RoboTwin 2.0
Emerging36papers using it
2025first seen
'RoboTwin 2.0' is a benchmark dataset used to evaluate robotic manipulation tasks, specifically focusing on spatial-temporal interactions and geometric constraints in action execution.
Papers using RoboTwin 2.0 (36)
- SimpleVLA-RL: Scaling VLA Training via Reinforcement LearningBridge-WA: Predicting Where and How the World Changes for Robotic ActionTraining Vision-Language-Action Models with Dense Embodied Chain-of-Thought SupervisionAgentic-VLA: Efficient Online Adaptation for Vision-Language-Action ModelsELAN4D: Embodiment-Centric 4D Supervision for Vision-Language-Action Models via Plug-and-Play AdaptationFeat2Go: Visual Feature-Grounded Value Estimation for Embodied Reinforcement LearningPACE: Phase-Aware Chunk Execution for Robot Policies with Action ChunkingLight-WAM: Efficient World Action Models with State-Fusion Action DecodingGEAR-VLA: Learning Geometry-Aware Action Representations for Generalizable Robotic ManipulationLatent Diffusion Policy: Shaping Latent Spaces for Diffusion-Based Robotic ManipulationEfficient-WAM: A 1B-Parameter World-Action Model with Low-Cost Future ImaginationSee Selectively, Act Adaptively: Dual-Level Structural Decomposition for Bimanual Robot ManipulationHyper-DP3: Frequency-Aware Right-Sizing of 3D Diffusion Policies for Visuomotor ControlPriorVLA: Prior-Preserving Adaptation for Vision-Language-Action ModelsLearning Action Manifold with Multi-view Latent Priors for Robotic ManipulationRotVLA: Rotational Latent Action for Vision-Language-Action ModelAttenA+: Rectifying Action Inequality in Robotic Foundation ModelsKey-Gram: Extensible World Knowledge for Embodied ManipulationSANTS: A State-Adaptive Scheduler for World Action Models3DVLA: Enhancing Vision-Language-Action Models via 3D Spatial and Instance UnderstandingStarVLA: A Lego-like Codebase for Vision-Language-Action Model DevelopingAIM: Intent-Aware Unified world action Modeling with Spatial Value MapsSTARRY: Spatial-Temporal Action-Centric World Modeling for Robotic ManipulationMotuBrain: An Advanced World Action Model for Robot ControlSeedPolicy: Horizon Scaling via Self-Evolving Diffusion Policy for Robot ManipulationOne-Step Flow Policy: Self-Distillation for Fast Visuomotor PoliciesVLA-Thinker: Boosting Vision-Language-Action Models through Thinking-with-Image ReasoningMemoAct: Atkinson-Shiffrin-Inspired Memory-Augmented Visuomotor Policy for Robotic ManipulationVLA-OPD: Bridging Offline SFT and Online RL for Vision-Language-Action Models via On-Policy DistillationHiFlow: Tokenization-Free Scale-Wise Autoregressive Policy Learning via Flow MatchingJEPA-VLA: Video Predictive Embedding is Needed for VLA ModelsHoloBrain-0 Technical ReportUniversal Pose Pretraining for Generalizable Vision-Language-Action PoliciesInformation Filtering via Variational Regularization for Robot ManipulationPocketDP3: Efficient Pocket-Scale 3D Visuomotor PolicyPEAfowl: Perception-Enhanced Multi-View Vision-Language-Action for Bimanual Manipulation