works on

From the 2 of 20 linked papers with an AI index.

collaborators

20 papers

cs.AI2026

Who Bridges Safety? Identifying and Targeting Cross-Lingual Shared Safety Pathways

Shuyi Miao, Wangjie Qiu, Pengyang Shao +4

Uncovering the internal mechanisms underlying the safety capabilities of large language models (LLMs) is crucial for developing trustworthy artificial intelligence. Currently, mech…

cs.CV2026

V-FIND: Revealing the Intrinsic Forgery Knowledge Encoded in Video Forgery Detectors

Shichao Kan, Chengpeng Hong, Jingtong Dou +8

As generated videos become increasingly realistic, reliable video forgery detection is increasingly important. Existing studies typically optimize and use video forgery detectors a…

cs.CR2026

Moving the Safety Barrier: Dynamic Routing Adaptive Alignment Against White-Box Attacks

Shangze Li, Chuancheng Shi, Simiao Xie +6

With the widespread deployment of large foundation models (LFMs) in open environments, safety threats are shifting from black-box jailbreaks toward white-box attacks that directly…

cs.AI2026

No Single Neuron of Failure: Distributed Safety Alignment Against White-Box Attacks

Simiao Xie, Chuancheng Shi, Shangze Li +5

With the rapid release of open-weight large foundation models, safety threats are shifting from black-box jailbreaks to neuron-level white-box attacks that directly identify and ma…

cs.CV2026

SafeNexus: Discovering and Steering Modality-Universal Safety Neurons in MLLMs

Jian Yu, Fei Shen, Cong Wang +6

Although Large Language Models (LLMs) have demonstrated promising safety performance, extending them to Multimodal Large Language Models (MLLMs) exposes a significant gap between e…

cs.CE2026

CoLAS: Multimodal Corroboration of Latent Asset Signals for Financial Trading

Yanzheng Jin, Pengyang Shao, Xiaohao Liu +3

CoLAS is a multimodal learning framework that extracts trading signals by identifying and reinforcing shared information across price data, news, and sentiment, improving robustnes…