arXiv AI
Aug 5

AgentPanel: Toward a New Paradigm for Human--AI Collaboration in Exploring Scientific Questions

arXiv:2608. 03283v1 Announce Type: new Abstract: Identifying promising scientific ideas remains an important challenge in research practice.

By Zhiyao Cui, Qianyi Wang, Haoyang Yan, Yiqun Zhang, Siyue Ren, Hangfan Zhang, Zelin Tan, Hao Li, Chunjiang Mu, Dexian Cai, Shao Zhang, Chen Zhang, Meng Li, Jianan Chai, Yuting Fan, Zichao Ye, Xiaolei Yang, Xinyao Lu, Yuyang Yu, Wenjie Lou, Xiaosong Wang, Fenghua Ling, Shiyang Feng, Mao Su, Qiaosheng Zhang, Bo Zhang, Yang Chen, Lei Bai, Shuyue Hu
arXiv AI
Sep 25

DocuTeam: Mixed-Initiative Multi-Agent Discussions around Evolving Documents

DocuTeam is a mixed‑initiative multi‑agent discussion system that allows both users and agents to start and steer conversations around evolving documents. Agents monitor changes to the document and proactively initiate or redirect discussions, while users can shape the dialogue or adopt agent suggestions. In a within‑subjects study with 20 participants, DocuTeam produced outcomes that were rated as more novel, relevant, and specific compared to a baseline, without increasing cognitive load.

By Heechan Lee, Juhyeon Choi, Tae Soo Kim, Juho Kim, Joseph Seering
arXiv AI
Sep 10

AutoKD: Autonomous Knowledge Discovery

arXiv:2609.06366v1 Announce Type: new Abstract: Scientific discovery in data-rich domains is currently constrained by human bandwidth: the growth in the volume and complexity of real-world data far o...

By Qinwen Ge, Bo Ni, Haowei Fu, Ngoc N. Tran, Erik Blasch, Tyler Derr
arXiv Machine Learning
Jul 17

Idea2Plan: Exploring AI-Powered Research Planning

arXiv:2510. 24891v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have demonstrated significant potential to accelerate scientific discovery as valuable tools for analyzing data, generating hypotheses, and supporting innovative approaches in various scientific fields.

By Jin Huang, Silviu Cucerzan, Sujay Kumar Jauhar, Ryen W. White