·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
America needs to stop getting shocked by Chinese AI1h◆Advancing next-gen AI with materials science innovation1h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else2h◆Capacity and Redundancy Trade-offs in Multi-Task Learning8h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation8h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making8h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection8h◆Supervised Reward Inference8h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization8h◆Is Progressive Disclosure All You Need for Long-Context Agents?8h◆Auto Research for Materials: Auditable AI-Scientist Workflows with Held-Out Transfer8h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability8h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification8h◆Retrieval is Enough: Training-Free Interpretability with a Tool-Using Agent8h◆RealDESED: A Real-World Domestic Sound Event Detection Benchmark8h◆Kernelized Linear Attention: Breaking the Capacity Wall with Symmetric Cones8h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration8h◆Autonomous Discovery of Wireless Communications Algorithms8h◆OrderMoE: An expert similarity driven distributed edge MoE inference8h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection8h◆America needs to stop getting shocked by Chinese AI1h◆Advancing next-gen AI with materials science innovation1h◆Gritt exits stealth with $34 million for robots to build solar plants—then, everything else2h◆Capacity and Redundancy Trade-offs in Multi-Task Learning8h◆Predictive Training with Latent Imagination for Visual Quadruped Navigation8h◆Where Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making8h◆Did We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection8h◆Supervised Reward Inference8h◆PPO-HSC: An Exploratory Reinforcement Learning Framework Based on Wide-Area Policy Coverage Optimization8h◆Is Progressive Disclosure All You Need for Long-Context Agents?8h◆Auto Research for Materials: Auditable AI-Scientist Workflows with Held-Out Transfer8h◆It Depends on the Dataset: When a Brain-Encoding Model's Predicted Responses Beat Their Visual Backbone for Video Memorability8h◆DMFNet: Dual-Backbone Multiscale Fusion Network for Urban Scene Classification8h◆Retrieval is Enough: Training-Free Interpretability with a Tool-Using Agent8h◆RealDESED: A Real-World Domestic Sound Event Detection Benchmark8h◆Kernelized Linear Attention: Breaking the Capacity Wall with Symmetric Cones8h◆Oracle Gap and Signal Fidelity: A Fixed-Pool Diagnostic for Test-Time Collaboration8h◆Autonomous Discovery of Wireless Communications Algorithms8h◆OrderMoE: An expert similarity driven distributed edge MoE inference8h◆Time-Frequency Consistency Learning for Robust Speech Deepfake Detection8h◆
News/SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-body Manipulation
arxiv
PublishedJuly 21, 2026 at 4:00 AM
—neutral

SoMA: A Real-to-Sim Neural Simulator for Robotic Soft-body Manipulation

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2602.02402v2 Announce Type: replace-cross Abstract: Simulating deformable objects under rich interactions remains a fundamental challenge for real-to-sim robot manipulation, with dynamics jointly driven by environmental effects and robot actions. Existing simulators rely on predefined physics

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivCapacity and Redundancy Trade-offs in Multi-Task Learning8harxivPredictive Training with Latent Imagination for Visual Quadruped Navigation8harxivWhere Not to Learn: Prior-Aligned Training with Subset-based Attribution Constraints for Reliable Decision-Making8harxivDid We Actually Fix It? An Independent Adversarial Stress-Test of Post-Point-Adjustment Evaluation Metrics for Time-Series Anomaly Detection8h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews