3 papers
cs.CL2025
All Roads Lead to Rome: Graph-Based Confidence Estimation for Large Language Model Reasoning
Caiqi Zhang, Chang Shu, Ehsan Shareghi +1
Confidence estimation is essential for the reliable deployment of large language models (LLMs). Existing methods are primarily designed for factual QA tasks and often fail to gener…
cs.CL2025
Multi-Trigger Poisoning Amplifies Backdoor Vulnerabilities in LLMs
Sanhanat Sivapiromrat, Caiqi Zhang, Marco Basaldella +1
Recent studies have shown that Large Language Models (LLMs) are vulnerable to data poisoning attacks, where malicious training examples embed hidden behaviours triggered by specifi…
cs.CL2025
UNCLE: Benchmarking Uncertainty Expressions in Long-Form Generation
Ruihan Yang, Caiqi Zhang, Zhisong Zhang +4
Large Language Models (LLMs) are prone to hallucination, particularly in long-form generations. A promising direction to mitigate hallucination is to teach LLMs to express uncertai…