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cs.CV2026

SJD-PAC: Accelerating Speculative Jacobi Decoding via Proactive Drafting and Adaptive Continuation

Jialiang Kang, Han Shu, Wenshuo Li +2

Speculative Jacobi Decoding (SJD) offers a draft-model-free approach to accelerate autoregressive text-to-image synthesis. However, the high-entropy nature of visual generation yie…

cs.CV2026

Align-KD: Distilling Cross-Modal Alignment Knowledge for Mobile Vision-Language Model Enhancement

Qianhan Feng, Wenshuo Li, Tong Lin +1

Vision-Language Models (VLMs) bring powerful understanding and reasoning capabilities to multimodal tasks. Meanwhile, the great need for capable aritificial intelligence on mobile…

cs.CV2026

TinySAM 2: Extreme Memory Compression for Efficient Track Anything Model

Zhaoyuan Ding, Yijing Yang, Han Shu +1

Segment Anything Model 2 (SAM 2) serves as a core foundation model in the field of video segmentation. Building upon the original SAM model, it introduces a memory bank mechanism a…

cs.CV2025

ViSpec: Accelerating Vision-Language Models with Vision-Aware Speculative Decoding

Jialiang Kang, Han Shu, Wenshuo Li +2

Speculative decoding is a widely adopted technique for accelerating inference in large language models (LLMs), yet its application to vision-language models (VLMs) remains underexp…

cs.CV2024

Full-Stage Pseudo Label Quality Enhancement for Weakly-supervised Temporal Action Localization

Qianhan Feng, Wenshuo Li, Tong Lin +1

Weakly-supervised Temporal Action Localization (WSTAL) aims to localize actions in untrimmed videos using only video-level supervision. Latest WSTAL methods introduce pseudo label…