Visually Grounded Reasoning

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17 papers in the last four weeks, up 183% on the four weeks before. 0.2% of all new papers.

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STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images
Jun 5, 2026Abhiroop Ajith, Constantinos ChamzasLong-Horizon Robotic Manipulation World Models for Robotics
Department of Robotics Engineering · Worcester Polytechnic Institute · United States
Thinking with Imagination: Agentic Visual Spatial Reasoning with World Simulators
Jun 4, 2026Chenming Zhu, Jingli Lin, Yilin Long +4Visual Spatial Reasoning World Model Learning
1The University of Hong Kong · 2Shanghai AI Laboratory · 3Shanghai Jiao Tong University +2
HyperVis: Continuous Latent Visual Relational Graphs on the Lorentz Hyperboloid for Compositional Reasoning
Jun 4, 2026Moshiur Farazi, Sameera Ramasinghe, Mahbub Ahmed Turza +1Visual Reasoning VLM Reasoning
Data Science and AI, University of Doha for Science and Technology, Qatar · Pluralis Research, Australia · Department of Electrical and Computer Engineering, North South University, Bangladesh
Imagine Before You Predict: Interleaved Latent Visual Reasoning for Video Event Prediction
Jun 4, 2026Tianxiang Jiang, Linquan Wu, Sheng Xia +5Large Vision-Language Models Latent Visual Reasoning
University of Science and Technology of China · Shanghai AI Laboratory · City University of Hong Kong +4
PlanBench-V: A Spatial Planning Map Benchmark for Vision-Language Models
Jun 4, 2026Minxin Chen, He Zhu, Junyou Su +3VLM Evaluation Spatial Reasoning Benchmarks
1Behavioral and Spatial AI Lab, Tongji University · 2Behavioral and Spatial AI Lab, Peking University · College of Architecture and Urban Planning, Tongji University
UltraVR: A Diagnostic Ultra-Resolution Image-VQA Benchmark for Evidence-Grounded Reasoning
Jun 4, 2026Gexin Huang, Yanting Yang, Myeongkyun Kang +6VLM Evaluation Visual Question Answering
University of British Columbia, Vancouver, BC, Canada · Vector Institute, Toronto, ON, Canada · The Hong Kong Polytechnic University, Hong Kong SAR, China +1
WorldBench: A Challenging and Visually Diverse Multimodal Reasoning Benchmark
Jun 4, 2026Yida Yin, Harish Krishnakumar, Chung Peng Lee +9Multimodal Large Language Models Multimodal Reasoning
Princeton University · NYU · University of Waterloo +1
What Objects Enable, Not What They Are: Functional Latent Spaces for Affordance Reasoning
Jun 4, 2026Rohan Siva, Neel P. Bhatt, Yunhao Yang +6Latent Visual Reasoning Robot Task Planning
1The University of Texas at Austin · 2Neurosymbolic Intelligence · University of Colorado Boulder
NoRA: Evaluating Grounded Reasonableness in Visual First-person Normative Action Reasoning
Jun 3, 2026Sichao Li, Sai Ma, Daniel Kilov +3VLM Evaluation Moral Reasoning in Language Models
The University of Sydney · Australian National University · RMIT University +1
Answer Self-Consistency with Margin-Triggered Question Re-Arbitration for the CVPR 2026 VidLLMs Challenge
Jun 3, 2026Tomoya Miyazawa, Hiroyasu OkunoVLM Evaluation Self-Consistency Decoding
Data Analytics Labo Co.
VAMPS: Visual-Assisted Mathematical Problem Solving Benchmark
Jun 2, 2026Amirhossein Dabiriaghdam, Shayan Vassef, Mohammadreza Bakhtiari +5Mathematical Reasoning Benchmarks Mathematical Reasoning
University of British Columbia · University of Illinois Chicago · Stony Brook University
Imaginative Perception Tokens Enhance Spatial Reasoning in Multimodal Language Models
Jun 2, 2026Mahtab Bigverdi, Linjie Li, Weikai Huang +8Visual Spatial Reasoning Visual Reasoning
University of Washington · 2Allen Institute for AI · 3Microsoft +1
Entropy Is Not Enough: Unlocking Effective Reinforcement Learning for Visual Reasoning via Vision-Anchored Token Selection
Jun 2, 2026Senjie Jin, Peixin Wang, Boyang Liu +8Token-Level Credit Assignment Visual Reasoning
College of Computer Science and Artificial Intelligence, Fudan University
TurtleAI: Benchmarking Multimodal Models for Visual Programming in Turtle Graphics
Jun 2, 2026Chao Wen, Jacqueline Staub, Adish SinglaVLM Evaluation LLM-Based Program Synthesis
MPI-SWS · University of Trier
World Models Meet Language Models: On the Complementarity of Concrete and Abstract Reasoning
Jun 2, 2026Yucheng Zhou, Wei Tao, Yiwen Guo +1On-Policy Self-Distillation World Models
University of Macau · LIGHTSPEED · Independent Researcher
VistaHop: Benchmarking Multi-hop Visual Reasoning for Visual DeepSearch
Jun 2, 2026Hang He, Chuhuai Yue, Chengqi Dong +6VLM Evaluation Visual Question Answering
1East China Normal University · 2Meituan · 3Shanghai Innovation Institute
Spectral-Progressive Thought Flow for Lightweight Multimodal Reasoning
Jun 1, 2026Yixian Shen, Zhiheng Yang, Qi Bi +6Efficient Multimodal Inference Visual Spatial Reasoning
Informatics Institute, University of Amsterdam, Amsterdam, The Netherlands · University of Thessaly, Volos, Greece · Department of Computer Science, University College London +3
Consistent Yet Wrong: Evidence Insensitivity in Spatial Vision-Language Models
Jun 1, 2026S Divakar Bhat, Toshihiko YamasakiVLM Evaluation Multi-View Consistency
The University of Tokyo, Japan
Question-Aware Evidence Ledgers for Video Relational Reasoning
Jun 1, 2026Yilin Ou, Mengshi Qi, Huadong MaVisual Spatial Reasoning Relational Reasoning
State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications, China
Active Exploring like a Pigeon: Reinforcing Spatial Reasoning via Agentic Vision-Language Models
Jun 1, 2026Wei Deng, Xianlin Zhang, Mengshi QiActive Perception Visual Spatial Reasoning
State Key Laboratory of Networking and Switching Technology · Beijing University of Posts and Telecommunications, China · School of Digital Media & Design Arts
InsightVQA: High-Dimensional Emotion-Cognitive Visual Question Answering Benchmark
Jun 1, 2026Shiyu Wang, Ziyu Liu, Chaoyi Yu +6VLM Evaluation Visual Question Answering
East China Normal University, Shanghai, China
Goal2Pixel: Grounding Goals to Pixels for Vision-Language Navigation
Jun 1, 2026Muyi Bao, Yuxin Cai, Hang Xu +7Embodied Navigation VLM Adaptation
Carnegie Mellon University · Nanyang Technological University
TRON: Targeted Rule-Verifiable Online Environments for Visual Reasoning RL
Jun 1, 2026Tianze Yang, Yucheng Shi, Ruitong Sun +3Reinforcement Learning VLM Reasoning
University of Georgia
Attention-guided Fine-tuning of Multimodal Large Language Models Improves Chain-of-Thought Reasoning
Jun 1, 2026Sanchit Sinha, Guangzhi Xiong, Bohan Liu +2Fine-Tuning Multimodal Large Language Models
University of Virginia
Perception First: A Frontier Native-Video Model with Self-Consistency for Implicit Video Question Answering
May 31, 2026Ali AlaviVisual Spatial Reasoning Video QA
The Ohio State University
Beyond Visual Memory: Mechanistic Diagnostics of Latent Visual Reasoning
May 31, 2026Garvin Guo, Yu Chen, Xiang Wang +4VLM Evaluation VLM Interpretability
Amap, Alibaba Group · Shanghai Innovation Institute
Temporal Evidence Routing with Structured Visual Evidence for TimeLogicQA
May 31, 2026Yuyang Sun, Yongliang Wu, Xingyu Zhu +8Video QA Structured Reasoning
Southeast University · National University of Singapore · Independent Researcher +2
Reasmory: 3D Reconstruction as Explicit Memory for VLMs Spatial Reasoning
May 31, 2026Jixuan He, Xueting Li, Chieh Hubert Lin +13D Spatial Reasoning VLM Reasoning
Cornell Tech, Cornell University · NVIDIA · illoca AI +1
Pause and Think: A Dataset and Benchmark for Video-Grounded Assistive Action Suggestion
May 30, 2026Shivam Singh, Saptarshi Majumder, Pratik Prabhanjan Brahma +2Vision-Language Grounding Video Reasoning
IIIT Hyderabad · Work done during Shivam Singh’s internship at Advanced Micro Devices, Inc. (AMD). · Advanced Micro Devices, Inc. (AMD)
DeepLatent: Think with Images via Parallel Latent Visual Reasoning
May 30, 2026Dongchen Lu, Zhimo Li, Mao Shu +1Latent Visual Reasoning VLM Reasoning
Baidu Inc. · Peking University

