3 papers
cs.LG2025
Breaking the Safety-Capability Tradeoff: Reinforcement Learning with Verifiable Rewards Maintains Safety Guardrails in LLMs
Dongkyu Derek Cho, Huan Song, Arijit Ghosh Chowdhury +6
Fine-tuning large language models (LLMs) for downstream tasks typically exhibit a fundamental safety-capability tradeoff, where improving task performance degrades safety alignment…
cs.AI2025
Learning from Generalization Patterns: An Evaluation-Driven Approach to Enhanced Data Augmentation for Fine-Tuning Small Language Models
Huan Song, Deeksha Razdan, Yiyue Qian +6
Small Language Models (SLMs) offer compelling advantages in deployment cost and latency, but their accuracy often lags behind larger models, particularly for complex domain-specifi…
cs.CL2025
LeMAJ (Legal LLM-as-a-Judge): Bridging Legal Reasoning and LLM Evaluation
Joseph Enguehard, Morgane Van Ermengem, Kate Atkinson +8
Evaluating large language model (LLM) outputs in the legal domain presents unique challenges due to the complex and nuanced nature of legal analysis. Current evaluation approaches…