activity
20242026
collaborators

8 papers

cs.CV2026

Just Noticeable Difference Modeling for Token Compression in Vision-Language-Action Models

Zhuoyuan Li, Rui Zhao, Jin Wang +5

Token compression has become a key technique for reducing the inference cost of large foundation models, with approaches such as token pruning and KV-cache reuse widely adopted in…

cs.CV2026

Current Injection Spiking Neural Network for Infrared and Visible Image Fusion

Rui Zhao, Zhuoyuan Li, Wenrui Li +4

Infrared and visible image fusion (IVIF) integrates the complementary information of two modalities into a single image with richer scene content. While existing methods are largel…

cs.CV2026

Just Noticeable Difference Modeling for Deep Visual Features

Rui Zhao, Wenrui Li, Lin Zhu +2

Deep visual features are increasingly used as the interface in vision systems, motivating the need to describe feature characteristics and control feature quality for machine perce…

cs.IR2026

RLPO: Residual Listwise Preference Optimization for Long-Context Review Ranking

Hao Jiang, Zhi Yang, Annan Wang +2

Review ranking is pivotal in e-commerce for prioritizing diagnostic and authentic feedback from the deluge of user-generated content. While large language models have improved sema…

cs.CV2025

Cross-architecture universal feature coding via distribution alignment

Changsheng Gao, Shan Liu, Feng Wu +1

Feature coding has become increasingly important in scenarios where semantic representations rather than raw pixels are transmitted and stored. However, most existing methods are a…

cs.MM2025

DT-UFC: Universal Large Model Feature Coding via Peaky-to-Balanced Distribution Transformation

Changsheng Gao, Zijie Liu, Li Li +3

Like image coding in visual data transmission, feature coding is essential for the distributed deployment of large models by significantly reducing transmission and storage burden.…

cs.CV2025

Compressed Feature Quality Assessment: Dataset and Baselines

Changsheng Gao, Wei Zhou, Guosheng Lin +1

The widespread deployment of large models in resource-constrained environments has underscored the need for efficient transmission of intermediate feature representations. In this…

cs.MM2024

Feature Coding in the Era of Large Models: Dataset, Test Conditions, and Benchmark

Changsheng Gao, Yifan Ma, Qiaoxi Chen +3

Large models have achieved remarkable performance across various tasks, yet they incur significant computational costs and privacy concerns during both training and inference. Dist…