Home | Yuchen Zhuang

Hello World! My name is Yuchen Zhuang. I am a Machine Learning Ph.D. student in Georgia Institute of Technology, advised by Prof. Chao Zhang. I am also very fortunate to work closely with Prof. Le Song and Prof. Bo Dai. My principal interest lies in the language intelligence, aiming for developing language model-based agents capable of exhibiting human-like reasoning and planning when tackling challenging real-world problems. My recent research covers the following directions:

Language Intelligence with Human-level Reasoning and Planning Capabilities: [ICLR'24, NeurIPS'23a, NeurIPS'23b, EMNLP'22];
Adapting or aligning language models to possess human-level capabilities on specific tasks: [arXiv'24];
Data-centric approaches that can offer high-quality data for effort-light model training and faithful evaluation: [NeurIPS'23c, KDD'23].

News

[--Pinned--] I am actively seeking industrial R&D opportunities, including both internship (Fall 2024) and full-time occupations (2025). I am open to topics and happy to engage in discussions regarding potential opportunities!
[03/2024] One paper got accepted in NAACL'24, introducing a new materials science information extraction dataset for polymers.
[03/2024] Will join Amazon as Applied Scientist Intern during Summer 2024. See you in Palo Alto!
[01/2024] Two collaborating papers are accepted in AISTATS'24 and EACL'24 separately. Congratuations to the collaborators!
[01/2024] One paper got accepted in ICLR'24, discussing efficient navigation of LLM agent in action space. Congratulations to my collaborators in Adobe Research! See you (maybe virtually) in Vienna!
[10/2023] Humbled to receive NeurIPS 2023 Scholar Award. See you in New Orleans!
[09/2023] Three paper got accepted in NeurIPS'23, discussing a closed-loop LLM-based autonomous agent, a tool-use dataset for LLMs, and attributed dataset generation with LLMs. See you in New Orleans!
[09/2023] One paper got accepted in BCB'23 and received Best Paper Award, discussing LLMs' application in clinical scenarios.
[08/2023] One paper got accepted in CIKM'23, discussing user main shopping intention identification. Congratualations to my collaborators in Amazon!
[05/2023] One paper got accepted in KDD'23, discussing noisy-label learning with training dynamics-enhanced generative model. See you in Long Beach!
[05/2023] One paper got accepted in ACL'23 (Findings), discussing retrieval-augmented zero-shot text classification.
[04/2023] One paper got accepted in ICML'23, discussing diffusion model for graph generation.

Selected Publications and Manuscripts

Please refer to publications or my Google Scholar profile for the full list. ("*" stands for equal contribution)

BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models

Haotian Sun*, Yuchen Zhuang*, Wei Wei, Chao Zhang, Bo Dai

arXiv'24 Paper Code Website

ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search

Yuchen Zhuang, Xiang Chen, Tong Yu, Saayan Mitra, Victor Bursztyn, Ryan A. Rossi, Somdeb Sarkhel, Chao Zhang

ICLR'24 Paper AK Daily

AdaPlanner: Adaptive Planning from Feedback with Language Models

Haotian Sun*, Yuchen Zhuang*, Lingkai Kong, Bo Dai, Chao Zhang

NeurIPS'23 Paper Code

ToolQA: A Dataset for LLM Question Answering with External Tools

Yuchen Zhuang*, Yue Yu*, Kuan Wang*, Haotian Sun, Chao Zhang

NeurIPS'23 Paper Code Data MarkTech Post

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

Yue Yu*, Yuchen Zhuang*, Jieyu Zhang*, Yu Meng, Alexander J. Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang

NeurIPS'23 Paper Code MarkTech Post

DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling

Yuchen Zhuang, Yue Yu, Lingkai Kong, Xiang Chen, Chao Zhang

KDD'23 Paper Code

Retrieval-Augmented Large Language Models for Adolescent Idiopathic Scoliosis Patients in Shared Decision-Making

Wenqi Shi, Yuchen Zhuang, Yuanda Zhu, Henry Iwinski, Michael Wattenbarger, May Dongmei Wang

BCB'23 (Best Paper) Paper

End-to-end Stochastic Optimization with Energy-based Model

Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang

NeurIPS'22 (Oral) Paper Code

ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select

Yuchen Zhuang, Yinghao Li, Jerry Junyang Cheung, Yue Yu, Yingjun Mou, Xiang Chen, Le Song, Chao Zhang

EMNLP'22 Paper Code

Industrial Experience

Adobe Research (May 2023-Aug 2023)

Research Scientist Intern

Mentor: Xiang Chen, Tong Yu, Ryan A Rossi, Victor Bursztyn, Somdeb Sarkhel, Manager: Saayan Mitra

Topic: ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search [ICLR'24]

Amazon (May 2022-Aug 2022)

Applied Scientist Intern, Personalization Group

Mentor: Xin Shen, Yan Zhao, Chaosheng Dong, Manager: Jin Li, Tong Zhao

Topic: G-STO: Sequential Main Shopping Intention Detection via Graph-Regularized Stochastic Transformer [CIKM'23]

Academic Services

Reviewer for conferences: ARR (2023-), EMNLP (2022-), ICLR (2024), NeurIPS (2023), KDD (2021-), ACL (2023), AAAI (2023-), ICML (2021), AISTATS (2024), SDM (2024).
Reviewer for workshops: FMDM@NeurIPS (2023), DMLR@ICML (2023), SPIGM@ICML (2023).
Reviewer for Journals: IEEE Journal on Selected Topics in Signal Processing (JSTSP).
Teaching Assistant, Georgia Tech NLP Bootcamp, Fall 2023-2024.
Teaching Assistant, Georgia Tech Big Data Bootcamp, Fall 2021-2024.
Graduate Teaching Assistant, CSE8803 DLT: Deep Learning for Text Data, Fall 2021.
Graduate Teaching Assistant, CSE7641 A: Machine Learning, Fall 2020.

Selected Awards

[10/2023] NeurIPS 2023 Scholar Award;
[09/2023] Best Paper Award, ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB);
[06/2020] Second Prize of Excellent Undergraduate Student Graduation Thesis in Jiangsu Province;
[06/2019] Most Influential Graduate Award Nomination (20/4000), Southeast University;
[12/2017] Excellent Paper Award, International Collaboration Symposium on Information, Production & Systems, Japan.