Author

Ye-Hao Lu

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Preprint Sep 2026

RefineDrive: Reliable Failure-Guided Learning for Vision-Language-Action Driving

Vision-Language-Action (VLA) models for autonomous driving rely heavily on successful expert demonstrations, leaving model-specific failures underexploited. Learning from these failures is hindered by unreliable diagnoses, poorly matched correction targets, and coarse rewards. We propose RefineDrive, a failure-guided p...

Zhe Sun, Zi-Yin Luo, Ye-Hao Lu et al. · 0 citations

Preprint Sep 2026

OmniCalib: Target-Free, Task-Structured Self-Calibration for Humanoid Robots

Assembly, wear, and component replacement perturb the sensor extrinsics and joint zeros encoded by a humanoid CAD model. Existing procedures calibrate one sensor pair or require external fiducials. Using only robot-native motion and onboard sensing, we present OmniCalib, a target-free workflow that calibrates the full...

Kai-Xiang Lu, Hai-Yu Lan, Chun-Xia Qiao et al. · 0 citations

Preprint Aug 2026

Multi-View Unified Camera Fields: Geometry-Shaped Action-Facing Representations for RGB-Only Multi-Camera VLA Policies

Multi-View Unified Camera Fields (MVUCF), a training-only framework that forms a shared action-facing latent field across views, and real-world humanoid experiments further provide evidence of its practical effectiveness under RGB-only deployment.

Jia-Rui Yang, Ye-Hao Lu, Yu-Ning Su et al. · 1 citation

#artificial intelligence Preprint Sep 2026

ExceptionDrive: A Planning-Oriented Counterfactual Corner-Case Benchmark for Autonomous Driving

Average performance on routine driving benchmarks does not establish planner reliability under rare, safety-critical hazards. We proposed ExceptionDrive, a counterfactual planning benchmark that uses VLM-assisted screening, localized multi-view editing, and quality auditing to insert hazards into real nuScenes scenes w...

Zi-Yin Luo, Zhe Sun, Ye-Hao Lu et al. · 0 citations

#artificial intelligence Preprint Apr 2026

UniRect-CoT: Enhancing Generation in Unified Multimodal Models via Reflective Rectification with Inherent Understanding

Unified Rectification-CoT is proposed, a training-free unified rectification chain-of-thought framework that generalizes across existing flow-based UMMs, consistently enhancing overall text-to-image generation performance.

Yi-Bo Jiang, Tao Wu, Rui Jiang et al. · 0 citations

Preprint Aug 2026

V-Link: Recovering Lost Visual Representations in Action DiT for Vision-Language-Action Models

V-Link is proposed, which explicitly recovers visual representations during the vision-language (VL) to action (A) feature transfer and injects them into Action DiT through asymmetric pathways.

Ye-Hao Lu, Jia-Rui Yang, Yu-Ning Su et al. · 0 citations

Preprint Aug 2026

TemporalFlow-VLA: Learning Physically Grounded Execution History for Long-Horizon Robot Manipulation

TemporalFlow-VLA provides a compact, physically grounded interface for exploiting ordered execution history without explicit motion estimation or geometric processing at deployment, and shows its clearest advantage over prior methods on longer-horizon, multi-stage manipulation.

Jia-Rui Yang, Ye-Hao Lu, Yu-Ning Su et al. · 2 citations