 2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts.

Sheng Shen, Le Hou, Yanqi Zhou, Nan Du, Shayne Longpre, Jason Wei, Hyung Won Chung, Barret Zoph, William Fedus, Xinyun Chen, Tu Vu, Yuexin Wu, Wuyang Chen, Albert Webson, Yunxuan Li, Vincent Y. Zhao, Hongkun Yu, Kurt Keutzer, Trevor Darrell, Denny Zhou

CoRR, 2023

Large Language Models are Visual Reasoning Coordinators.

Liangyu Chen, Bo Li, Sheng Shen, Jingkang Yang, Chunyuan Li, Kurt Keutzer, Trevor Darrell, Ziwei Liu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Poisoning Language Models During Instruction Tuning.

Alexander Wan, Eric Wallace, Sheng Shen, Dan Klein

Proceedings of the International Conference on Machine Learning, 2023

Scaling Vision-Language Models with Sparse Mixture of Experts.

Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Crosslingual Generalization through Multitask Finetuning.

Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

K-LITE: Learning Transferable Visual Models with External Knowledge.

Sheng Shen, Chunyuan Li, Xiaowei Hu, Yujia Xie, Jianwei Yang, Pengchuan Zhang, Zhe Gan, Lijuan Wang, Lu Yuan, Ce Liu, Kurt Keutzer, Trevor Darrell, Anna Rohrbach, Jianfeng Gao

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exposing the Limits of Video-Text Models through Contrast Sets.

Jae Sung Park, Sheng Shen, Ali Farhadi, Trevor Darrell, Yejin Choi, Anna Rohrbach

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Learned Token Pruning for Transformers.

Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Woosuk Kwon, Joseph Hassoun, Kurt Keutzer

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Staged Training for Transformer Language Models.

Sheng Shen, Pete Walsh, Kurt Keutzer, Jesse Dodge, Matthew E. Peters, Iz Beltagy

Proceedings of the International Conference on Machine Learning, 2022

How Much Can CLIP Benefit Vision-and-Language Tasks?

Sheng Shen, Liunian Harold Li, Hao Tan, Mohit Bansal, Anna Rohrbach, Kai-Wei Chang, Zhewei Yao, Kurt Keutzer

Proceedings of the Tenth International Conference on Learning Representations, 2022

Multitask Prompted Training Enables Zero-Shot Task Generalization.

Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Arun Raja, Manan Dey, M Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Teven Le Scao, Stella Biderman, Leo Gao, Thomas Wolf, Alexander M. Rush

Proceedings of the Tenth International Conference on Learning Representations, 2022

What Language Model to Train if You Have One Million GPU Hours?

Teven Le Scao, Thomas Wang, Daniel Hesslow, Lucile Saulnier, Stas Bekman, M. Saiful Bari, Stella Biderman, Hady Elsahar, Niklas Muennighoff, Jason Phang, Ofir Press, Colin Raffel, Victor Sanh, Sheng Shen, Lintang Sutawika, Jaesung Tae, Zheng Xin Yong, Julien Launay, Iz Beltagy

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Multitask Prompted Training Enables Zero-Shot Task Generalization.

Victor Sanh, Albert Webson, Colin Raffel, Stephen H. Bach, Lintang Sutawika, Zaid Alyafeai, Antoine Chaffin, Arnaud Stiegler, Teven Le Scao, Arun Raja, Manan Dey, M. Saiful Bari, Canwen Xu, Urmish Thakker, Shanya Sharma, Eliza Szczechla, Taewoon Kim, Gunjan Chhablani, Nihal V. Nayak, Debajyoti Datta, Jonathan Chang, Mike Tian-Jian Jiang, Han Wang, Matteo Manica, Sheng Shen, Zheng Xin Yong, Harshit Pandey, Rachel Bawden, Thomas Wang, Trishala Neeraj, Jos Rozen, Abheesht Sharma, Andrea Santilli, Thibault Févry, Jason Alan Fries, Ryan Teehan, Stella Biderman, Leo Gao, Tali Bers, Thomas Wolf, Alexander M. Rush

CoRR, 2021

Learned Token Pruning for Transformers.

