most citedWKVQuant: Quantizing Weight and Key/Value Cache for Large Language Models Gains More

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cs.CV2025

EA-ViT: Efficient Adaptation for Elastic Vision Transformer

Chen Zhu, Wangbo Zhao, Huiwen Zhang +9

Vision Transformers (ViTs) have emerged as a foundational model in computer vision, excelling in generalization and adaptation to downstream tasks. However, deploying ViTs to suppo…

cs.CV2025

MQuant: Unleashing the Inference Potential of Multimodal Large Language Models via Full Static Quantization

JiangYong Yu, Sifan Zhou, Dawei Yang +7

Multimodal large language models (MLLMs) have garnered widespread attention due to their ability to understand multimodal input. However, their large parameter sizes and substantia…

cs.CV2024

MVCTrack: Boosting 3D Point Cloud Tracking via Multimodal-Guided Virtual Cues

Zhaofeng Hu, Sifan Zhou, Zhihang Yuan +3

3D single object tracking is essential in autonomous driving and robotics. Existing methods often struggle with sparse and incomplete point cloud scenarios. To address these limita…

cs.CV2024

Information Entropy Guided Height-aware Histogram for Quantization-friendly Pillar Feature Encoder

Sifan Zhou, Zhihang Yuan, Dawei Yang +5

Real-time and high-performance 3D object detection plays a critical role in autonomous driving and robotics. Recent pillar-based 3D object detectors have gained significant attenti…

cs.CV2024

PillarTrack:Boosting Pillar Representation for Transformer-based 3D Single Object Tracking on Point Clouds

Weisheng Xu, Sifan Zhou, Jiaqi Xiong +2

LiDAR-based 3D single object tracking (3D SOT) is a critical issue in robotics and autonomous driving. Existing 3D SOT methods typically adhere to a point-based processing pipeline…