(* denotes equal contribution, = denotes student I mentor)

Agentic AI

• Adaptive In-conversation Team Building for Language Model Agents
  Linxin Song, Jiale Liu, Jieyu Zhang, Shaokun Zhang, Ao Luo, Shijian Wang, Qingyun Wu, Chi Wang.
• Offline Training of Language Model Agents with Functions as Learnable Weights
  Shaokun Zhang*, Jieyu Zhang*, Jiale Liu, Linxin Song, Chi Wang, Ranjay Krishna, Qingyun Wu.
  ICML 2024
• EcoAssistant: Using LLM Assistant More Affordably and Accurately
  Jieyu Zhang, Ranjay Krishna, Ahmed Awadallah, Chi Wang.
  LLM Agents @ ICLR 2024
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework
  Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Beibin Li, Erkang Zhu, Li Jiang, Xiaoyun Zhang, Shaokun Zhang, Jiale Liu, Ahmed Awadallah, Ryen White, Doug Burger, Chi Wang
  COLM 2024 | LLM Agents @ ICLR 2024 Best Paper
  Github 28,000+ Star & 4,000+ Fork
  The Economist article
  The Forbes article

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Model Evaluation

• Task Me Anything
  Jieyu Zhang, Weikai Huang*, Zixian Ma*, Oscar Michel, Dong He, Tanmay Gupta, Wei-Chiu Ma, Ali Farhadi, Aniruddha Kembhavi, Ranjay Krishna.
• m&m’s: A Benchmark to Evaluate Tool-Use for multi-step multi-modal Tasks
  Zixian Ma, Weikai Huang, Jieyu Zhang, Tanmay Gupta, Ranjay Krishna.
  ECCV 2024
• SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models
  Xiaoxuan Wang*, Ziniu Hu*, Pan Lu*, Yanqiao Zhu*, Jieyu Zhang, Satyen Subramaniam, Arjun R. Loomba, Shichang Zhang, Yizhou Sun, Wei Wang
  ICML 2024
  Nature News Feature
• SugarCrepe: Fixing Hackable Benchmarks for Vision-Language Compositionality
  Cheng-Yu Hsieh*, Jieyu Zhang*, Zixian Ma, Aniruddha Kembhavi, Ranjay Krishna.
  NeurIPS 2023
• WRENCH: A Comprehensive Benchmark for Weak Supervision
  Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner.
  NeurIPS 2021 Oral Presentation

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Dataset Curation

• DataComp: In Search of the Next Generation of Multimodal Datasets
  34 authors.
  NeurIPS 2023 Oral Presentation
• On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
  Jieyu Zhang*, Bohan Wang*, Zhengyu Hu, Pang Wei Koh, Alexander Ratner.
  NeurIPS 2023
• Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
  Yue Yu*, Yuchen Zhuang*, Jieyu Zhang*, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang.
  NeurIPS 2023

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Data Labeling

• Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision
  Jieyu Zhang*, Linxin Song=*, Alexander Ratner.
  AISTATS 2023
• Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
  Jeffrey Li, Jieyu Zhang, Ludwig Schmidt, Alexander Ratner.
  NeurIPS 2023
• Understanding Programmatic Weak Supervision via Source-aware Influence Function
  Jieyu Zhang*, Haonan Wang*, Cheng-Yu Hsieh, Alexander Ratner.
  NeurIPS 2022
• Creating Training Sets via Weak Indirect Supervision
  Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner.
  ICLR 2022
• Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming
  Cheng-Yu Hsieh, Jieyu Zhang, Alexander Ratner.
  VLDB 2022

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