Author

Meng Zhang

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Preprint Aug 2026

GSTEP: Global Spatio-Temporal Density-Driven Visual Token Pruning for Efficient Video Large Language Models

Video large language models (VideoLLMs) achieve strong video understanding performance, but their inference remains expensive due to the large number of redundant spatio-temporal visual tokens in long videos. Existing token pruning methods alleviate this cost by reducing redundant tokens, yet most of them rely on segme...

Meng-Jie Zhang, Qi-Hui Zhu, Tao Zhang et al. · 0 citations

#natural language process... Preprint Sep 2026

LatCom: Cross-Agent Latent Compression for Efficient Multi-Agent Collaboration

This work proposes LatCom, a cross-agent latent compression framework for efficient multi-agent latent collaboration, which achieves an average 2.46x inference speed-up over LatentMAS and reduces output token usage by 70.3% while maintaining comparable average accuracy.

Shi-Nan Zhang, Tao Zhang, Qi-Hui Zhu et al. · 0 citations

Jul 2026

RP-OPSD: Resolution-Privileged On-Policy Self-Distillation for Multimodal Large Language Models

It is demonstrated that resolution differences can serve as a simple and scalable source of privileged information, providing an effective and efficient approach to on-policy self-distillation for multimodal large language models.

Qihui Zhu, Yucheng Wang, Zi-Jian Wen et al. · arXiv.org · 0 citations