4 papers
OpenHalDet: A Unified Benchmark for Hallucination Detection across Diverse Generation Scenarios
Xinyi Li, Zhen Fang, Yongxin Deng +12
Hallucination detection is essential for the reliable deployment of large language models (LLMs). However, existing evaluations face two core challenges: inconsistent inference con…
Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection
Yongxin Deng, Zhen Fang, Sharon Li +1
Hallucination detection is critical for deploying large language models (LLMs) in real-world applications. Existing hallucination detection methods achieve strong performance when…
Reward Guidance for Reinforcement Learning Tasks Based on Large Language Models: The LMGT Framework
Yongxin Deng, Xihe Qiu, Jue Chen +1
The inherent uncertainty in the environmental transition model of Reinforcement Learning (RL) necessitates a delicate balance between exploration and exploitation. This balance is…
FedSlate:A Federated Deep Reinforcement Learning Recommender System
Yongxin Deng, Xihe Qiu, Xiaoyu Tan +1
Reinforcement learning methods have been used to optimize long-term user engagement in recommendation systems. However, existing reinforcement learning-based recommendation systems…