Hi, nice to meet you!

I am Botao Yu (余博涛), a first-year PhD student at The Ohio State University, advised by Prof. Huan Sun. Previously, I earned my Master’s degree at Nanjing University, advised by Prof. Wei Hu (胡伟).

My research interest includes AI for Science (esp. Chemistry), LLMs, NLP, AI music, and deep learning.

🔥 News

  • 2024.11: Please check out our new preprint ChemAgent, an enhanced chemistry agent and its performance on various chemistry problems.
  • 2024.10: Please check out our new preprint ScienceAgentBench, a benchmark to assess language models in scientific tasks.
  • 2024.09: Check out our new preprint MMMU-Pro, an enhanced version of MMMU featuring full-vision evaluation.
  • 2024.07: Our paper LlaSMol is accepted to COLM 2024 🎉!
  • 2024.05: Our paper MMMU is selected as Oral (0.8%) and nominated for best paper (24 in total) at CVPR 2024 🎊!
  • 2023.08: Arrived at Columbus. My PhD journey officially starts 😋!
  • 2023.05: Please check out our preprint MuseCoco, a text-to-music generation system.
  • 2022.09: Our paper Museformer is accepted to NeurIPS 2022 🎉!

📝 Publication

Sadly, there are no such publications.
  • [Preprint 2024] Tooling or Not Tooling? The Impact of Tools on Language Agents for Chemistry Problem Solving

    Botao Yu, Frazier N. Baker*, Ziru Chen*, Garrett Herb, Boyu Gou, Daniel Adu-Ampratwum, Xia Ning, Huan Sun (* equal contribution)
    We propose a tool-augmented language agent for chemistry named ChemAgent, and evaluate it on both specialized chemistry tasks and general chemistry questions. The results show that tools cannot always help and may cause more reasoning errors.
  • [Preprint 2024] ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

    Ziru Chen, Shijie Chen, Yuting Ning, Qianheng Zhang, Boshi Wang, Botao Yu, Yifei Li, Zeyi Liao, Chen Wei, Zitong Lu, Vishal Dey, Mingyi Xue, Frazier N. Baker, Benjamin Burns, Daniel Adu-Ampratwum, Xuhui Huang, Xia Ning, Song Gao, Yu Su, Huan Sun
    The study introduces a benchmark for evaluating language models in scientific discovery, using 102 tasks from peer-reviewed publications and expert validation. It reveals current limitations in code generation, highlighting the need for rigorous task assessments.
  • [Preprint 2024] MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark

    Xiang Yue*, Tianyu Zheng*, Yuansheng Ni*, Yubo Wang, Kai Zhang, Shengbang Tong, Yuxuan Sun, Ming Yin, Botao Yu, Ge Zhang, Huan Sun, Yu Su, Wenhu Chen, Graham Neubig (* equal contribution)
    An enhanced version of MMMU featuring full-vision evaluation for multi-discipline multimodal understanding.
  • [COLM 2024] LlaSMol: Advancing Large Language Models for Chemistry with a Large-Scale, Comprehensive, High-Quality Instruction Tuning Dataset

    Botao Yu, Frazier N. Baker*, Ziqi Chen*, Xia Ning, Huan Sun (* equal contribution)
    We propose a carefully curated chemistry task dataset for instruction tuning and a series of LLMs that significantly outperform GPT-4 and Claude-3-Opus on various chemistry tasks.
  • [CVPR 2024 Oral] MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

    Xiang Yue*, Yuansheng Ni*, Kai Zhang*, Tianyu Zheng*, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, Cong Wei, Botao Yu, Ruibin Yuan, Renliang Sun, Ming Yin, Boyuan Zheng, Zhenzhu Yang, Yibo Liu, Wenhao Huang, Huan Sun*, Yu Su*, Wenhu Chen* (* core contributors)
    This paper proposes a massive multi-discipline multimodal understanding and reasoning benchmark for expert AGI.
  • [Preprint 2023] MuseCoco: Generating Symbolic Music from Text

    Peiling Lu*, Xin Xu*, Chenfei Kang*, Botao Yu*, Chengyi Xing*, Xu Tan, Jiang Bian (* equal contribution)
    A two-stage text-to-music generation system for creating symbolic music from textual descriptions.
  • [Preprint 2023] EmoGen: Eliminating Subjective Bias in Emotional Music Generation

    Chenfei Kang, Peiling Lu, Botao Yu, Xu Tan, Wei Ye, Shikun Zhang, Jiang Bian
    A method for generating emotional music while reducing subjective bias in the process.
  • [NeurIPS 2022] Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation

    Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu
    We propose a fine- and coarse-grained attention mechanism for modeling the structures of music.
  • [ISMIR 2022] MeloForm: Generating Melody with Musical Form Based on Expert Systems and Neural Networks

    Peiling Lu, Xu Tan, Botao Yu, Tao Qin, Sheng Zhao, Tie-Yan Liu
    A system for generating melodies with musical form using a combination of expert systems and neural networks.
  • [EMNLP 2021] Knowing False Negatives: An Adversarial Training Method for Distantly Supervised Relation Extraction

    Kailong Hao, Botao Yu, Wei Hu
    An adversarial training method to improve distantly supervised relation extraction by addressing false negatives.
  • [APWeb-WAIM 2020] Joint Reasoning of Events, Participants and Locations for Plot Relation Recognition

    Shengguang Qiu, Botao Yu, Lei Qian, Qiang Guo, Wei Hu
    A method for recognizing plot relations by jointly reasoning about events, participants, and locations in narratives.

📖 Education

  • 2023.08 - Now       Columbus, Ohio, USA

    PhD student in Computer Science and Engineering @ The Ohio State University

  • 2019.09 - 2023.06       Nanjing, Jiangsu, China

    Master’s student in Computer Science @ Nanjing University (南京大学)

  • 2015.09 - 2019.06       Dalian, Liaoning, China

    Undergraduate student in Software Engineering @ Dalian University of Technology (大连理工大学)

  • 2012.09 - 2015.06       Changsha, Hunan, China

    High school student @ The High School Attached To Hunan Normal University (湖南师大附中)

💻 Internship

  • 2021.04 - 2022.03       Beijing, China

    Research intern @ Microsoft Research Asia (微软亚洲研究院)

Psst! 🔍 Kudos on your keen eye! Didn't expect anyone to notice this microscopic text. Since you've ventured this far, fancy embarking on a friendship adventure?

Last modified: Nov. 13, 2024