activity
20232026
most citedA Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks

2 citations · 2 across the 32 of their papers we have counts for

collaborators

33 papers

cs.CL2026

CHILLGuard: Towards Fine-Grained Chinese LLM Safety Guardrail with Scalable Data Construction and Model-aware Preference Alignment

Wenbo Yu, Bohua Wang, Hao Fang +10

Malicious content generated from large language models (LLMs) could pose severe safety risks and ethical concerns. While existing LLM safety guardrails excel in English or multilin…

cs.CR2026

MemVenom: Triggered Poisoning of Multimodal Memories in Web Agents

Yv Zhang, Hao Sun, Hao Fang +5

External memory has become a core component of modern web agents, enabling long-horizon reasoning through the retrieval of past experiences. However, this paradigm introduces a cri…

cs.CR2026

Bypassing Copyright Protection in Diffusion-based Customization via Two-Stage Latent Feature Optimization

Ziang Xu, Wenbo Yu, Hongyao Yu +6

With the growing concerns over copyright infringement in diffusion-based customization, adversarial attacks have emerged as a prominent defense strategy to prevent malicious conten…

cs.AI2026

Alignment Imprint: Zero-Shot AI-Generated Text Detection via Provable Preference Discrepancy

Junxi Wu, Kailin Huang, Dongjian Hu +4

Detecting AI-generated text is an important but challenging problem. Existing likelihood-based detection methods are often sensitive to content complexity and may exhibit unstable…

cs.CV2026

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: AI Flash Portrait (Track 3)

Ya-nan Guan, Shaonan Zhang, Hang Guo +55

In this paper, we present a comprehensive overview of the NTIRE 2026 3rd Restore Any Image Model (RAIM) challenge, with a specific focus on Track 3: AI Flash Portrait. Despite sign…

cs.CV2026

Seeing Through the Chain: Mitigate Hallucination in Multimodal Reasoning Models via CoT Compression and Contrastive Preference Optimization

Hao Fang, Jinyu Li, Jiawei Kong +4

While multimodal reasoning models (MLRMs) have exhibited impressive capabilities, they remain prone to hallucinations, and effective solutions are still underexplored. In this pape…