Author

Wenhao Ding

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#artificial intelligence Preprint Oct 2026

Grounding What Shapes the Plan: Rethinking Groundedness for Physical Intelligence in Autonomous Driving

Driving models increasingly ground reasoning in causal relations, spatial structure, perceptual evidence, and predicted futures. These advances make reasoning more faithful to the driving scene, but leave a fundamental question unresolved: what should groundedness mean when the model ultimately outputs an action? Corre...

Minkyoung Cho, Ze-Wei Zhou, Wen-Hao Ding et al. · 0 citations

Preprint Oct 2026

CtrlWAM: Controllable World Action Models with Aligned Intent and Foresight

World action models (WAMs) jointly predict actions (intent) and visual future (foresight). Standard training adds noise to recorded actions and video simultaneously, but such training paradigms introduce a mismatch: perturbed actions imply counterfactual future visual, while the noised video remains tied to the GT reco...

Chensheng Peng, Wen-Hao Ding, Ran Tian et al. · 1 citation

#artificial intelligence Jun 2026

Planning-aligned Token Compression for Long-Context Autonomous Driving

This work proposes COMPACT-VA, a planning-aligned working memory framework built on conditional VQ-VAE, compressing extended context into bounded representations, and evaluates on high-signal dynamic scenarios where historical context is most critical for behavior correctness, and accordingly design behavioral metrics.

Zhixuan Liang, Yuxiao Chen, Yurong You et al. · arXiv.org · 1 citation