SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training | Paper Citation Record

Observation 8d43ba3e-0161-4a4a-9cf7-ffb9ce0813ec · outbound

This paper cites Decomposing the generalization gap in imitation learning for visual robotic manipulation,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Decomposing the generalization gap in imitation learning for visual robotic manipulation,

Reference 1

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Observation 8286c790-cab7-41b5-b7db-205f226ad2bb · outbound

This paper cites Bc-z: Zero-shot task generalization with robotic imitation learning,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Bc-z: Zero-shot task generalization with robotic imitation learning,

Reference 2

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Observation 674a39c4-bdf9-4003-802f-b423a61885ea · outbound

This paper cites Robo-abc: Affordance generalization beyond categories via semantic correspon- dence for robot manipulation,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Robo-abc: Affordance generalization beyond categories via semantic correspon- dence for robot manipulation,

Reference 3

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Observation a6e07395-7b73-4db0-8961-cf06c0845c90 · outbound

This paper cites THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation

Reference 4

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Observation ae2dce9d-b68f-4db2-a8c2-06da501a52d5 · outbound

This paper cites Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations

Reference 5

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Observation b526a5b8-3a6d-4263-a6ae-157a90d5d7c6 · outbound

This paper cites Towards human-level bimanual dexterous manipulation with reinforcement learning,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Towards human-level bimanual dexterous manipulation with reinforcement learning,

Reference 6

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Observation ea34ad8a-82f9-4817-924c-d40a57ff42e7 · outbound

This paper cites ALOHA Unleashed: A Simple Recipe for Robot Dexterity.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training ALOHA Unleashed: A Simple Recipe for Robot Dexterity

Reference 7

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Observation 2bb24c50-41b7-42f0-8bf0-020c4301c021 · outbound

This paper cites Reinforcement learning on variable impedance con- troller for high-precision robotic assembly,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Reinforcement learning on variable impedance con- troller for high-precision robotic assembly,

Reference 8

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Observation c31bab30-118e-4053-bfa5-6ce9bce6b9a2 · outbound

This paper cites Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Precise and Dexterous Robotic Manipulation via Human-in-the-Loop Reinforcement Learning

Reference 9

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Observation 9e3790b2-9ba3-4b4f-b199-b332c6ae941e · outbound

This paper cites SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning

Reference 10

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Observation 128838ac-81bb-4e6d-a411-457e345dfcaa · outbound

This paper cites Manipulate-Anything: Automating Real-World Robots using Vision-Language Models.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Manipulate-Anything: Automating Real-World Robots using Vision-Language Models

Reference 11

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Observation 0858f152-5abc-4e48-aaaa-e10c254f3969 · outbound

This paper cites RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulation

Reference 12

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Observation 8abf3237-7c10-44a6-beb4-9c25ded7f41c · outbound

This paper cites GenSim: Generating Robotic Simulation Tasks via Large Language Models.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training GenSim: Generating Robotic Simulation Tasks via Large Language Models

Reference 13

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Observation 3a115cd5-3891-4225-bbf4-c27c95ed7077 · outbound

This paper cites GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training GenSim2: Scaling Robot Data Generation with Multi-modal and Reasoning LLMs

Reference 14

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Observation c9c5f199-c835-44ee-98bf-c5841683568f · outbound

This paper cites MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training MimicGen: A Data Generation System for Scalable Robot Learning using Human Demonstrations

Reference 15

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Observation 8ff44fa6-60e8-479f-abb3-d3f059b48f00 · outbound

This paper cites DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training DexMimicGen: Automated Data Generation for Bimanual Dexterous Manipulation via Imitation Learning

Reference 16

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Observation ceec7d54-e601-442a-ae45-993ba96b57c7 · outbound

This paper cites Skillgen: Auto- mated demonstration generation for efficient skill learning and deploy- ment,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Skillgen: Auto- mated demonstration generation for efficient skill learning and deploy- ment,

Reference 17

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Observation 9cdb3501-91de-4fd6-90d7-c3074bd74d3c · outbound

This paper cites SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training SkillMimicGen: Automated Demonstration Generation for Efficient Skill Learning and Deployment

