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Xiang Yue

(Pronounced as "Shiang Yoo-eh", 岳翔)

Postdoctoral Researcher
Language Technologies Institute
School of Computer Science
Carnegie Mellon University

Email: xyue2@andrew.cmu.edu

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Bio

I am a postdoctoral researcher at CMU working with Prof. Graham Neubig on natural language processing (NLP) and large language models (LLMs). I obtained my Ph.D. from The Ohio State University (OSU-NLP-Group), where I was trained by Prof. Huan Sun and Prof. Yu Su. I also collaborate closely with Prof. Wenhu Chen at University of Waterloo. I received my B.S. in Computer Science from Wuhan University in 2018.


🔥I am on the academic job market this year! Please feel free to reach out if you'd like to discuss opportunities. ✈️ I am attending NeurIPS 2024!

My research aims to understand and enhance the reasoning capabilities of LLMs across different modalities and contexts while improving their responsibility and reliability.
  • Understanding LLMs' reasoning through rigorous evaluation and benchmarking.
  • Improving LLMs' reasoning capabilities with synthetic data generation techniques. I love simple, scalable and cost-effective data solutions and enjoy pushing the boundary of state-of-the-arts while open-sourcing everything I build.
    • Representative Work: MAmmoTH and MAmmoTH2: Strong reasoning models achieving SoTA in 2023 and 2024 by scaling up reasoning rationales from different sources. Notable, MAmmoTH2's 10 million synthetic instructions achieve performance comparable to Meta Llama 3 Instruct, which relies on 10 million human-annotated examples.
    • Other Major Contributed Projects: Pangea (SoTA open-source multilingual multimodal model on both English and Multilingual evaluations), OpenCodeInterpreter (ACL 2024 Findings; 90+ accuracy on HumanEval with 7B size), MAmmoTH-VL (SoTA open-source multimodal model), MultiUI (7M multimodal GUI understanding and agent data samples)
  • Designing responsible and inclusive AI models cover different aspects (e.g., Privacy, Attribution, Multilinguality) for real-world applications (e.g., Healthcare).

What's New

Last Updated: 12/2024