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Bin Xiao

Member of Technical Staff, Microsoft Superintelligence team, Microsoft

  • Member of Technical Staff, Microsoft Superintelligence team, Microsoft1

Bin Xiao is a Member of Technical Staff on the Microsoft Superintelligence team, working on multimodal foundation models, computer vision and agentic AI. Xiao is the first author of "Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks", presented as an oral paper at CVPR 2024, and Xiao's site says Xiao led the Florence-1 and Florence-2 vision foundation models from 2020 to 2023. Xiao also led the Phi-3 Vision and Phi-3.5 Vision models and co-authored the HRNet and CvT papers.12

At a glance

Current role
Member of Technical Staff, Microsoft Superintelligence team
Company
Microsoft
Sector
Company
Work listed
3
Honors
1
Sources cited
2
Profile reviewed

Research

Xiao's early work covered visual representation learning and human pose estimation, including "Simple Baselines for Human Pose Estimation and Tracking" (ECCV 2018) as first author, the HRNet paper (CVPR 2019) and CvT, which added convolutions to vision transformers (ICCV 2021). Xiao's site lists first place in the single-person pose estimation track of the 2019 Look into Person challenge.1

From 2020 to 2023 Xiao led the Florence-1 and Florence-2 vision foundation models; the Florence-2 paper, posted in November 2023 with Lu Yuan as senior author, unifies captioning, detection, grounding and segmentation behind text prompts. In 2024 Xiao led Phi-3 Vision and Phi-3.5 Vision.12

Recent work

Xiao's site describes work on multimodal Llama post-training for visual understanding in 2024 and 2025, and since 2025 on post-training for reasoning, coding and agentic models, including Microsoft AI's MAI-Thinking-1 and MAI-Code-1-Flash releases in 2026.1

Work and contributions

  • Microsoft Florence-2 Open weights

    First author of the Florence-2 paper, which presents a prompt-based sequence-to-sequence vision model for captioning, object detection, grounding and segmentation.21

  • Florence-2-large Open weights

    Led the Florence-2 vision foundation model work from which the Florence-2-large checkpoint was released.12

  • Phi-3 Vision and Phi-3.5 Vision Open weights

    Led Microsoft's Phi-3 Vision and Phi-3.5 Vision compact multimodal language models in 2024.1

Timeline

  1. Published "Simple Baselines for Human Pose Estimation and Tracking" at ECCV 2018 as first author.1
  2. Co-authored the HRNet paper on high-resolution representation learning at CVPR 2019.1
  3. Began leading the Florence vision foundation model work.1
  4. Posted the Florence-2 paper as first author.2
  5. Led the Phi-3 Vision and Phi-3.5 Vision multimodal models; Florence-2 presented as a CVPR 2024 oral.1
  6. Contributed to Microsoft AI's MAI-Thinking-1 and MAI-Code-1-Flash releases.1

Honors and recognition

  • First place, Look into Person Challenge (single-person pose estimation) · Look into Person (LIP) Challenge, 20191

Where they work

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References

2 sources · profile reviewed Oct 22, 2026 · data updated Oct 22, 2026

  1. Bin Xiao — Research & PublicationsBin Xiao · Official page · accessed Oct 22, 2026
  2. Florence-2: Advancing a Unified Representation for a Variety of Vision Tasks (arXiv 2311.06242)arXiv · Paper · published Nov 10, 2023 · accessed Oct 22, 2026