Huteng Dai
Assistant Professor
Studies how humans and language models learn language from noisy data, including phonology, formal language theory and interpretability.
Huteng Dai's lab at Michigan works on large language models, interpretability, evaluation & safety of LMs and trustworthy & safe ML. 3 papers since 2023, 1 at top venues, mostly EMNLP. 2 PhD students and 1 master's student. 2 alumni. Applications close .
At a glance
- papers, 2023–2026
- 1/ year
- at T1 venues
- 33%
- PhD students
- 2
- MS students
- 1
- alumni listed
- 2
Papers by yearfrom the lab homepage, 2023–2026
- 0 papers2026 · T1 0 · collecting
- 2 papers2025 · T1 1
- 0 papers2024 · T1 0
- 1 papers2023 · T1 0
T1 venuesOtherVenues: EMNLP
Research focuspaper titles that use each topic's words
- Large language models0 papers
- Interpretability, evaluation & safety of LMs0 papers
- Trustworthy & safe ML0 papers
- noisy0 papers
- language0 papers
Paper list
From the lab homepage.
20252 papers
20231 paper
- Proceedings of the Society for Computation in LinguisticsRethinking Representations: A Log-bilinear Model of Phonotactics (opens in a new tab)
Where alumni went2 listed
Apply to MichiganFall 2027
Michigan CSE Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
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- Fee
- See program page
Not yet confirmed for this intake.
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Data
Checked against the lab homepage.
- Collected
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- Papers
- The lab homepage
- Members
- Lab homepage
- Alumni
- Lab homepage
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