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Yisong Yue

5 papers hereh-index 8249 citations9 works total

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

author position
  • middle author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.LG1
same name
  • Yisong Yue — 11 papers, h 5
  • Yisong Yue — 9 papers, h 8
  • Yisong Yue — 7 papers, h 7
  • Yisong Yue — 5 papers, h 3
  • Yisong Yue — 5 papers, h 3
  • Yisong Yue — 5 papers, h 4

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

5 papers

cs.CV2026

NitroGen: An Open Foundation Model for Generalist Gaming Agents

Loïc Magne, Anas Awadalla, Guanzhi Wang +11

We introduce NitroGen, a vision-action foundation model for generalist gaming agents that is trained on 40,000 hours of gameplay videos across more than 1,000 games. We incorporate…

cs.CV2025

Feedforward 3D Editing via Text-Steerable Image-to-3D

Ziqi Ma, Hongqiao Chen, Yisong Yue +1

Recent progress in image-to-3D has opened up immense possibilities for design, AR/VR, and robotics. However, to use AI-generated 3D assets in real applications, a critical requirem…

cs.CV2025

Visual Agentic AI for Spatial Reasoning with a Dynamic API

Damiano Marsili, Rohun Agrawal, Yisong Yue +1

Visual reasoning -- the ability to interpret the visual world -- is crucial for embodied agents that operate within three-dimensional scenes. Progress in AI has led to vision and l…

cs.CV2025

Find Any Part in 3D

Ziqi Ma, Yisong Yue, Georgia Gkioxari

Why don't we have foundation models in 3D yet? A key limitation is data scarcity. For 3D object part segmentation, existing datasets are small in size and lack diversity. We show t…

cs.LG2025

TOTEM: TOkenized Time Series EMbeddings for General Time Series Analysis

Sabera Talukder, Yisong Yue, Georgia Gkioxari

This work studies the problem of time series analysis with generalist (or foundation) models, which are models trained across many data domains. Drawing inspiration from the widesp…

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