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From the 1 of 9 linked papers with an AI index.

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9 papers

cs.CV2026

Beyond the Eye: Efficient Multimodal Reasoning via Self-Regulated Implicit Visual Tools

Xiuwei Chen, Quanlin Chen, Wentao Hu +8

The paper introduces Beyond the Eye (BEE), an implicit visual‑tool framework for multimodal large language models that learns to self‑regulate when to invoke visual tools, reducing…

cs.CV2026

SyncLoop: A Multimodal Dual-Loop Framework for Self-Improving Mathematical Reasoning

Xiuwei Chen, Wentao Hu, Hanhui Li +9

Recent advances in multimodal large language models (MLLMs) have shown impressive reasoning capabilities. However, further enhancing existing MLLMs necessitates high-quality vision…

cs.CV2026

Latent Visual States for Efficient Multimodal Reasoning

Xiuwei Chen, Wentao Hu, Yongxin Wang +8

The integration of visual evidence has significantly enhanced the capabilities of large multimodal models. However, this integration predominantly relies on generating discrete out…

cs.CV2026

Intend, Reflect, Refine: An Adaptive Multimodal Reflection Framework for Autonomous Driving

Zisheng Chen, Yuping Qiu, Jianhua Han +6

Recent Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving by incorporating reasoning for better interpretability and planning quality. However, most ex…

cs.RO2026

AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots

Likui Zhang, Tao Tang, Zhihao Zhan +9

Recent advances in Visual-Language-Action (VLA) models have shown promising potential for robotic manipulation tasks. However, real-world robotic tasks often involve long-horizon,…

cs.CV2026

SemHiTok: A Unified Image Tokenizer via Semantic-Guided Hierarchical Codebook for Multimodal Understanding and Generation

Zisheng Chen, Chunwei Wang, Runhui Huang +6

In this paper, we introduce SemHiTok, a unified image Tokenizer via Semantic-Guided Hierarchical codebook that provides consistent discrete representations for multimodal understan…