collaborators

15 papers

cs.MM2026

Balancing Efficiency and Efficacy: Training-Free Attention-Guided Switching Between Explicit and Latent Thoughts for MLLMs

Haoqian Kang, Liupeng Li, Kuofeng Gao +5

Reasoning in Multimodal Large Language Models (MLLMs) requires both fine-grained visual perception and rigorous logical deduction. Explicit text-based Chain-of-Thought (CoT) is com…

cs.CV2026

Towards Consistent and Efficient Dataset Distillation via Diffusion-Driven Selection

Xinhao Zhong, Shuoyang Sun, Zhaoyang Xu +4

Dataset distillation provides an effective approach to reduce memory and computational costs by optimizing a compact dataset that achieves performance comparable to the full origin…

cs.CV2026

Beyond Heuristics: Learnable Density Control for 3D Gaussian Splatting

Zhenhua Ning, Xin Li, Jun Yu +3

While 3D Gaussian Splatting (3DGS) has demonstrated impressive real-time rendering performance, its efficacy remains constrained by a reliance on heuristic density control. Despite…

cs.CV2026

From Verbatim to Gist: Distilling Pyramidal Multimodal Memory via Semantic Information Bottleneck for Long-Horizon Video Agents

Niu Lian, Yuting Wang, Hanshu Yao +5

While multimodal large language models have demonstrated impressive short-term reasoning, they struggle with long-horizon video understanding due to limited context windows and sta…

cs.CV2026

Imagine Before Concentration: Diffusion-Guided Registers Enhance Partially Relevant Video Retrieval

Jun Li, Xuhang Lou, Jinpeng Wang +4

Partially Relevant Video Retrieval (PRVR) aims to retrieve untrimmed videos based on text queries that describe only partial events. Existing methods suffer from incomplete global…

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…