3 papers
cs.AI2026
SAAS: Self-Aware Reinforcement Learning for Over-Search Mitigation in Agentic Search
Yunbo Tang, Chengyi Yang, Shiyu Liu +4
Agentic search enables LLMs to solve complex multi-hop questions through iterative reasoning and external search. Despite the effectiveness, these systems often suffer from a criti…
cs.CV2026
Countering the Over-Reliance Trap: Mitigating Object Hallucination for LVLMs via a Self-Validation Framework
Shiyu Liu, Xinyi Wen, Zhibin Lan +2
Despite progress in Large Vision Language Models (LVLMs), object hallucination remains a critical issue in image captioning task, where models generate descriptions of non-existent…
cs.CL2024
A Learning Rate Path Switching Training Paradigm for Version Updates of Large Language Models
Zhihao Wang, Shiyu Liu, Jianheng Huang +5
Due to the continuous emergence of new data, version updates have become an indispensable requirement for Large Language Models (LLMs). The training paradigms for version updates o…