I am a second-year PhD student at University of Notre Dame beginning in 2023 Spring, advised by Prof. Xiangliang Zhang.
I am also proud to be a member of the NSF Center for Computer-Assisted Synthesis (C-CAS), where I am currently working as a research assistant.
Previously, I received my M.S. degree in computer science from King Abdullah University of Science and Technology (KAUST). I also received my B.Eng. degree in software engineering from Xidian University.
My long-term research goal is to develop intelligent systems with human-like planning and reasoning abilities. The central theme of my current research is to improve these capabilities from diversity, uncertainty-aware, learning from feedback, scalability, step-by-step perspectives.
For technologies, my studies encompass LLM, LLM-based Agents, LLM Interpretability, Generative Models, and Mixture-of-experts.
For practical applications, my studies encompass Scientific Domains, Bayesian Optimization, Recommender Systems, all of which naturally require better planning and reasoning capabilities of the intelligent systems.
I am actively seeking a research intern opportunity about large language models! Additonally, if you are seeking any form of academic cooperation, please feel free to contact me at tguo2@nd.edu or wechat ID: Great_buckwheat
Publications
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Data Interpreter: An LLM Agent For Data Science.
Sirui Hong, Yizhang Lin, Bangbang Liu, Binhao Wu, Danyang Li, Jiaqi Chen, Jiayi Zhang, Jinlin Wang, Lingyao Zhang, Mingchen Zhuge, Taicheng Guo, Tuo Zhou, Wei Tao, Wenyi Wang, Xiangru Tang, Xiangtao Lu, Xinbing Liang, Yaying Fei, Yuheng Cheng, Zongze Xu, Chenglin Wu, Li Zhang, Min Yang, Xiawu Zheng.
Preprint
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A Property-Guided Diffusion Model for Generating Molecular Graphs.
Changsheng Ma, Taicheng Guo, Qiang Yang, Xiuying Chen, Xin Gao, Shangsong Liang, Nitesh Chawla, Xiangliang Zhang
In the IEEE International Conference on Acoustics, Speech and Signal Processing.(ICASSP 2024)
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SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark.
Zhenwen Liang, Kehan Guo, Gang Liu, Taicheng Guo, Yujun Zhou, Tianyu Yang, Jiajun Jiao, Renjie Pi, Jipeng Zhang, Xiangliang Zhang
Preprint
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Rethinking Scientific Summarization Evaluation: Grounding Explainable Metrics on Facet-aware Benchmark.
Xiuying Chen, Tairan Wang, Qingqing Zhu, Taicheng Guo, Shen Gao, Zhiyong Lu, Xin Gao, Xiangliang Zhang
Preprint
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Defending Jailbreak Prompts via In-Context Adversarial Game.
Yujun Zhou, Yufei Han, Haomin Zhuang, Taicheng Guo, Kehan Guo, Zhenwen Liang, Hongyan Bao, Xiangliang Zhang
Preprint
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Data-Efficient, Chemistry-Aware Machine Learning Predictions of Diels–Alder Reaction Outcomes.
Angus Keto, Taicheng Guo, Morgan Underdue, Thijs Stuyver, Connor Coley, Xiangliang Zhang, Elizabeth Krenske, Olaf Wiest
Preprint
Competition Awards
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KDD Cup 2020 Regular Machine Learning Competition Track.
Ranked 2nd place. 🥈
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NeurIPS 2020 Black-Box Optimization Challenge.
Ranked 2nd place in warm-start friendly leaderboard. 🥈
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Kaggle Arabic Sentiment Analaysis.
Ranked 5th place.
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Kaggle Expert
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IEEE Computer Society Global student challenge.
Ranked 1st place. 🏅
Professional Service
Reviewer: WWW, KDD, Nature Communications
Teaching Assistant: CSE 40625 Machine Learning, University of Notre Dame, Fall 2023
Last update: Mar, 2024. Webpage template borrows from
Stephen Bach.
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