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From the 2 of 17 linked papers with an AI index.

most citedEgocentric Bias in Vision-Language Models

1 citations · 1 across the 10 of their papers we have counts for

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cs.AI2026

Contextualized Evaluation of Vision Language Models through Dynamic, Multi-turn Interactions

Yijiang Li, Huiqi Zou, Bingyang Wang +1

The paper presents CEDI, a framework that evaluates vision‑language models through multi‑turn, interactive dialogues between the model, an automated examiner, and a grader, uncover…

cs.AI2026

Vision Language Models Cannot Reason About Physical Transformation

Dezhi Luo, Yijiang Li, Maijunxian Wang +7

Understanding physical transformations is fundamental for reasoning in dynamic environments. While Vision Language Models (VLMs) show promise in embodied applications, whether they…

cs.AI2026

SPACENUM: Revisiting Spatial Numerical Understanding in VLMs

Jianshu Zhang, Yijiang Li, Huifeixin Chen +4

Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce numerical outputs such as action magnitudes and spatial coordinates. Altho…

cs.AI2025

The Philosophical Foundations of Growing AI Like A Child

Dezhi Luo, Yijiang Li, Hokin Deng

Despite excelling in high-level reasoning, current language models lack robustness in real-world scenarios and perform poorly on fundamental problem-solving tasks that are intuitiv…

cs.AI2025

Vision Language Models Know Law of Conservation without Understanding More-or-Less

Dezhi Luo, Haiyun Lyu, Qingying Gao +3

Understanding law of conservation is a critical milestone in human cognitive development considered to be supported by the apprehension of quantitative concepts and the reversibili…

cs.AI2025

Probing Mechanical Reasoning in Large Vision Language Models

Haoran Sun, Qingying Gao, Haiyun Lyu +3

Mechanical reasoning is a hallmark of human intelligence, defined by its ubiquitous yet irreplaceable role in human activities ranging from routine tasks to civil engineering. Embe…