1 citations · 2 across the 9 of their papers we have counts for
6 papers · 1 filter
FABLE: Fine-grained Fact Anchoring for Unstructured Model Editing
Peng Wang, Biyu Zhou, Xuehai Tang +2
Unstructured model editing aims to update models with real-world text, yet existing methods often memorize text holistically without reliable fine-grained fact access. To address t…
Paper Summary Attack: Jailbreaking LLMs through LLM Safety Papers
Liang Lin, Zhihao Xu, Xuehai Tang +5
The safety of large language models (LLMs) has garnered significant research attention. In this paper, we argue that previous empirical studies demonstrate LLMs exhibit a propensit…
Exploiting Synergistic Cognitive Biases to Bypass Safety in LLMs
Xikang Yang, Biyu Zhou, Xuehai Tang +2
Large Language Models (LLMs) demonstrate impressive capabilities across a wide range of tasks, yet their safety mechanisms remain susceptible to adversarial attacks that exploit co…
LyapLock: Bounded Knowledge Preservation in Sequential Large Language Model Editing
Peng Wang, Biyu Zhou, Xuehai Tang +2
Large Language Models often contain factually incorrect or outdated knowledge, giving rise to model editing methods for precise knowledge updates. However, current mainstream locat…
Chain of Attack: a Semantic-Driven Contextual Multi-Turn attacker for LLM
Xikang Yang, Xuehai Tang, Songlin Hu +1
Large language models (LLMs) have achieved remarkable performance in various natural language processing tasks, especially in dialogue systems. However, LLM may also pose security…
Hierarchical Interaction Networks with Rethinking Mechanism for Document-level Sentiment Analysis
Lingwei Wei, Dou Hu, Wei Zhou +5
Document-level Sentiment Analysis (DSA) is more challenging due to vague semantic links and complicate sentiment information. Recent works have been devoted to leveraging text summ…