1 citations · 1 across the 6 of their papers we have counts for
6 papers
Reasoning as an Attack Surface: Adaptive Evolutionary CoT Jailbreaks for LLMs
Jianan Li, Simeng Qin, Xiaojun Jia +5
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in reasoning and generation tasks and are increasingly deployed in real-world applications. However, their e…
Obscure but Effective: Classical Chinese Jailbreak Prompt Optimization via Bio-Inspired Search
Xun Huang, Simeng Qin, Xiaoshuang Jia +6
As Large Language Models (LLMs) are increasingly used, their security risks have drawn increasing attention. Existing research reveals that LLMs are highly susceptible to jailbreak…
ODAR: Principled Adaptive Routing for LLM Reasoning via Active Inference
Siyuan Ma, Bo Gao, Xiaojun Jia +6
The paradigm of large language model (LLM) reasoning is shifting from parameter scaling to test-time compute scaling, yet many existing approaches still rely on uniform brute-force…
Multi-scale Temporal Prediction via Incremental Generation and Multi-agent Collaboration
Zhitao Zeng, Guojian Yuan, Junyuan Mao +3
Accurate temporal prediction is the bridge between comprehensive scene understanding and embodied artificial intelligence. However, predicting multiple fine-grained states of a sce…
Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment
Ruoxi Cheng, Haoxuan Ma, Weixin Wang +7
Alignment is vital for safely deploying large language models (LLMs). Existing techniques are either reward-based (training a reward model on preference pairs and optimizing with r…
PBI-Attack: Prior-Guided Bimodal Interactive Black-Box Jailbreak Attack for Toxicity Maximization
Ruoxi Cheng, Yizhong Ding, Shuirong Cao +6
Understanding the vulnerabilities of Large Vision Language Models (LVLMs) to jailbreak attacks is essential for their responsible real-world deployment. Most previous work requires…