4 papers
Invisible Ink, Visible Lies: How Production Watermarking Causes LLMs to Hallucinate
Haocheng Ye, Aoting Hu, Xinwei Zhang +3
Text watermarking helps identify AI-generated content, but its effect on factual reliability remains underexplored. In this paper, we study watermarking hallucination: factual erro…
BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models
Yuanhao Li, Hongbo Wang, Xiaotang Shang +3
Reinforcement learning for program repair is hindered by sparse execution feedback and coarse sequence-level rewards that obscure which edits actually fix bugs. We present BoostAPR…
Defusing the Trigger: Tail-Risk-Informed Attention Rebalancing for LLM Backdoor Mitigation
Kaisheng Fan, Yishu Gao, Xunzhu Tang +2
Backdoored large language models (LLMs) exhibit attacker-specified behavior at inference time while retaining normal performance on benign inputs. Existing mitigations often requir…
ReasonBridge: Efficient Reasoning Transfer from Closed to Open-Source Language Models
Ziqi Zhong, Xunzhu Tang
Recent advancements in Large Language Models (LLMs) have revealed a significant performance gap between closed-source and open-source models, particularly in tasks requiring comple…