2 papers
cs.CL2025
AdEval: Alignment-based Dynamic Evaluation to Mitigate Data Contamination in Large Language Models
Yang Fan
As Large Language Models (LLMs) are pre-trained on ultra-large-scale corpora, the problem of data contamination is becoming increasingly serious, and there is a risk that static ev…
cs.CR2025
Beyond Surface-Level Patterns: An Essence-Driven Defense Framework Against Jailbreak Attacks in LLMs
Shiyu Xiang, Ansen Zhang, Yanfei Cao +2
Although Aligned Large Language Models (LLMs) are trained to refuse harmful requests, they remain vulnerable to jailbreak attacks. Unfortunately, existing methods often focus on su…