collaborators

10 papers

cs.CV2026

Topology-Aware Layer Pruning for Large Vision-Language Models

Pengcheng Zheng, Chaoning Zhang, Ya Wen +10

Large Language Models (LLMs) have demonstrated strong capabilities in natural language understanding and reasoning, while recent extensions that incorporate visual inputs enable th…

cs.AI2026

Lightweight LLM Agent Memory with Small Language Models

Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9

Although LLM agents can leverage tools for complex tasks, they still need memory to maintain cross-turn consistency and accumulate reusable information in long-horizon interactions…

cs.CV2026

Relaxing Anchor-Frame Dominance for Mitigating Hallucinations in Video Large Language Models

Zijian Liu, Sihan Cao, Pengcheng Zheng +5

Recent Video Large Language Models (Video-LLMs) have demonstrated strong capability in video understanding, yet they still suffer from hallucinations. Existing mitigation methods t…

cs.CV2026

Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps

Jianwei Zhang, Sihan Cao, Chaoning Zhang +7

Recent large-scale generative models enable high-quality 3D synthesis. However, the public accessibility of pre-trained weights introduces a critical vulnerability. Adversaries can…

cs.CV2026

RCP: Representation Consistency Pruner for Mitigating Distribution Shift in Large Vision-Language Models

Jianwei Zhang, Chaoning Zhang, Sihan Cao +7

Large Vision-Language Models (LVLMs) suffer from prohibitive inference costs due to the massive number of visual tokens processed by the language decoder. Existing pruning methods…

cs.CL2026

TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models

Jiaquan Zhang, Qigan Sun, Chaoning Zhang +11

Enhancing the reasoning capability of large language models (LLMs) remains a core challenge in natural language processing. The Chain-of-Thought (CoT) paradigm dominates practical…