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Y. Wang

4 papers hereh-index 7518 citations11 works total

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

author position
  • middle author4

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

fields
  • cs.RO3
  • cs.CV1
same name
  • Y. Wang — 253 papers, h 61
  • Y. Wang — 104 papers, h 60
  • Y. Wang — 86 papers
  • Y. Wang — 81 papers
  • Y. Wang — 75 papers
  • Y. Wang — 63 papers

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 citedAHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation

4 citations · 4 across the 3 of their papers we have counts for

collaborators

4 papers

cs.RO2025

MolmoAct: Action Reasoning Models that can Reason in Space

Jason Lee, Jiafei Duan, Haoquan Fang +16

Reasoning is central to purposeful action, yet most robotic foundation models map perception and instructions directly to control, which limits adaptability, generalization, and se…

cs.CV2025

PointArena: Probing Multimodal Grounding Through Language-Guided Pointing

Long Cheng, Jiafei Duan, Yi Ru Wang +12

Pointing serves as a fundamental and intuitive mechanism for grounding language within visual contexts, with applications spanning robotics, assistive technologies, and interactive…

cs.RO2025

SAM2Act: Integrating Visual Foundation Model with A Memory Architecture for Robotic Manipulation

Haoquan Fang, Markus Grotz, Wilbert Pumacay +4

Robotic manipulation systems operating in diverse, dynamic environments must exhibit three critical abilities: multitask interaction, generalization to unseen scenarios, and spatia…

cs.RO2024★ 4 cited

AHA: A Vision-Language-Model for Detecting and Reasoning Over Failures in Robotic Manipulation

Jiafei Duan, Wilbert Pumacay, Nishanth Kumar +7

Robotic manipulation in open-world settings requires not only task execution but also the ability to detect and learn from failures. While recent advances in vision-language models…

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