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Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization
Paper • 2608.26103 • Published • 24 -
Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Paper • 2608.27550 • Published • 81 -
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning
Paper • 2608.27549 • Published • 48 -
Agentic Game Development as a Verifiable Trajectory Data Engine for Scaling World Models
Paper • 2608.25518 • Published • 58
Collections
Discover the best community collections!
Collections including paper arxiv:2608.27549
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IRASim: Learning Interactive Real-Robot Action Simulators
Paper • 2406.14540 • Published • 6 -
WildActor: Unconstrained Identity-Preserving Video Generation
Paper • 2603.00586 • Published • 38 -
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Paper • 2605.18287 • Published • 14 -
PhysiFormer: Learning to Simulate Mechanics in World Space
Paper • 2606.27364 • Published • 12
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WorldVLA: Towards Autoregressive Action World Model
Paper • 2506.21539 • Published • 40 -
LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation
Paper • 2509.05263 • Published • 11 -
VLA-RFT: Vision-Language-Action Reinforcement Fine-tuning with Verified Rewards in World Simulators
Paper • 2510.00406 • Published • 68 -
GigaBrain-0: A World Model-Powered Vision-Language-Action Model
Paper • 2510.19430 • Published • 55
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Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 39 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 36 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 26
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Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video
Paper • 2605.15182 • Published • 40 -
STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
Paper • 2605.06527 • Published • 47 -
Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis
Paper • 2605.14392 • Published • 9 -
World Action Models: The Next Frontier in Embodied AI
Paper • 2605.12090 • Published • 73
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MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds
Paper • 2508.14879 • Published • 70 -
VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space
Paper • 2508.19247 • Published • 43 -
Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels
Paper • 2508.17437 • Published • 38 -
Multi-View 3D Point Tracking
Paper • 2508.21060 • Published • 23
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The Debugging Decay Index: Rethinking Debugging Strategies for Code LLMs
Paper • 2506.18403 • Published • 3 -
ReCode: Updating Code API Knowledge with Reinforcement Learning
Paper • 2506.20495 • Published • 10 -
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Paper • 2507.23348 • Published • 12 -
LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering
Paper • 2509.09614 • Published • 7
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Zero-WAM: In-Context World-Action Modeling from Human Videos for Open-Ended Task Generalization
Paper • 2608.26103 • Published • 24 -
Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
Paper • 2608.27550 • Published • 81 -
Code as Worlds: Agentic Discovery of Executable World Representations for Physical Reasoning
Paper • 2608.27549 • Published • 48 -
Agentic Game Development as a Verifiable Trajectory Data Engine for Scaling World Models
Paper • 2608.25518 • Published • 58
-
Warp-as-History: Generalizable Camera-Controlled Video Generation from One Training Video
Paper • 2605.15182 • Published • 40 -
STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
Paper • 2605.06527 • Published • 47 -
Learning to Build the Environment: Self-Evolving Reasoning RL via Verifiable Environment Synthesis
Paper • 2605.14392 • Published • 9 -
World Action Models: The Next Frontier in Embodied AI
Paper • 2605.12090 • Published • 73
-
IRASim: Learning Interactive Real-Robot Action Simulators
Paper • 2406.14540 • Published • 6 -
WildActor: Unconstrained Identity-Preserving Video Generation
Paper • 2603.00586 • Published • 38 -
StableVLA: Towards Robust Vision-Language-Action Models without Extra Data
Paper • 2605.18287 • Published • 14 -
PhysiFormer: Learning to Simulate Mechanics in World Space
Paper • 2606.27364 • Published • 12
-
MeshCoder: LLM-Powered Structured Mesh Code Generation from Point Clouds
Paper • 2508.14879 • Published • 70 -
VoxHammer: Training-Free Precise and Coherent 3D Editing in Native 3D Space
Paper • 2508.19247 • Published • 43 -
Pixie: Fast and Generalizable Supervised Learning of 3D Physics from Pixels
Paper • 2508.17437 • Published • 38 -
Multi-View 3D Point Tracking
Paper • 2508.21060 • Published • 23
-
WorldVLA: Towards Autoregressive Action World Model
Paper • 2506.21539 • Published • 40 -
LatticeWorld: A Multimodal Large Language Model-Empowered Framework for Interactive Complex World Generation
Paper • 2509.05263 • Published • 11 -
VLA-RFT: Vision-Language-Action Reinforcement Fine-tuning with Verified Rewards in World Simulators
Paper • 2510.00406 • Published • 68 -
GigaBrain-0: A World Model-Powered Vision-Language-Action Model
Paper • 2510.19430 • Published • 55
-
The Debugging Decay Index: Rethinking Debugging Strategies for Code LLMs
Paper • 2506.18403 • Published • 3 -
ReCode: Updating Code API Knowledge with Reinforcement Learning
Paper • 2506.20495 • Published • 10 -
SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution
Paper • 2507.23348 • Published • 12 -
LoCoBench: A Benchmark for Long-Context Large Language Models in Complex Software Engineering
Paper • 2509.09614 • Published • 7
-
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 39 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 36 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 26