arxiv
PublishedJune 12, 2026 at 4:00 AM
—neutral
Small LLMs for Biomedical Claim Verification: Cost-Effective Fine-Tuning, Structural Dataset Shortcuts, and Cross-Domain Generalization
Publisher summary· verbatim
arXiv:2606.12854v1 Announce Type: new Abstract: Large Language Models such as GPT-4o and GPT-5 achieve strong zero-shot performance on biomedical claim verification, but cost and opacity limit scalable use. We fine-tune three small LLMs: Phi-3-mini (3.8B), Qwen2.5-3B, and Mistral-7B, via QLoRA on Sc
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivMagnifying What Matters: Attention-Guided Adaptive Rendering for Visual Text Comprehension2harxivGetting Better at Working With You: Compiling User Corrections into Runtime Enforcement for Coding Agents2harxivLoHoSearch: Benchmarking Long-Horizon Search Agents Beyond the Human Difficulty Ceiling2harxivDirect Preference Optimization for Chatbot Fine-Tuning: An Empirical Study2hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