Reference 18

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Observation 6bb79347-5f8f-4007-a9d5-d159dc61a357 · outbound

This paper cites RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots

Reference 19

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Observation 9c166087-47a0-4197-aab4-70beedbeed2e · outbound

This paper cites Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Reconciling Reality through Simulation: A Real-to-Sim-to-Real Approach for Robust Manipulation

Reference 20

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Observation 8dff70b7-1e98-4b6e-8e90-63f72d1d6cba · outbound

This paper cites SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splatting.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training SplatSim: Zero-Shot Sim2Real Transfer of RGB Manipulation Policies Using Gaussian Splatting

Reference 21

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Observation bf945e3d-5183-47b4-9c42-33be5b01ecc2 · outbound

This paper cites Robo-GS: A Physics Consistent Spatial-Temporal Model for Robotic Arm with Hybrid Representation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Robo-GS: A Physics Consistent Spatial-Temporal Model for Robotic Arm with Hybrid Representation

Reference 22

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Observation 351d99b1-c142-448a-b81b-d91deba851a5 · outbound

This paper cites Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Re$^3$Sim: Generating High-Fidelity Simulation Data via 3D-Photorealistic Real-to-Sim for Robotic Manipulation

Reference 23

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Observation f01e55e5-7bb1-43e6-bf80-2634c230df3b · outbound

This paper cites RL-GSBridge: 3D Gaussian Splatting Based Real2Sim2Real Method for Robotic Manipulation Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training RL-GSBridge: 3D Gaussian Splatting Based Real2Sim2Real Method for Robotic Manipulation Learning

Reference 24

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Observation c3bd9742-0f67-46a1-9bb5-8663222f2895 · outbound

This paper cites A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training A Real-to-Sim-to-Real Approach to Robotic Manipulation with VLM-Generated Iterative Keypoint Rewards

Reference 25

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Observation 0bcdfc61-747c-4fae-8319-5a4e99809199 · outbound

This paper cites What went wrong? closing the sim-to-real gap via differentiable causal discovery,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training What went wrong? closing the sim-to-real gap via differentiable causal discovery,

Reference 26

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Observation fcee1a07-2c6a-43df-a363-8ace2fa99fbd · outbound

This paper cites Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Bridging the Sim-to-Real Gap from the Information Bottleneck Perspective

Reference 27

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Observation 4158a578-a9ce-40a9-9745-4241f36e7eee · outbound

This paper cites Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Isaac Gym: High Performance GPU-Based Physics Simulation For Robot Learning

Reference 28

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Observation ebd24134-678c-4399-bac2-3eba945dc750 · outbound

This paper cites Towards building ai-cps with nvidia isaac sim: An industrial benchmark and case study for robotics manipulation,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Towards building ai-cps with nvidia isaac sim: An industrial benchmark and case study for robotics manipulation,

Reference 29

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Observation 0e5d95f8-c6c6-4f32-9034-9d550f6f1e88 · outbound

This paper cites MuJoCo Playground.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training MuJoCo Playground

Reference 30

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Observation f53a35b4-2377-4b1f-95e9-43b7c0f7c9be · outbound

This paper cites Imitation Bootstrapped Reinforcement Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Imitation Bootstrapped Reinforcement Learning

Reference 31

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Observation 33688414-594b-4b67-9094-426eb411a854 · outbound

This paper cites Efficient online reinforcement learning with offline data,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Efficient online reinforcement learning with offline data,

Reference 32

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Observation 689c3033-cf16-4782-a3a7-eb31f2b0ae21 · outbound

This paper cites Improving Vision-Language-Action Model with Online Reinforcement Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Improving Vision-Language-Action Model with Online Reinforcement Learning

Reference 33

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Observation cea5a52e-2246-4966-8aa4-4ad35c0c9cde · outbound

This paper cites ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training ConRFT: A Reinforced Fine-tuning Method for VLA Models via Consistency Policy

Reference 34

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Observation 1199fad7-cb07-4c6f-8cdf-51107cddef73 · outbound

This paper cites REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation

Reference 35

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Observation e4657a64-a231-49ce-90fd-cbcc2870ed53 · outbound

