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Robot Manipulation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
DreamVLA: A Vision-Language-Action Model Dreamed with Comprehensive World Knowledge
Geometry-aware 4D Video Generation for Robot Manipulation
Compliant Residual DAgger: Improving Real-World Contact-Rich Manipulation with Human Corrections
CapsDT: Diffusion-Transformer for Capsule Robot Manipulation
CodeDiffuser: Attention-Enhanced Diffusion Policy via VLM-Generated Code for Instruction Ambiguity
Robust Instant Policy: Leveraging Student's t-Regression Model for Robust In-context Imitation Learning of Robot Manipulation
SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning
A Survey on Imitation Learning for Contact-Rich Tasks in Robotics
What Matters in Learning from Large-Scale Datasets for Robot Manipulation
Touch begins where vision ends: Generalizable policies for contact-rich manipulation
Demonstrating Multi-Suction Item Picking at Scale via Multi-Modal Learning of Pick Success
BridgeVLA: Input-Output Alignment for Efficient 3D Manipulation Learning with Vision-Language Models
3DFlowAction: Learning Cross-Embodiment Manipulation from 3D Flow World Model
OG-VLA: 3D-Aware Vision Language Action Model via Orthographic Image Generation
Bi-Manual Joint Camera Calibration and Scene Representation
ForceVLA: Enhancing VLA Models with a Force-aware MoE for Contact-rich Manipulation
PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation
WorldEval: World Model as Real-World Robot Policies Evaluator
Is Single-View Mesh Reconstruction Ready for Robotics?
SEM: Enhancing Spatial Understanding for Robust Robot Manipulation
Object-Focus Actor for Data-efficient Robot Generalization Dexterous Manipulation
Robo2VLM: Visual Question Answering from Large-Scale In-the-Wild Robot Manipulation Datasets
RLVR-World: Training World Models with Reinforcement Learning
Vid2World: Crafting Video Diffusion Models to Interactive World Models
Incentivizing Multimodal Reasoning in Large Models for Direct Robot Manipulation
Exploiting Radiance Fields for Grasp Generation on Novel Synthetic Views
Object-Centric Representations Improve Policy Generalization in Robot Manipulation
Zero-Shot Visual Generalization in Robot Manipulation
FlowDreamer: A RGB-D World Model with Flow-based Motion Representations for Robot Manipulation
EmbodiedMAE: A Unified 3D Multi-Modal Representation for Robot Manipulation
NVSPolicy: Adaptive Novel-View Synthesis for Generalizable Language-Conditioned Policy Learning
IN-RIL: Interleaved Reinforcement and Imitation Learning for Policy Fine-Tuning
LODGE: Joint Hierarchical Task Planning and Learning of Domain Models with Grounded Execution
Mini Diffuser: Fast Multi-task Diffusion Policy Training Using Two-level Mini-batches
ManipBench: Benchmarking Vision-Language Models for Low-Level Robot Manipulation
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