2 citations · 3 across the 18 of their papers we have counts for
19 papers
VBVR-Pro: A Scalable and Verifiable Suite for Native Visual Reasoning
Junxiang Xu, Ruisi Wang, Fanyi Pu +49
Native visual reasoning treats visual generation as the medium of reasoning itself: visual states (i.e. images and videos) are not merely inputs to be understood or outputs to be r…
Ideas Have Genomes: Benchmarking Scientific Lineage Reasoning and Lineage-Grounded Idea Generation
Yifan Zhou, Qihao Yang, Yan Li +14
Scientific ideas rarely start from a blank page. They inherit mechanisms, repair known limitations, and recombine pieces of earlier work, much like biological genomes. Current benc…
PhyGround: Benchmarking Physical Reasoning in Generative World Models
Juyi Lin, Arash Akbari, Yumei He +13
Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern real-world dynamics. However, ev…
Demystifying Video Reasoning
Ruisi Wang, Zhongang Cai, Fanyi Pu +11
Recent advances in video generation have revealed an unexpected phenomenon: diffusion-based video models exhibit non-trivial reasoning capabilities. Prior work attributes this to a…
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…
A Very Big Video Reasoning Suite
Maijunxian Wang, Ruisi Wang, Juyi Lin +53
Rapid progress in video models has largely focused on visual quality, leaving their reasoning capabilities underexplored. Video reasoning grounds intelligence in spatiotemporally c…
Egocentric Bias in Vision-Language Models
Maijunxian Wang, Yijiang Li, Bingyang Wang +6
Visual perspective taking--inferring how the world appears from another's viewpoint--is foundational to social cognition. We introduce FlipSet, a diagnostic benchmark for Level-2 v…
Video Models Start to Solve Chess, Maze, Sudoku, Mental Rotation, and Raven' Matrices
Hokin Deng
We show that video generation models could reason now. Testing on tasks such as chess, maze, Sudoku, mental rotation, and Raven's Matrices, leading models such as Sora-2 achieve si…
Rethinking the Simulation vs. Rendering Dichotomy: No Free Lunch in Spatial World Modelling
Dezhi Luo, Qingying Gao, Hokin Deng
Spatial world models, representations that support flexible reasoning about spatial relations, are central to developing computational models that could operate in the physical wor…
Vision-Language Models Mistake Head Orientation for Gaze Direction: Nonverbal Conversation Cues
Zory Zhang, Pinyuan Feng, Bingyang Wang +7
Where someone looks is a nonverbal communication cue that children and adults readily use. How well can Vision-Language Models (VLMs) infer gaze targets? To construct evaluation st…
Increasing Computation Resolves Conflicts in Vision Language Models
Bingyang Wang, Yijiang Li, Yitong Qiao +7
Cognitive control, the ability to coordinate competing information sources in pursuit of goals, is fundamental to intelligent behavior. We systematically investigate whether Vision…
Proceedings of 1st Workshop on Advancing Artificial Intelligence through Theory of Mind
Mouad Abrini, Omri Abend, Dina Acklin +105
This volume includes a selection of papers presented at the Workshop on Advancing Artificial Intelligence through Theory of Mind held at AAAI 2025 in Philadelphia US on 3rd March 2…
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…
Probing Perceptual Constancy in Large Vision-Language Models
Haoran Sun, Bingyang Wang, Suyang Yu +14
Perceptual constancy is the ability to maintain stable perceptions of objects despite changes in sensory input, such as variations in distance, angle, or lighting. This ability is…
Core Knowledge Deficits in Multi-Modal Language Models
Yijiang Li, Qingying Gao, Tianwei Zhao +8
While Multi-modal Large Language Models (MLLMs) demonstrate impressive abilities over high-level perception and reasoning, their robustness in the wild remains limited, often falli…
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…
Vision Language Models See What You Want but not What You See
Qingying Gao, Yijiang Li, Haiyun Lyu +3
Knowing others' intentions and taking others' perspectives are two core components of human intelligence that are considered to be instantiations of theory-of-mind. Infiltrating ma…
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…
Use-dependent Biases as Optimal Action under Information Bottleneck
Hokin Deng, Adrian Haith
Use-dependent bias is a phenomenon in human sensorimotor behavior whereby movements become biased towards previously repeated actions. Despite being well-documented, the reason why…