5 papers · 1 filter
AERO: Autonomous Evolutionary Reasoning Optimization via Endogenous Dual-Loop Feedback
Zhitao Gao, Jie Ma, Xuhong Li +5
Large Language Models (LLMs) have achieved significant success in complex reasoning but remain bottlenecked by reliance on expert-annotated data and external verifiers. While exist…
Detecting Training Data of Large Language Models via Expectation Maximization
Gyuwan Kim, Yang Li, Evangelia Spiliopoulou +2
Membership inference attacks (MIAs) aim to determine whether a specific example was used to train a given language model. While prior work has explored prompt-based attacks such as…
Play Favorites: A Statistical Method to Measure Self-Bias in LLM-as-a-Judge
Evangelia Spiliopoulou, Riccardo Fogliato, Hanna Burnsky +4
Large language models (LLMs) can serve as judges that offer rapid and reliable assessments of other LLM outputs. However, models may systematically assign overly favorable ratings…
Unraveling and Mitigating Safety Alignment Degradation of Vision-Language Models
Qin Liu, Chao Shang, Ling Liu +7
The safety alignment ability of Vision-Language Models (VLMs) is prone to be degraded by the integration of the vision module compared to its LLM backbone. We investigate this phen…
General Purpose Verification for Chain of Thought Prompting
Robert Vacareanu, Anurag Pratik, Evangelia Spiliopoulou +6
Many of the recent capabilities demonstrated by Large Language Models (LLMs) arise primarily from their ability to exploit contextual information. In this paper, we explore ways to…