Scholar
Alisa Liu
Google Scholar ID: 3-lTFAwAAAAJ
University of Washington
natural language processing
artificial intelligence
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Homepage
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Google Scholar
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Citations & Impact
All-time
Citations
5,067
H-index
14
i10-index
15
Publications
20
Co-authors
5
list available
Contact
Email
alisaliu@cs.washington.edu
Twitter
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GitHub
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Publications
11 items
Are Language Models Sensitive to Morally Irrelevant Distractors?
2026
Cited
0
Are you going to finish that? A Practical Study of the Partial Token Problem
2026
Cited
1
NVIDIA Nemotron 3: Efficient and Open Intelligence
2025
Cited
0
Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
2025
Cited
0
Broken Tokens? Your Language Model can Secretly Handle Non-Canonical Tokenizations
2025
Cited
0
Sampling from Your Language Model One Byte at a Time
2025
Cited
0
LLAMAPIE: Proactive In-Ear Conversation Assistants
2025
Cited
0
SuperBPE: Space Travel for Language Models
2025
Cited
0
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Resume (English only)
Academic Achievements
Published 'Broken Tokens? Your Language Model can Secretly Handle Non-Canonical Tokenizations' at NeurIPS 2025 (Spotlight)
Published 'SuperBPE: Space Travel for Language Models' at COLM 2025
Published 'Tuning Language Models by Proxy' at COLM 2024 (Spotlight, top 7%)
Published 'We're Afraid Language Models Aren't Modeling Ambiguity' at EMNLP 2023
Co-authored 'Self-Instruct: Aligning Language Models with Self-Generated Instructions' at ACL 2023
Co-authored 'Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts' at ACL 2023
First-authored 'WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation' at EMNLP Findings 2022
Multiple publications at top venues including NAACL 2025, ICML 2024, TMLR 2023, ACL Findings 2025, and NeurIPS 2024
Background
Final-year PhD student in Computer Science at the University of Washington
Research focuses on natural language processing, particularly tokenization, decoding-time algorithms, and data creation
Advised by Yejin Choi and Noah Smith
Supported by the NSF Graduate Research Fellowship and OpenAI SuperAlignment Fellowship
On the job market for 2026
Co-authors
5 total
Noah A. Smith
University of Washington; Allen Institute for Artificial Intelligence
Yejin Choi
Stanford University / NVIDIA
Nathan Lambert
Research Scientist, Allen AI
Jonathan Hayase
University of Washington
sewoong oh
Professor, University of Washington
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