Published multiple papers in areas such as dynamic graph modeling, dialogue attribution, graph clustering, abstractive text summarization, multi-modal machine translation, etc. Some of the papers include:
- DyG-Mamba: Continuous State Space Modeling on Dynamic Graphs
- S2N: A Synthetic Data-Driven Approach for Speaker-to-Dialogue Attribution in Novels
- Revisiting Dynamic Graph Clustering via Matrix Factorization
- Active Learning for Abstractive Text Summarization via LLM-Determined Curriculum and Certainty Gain Maximization
- FINE-LMT: Fine-grained Feature Learning for Multi-Modal Machine Translation
- Community-Invariant Graph Contrastive Learning
- Active Learning with Task Adaptation Pre-training for Speech Emotion Recognition
- Bidirectional Transformer Reranker for Grammatical Error Correction
- Generic Mechanism for Reducing Repetitions in Encoder-Decoder Models
- A Language Model-based Generative Classifier for Sentence-level Discourse Parsing
Research Experience
Extensive research experience in natural language processing, including text understanding and generation, multi-modal machine translation, etc.
Education
Currently a postdoc in the Natural Language Understanding Team at RIKEN Center for Advanced Intelligence Project (AIP), supervised by Prof. Kentaro Inui at Tohoku University.
Background
Research interests: natural language processing, focusing on developing general functions and mechanisms that can be easily used. Professional field: natural language understanding.
Miscellany
Personal homepage provides links to ORCID, Semantic Scholar, and Google Scholar for tracking the latest publications.