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cs.CV2026

EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning

Pengtao Ma, Ziliang Zhou, Ciyu Ruan +7

First-person dynamic spatial reasoning requires models to track continuous motion and precise geometric structure, but the quadratic attention cost of Transformer-based Video-LLMs…

cs.CV2025

Progressive Supernet Training for Efficient Visual Autoregressive Modeling

Xiaoyue Chen, Yuling Shi, Kaiyuan Li +5

Visual Auto-Regressive (VAR) models significantly reduce inference steps through the "next-scale" prediction paradigm. However, progressive multi-scale generation incurs substantia…

cs.CV2025

EgoPrune: Efficient Token Pruning for Egomotion Video Reasoning in Embodied Agent

Jiaao Li, Kaiyuan Li, Chen Gao +2

Egomotion videos are first-person recordings where the view changes continuously due to the agent's movement. As they serve as the primary visual input for embodied AI agents, maki…

cs.CV2025

DIMM: Decoupled Multi-hierarchy Kalman Filter for 3D Object Tracking

Jirong Zha, Yuxuan Fan, Kai Li +4

State estimation is challenging for 3D object tracking with high maneuverability, as the target's state transition function changes rapidly, irregularly, and is unknown to the esti…

cs.CV2025

Balanced Token Pruning: Accelerating Vision Language Models Beyond Local Optimization

Kaiyuan Li, Xiaoyue Chen, Chen Gao +2

Large Vision-Language Models (LVLMs) have shown impressive performance across multi-modal tasks by encoding images into thousands of tokens. However, the large number of image toke…

cs.CV2025

The Point, the Vision and the Text: Does Point Cloud Boost Spatial Reasoning of Large Language Models? A Bias-Controlled Study

Weichen Zhang, Ruiying Peng, Xin Zeng +9

3D Large Language Models (LLMs) leveraging spatial information in point clouds for 3D spatial reasoning attract great attention. Despite some promising results, the advantages of p…

cs.CV2025

PLPHP: Per-Layer Per-Head Vision Token Pruning for Efficient Large Vision-Language Models

Yu Meng, Kaiyuan Li, Chenran Huang +4

Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across a range of multimodal tasks. However, their inference efficiency is constrained by the large n…

cs.CV2025

Understanding and Evaluating Hallucinations in 3D Visual Language Models

Ruiying Peng, Kaiyuan Li, Weichen Zhang +3

Recently, 3D-LLMs, which combine point-cloud encoders with large models, have been proposed to tackle complex tasks in embodied intelligence and scene understanding. In addition to…