collaborators

10 papers

cs.AI2026

Entropy-Gradient Inversion: Moving Toward Internal Mechanism of Large Reasoning Models

Junyao Yang, Chen Qian, Kun Wang +4

The advancement of Large Reasoning Models (LRMs) has catalyzed a paradigm shift from reactive ``fast thinking'' text generation to systematic, step-by-step ``slow thinking'' reason…

cs.LG2026

PRISM: Preference-Aware Influence Function Based Data Selection Method for Efficient Fine-Tuning

Qihao Lin, Guanxu Chen, Dongrui Liu +1

As LLMs continue to scale up, improving training efficiency heavily relies on effective data utilization. Data selection mitigates this issue by allocating the limited training bud…

cs.CR2026

Frequency-Domain Regularized Adversarial Alignment for Transferable Attacks against Closed-Source MLLMs

Leitao Yuan, Qinghua Mao, Daizong Liu +5

Multimodal large language models (MLLMs) remain vulnerable to transfer-based targeted attacks, where perturbations optimized on open-source surrogate encoders can generalize to clo…

cs.SD2026

A Survey of Large Audio Language Models: Generalization, Trustworthiness, and Outlook

Kaiwen Luo, Zhenhong Zhou, Leo Wang +34

Advances in Large Language Models (LLMs) have paved the way for Multimodal Large Language Models (MLLMs). Among these, Large Audio Language Models (LALMs) are essential for realizi…

cs.CV2026

Focused Forcing: Content-Aware Per-Frame KV Selection for Efficient Autoregressive Video Diffusion

Peiliang Cai, Evelyn Zhang, Jiacheng Liu +8

Recent advances in autoregressive video diffusion have enabled sequential and streaming video generation. However, long-horizon generation requires increasingly large KV caches, ma…

cs.CV2026

Attention Hijacking: Response Manipulation Across Queries in Vision-Language Models

Zhiqiang Wang, Dongrui Liu, Yan Li +4

Existing adversarial attacks on vision-language models (VLMs) can steer model outputs toward attacker-specified target responses, but their effectiveness often degrades when the sa…