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Hao Liu

6 papers hereh-index 324 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author5

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.RO4
  • cs.CV2
same name
  • Hao Liu — 14 papers, h 8
  • Hao Liu — 14 papers, h 5
  • Hao Liu — 11 papers, h 8
  • Hao Liu — 11 papers, h 10
  • Hao Liu — 9 papers, h 4
  • Hao Liu — 8 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.ROShow all

4 papers · 1 filter

cs.RO2026

Neural Implicit Action Fields: From Discrete Waypoints to Continuous Functions for Vision-Language-Action Models

Haoyun Liu, Jianzhuang Zhao, Xinyuan Chang +11

Despite the rapid progress of vision-language-action (VLA) models, the prevailing practice of predicting action chunks as discrete waypoints remains structurally misaligned with th…

cs.RO2026

Stable Language Guidance for Vision-Language-Action Models

Zhihao Zhan, Yuhao Chen, Jiaying Zhou +5

Vision-Language-Action (VLA) models have demonstrated impressive capabilities in generalized robotic control; however, they remain notoriously brittle to linguistic perturbations.…

cs.RO2026

E0: Enhancing Generalization and Fine-Grained Control in VLA Models via Tweedie Discrete Diffusion

Zhihao Zhan, Jiaying Zhou, Likui Zhang +10

Vision-Language-Action (VLA) models offer a unified framework for robotic manipulation by integrating visual perception, language understanding, and control generation. However, ex…

cs.RO2026

RADAR: Benchmarking Vision-Language-Action Generalization via Real-World Dynamics, Spatial-Physical Intelligence, and Autonomous Evaluation

Yuhao Chen, Zhihao Zhan, Xiaoxin Lin +11

VLA models have achieved remarkable progress in embodied intelligence; however, their evaluation remains largely confined to simulations or highly constrained real-world settings.…

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