activity
20242026
collaborators

12 papers

cs.CL2026

New Terms, New Toxicity: Consensus-based Chinese Neologism Toxicity Detection via Search-Augmented LLMs

Shiyao Cui, QingLin Zhang, Di Wang +7

Neologisms, emerging terms in meaning or form, can serve as new vehicles for toxic expression, like "country girl" as a stigmatizing label targeting feminism. Such toxic neologisms…

cs.AI2026

Survive at All Costs: Exploring LLM's Risky Behaviors under Survival Pressure

Yida Lu, Jianwei Fang, Xuyang Shao +7

As Large Language Models (LLMs) evolve from chatbots to agentic assistants, they are increasingly observed to exhibit risky behaviors when subjected to survival pressure, such as t…

cs.CL2026

The Missing Half: Unveiling Training-time Implicit Safety Risks Beyond Deployment

Zhexin Zhang, Yida Lu, Junfeng Fang +8

Safety risks of AI models have been widely studied at deployment time, such as jailbreak attacks that elicit harmful outputs. In contrast, safety risks emerging during training rem…

cs.CV2026

The Side Effects of Being Smart: Safety Risks in MLLMs' Multi-Image Reasoning

Renmiao Chen, Yida Lu, Shiyao Cui +6

As Multimodal Large Language Models (MLLMs) acquire stronger reasoning capabilities to handle complex, multi-image instructions, this advancement may pose new safety risks. We stud…

cs.CV2025

VPO: Aligning Text-to-Video Generation Models with Prompt Optimization

Jiale Cheng, Ruiliang Lyu, Xiaotao Gu +9

Video generation models have achieved remarkable progress in text-to-video tasks. These models are typically trained on text-video pairs with highly detailed and carefully crafted…

cs.MM2025

ShieldVLM: Safeguarding the Multimodal Implicit Toxicity via Deliberative Reasoning with LVLMs

Shiyao Cui, Qinglin Zhang, Xuan Ouyang +6

Toxicity detection in multimodal text-image content faces growing challenges, especially with multimodal implicit toxicity, where each modality appears benign on its own but convey…