Mengyu Ye

Ph.D. student @ Tohoku University Fundamental AI lab.

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ye.mengyu.s1 [at] dc.tohoku.ac.jp

I am a final-year Ph.D. student in NLP and machine learning at Tohoku University, advised by Prof. Jun Suzuki, and a Google PhD Fellow. My research centers on the evaluation of large language models: how reliably we can measure their capabilities, how they generate and reason, and where they fail. This autumn I will join Prof. Mrinmaya Sachan’s group at ETH Zürich as a visiting researcher.

I pursue this across model families, from autoregressive to diffusion language models, as well as agentic systems, with publications at NeurIPS, ACL, and EMNLP. Most recently, I led Sumi, a fully open 7B uniform diffusion language model pretrained from scratch on 1.5T tokens.

news

Jun 23, 2026 We release Sumi, a fully open 7B uniform diffusion language model pretrained from scratch on 1.5T tokens, with weights, checkpoints, and the full training recipe — paper now on arXiv.
Jun 22, 2026 I will join Prof. Mrinmaya Sachan’s group at ETH Zürich as a visiting researcher from autumn 2026 to March 2027.
Jan 30, 2026 We release a new paper on relaxing positional alignment in masked diffusion LMs, identifying a key failure mode in open-ended generation, now on arXiv.
Dec 08, 2025 Our team won the Best Static Evaluation Prize in the MMU-RAG NeurIPS 2025 Competition.
Dec 01, 2025 Released a CLI tool that uses an LLM agent to automatically clean, format, and update BibTeX references.

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