arXiv AI
Aug 26

Generating Biomedical Fact-Checking Reports with RL-Enhanced Agentic Search

The paper introduces BioCheck Agent, an LLM-based system that generates structured biomedical fact‑checking reports using agentic search and a reinforcement‑learning framework called EG‑GRPO. Unlike prior methods that output only supported or refuted labels, BioCheck Agent synthesizes conclusions with retrieved evidence from PubMed, employing advanced Boolean search operators. Experiments show that, compared to the base Qwen3.5‑4B model, BioCheck Agent improves label prediction accuracy on SciFact by 9.95 %, raises evidence quality by 3.7 %, and reduces hallucinations by 19.63 %.

By Jiongxiao Wang, Dingli Ma, Chaoqun Ni
arXiv AI
Jul 8

Prompt-to-Paper: Agentic AI System for Bioinformatics

arXiv:2607. 05456v1 Announce Type: new Abstract: While recent advances in large language models have enabled end-to-end automated manuscript generation, existing systems suffer from three critical deficiencies: (i) generated claims are not deterministically grounded in verifiable literature, (ii) experimental results are frequently fabricated rather than executed, and (iii) there exists no standardized, multi-dimensional framework to assess whether AI-generated manuscripts meet the quality and rigor required for real-world publication.

By Ramsha Kamran, Maheera Amjad, Zartasha Mustansar, Arsalan Shaukat, Salma Sherbaz, Muhammad U. S. Khan