Search Results for author: Yanjun Shao

Found 6 papers, 6 papers with code

ChemAgent: Self-updating Library in Large Language Models Improves Chemical Reasoning

1 code implementation11 Jan 2025 Xiangru Tang, Tianyu Hu, Muyang Ye, Yanjun Shao, Xunjian Yin, Siru Ouyang, Wangchunshu Zhou, Pan Lu, Zhuosheng Zhang, Yilun Zhao, Arman Cohan, Mark Gerstein

To address these challenges, we present ChemAgent, a novel framework designed to improve the performance of LLMs through a dynamic, self-updating library.

Drug Discovery

OpenHands: An Open Platform for AI Software Developers as Generalist Agents

2 code implementations23 Jul 2024 Xingyao Wang, Boxuan Li, Yufan Song, Frank F. Xu, Xiangru Tang, Mingchen Zhuge, Jiayi Pan, Yueqi Song, Bowen Li, Jaskirat Singh, Hoang H. Tran, Fuqiang Li, Ren Ma, Mingzhang Zheng, Bill Qian, Yanjun Shao, Niklas Muennighoff, Yizhe Zhang, Binyuan Hui, Junyang Lin, Robert Brennan, Hao Peng, Heng Ji, Graham Neubig

OpenDevin), a platform for the development of powerful and flexible AI agents that interact with the world in similar ways to those of a human developer: by writing code, interacting with a command line, and browsing the web.

Step-Back Profiling: Distilling User History for Personalized Scientific Writing

1 code implementation20 Jun 2024 Xiangru Tang, Xingyao Zhang, Yanjun Shao, Jie Wu, Yilun Zhao, Arman Cohan, Ming Gong, Dongmei Zhang, Mark Gerstein

To conduct the experiments, we construct a Personalized Scientific Writing (PSW) dataset to study multi-user personalization.

PRESTO: Progressive Pretraining Enhances Synthetic Chemistry Outcomes

1 code implementation19 Jun 2024 He Cao, Yanjun Shao, Zhiyuan Liu, Zijing Liu, Xiangru Tang, Yuan YAO, Yu Li

Current approaches, however, often neglect the critical role of multiple molecule graph interaction in understanding chemical reactions, leading to suboptimal performance in synthetic chemistry tasks.

cross-modal alignment

ML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level Code

1 code implementation16 Nov 2023 Xiangru Tang, Yuliang Liu, Zefan Cai, Yanjun Shao, Junjie Lu, Yichi Zhang, Zexuan Deng, Helan Hu, Kaikai An, Ruijun Huang, Shuzheng Si, Sheng Chen, Haozhe Zhao, Liang Chen, Yan Wang, Tianyu Liu, Zhiwei Jiang, Baobao Chang, Yin Fang, Yujia Qin, Wangchunshu Zhou, Yilun Zhao, Arman Cohan, Mark Gerstein

Despite Large Language Models (LLMs) like GPT-4 achieving impressive results in function-level code generation, they struggle with repository-scale code understanding (e. g., coming up with the right arguments for calling routines), requiring a deeper comprehension of complex file interactions.

Code Generation Navigate +1

Colossal-Auto: Unified Automation of Parallelization and Activation Checkpoint for Large-scale Models

1 code implementation6 Feb 2023 Yuliang Liu, Shenggui Li, Jiarui Fang, Yanjun Shao, Boyuan Yao, Yang You

To address these challenges, we introduce a system that can jointly optimize distributed execution and gradient checkpointing plans.

Scheduling

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