Hello World! My name is Yuchen Zhuang. I am a final-year Machine Learning Ph.D. candidate 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 large language model-based agents capable of exhibiting human-like reasoning and planning when tackling challenging real-world problems. My experience spans various stages of LLM development, including model pre-training, instruction fine-tuning, RLHF, and evaluation. I am honored to have been selected as a recipient of the 2024 J.P. Morgan PhD Fellowship Award. 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: [ICML'24, NeurIPS'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 (Spring 2025, starting from Dec 2024) and full-time occupations (2025). I am open to topics and happy to engage in discussions regarding potential opportunities!
- [11/2024] Awarded the 2024 J.P. Morgan Chase AI PhD Fellowship.
- [09/2024] Two papers got accepted in NeurIPS'24, discussing LLM personalization with model factorization, and LLM alignment with representation editing. See you in Vancouver!
- [09/2024] Three papers got accepted in EMNLP'24, introducing RAG, LLM Agent, and domain adaptation in medical applications.
- [07/2024] Our paper got accepted in COLM'24, introducing principle discovery for LLM reasoning. See you in Philadelphia, PA!
- [06/2024] Our ICML paper has been selected as Spotlight! Congratulations to all the collaborators.
- [05/2024] One paper got accepted in ICML'24, introducing a novel method for black-box LLM adaptation. See you (virtually) in Vienna!
- [03/2024] Will join Amazon Rufus Team as Applied Scientist Intern during Summer 2024. See you in Palo Alto!
- [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 papers 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!
Selected Publications and Manuscripts
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
AdaPlanner: Adaptive Planning from Feedback with Language Models
ToolQA: A Dataset for LLM Question Answering with External Tools
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
Retrieval-Augmented Large Language Models for Adolescent Idiopathic Scoliosis Patients in Shared Decision-Making
BCB'23 (Best Paper) Paper
End-to-end Stochastic Optimization with Energy-based Model
ReSel: N-ary Relation Extraction from Scientific Text and Tables by Learning to Retrieve and Select
Industrial Experience
Amazon (May 2024-Aug 2024)
Topic: Pre-Training Agent LLM to Enhance the Foundamental Agentic Capabilities
Adobe Research (May 2023-Aug 2023)
Topic: ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search [ICLR'24]
Amazon (May 2022-Aug 2022)
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
- [11/2024] 2024 J.P. Morgan Chase AI PhD Fellowship;
- [10/2023] NeurIPS 2023 Scholar Award;
- [09/2023] Best Paper Award, ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB);
- [08/2023] KDD 2023 Student Travel Grant;
- [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.