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20242026
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cs.CV2026

Position Rebinding Cache Reuse: Replay-Free Visual Revisiting for Interleaved Multimodal Reasoning

Mengzhao Wang, Yanli Ji, Wangmeng Zuo +2

Interleaved multimodal reasoning improves visual grounding by revisiting visual evidence during multi-step generation, yet existing methods typically rely on token replay, repeated…

cs.CV2025

FAVOR-Bench: A Comprehensive Benchmark for Fine-Grained Video Motion Understanding

Chongjun Tu, Lin Zhang, Pengtao Chen +5

Multimodal Large Language Models (MLLMs) have shown remarkable capabilities in video content understanding but still struggle with fine-grained motion comprehension. To comprehensi…

cs.CV2025

TokenCarve: Information-Preserving Visual Token Compression in Multimodal Large Language Models

Xudong Tan, Peng Ye, Chongjun Tu +5

Multimodal Large Language Models (MLLMs) are becoming increasingly popular, while the high computational cost associated with multimodal data input, particularly from visual tokens…

cs.CV2025

Attention Reallocation: Towards Zero-cost and Controllable Hallucination Mitigation of MLLMs

Chongjun Tu, Peng Ye, Dongzhan Zhou +4

Multi-Modal Large Language Models (MLLMs) stand out in various tasks but still struggle with hallucinations. While recent training-free mitigation methods mostly introduce addition…

cs.CV2024

-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers

Pengtao Chen, Mingzhu Shen, Peng Ye +5

Diffusion models are widely recognized for generating high-quality and diverse images, but their poor real-time performance has led to numerous acceleration works, primarily focusi…