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researcher

Jianye Hao

4 papers hereh-index 9416 citations11 works total

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

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • cs.RO3
  • cs.CL1
same name
  • Jianye Hao — 20 papers, h 9
  • Jianye Hao — 16 papers, h 13
  • Jianye Hao — 11 papers, h 14
  • Jianye Hao — 9 papers, h 5
  • Jianye Hao — 7 papers, h 3
  • Jianye Hao — 6 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

most citedA Survey on Vision-Language-Action Models for Embodied AI

20 citations · 20 across the 1 of their papers we have counts for

collaborators

4 papers

cs.RO2026★ 20 cited

A Survey on Vision-Language-Action Models for Embodied AI

Yueen Ma, Zixing Song, Yuzheng Zhuang +2

Embodied AI is widely recognized as a cornerstone of artificial general intelligence (AGI) because it involves controlling embodied agents to perform tasks in the physical world. B…

cs.RO2026

Astra: Efficient Transformer Architecture and Contrastive Dynamics Learning for Embodied Instruction Following

Yueen Ma, Dafeng Chi, Shiguang Wu +3

Vision-language-action models have gained significant attention for their ability to model multimodal sequences in embodied instruction following tasks. However, most existing mode…

cs.RO2025

ET-Plan-Bench: Embodied Task-level Planning Benchmark Towards Spatial-Temporal Cognition with Foundation Models

Lingfeng Zhang, Yuening Wang, Hongjian Gu +12

Recent advancements in Large Language Models (LLMs) have spurred numerous attempts to apply these technologies to embodied tasks, particularly focusing on high-level task planning…

cs.CL2025

3D-MoE: A Mixture-of-Experts Multi-modal LLM for 3D Vision and Pose Diffusion via Rectified Flow

Yueen Ma, Yuzheng Zhuang, Jianye Hao +1

3D vision and spatial reasoning have long been recognized as preferable for accurately perceiving our three-dimensional world, especially when compared with traditional visual reas…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.