ForkCast: Predictive Recovery for Vision-Language-Action Policies via Counterfactual Futures
cs.RO
Submitted: 2026-10-13
Updated: 2026-10-13
Comments: 9 pages, 5 figures, 3 tables
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Sources
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- Xiaomi-Robotics-0: An Open-Sourced Vision-Language-Action Model with Real-Time Execution
- Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- SaPaVe: Towards Active Perception and Manipulation in Vision-Language-Action Models for Robotics
- Can We Detect Failures Without Failure Data? Uncertainty-Aware Runtime Failure Detection for Imitation Learning Policies
- Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents
- PATCH: Action-Chunk-Conditioned Latent Patch Innovation Monitoring for Robot Manipulation
- Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress
- V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
- DINO-WM: World Models on Pre-trained Visual Features enable Zero-shot Planning
- DREAMSTEER: Latent World Models Can Steer VLA Policies During Deployment Without Any Finetuning
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- AnyCamVLA: Zero-Shot Camera Adaptation for Viewpoint Robust Vision-Language-Action Models
- LIBERO-Occ: Evaluating and Improving Vision-Language-Action Models under Scene-Induced Occlusion via Viewpoint Imagination
- Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance
- RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models
- Look Before You Leap: Distilling Tree Search into Action Evaluation for Frozen VLA Models
- From Foresight to Forethought: VLM-In-the-Loop Policy Steering via Latent Alignment
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- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies