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From the 1 of 17 linked papers with an AI index.

most citedTowards Scientific Intelligence: A Survey of LLM-based Scientific Agents

6 citations · 6 across the 12 of their papers we have counts for

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cs.CV2026

SWITCH: Benchmarking Modeling and Handling of Tangible Interfaces in Long-horizon Embodied Scenarios

Juntao Cheng, Wanyue Zhang, Zhiwei Yu +7

Tangible control interfaces (TCIs), such as appliance panels, remotes, elevators, and embedded GUIs, are a fundamental component of everyday human-built environments. Interacting w…

cs.CV2026

World2VLM: Distilling World Model Imagination into VLMs for Dynamic Spatial Reasoning

Wanyue Zhang, Wenxiang Wu, Wang Xu +6

Vision-language models (VLMs) have shown strong performance on static visual understanding, yet they still struggle with dynamic spatial reasoning that requires imagining how scene…

cs.CV2025

Teaching Vision-Language Models to Ask: Resolving Ambiguity in Visual Questions

Pu Jian, Donglei Yu, Wen Yang +2

In visual question answering (VQA) context, users often pose ambiguous questions to visual language models (VLMs) due to varying expression habits. Existing research addresses such…

cs.CV2025

Look Again, Think Slowly: Enhancing Visual Reflection in Vision-Language Models

Pu Jian, Junhong Wu, Wei Sun +3

Recent advances in text-only "slow-thinking" reasoning have prompted efforts to transfer this capability to vision-language models (VLMs), for training visual reasoning models (\te…

cs.CV2025

Why Do MLLMs Struggle with Spatial Understanding? A Systematic Analysis from Data to Architecture

Wanyue Zhang, Yibin Huang, Yangbin Xu +5

Spatial understanding is essential for Multimodal Large Language Models (MLLMs) to support perception, reasoning, and planning in embodied environments. Despite recent progress, ex…