3 papers
q-bio.GN2026
oxo-call: Documentation-grounded Skill Augmentation for Accurate Bioinformatics Command-line Generation with Large Language Models
Yun Peng, Yujun Sun, Jia Ding +6
Command-line bioinformatics tools remain essential for genomic analysis, yet their diversity in syntax and parameterization presents a persistent barrier to productive research. We…
cs.CL2026
Triviality Corrected Endogenous Reward
Xinda Wang, Zhengxu Hou, Yangshijie Zhang +6
Reinforcement learning for open-ended text generation is constrained by the lack of verifiable rewards, necessitating reliance on judge models that require either annotated data or…
cs.CL2026
EvolvR: Self-Evolving Pairwise Reasoning for Story Evaluation to Enhance Generation
Xinda Wang, Zhengxu Hou, Yangshijie Zhang +6
Although the effectiveness of Large Language Models (LLMs) as judges (LLM-as-a-judge) has been validated, their performance remains limited in open-ended tasks, particularly in sto…