Hi, welcome to my Resume page. Please see my English Resume or my Chinese Resume for the printout version.
Experiences
Research Projects
- LLM-informed Syntax Parsing University of Tokyo 2023--2025
- Developed LLM-informed methods for unsupervised constituency and dependency parsing, combining paraphrase-based resampling, reinforcement-learning, and grammatical priors.
- Designed a paraphrase-based resampling method to mitigate spurious textual patterns in unsupervised constituency parsing; improved accuracy by 8 absolute points across four languages.
- Estimated word--word mutual information with grammatical constraints for LLM-based dependency parsing; improved parsing accuracy by over 5%.
- Published related work at ICLR 2025 Spotlight, ACL 2024, and NAACL 2024.
- Syntax-informed Semantic Dependency Parsing with Mixture-of-Experts University of Tokyo 2021--2022
- Developed a mixture-of-experts approach to condition semantic dependency labels on automatically discovered syntactic patterns.
- Improved semantic dependency parsing accuracy by $\sim$1 absolute F1 point over state-of-the-art methods.
- Published as ACL 2022 Oral work.
Last publications
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ICLR Spotlight
Is language modeling sufficient for accurate unsupervised parsing? No, sentence-level semantic information greatly contribute to robust and accurate parsing.
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AAAI Oral
Proper prosody modeling helps with speech intelligibility.
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Findings of ACL
Does neural similarity capture substring-level semantic similarity? Not necessarily, substring-frequency among paraphrases might be a better choice.
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NAACL
A better LM-based mutual information estimate helps with dependency parsing, though the MI estimate often ignore import syntactic information.
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Journal of Natural Language Processing
This comment investigates the correlation between syntactic and semantic dependencies in semantic role labeling.
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Modeling Syntactic-Semantic Dependency Correlations in Semantic Role Labeling Using Mixture Models
May 2022ACL Oral
How will syntax better help semantic parsing? Just separately model the semantic dependency per syntactic pattern and cluster the pattern using variational inference.
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An Improved StarGAN for Emotional Voice Conversion: Enhancing Voice Quality and Data Augmentation
Sep 2021Interspeech
Presents an improved StarGAN architecture for emotional voice conversion. Two stage training helps with StarGAN generation quality.
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NLP-COVID Workshop @ EMNLP
This paper describes a large-scale system for aggregating worldwide information about the COVID-19 pandemic.
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Frontiers in Artificial Intelligence
This journal article details a pattern-based approach for named entity recognition in Chinese medical imaging reports.
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A Bibliometric Analysis of the Research Status of the Technology Enhanced Language Learning
Sep 2018SETE@ICWL
This paper presents a bibliometric analysis of the research landscape in Technology Enhanced Language Learning (TELL).
Skills
ML/LLM
LLM Application, Multimodal Translation, Automated Evaluation, Unsupervised Learning, Syntax/Semantics Parsing, Audio Biosignals
Programming
Python, TypeScript, Bash
Frameworks
PyTorch, Lightning, vLLM, Hydra, TensorFlow, Hugging Face Accelerate
Infrastructure
AWS, Slurm, Megatron, Docker, Cloudflare
Languages
Chinese (Native), Japanese (N1, Business), English (C1, Business Level)
Education
Grants and Awards
- 2023
DC2 Fellowship
Japan Society for the Promotion of Science
- 2024
Special Allowance for Outstanding Student
Japan Society for the Promotion of Science
- 2025
Travel Grant ($2000)
Association for the Advancement of Artificial Intelligence
- 2022
IST-RA Fellowship
The University of Tokyo