arXiv AI By Maxwell J. Jacobson, Daniel Xie, Jackson Shen, Adil Wazeer, Guang Lin, Xiao-Ying Yu, Haiyan Wang, Xinghang Zhang, Yexiang Xue

A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization

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arXiv AI
Aug 20

Self-prompting and cross-model consensus enable reproducible data extraction from scientific literature with large language models

The paper investigates how large language models can extract contextualized data from scientific literature. It presents four workflows: expert‑written prompts, self‑generated prompts, autonomous literature discovery, and dataset creation from guidelines. While models perform well with prompts, they struggle with context, hallucinate references, and still need human oversight for final validation.

By Valentin Romanov, Monique Bax, Steven Niederer
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 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