47 citations · 53 across the 6 of their papers we have counts for
6 papers
Qworld: Question-Specific Evaluation Criteria for LLMs
Shanghua Gao, Yuchang Su, Pengwei Sui +2
Evaluating large language models (LLMs) on open-ended questions is difficult because response quality depends on the question's context. Binary scores and static rubrics fail to ca…
A Generative AI System for Biomedical Data Discovery with Grammar-Based Visualizations
Devin Lange, Shanghua Gao, Pengwei Sui +4
We explore the potential for combining generative AI with grammar-based visualizations for biomedical data discovery. In our prototype, we use a multi-agent system to generate visu…
ToolUniverse: An open platform for democratizing AI scientists
Shanghua Gao, Richard Zhu, Pengwei Sui +8
AI scientists are emerging computational systems that serve as collaborative partners in discovery. These systems remain difficult to build because they are bespoke, tied to rigid…
YAC: Bridging Natural Language and Interactive Visual Exploration with Generative AI for Biomedical Data Discovery
Devin Lange, Shanghua Gao, Pengwei Sui +7
Incorporating natural language input has the potential to improve the capabilities of biomedical data discovery interfaces. However, user interface elements and visualizations are…
Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
Zhenglun Kong, Zheng Zhan, Shiyue Hou +10
Large language models (LLMs) have shown remarkable promise but remain challenging to continually improve through traditional finetuning, particularly when integrating capabilities…
Learning Implicit Credit Assignment for Cooperative Multi-Agent Reinforcement Learning
Meng Zhou, Ziyu Liu, Pengwei Sui +2
We present a multi-agent actor-critic method that aims to implicitly address the credit assignment problem under fully cooperative settings. Our key motivation is that credit assig…