2 papers
cs.CL2025
Limited Preference Data? Learning Better Reward Model with Latent Space Synthesis
Leitian Tao, Xuefeng Du, Sharon Li
Reward modeling, crucial for aligning large language models (LLMs) with human preferences, is often bottlenecked by the high cost of preference data. Existing textual data synthesi…
cs.LG2024
HaloScope: Harnessing Unlabeled LLM Generations for Hallucination Detection
Xuefeng Du, Chaowei Xiao, Yixuan Li
The surge in applications of large language models (LLMs) has prompted concerns about the generation of misleading or fabricated information, known as hallucinations. Therefore, de…