Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation | Paper Citation Record

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Unresolved cited work

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Wasserstein Generative Adversarial Networks

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Efficient Online Reinforcement Learning with Offline Data

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Blending MPC & Value Function Approximation for Efficient Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Unresolved cited work

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Unresolved cited work

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This paper cites Diffusion policy: Visuomotor policy learning via action diffusion.The International Journal of Robotics Research, 44(10-11):1684–1704, September 2025.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Diffusion policy: Visuomotor policy learning via action diffusion.The International Journal of Robotics Research, 44(10-11):1684–1704, September 2025

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation From Play to Policy: Conditional Behavior Generation from Uncurated Robot Data

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This paper cites Model-Based Inverse Reinforcement Learning from Visual Demonstra- tions.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Model-Based Inverse Reinforcement Learning from Visual Demonstra- tions

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This paper cites Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Learning Robust Rewards with Adverserial Inverse Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation IQ-Learn: Inverse soft-Q Learning for Imitation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Improved Training of Wasserstein GANs

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This paper cites Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor

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This paper cites Mastering diverse control tasks through world models.Nature, 640(8059):647–653, April 2025.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Mastering diverse control tasks through world models.Nature, 640(8059):647–653, April 2025

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Model Predictive Adversarial Imitation Learn- ing for Planning from Observation, July 2025

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This paper cites TD- MPC2: Scalable, Robust World Models for Continuous 10 Control.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation TD- MPC2: Scalable, Robust World Models for Continuous 10 Control

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This paper cites Learn- ing Massively Multitask World Models for Continuous Control, December 2025.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Learn- ing Massively Multitask World Models for Continuous Control, December 2025

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This paper cites Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation.

Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Generative Adversarial Imitation Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Discriminator-Actor-Critic: Addressing Sample Ineffi- ciency and Reward Bias in Adversarial Imitation Learn- ing

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation MoDem-V2: Visuo-Motor World Models for Real-World Robot Manipulation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Unifying Model Predictive Path Integral Control, Reinforcement Learning, and Diffusion Models for Optimal Control and Planning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Understanding and Preventing Capacity Loss in Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Learning to Adapt in Dynamic, Real-World Environments Through Meta-Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Cosmos World Foundation Model Platform for Physical AI

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation What Matters for Adversarial Imitation Learning? InAdvances in Neural Information Processing Systems, volume 34, pages 14656– 14668

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Much Ado About Noising: Dispelling the Myths of Generative Robotic Control, December 2025

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation PyTorch: An Imperative Style, High-Performance Deep Learning Library

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation AMP: adversarial motion priors for stylized physics-based character control.ACM Trans- actions on Graphics, 40(4):1–20, August 2021

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Visual Adversarial Imitation Learning using Variational Models

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Random Features for Large-Scale Kernel Machines

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation URL https://proceedings.mlr

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Proximal Policy Optimization Algorithms

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Latent Plans for Task-Agnostic Offline Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Reinforcement Learning: An Introduction

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Sample-efficient Adversarial Imitation Learning from Observation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Gymnasium: A Standard Interface for Reinforcement Learning Environments

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Generative Adversarial Imitation from Observation

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Rehg, and Evangelos A

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation XIRL: Cross-embodiment Inverse Reinforcement Learning

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation MimicPlay: Long-Horizon Imitation Learning by Watching Human Play

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation somersaulting

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation Influence

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation URL https://ieeexplore.ieee.org/document/10611477/

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Online World Modeling Enables Real-World Inverse Reinforcement Learning from Observation URL https://proceedings

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