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From the 1 of 15 linked papers with an AI index.

collaborators

15 papers

cs.CV2026

MultiAnimate: A Unified Framework for Controllable Multi-Character Animation

Zhongyi Zhang, Guangyuan Wang, Li Hu +6

The paper presents MultiAnimate, a framework that can animate several characters together in a shared scene while keeping each character's appearance and spatial relationships cons…

cs.CR2026

GUIGuard-Bench: Toward a General Evaluation for Privacy-Preserving GUI Agents

Yanxi Wang, Zhiling Zhang, Wenbo Zhou +6

As GUI agents increasingly rely on screenshots to perceive and operate digital environments, they may inadvertently expose sensitive information such as identities, accounts, locat…

cs.LG2026

VLMShield: Efficient and Robust Defense of Vision-Language Models against Malicious Prompts

Peigui Qi, Kunsheng Tang, Yanpu Yu +7

Vision-Language Models (VLMs) face significant safety vulnerabilities from malicious prompt attacks due to weakened alignment during visual integration. Existing defenses suffer fr…

cs.CR2026

State-Dependent Safety Failures in Multi-Turn Language Model Interaction

Pengcheng Li, Jie Zhang, Tianwei Zhang +5

Safety alignment in large language models is typically evaluated under isolated queries, yet real-world use is inherently multi-turn. Although multi-turn jailbreaks are empirically…

cs.CV2026

Rethinking Multi-Condition DiTs: Eliminating Redundant Attention via Position-Alignment and Keyword-Scoping

Chao Zhou, Tianyi Wei, Yiling Chen +2

While modern text-to-image models excel at prompt-based generation, they often lack the fine-grained control necessary for specific user requirements like spatial layouts or subjec…

cs.CL2026

Character as a Latent Variable in Large Language Models: A Mechanistic Account of Emergent Misalignment and Conditional Safety Failures

Yanghao Su, Wenbo Zhou, Tianwei Zhang +4

Emergent Misalignment refers to a failure mode in which fine-tuning large language models (LLMs) on narrowly scoped data induces broadly misaligned behavior. Prior explanations mai…