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xid32/README.md

Hi there 👋

I'm Xingjian Diao, a Ph.D. student in Computer Science at Dartmouth College 🌲, co-advised by Prof. Soroush Vosoughi and Prof. Jiang Gui.

Previously, I completed my M.S. in Computer Science at Northwestern University 💜, advised by Prof. Nabil Alshurafa. I received my B.S. in Computer Science from the University of Pittsburgh 💙, graduating with Cum Laude honors.


🔍 Research

My research focuses on multimodal learning for video, audio, and language understanding. I have developed methods for multimodal reasoning, efficient multimodal learning, and generative multimodal modeling, aiming to build scalable and generalizable multimodal models that advance multimodal question answering, video understanding, and audio–visual reasoning across complex real-world scenarios and dynamic environments. Highlights of my work include:


🧑‍💻 Internship Experience

  • Amazon Science (Jun 2025 – Sept 2025)
    Applied Scientist Intern, Santa Cruz, CA
    Research on multimodal learning.

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  1. SoundMind SoundMind Public

    We introduce the Audio Logical Reasoning (ALR) dataset, consisting of 6,446 text-audio annotated samples specifically designed for complex reasoning tasks. Building on this resource, we propose Sou…

    Python 1.1k 131

  2. NAACL_2025_TWM NAACL_2025_TWM Public

    We introduce temporal working memory (TWM), which aims to enhance the temporal modeling capabilities of Multimodal foundation models (MFMs). This plug-and-play module can be easily integrated into …

    Python 312 30