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Spatial Reasoning

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Showing 201–225 of 453 papers

TitleStatusHype
A Pilot Evaluation of ChatGPT and DALL-E 2 on Decision Making and Spatial Reasoning—0
Embodied Scene Understanding for Vision Language Models via MetaVQA—0
Embodied Chain of Action Reasoning with Multi-Modal Foundation Model for Humanoid Loco-manipulation—0
Boosting Diffusion-Based Text Image Super-Resolution Model Towards Generalized Real-World Scenarios—0
An Evaluation of ChatGPT-4's Qualitative Spatial Reasoning Capabilities in RCC-8—0
Ego-Humans: An Ego-Centric 3D Multi-Human Benchmark—0
Ego-Centric Spatial Memory Networks—0
EarthGPT-X: Enabling MLLMs to Flexibly and Comprehensively Understand Multi-Source Remote Sensing Imagery—0
A Neural Representation Framework with LLM-Driven Spatial Reasoning for Open-Vocabulary 3D Visual Grounding—0
Navigating Motion Agents in Dynamic and Cluttered Environments through LLM Reasoning—0
Beyond the Hype: A dispassionate look at vision-language models in medical scenario—0
DriveVLM: The Convergence of Autonomous Driving and Large Vision-Language Models—0
Learning to encode spatial relations from natural language—0
Beyond Semantics: Rediscovering Spatial Awareness in Vision-Language Models—0
An Empirical Study of Conformal Prediction in LLM with ASP Scaffolds for Robust Reasoning—0
Advancing Egocentric Video Question Answering with Multimodal Large Language Models—0
3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow—0
Learning event representation: As sparse as possible, but not sparser—0
Large Language Models and Mathematical Reasoning Failures—0
Do Multimodal Language Models Really Understand Direction? A Benchmark for Compass Direction Reasoning—0
Beyond Recognition: Evaluating Visual Perspective Taking in Vision Language Models—0
Large Language-Geometry Model: When LLM meets Equivariance—0
LanguageRefer: Spatial-Language Model for 3D Visual Grounding—0
DivCon: Divide and Conquer for Progressive Text-to-Image Generation—0
LABNet: Local Graph Aggregation Network with Class Balanced Loss for Vehicle Re-Identification—0
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