3 papers
cs.AI2026
Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection
Daniel Xie, Maxwell J. Jacobson, Adil Wazeer +3
Reducing hallucinations in Large Language Models (LLMs) is essential for accurate data extraction from large text corpora. Current methods, like prompt engineering and chain-of-tho…
cs.AI2026
A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization
Maxwell J. Jacobson, Daniel Xie, Jackson Shen +6
Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including autonomous summarization and qu…
cs.CV2023
End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning
Md Nasim, Anter El-Azab, Xinghang Zhang +1
The availability of tera-byte scale experiment data calls for AI driven approaches which automatically discover scientific models from data. Nonetheless, significant challenges pre…