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20242026
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cs.CV2026

SpatialImaginer: Towards Adaptive Visual Imagination for Spatial Reasoning

Yian Li, Yang Jiao, Bin Zhu +4

Spatial intelligence, which refers to the ability to reason about geometric and physical structure from visual observations, remains a core challenge for multimodal large language…

cs.CV2025

UniToken: Harmonizing Multimodal Understanding and Generation through Unified Visual Encoding

Yang Jiao, Haibo Qiu, Zequn Jie +4

We introduce UniToken, an auto-regressive generation model that encodes visual inputs through a combination of discrete and continuous representations, enabling seamless integratio…

cs.CV2024

Making Large Language Models Better Planners with Reasoning-Decision Alignment

Zhijian Huang, Tao Tang, Shaoxiang Chen +5

Data-driven approaches for autonomous driving (AD) have been widely adopted in the past decade but are confronted with dataset bias and uninterpretability. Inspired by the knowledg…

cs.CV2024

MindBench: A Comprehensive Benchmark for Mind Map Structure Recognition and Analysis

Lei Chen, Feng Yan, Yujie Zhong +3

Multimodal Large Language Models (MLLM) have made significant progress in the field of document analysis. Despite this, existing benchmarks typically focus only on extracting text…

cs.CV2024

Fewer Tokens and Fewer Videos: Extending Video Understanding Abilities in Large Vision-Language Models

Shimin Chen, Yitian Yuan, Shaoxiang Chen +2

Amidst the advancements in image-based Large Vision-Language Models (image-LVLM), the transition to video-based models (video-LVLM) is hindered by the limited availability of quali…

cs.CV2024

Lumen: Unleashing Versatile Vision-Centric Capabilities of Large Multimodal Models

Yang Jiao, Shaoxiang Chen, Zequn Jie +3

Large Multimodal Model (LMM) is a hot research topic in the computer vision area and has also demonstrated remarkable potential across multiple disciplinary fields. A recent trend…