1 citations · 1 across the 8 of their papers we have counts for
3 papers · 1 filter
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…
TabEmb: Joint Semantic-Structure Embedding for Table Annotation
Ehsan Hoseinzade, Ke Wang, Anandharaju Durai Raju
Table annotation is crucial for making web and enterprise tables usable in downstream NLP applications. Unlike textual data where learning semantically rich token or sentence embed…
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…