Author

Xu Wang

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Preprint Oct 2026

VLA-$\Delta$: Learning Physical State Transition for Vision-Language-Action Models

Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performance across various benchmarks. However, most VLAs directly map observations to demonstrated actions without explicit supervision of intermediate physical state changes,...

Qian-Yu Lu, Jia-Run Li, Ce Zhang et al. · 0 citations

Preprint Aug 2026

HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting

HUGIN, a training framework with two complementary components for Joint Multi-Scene Understanding, supports the practical viability of VLM-based planning for autonomous logistics sorting and provides a high-quality industrial sorting dataset and benchmark.

Xikai Sun, Cangtian Zhou, Kebin Liu et al. · 0 citations

#artificial intelligence Preprint Sep 2026

One MLLM, One Call: Efficient Zero-Shot Vision-and-Language Navigation via Spatial-Aware Waypoints

O2C-Nav is proposed, an efficient zero-shot navigation framework that calls only a single large model once per decision step and introduces a training-free structured waypoint generator and a novel abstract representation that projects sparse, history-aware candidate waypoints directly onto RGB images as visual markers...

Shi-Qi Pan, Qi Zheng, Hanmeng Sun et al. · 1 citation

Jul 2026

Show, Don't Tell: Evaluating Spatial Cognition in Generative Pixels Rather Than LLM Text

ProVisE (Protocolized Visual Evaluation), a benchmark-agnostic framework that elicits protocol-constrained visual answers from image-generation models and parses them into structured predictions compatible with original metrics, is proposed and revealed, revealing complementary strengths of pixel-space expression and t...

Xu Wang, Kaixiang Yao, Miao Pan et al. · arXiv.org · 1 citation