1 citations · 2 across the 13 of their papers we have counts for
6 papers · 1 filter
Reasoning or Retrieval? A Study of Answer Attribution on Large Reasoning Models
Yuhui Wang, Changjiang Li, Guangke Chen +2
Large reasoning models (LRMs) exhibit unprecedented capabilities in solving complex problems through Chain-of-Thought (CoT) reasoning. However, recent studies reveal that their fin…
Self-Improving Model Steering
Rongyi Zhu, Yuhui Wang, Tanqiu Jiang +2
Model steering represents a powerful technique that dynamically aligns large language models (LLMs) with human preferences during inference. However, conventional model-steering me…
Your Agent Can Defend Itself against Backdoor Attacks
Li Changjiang, Liang Jiacheng, Cao Bochuan +2
Despite their growing adoption across domains, large language model (LLM)-powered agents face significant security risks from backdoor attacks during training and fine-tuning. Thes…
Dynamic Token Reweighting for Robust Vision-Language Models
Tanqiu Jiang, Jiacheng Liang, Rongyi Zhu +3
Large vision-language models (VLMs) are highly vulnerable to multimodal jailbreak attacks that exploit visual-textual interactions to bypass safety guardrails. In this paper, we pr…
AutoRAN: Automated Hijacking of Safety Reasoning in Large Reasoning Models
Jiacheng Liang, Tanqiu Jiang, Yuhui Wang +3
This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its core, AutoRAN pioneers an execution…
GraphRAG under Fire
Jiacheng Liang, Yuhui Wang, Changjiang Li +4
GraphRAG advances retrieval-augmented generation (RAG) by structuring external knowledge as multi-scale knowledge graphs, enabling language models to integrate both broad context a…