{"total":20,"rows":[{"id":"2606.02800","title":"Cosmos 3: Omnimodal World Models for Physical AI","created":"2026-06-01","cited_by_count":165,"area":"wm"},{"id":"2604.08995","title":"Matrix-Game 3.0: Real-Time and Streaming Interactive World Model with Long-Horizon Memory","created":"2026-04-10","cited_by_count":100,"area":"wm"},{"id":"2605.00078","title":"Being-H0.7: A Latent World-Action Model from Egocentric Videos","created":"2026-04-30","cited_by_count":75,"area":"wm"},{"id":"2604.05015","title":"Video-MME-v2: Towards the Next Stage in Benchmarks for Comprehensive Video Understanding","created":"2026-04-06","cited_by_count":55,"area":"wm"},{"id":"2605.06388","title":"Reconstruction or Semantics? What Makes a Latent Space Useful for Robotic World Models","created":"2026-05-07","cited_by_count":22,"area":"wm"},{"id":"2511.20937","title":"ENACT: Evaluating Embodied Cognition with World Modeling of Egocentric Interaction","created":"2025-11-26","cited_by_count":15,"area":"wm"},{"id":"2604.18486","title":"Xiaomi OneVL: One-Step Latent Reasoning and Planning with Vision-Language Explanation","created":"2026-04-20","cited_by_count":10,"area":"wm"},{"id":"2606.16533","title":"Kairos: A Regret-Aware Native World-Action Model Stack for Physical AI","created":"2026-06-15","cited_by_count":9,"area":"wm"},{"id":"2605.25343","title":"Toward Native Multimodal Modeling: A Roadmap","created":"2026-05-25","cited_by_count":7,"area":"wm"},{"id":"2602.23058","title":"GeoWorld: Geometric World Models","created":"2026-02-26","cited_by_count":6,"area":"wm"},{"id":"2603.07562","title":"Brain-WM: Brain Glioblastoma World Model","created":"2026-03-08","cited_by_count":5,"area":"wm"},{"id":"2607.13681","title":"Towards Spatial Supersensing in the Wild","created":"2026-07-15","cited_by_count":4,"area":"wm"},{"id":"2604.09535","title":"EgoTL: Egocentric Think-Aloud Chains for Long-Horizon Tasks","created":"2026-04-10","cited_by_count":3,"area":"wm"},{"id":"2511.23476","title":"Thinking by Doing: Building Efficient World Model Reasoning in LLMs via Multi-turn Interaction","created":"2025-11-28","cited_by_count":2,"area":"wm"},{"id":"2603.14941","title":"RS-WorldModel: a Unified Model for Remote Sensing Understanding and Future Sense Forecasting","created":"2026-03-16","cited_by_count":2,"area":"wm"},{"id":"2604.08719","title":"LMGenDrive: Bridging Multimodal Understanding and Generative World Modeling for End-to-End Driving","created":"2026-04-09","cited_by_count":2,"area":"wm"},{"id":"2605.16713","title":"GeoWorld-VLM: Geometry from World Models for Vision-Language Models","created":"2026-05-15","cited_by_count":1,"area":"wm"},{"id":"2606.28385","title":"RoboGaze: Evaluating Robot World Models via Structured Vision-Language Analysis","created":"2026-06-22","cited_by_count":1,"area":"wm"},{"id":"2511.18735","title":"Thinking Ahead: Foresight Intelligence in MLLMs and World Model","created":"2025-11-24","cited_by_count":0,"area":"wm"},{"id":"2609.25961","title":"An Action Is Worth One Patch: Unified World-Action Modeling with PatchWAM","created":"2026-09-22","cited_by_count":0,"area":"wm"}],"next_cursor":null}