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cs.CL2026
PriFT: Guiding Supervised Fine-Tuning with Pretrained Priors
Ke Wang, Shuangqi Li, Mathieu Salzmann +1
Supervised fine-tuning (SFT) is an efficient approach for downstream task adaptation and often serves as the initialization stage for reinforcement learning (RL), but it can show w…
cs.CL2026
HalluSAE: Detecting Hallucinations in Large Language Models via Sparse Auto-Encoders
Boshui Chen, Zhaoxin Fan, Ke Wang +5
Large Language Models (LLMs) are powerful and widely adopted, but their practical impact is limited by the well-known hallucination phenomenon. While recent hallucination detection…