This paper cites Reset-free reinforcement learning via multi-task learning: Learning dexterous manipulation behaviors without human intervention,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Reset-free reinforcement learning via multi-task learning: Learning dexterous manipulation behaviors without human intervention,

Reference 36

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Observation 699de270-e8a1-4266-a494-4db47cd923e0 · outbound

This paper cites Dexterous manipulation from images: Autonomous real- world rl via substep guidance,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Dexterous manipulation from images: Autonomous real- world rl via substep guidance,

Reference 37

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Observation 33ee60cd-a81e-48d3-8c09-ebdd61e8a0d1 · outbound

This paper cites The Ingredients of Real-World Robotic Reinforcement Learning.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training The Ingredients of Real-World Robotic Reinforcement Learning

Reference 38

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Observation 27b35f85-bce8-479a-a856-7eff8c3cd827 · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 39

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Observation 46020fc4-2bfe-4ee9-9aef-a716cf2c4399 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Robot fine-tuning made easy: Pre-training rewards and policies for autonomous real-world reinforcement learning,

Reference 40

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Observation ba3f8c42-beed-4bc0-8510-eae4208a51e4 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data

Reference 41

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Observation 9b0284e4-89fd-4702-8213-869ba3207570 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Reinforcement Learning with Foundation Priors: Let the Embodied Agent Efficiently Learn on Its Own

Reference 42

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Observation c8bcfd32-6511-4a9f-ba0f-67ebe3691da3 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Rapidly Adapting Policies to the Real World via Simulation-Guided Fine-Tuning

Reference 43

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Observation 4c314e9b-5349-43c5-a60e-705c2099d1e1 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL

Reference 44

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Observation 724ec207-d5bb-497f-9719-741d7e106bd1 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Cherry-picking with reinforcement learning

Reference 45

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Observation 9e3fced4-fb4a-4595-b606-2a95f87830fc · outbound

This paper cites Sim-to-real transfer in deep reinforcement learning for robotics: a survey,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Sim-to-real transfer in deep reinforcement learning for robotics: a survey,

Reference 46

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Observation 30204e0e-74b0-4c53-b43a-46eed3f9a095 · outbound

This paper cites In-hand object rotation via rapid motor adaptation,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training In-hand object rotation via rapid motor adaptation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:07.729507Z

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Observation 2f8129f5-a538-4150-bf0f-cd3d3de4da59 · outbound

This paper cites Lessons from Learning to Spin "Pens".

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Lessons from Learning to Spin "Pens"

Reference 48

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Observation 34830cca-fc80-47c9-a996-2085f0998c5b · outbound

This paper cites DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training DextrAH-RGB: Visuomotor Policies to Grasp Anything with Dexterous Hands

Reference 49

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Observation b4a0c2bd-be1d-44fc-a4b0-ee3c8103d2c5 · outbound

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SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Automated Creation of Digital Cousins for Robust Policy Learning

Reference 50

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Observation b6f5767f-c4a0-4c4b-9f34-8a6c70951b2c · outbound

This paper cites RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version).

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training RoboTwin: Dual-Arm Robot Benchmark with Generative Digital Twins (early version)

Reference 51

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Observation 90a92602-bde2-4fd0-a787-e454b79872ff · outbound

This paper cites Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Video2Policy: Scaling up Manipulation Tasks in Simulation through Internet Videos

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:06.404152Z

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This paper cites Mujoco: A physics engine for model-based control,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Mujoco: A physics engine for model-based control,

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:06.409417Z

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Observation 658d592a-fddc-43e1-ba7c-fd71296ba7f3 · outbound

This paper cites Partmanip: Learning cross-category generalizable part manipulation policy from point cloud observations,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Partmanip: Learning cross-category generalizable part manipulation policy from point cloud observations,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:07.664945Z

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Observation 4453d2f8-b5c3-4030-ba4a-4d6d1a01c782 · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training SAM 2: Segment Anything in Images and Videos

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:06.418776Z

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This paper cites Open x-embodiment: Robotic learning datasets and rt-x models,.

SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training Open x-embodiment: Robotic learning datasets and rt-x models,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:07.634506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

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