Jun 5, 2026, cs.ROJ/K move · Enter open · S save

STRIPS-WM: Learning Grounded Propositional STRIPS-style World Models from Images

Abhiroop Ajith, Constantinos Chamzas

Department of Robotics Engineering · Worcester Polytechnic Institute · United States

Long-Horizon Robotic Manipulation World Models for Robotics Symbolic Planning World Model-Based Planning Robot Task Planning Visually Grounded Reasoning

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Robots performing long-horizon visual manipulation observe high-dimensional images, but successful plans depend on action-relevant facts: what can be done now and what changes afterward. A useful planning representation should discard irrelevant visual details while preserving action applicability and effects. Classical task planners exploit this structure through symbolic operators with preconditions and effects, but obtaining such representations from raw visual experience remains challenging. We study a visual task-planning setting in which a robot receives only image transitions: the current image, executed high-level action, and the resulting image. At test time, given a start image and a goal image, the robot must produce a sequence of high-level actions that reaches the goal. To address this problem, we introduce STRIPS-WM, a framework for learning image-grounded STRIPS-style world models directly from visual transitions. STRIPS-WM first induces a finite abstract transition graph from images, then learns latent binary predicates and one grounded propositional operator per action label. The learned operators form a symbolic action model with sparse preconditions and add/delete effects. Finally, the learned predicates are distilled into a visual encoder, enabling classical planning directly from novel start and goal images. Experiments on visual rearrangement tasks show that STRIPS-WM improves image-to-plan success over the tested visual rollout, latent graph-search and latent-symbolic baselines.

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