ICLR 2025 Past Robotics
7th Robot Learning Workshop: Towards Robots with Human-Level Abilities
WRL@ICLR 2025
- Submission deadline
- Feb 13, 2025, 11:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (49)
Fetched from OpenReview (v2) on 2026-06-10.
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A New Perspective on Transformers in Online Reinforcement Learning for Continuous Control
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Accelerating Goal-Conditioned RL Algorithms and Research
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Accelerating Transformers in Online RL
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Achieving Human Level Competitive Robot Table Tennis
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AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons
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ANYDEXGRASP: LEARNING GENERAL DEXTEROUS GRASPING FOR ANY HANDS WITH HUMAN-LEVEL LEARNING EFFICIENCY
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AutoEval: Autonomous Evaluation of Generalist Robot Manipulation Policies in the Real World
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Bridging the Sim-to-Real Gap for Athletic Loco-Manipulation
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Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback
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ControlManip: Few-Shot Manipulation Fine-tuning via Object-centric Conditional Control
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DemoGen: Synthetic Demonstration Generation for Data-Efficient Visuomotor Policy Learning
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Diffusion-Based Maximum Entropy Reinforcement Learning
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Efficient Diffusion Transformer Policies with Mixture of Expert Denoisers for Multitask Learning
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Efficient Robotic Policy Learning via Latent Space Backward Planning
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Environment as Policy: Generative Curriculum Learning for Autonomous Racing
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FLOWER: Democratizing Generalist Robot Policies with Efficient Vision-Language-Action Flow Policies
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From Tabula Rasa to Emergent Abilities: Discovering Robot Skills via Reset-Free Unsupervised Quality-Diversity
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Improving Efficiency of Sampling-based Motion Planning via Message-Passing Monte Carlo
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Instant Policy: In-Context Imitation Learning via Graph Diffusion
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KineSoft: Learning Proprioceptive Manipulation Policies with Soft Robot Hands
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Learning a Thousand Tasks in a Day
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Learning Composable Diffusion Guidance for Motion Priors
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Learning Long-Context Robot Policies via Past-Token Prediction
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Learning the RoPEs: Better 2D and 3D Position Encodings with STRING
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ManiSkill3: GPU Parallelized Robot Simulation and Rendering for Generalizable Embodied AI
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Memory, Benchmark & Robots: A Benchmark for Solving Complex Tasks with Reinforcement Learning
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Navigation with QPHIL: Quantizing Planner for Hierarchical Implicit Q-Learning
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Object-Centric Latent Action Learning
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Optimism via Intrinsic Rewards: Scalable and Principled Exploration for Model-based Reinforcement Learning
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PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation
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PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
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Policy-Agnostic RL: Offline RL and Online RL Fine-Tuning of Any Class and Backbone
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PP-Tac: Paper Picking Using Omnidirectional Tactile Feedback in Dexterous Robotic Hands
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RecFlow Policy: Fast and Accurate Visuomotor Policy Learning via Rectified Action Flow
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RILe: Reinforced Imitation Learning
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RL Zero: Zero-Shot Language to Behaviors without any Supervision
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RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics
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SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation
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Self-supervised Visual State Representation Learning for robotics from Dynamic Scenes
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Small features matter: Robust representation for world models
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Stress-Testing Offline Reward-Free Reinforcement Learning: A Case for Planning with Latent Dynamics Models
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Student-Informed Teacher Training
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Teaching Visual Language Models to Navigate using Maps
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TOP-ERL: Transformer-based Off-Policy Episodic Reinforcement Learning
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Towards Fusing Point Cloud and Visual Representations for Imitation Learning
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Universal Actions for Enhanced Embodied Foundation Models
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Value-Based Deep RL Scales Predictably
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World Models as Reference Trajectories for Rapid Motor Adaptation
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X-IL: Exploring the Design Space of Imitation Learning Policies