Sehoon Kim, Sheng Shen, David Thorsley, Amir Gholami, Joseph Hassoun, Kurt Keutzer

CoRR, 2021

MLPruning: A Multilevel Structured Pruning Framework for Transformer-based Models.

Zhewei Yao, Linjian Ma, Sheng Shen, Kurt Keutzer, Michael W. Mahoney

CoRR, 2021

Noisy Self-Knowledge Distillation for Text Summarization.

Yang Liu, Sheng Shen, Mirella Lapata

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Discovering Non-monotonic Autoregressive Orderings with Variational Inference.

Xuanlin Li, Brandon Trabucco, Dong Huk Park, Michael Luo, Sheng Shen, Trevor Darrell, Yang Gao

Proceedings of the 9th International Conference on Learning Representations, 2021

What's Hidden in a One-layer Randomly Weighted Transformer?

Sheng Shen, Zhewei Yao, Douwe Kiela, Kurt Keutzer, Michael W. Mahoney

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Reservoir Transformers.

Sheng Shen, Alexei Baevski, Ari S. Morcos, Kurt Keutzer, Michael Auli, Douwe Kiela

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.

Zhewei Yao, Amir Gholami, Sheng Shen, Mustafa Mustafa, Kurt Keutzer, Michael W. Mahoney

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Reservoir Transformer.

Sheng Shen, Alexei Baevski, Ari S. Morcos, Kurt Keutzer, Michael Auli, Douwe Kiela

CoRR, 2020

ADAHESSIAN: An Adaptive Second Order Optimizer for Machine Learning.

Zhewei Yao, Amir Gholami, Sheng Shen, Kurt Keutzer, Michael W. Mahoney

CoRR, 2020

Rethinking Batch Normalization in Transformers.

Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer

CoRR, 2020

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers.

Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joseph E. Gonzalez

CoRR, 2020

Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification (Extended Abstract).

Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

PowerNorm: Rethinking Batch Normalization in Transformers.

Sheng Shen, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer

Proceedings of the 37th International Conference on Machine Learning, 2020

Train Big, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers.

Zhuohan Li, Eric Wallace, Sheng Shen, Kevin Lin, Kurt Keutzer, Dan Klein, Joey Gonzalez

Proceedings of the 37th International Conference on Machine Learning, 2020

MAF: Multimodal Alignment Framework for Weakly-Supervised Phrase Grounding.

Qinxin Wang, Hao Tan, Sheng Shen, Michael W. Mahoney, Zhewei Yao

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

On the Generation of Medical Question-Answer Pairs.

Sheng Shen, Yaliang Li, Nan Du, Xian Wu, Yusheng Xie, Shen Ge, Tao Yang, Kai Wang, Xingzheng Liang, Wei Fan

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Q-BERT: Hessian Based Ultra Low Precision Quantization of BERT.

Sheng Shen, Zhen Dong, Jiayu Ye, Linjian Ma, Zhewei Yao, Amir Gholami, Michael W. Mahoney, Kurt Keutzer

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification.

Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu

Proceedings of the World Wide Web Conference, 2019

Pragmatically Informative Text Generation.

Sheng Shen, Daniel Fried, Jacob Andreas, Dan Klein

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

An annotated dataset of literary entities.

David Bamman, Sejal Popat, Sheng Shen

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

2018

Ermes: Emoji-Powered Representation Learning for Cross-Lingual Sentiment Classification.

Zhenpeng Chen, Sheng Shen, Ziniu Hu, Xuan Lu, Qiaozhu Mei, Xuanzhe Liu

CoRR, 2018

2017

Towards Release Strategy Optimization for Apps in Google Play.

Sheng Shen, Xuan Lu, Ziniu Hu

CoRR, 2017

Towards Release Strategy Optimization for Apps in Google Play.

Sheng Shen, Xuan Lu, Ziniu Hu, Xuanzhe Liu

Proceedings of the 9th Asia-Pacific Symposium on Internetware, 2017