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20232026
most citedLet All be Whitened: Multi-teacher Distillation for Efficient Visual Retrieval

1 citations · 1 across the 13 of their papers we have counts for

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cs.CR2026

Understanding and Mitigating Prompt Leaking Attacks in Real-World LLM-Based Applications

Yong Yang, Chong Fu, Tong Zhang +6

Large language model (LLM)-based applications rely on system prompts to encode core logic and developer-defined constraints, making these prompts important intellectual property. H…

cs.LG2026

Accelerating GPU Inference of Large Language Models with Moderately Unstructured Sparse Weight Matrices

Tao Lu, Haoyu Wang, Zonghui Wang +3

With the growing deployment of large language models (LLMs), LLM inference cost has become a key challenge. Pruning techniques that introduce sparsity into weight matrices can acce…

cs.CV2026

MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models

Yuansheng Gao, Wenbin Xing, Jiahao Yuan +4

Video Large Multimodal Models have achieved remarkable progress in video understanding, yet they remain prone to hallucinations, where generated responses are not faithfully suppor…

cs.LG2026

On the (Generative) Linear Sketching Problem

Xinyu Yuan, Yan Qiao, Zonghui Wang +1

Sketch techniques have been extensively studied in recent years and are especially well-suited to data streaming scenarios, where the sketch summary is updated quickly and compactl…

cs.LG2026

Divide, Harmonize, Then Conquer It: Shooting Multi-Commodity Flow Problems with Multimodal Language Models

Xinyu Yuan, Yan Qiao, Zonghui Wang +1

The multi-commodity flow (MCF) problem is a fundamental topic in network flow and combinatorial optimization, with broad applications in transportation, communication, and logistic…

cs.NI2026

LMTE: Putting the "Reasoning" into WAN Traffic Engineering with Language Models

Xinyu Yuan, Yan Qiao, Zonghui Wang +2

The rapid expansion of modern wide-area networks (WANs) has made traffic engineering (TE) increasingly challenging, as traditional solvers struggle to keep pace. Although existing…

cs.CV2026

Enhancing Video Representations with Spatiotemporal-Semantic Residual to Mitigate Hallucinations in Video Large Multimodal Models

Yuansheng Gao, Jinman Zhao, Tong Zhang +5

Although Video Large Multimodal Models have achieved strong performance in video understanding, they still suffer from hallucination. Existing inference-time intervention methods u…