{"total":36,"rows":[{"id":"2409.05865","title":"Robot Utility Models: General Policies for Zero-Shot Deployment in New Environments","created":"2024-09-09","cited_by_count":44,"area":null},{"id":"2409.18382","title":"CurricuLLM: Automatic Task Curricula Design for Learning Complex Robot Skills using Large Language Models","created":"2024-09-27","cited_by_count":22,"area":null},{"id":"2410.03035","title":"SPINE: Online Semantic Planning for Missions with Incomplete Natural Language Specifications in Unstructured Environments","created":"2024-10-03","cited_by_count":18,"area":null},{"id":"2411.01775","title":"Eurekaverse: Environment Curriculum Generation via Large Language Models","created":"2024-11-04","cited_by_count":16,"area":null},{"id":"2505.01458","title":"A Survey of Robotic Navigation and Manipulation with Physics Simulators in the Era of Embodied AI","created":"2025-05-01","cited_by_count":16,"area":null},{"id":"2504.19139","title":"Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments","created":"2025-04-27","cited_by_count":12,"area":null},{"id":"2501.13075","title":"Evolution and The Knightian Blindspot of Machine Learning","created":"2025-01-22","cited_by_count":11,"area":null},{"id":"2505.09108","title":"Air-Ground Collaboration for Language-Specified Missions in Unknown Environments","created":"2025-05-14","cited_by_count":11,"area":null},{"id":"2409.17652","title":"FactorSim: Generative Simulation via Factorized Representation","created":"2024-09-26","cited_by_count":10,"area":null},{"id":"2504.04191","title":"GROVE: A Generalized Reward for Learning Open-Vocabulary Physical Skill","created":"2025-04-05","cited_by_count":9,"area":null},{"id":"2407.08626","title":"RoboMorph: Evolving Robot Morphology using Large Language Models","created":"2024-07-11","cited_by_count":8,"area":null},{"id":"2410.00231","title":"Helpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models","created":"2024-09-30","cited_by_count":8,"area":null},{"id":"2410.15489","title":"Generative AI Agents in Autonomous Machines: A Safety Perspective","created":"2024-10-20","cited_by_count":7,"area":null},{"id":"2502.01702","title":"Al-Khwarizmi: Discovering Physical Laws with Foundation Models","created":"2025-02-03","cited_by_count":5,"area":null},{"id":"2502.08643","title":"A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards","created":"2025-02-12","cited_by_count":5,"area":null},{"id":"2609.29166","title":"HarnessPAI: An Evolving Harness for Physical AI","created":"2026-09-24","cited_by_count":5,"area":null},{"id":"2605.00244","title":"Lucid-XR: An Extended-Reality Data Engine for Robotic Manipulation","created":"2026-04-30","cited_by_count":4,"area":null},{"id":"2409.08904","title":"AnyBipe: An End-to-End Framework for Training and Deploying Bipedal Robots Guided by Large Language Models","created":"2024-09-13","cited_by_count":3,"area":null},{"id":"2605.03408","title":"Discovering Reinforcement Learning Interfaces with Large Language Models","created":"2026-05-05","cited_by_count":2,"area":null},{"id":"2507.12666","title":"Fly, Fail, Fix: Iterative Game Repair with Reinforcement Learning and Large Multimodal Models","created":"2025-07-16","cited_by_count":1,"area":null},{"id":"2508.05535","title":"Mixed-Initiative Dialog for Human-Robot Collaborative Manipulation","created":"2025-08-07","cited_by_count":1,"area":null},{"id":"2509.07445","title":"Text2Touch: Tactile In-Hand Manipulation with LLM-Designed Reward Functions","created":"2025-09-09","cited_by_count":1,"area":null},{"id":"2602.02137","title":"DCoPilot: Generative AI-Empowered Policy Adaptation for Dynamic Data Center Operations","created":"2026-02-02","cited_by_count":1,"area":null},{"id":"2605.30326","title":"RoboWits: Unexpected Challenges for Robotic Creative Problem Solving","created":"2026-05-28","cited_by_count":1,"area":null},{"id":"2608.01851","title":"Weights or Skills? A Survey of Robot-Learning Techniques: from Action-Predicting Weights to Robots that Write their Own Skills","created":"2026-08-03","cited_by_count":1,"area":null},{"id":"2608.31167","title":"SUN: Agentic Robot Policy Learning with Persistent Task Programs","created":"2026-08-31","cited_by_count":1,"area":null},{"id":"2609.36012","title":"In-Context Learning for Robots: Methods and Applications","created":"2026-09-28","cited_by_count":1,"area":null},{"id":"2605.07325","title":"CSR: Infinite-Horizon Real-Time Policies with Massive Cached State Representations","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2605.08315","title":"Reflective Prompted Policy Optimization: Trajectory-Grounded Revision and Salience Bias","created":"2026-05-08","cited_by_count":0,"area":null},{"id":"2607.27630","title":"SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2609.09250","title":"No Free Checker: A Survey of Verifiers for Robot Policies","created":"2026-09-08","cited_by_count":0,"area":null},{"id":"2609.36924","title":"Track-and-Complete: Learning Humanoid Skills from a Single Failed Human Video","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.02196","title":"InterEvolve: Test-Time Evolution of Reward Programs for Humanoid Loco-Manipulation","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.04364","title":"A Bird's-Eye View of Iterative Reward Design","created":"2026-10-03","cited_by_count":0,"area":null},{"id":"2610.17174","title":"Generative Flow on Symbolic Abstractions for Embodiment Capability Discovery","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.18835","title":"RoboSimStudio: An Interactive Toolkit for Human and Agent Rapid Real2Sim of Robot Manipulation Tasks","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}