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