Papers by Takehito Utsuro
Presentation Slide Translation and Layout Error Correction by LLMs (2026.acl-srw)
Copied to clipboard
| Challenge: | Existing translation tools suffer from layout errors due to text expansion during translation . a new approach to translating Japanese slides into English is proposed to overcome this issue . |
| Approach: | They propose a framework to translate Japanese slides into English and correct layout errors by using multimodal LLMs with slide images and XML structures. |
| Outcome: | The proposed method outperforms baselines and achieves 4.1% layout error rate and over 80% success rate. |
Mixed Multi-Head Self-Attention for Neural Machine Translation (D19-56)
Copied to clipboard
| Challenge: | Recent advances in neural machine translation have been made in the field of multi-head self-attention and there is no explicit mechanism to ensure that different attention heads capture different features. |
| Approach: | They propose a novel multi-head self-attention model which models not only global and local attention but also forward and backward attention in different attention heads. |
| Outcome: | The proposed model improves on WAT17 English-Japanese and IWSLT14 German-English translation tasks without increasing the number of parameters. |
Coding Open-Ended Responses using Pseudo Response Generation by Large Language Models (2024.naacl-srw)
Copied to clipboard
| Challenge: | Existing pipelines for survey research using open-ended responses require time and cost-consuming manual tasks. |
| Approach: | They propose an LLM-based method to automate parts of the grounded theory approach . they generate and annotate pseudo open-ended responses and use them as training data . |
| Outcome: | The proposed method is highly efficient andcost-saving compared to human-based methods. |
Document Alignment based on Overlapping Fixed-Length Segments (2024.acl-srw)
Copied to clipboard
| Challenge: | Existing studies show that web crawling can be used to obtain large-scale parallel corpora for NLP tasks. |
| Approach: | They propose a sentence-based segmentation method for document alignment . they compare it with a fixed-length segmentation technique to handle long-text encoding better. |
| Outcome: | The proposed method improves document alignment and recall by 1% to 10% on a document alignment task for Japanese-English and French-English datasets. |
Attention over Heads: A Multi-Hop Attention for Neural Machine Translation (P19-2)
Copied to clipboard
| Challenge: | Existing multihop attentions for machine comprehension are recurrent and hierarchical . a proposed multi-hop attention for the Transformer refines the attention for an output symbol many times . |
| Approach: | They propose a multi-hop attention for the Transformer which integrates attentions from each head. |
| Outcome: | The proposed model outperforms the baseline Transformer in terms of translation accuracy and speed. |
BiMax: Bidirectional MaxSim Score for Document-Level Alignment (2025.findings-emnlp)
Copied to clipboard
| Challenge: | Document alignment is necessary for the hierarchical mining of documents across source and target languages. |
| Approach: | They propose a cross-lingual Bidirectional Maxsim score for computing doc-to-doc similarity. |
| Outcome: | The proposed method achieves accuracy comparable to OT with an approximate 100-fold speed increase. |
Better Generalizing to Unseen Concepts: An Evaluation Framework and An LLM-Based Auto-Labeled Pipeline for Biomedical Concept Recognition (2026.eacl-long)
Copied to clipboard
Shanshan Liu, Noriki Nishida, Fei Cheng, Narumi Tokunaga, Rumana Ferdous Munne, Yuki Yamagata, Kouji Kozaki, Takehito Utsuro, Yuji Matsumoto
| Challenge: | Existing methods for recognizing ontology concepts are limited by the number of annotations available. |
| Approach: | They propose an evaluation framework built on hierarchical concept indices and novel metrics to measure generalization. |
| Outcome: | The proposed evaluation framework is built on hierarchical concept indices and novel metrics to measure generalization. |
Integrating Disfluency-based and Prosodic Features with Acoustics in Automatic Fluency Evaluation of Spontaneous Speech (2020.lrec-1)
Copied to clipboard
| Challenge: | acoustics, prosody, and disfluency-based features are used to evaluate fluent/disfluent speech . filling pauses and word fragments are used for automatic fluency evaluation . |
| Approach: | They integrate acoustics, prosody, and disfluency-based features into an automatic fluency evaluation task. |
| Outcome: | The proposed model improves when integrated with prosodic features, but not when disfluent speech is detected. |
MRC Examples Answerable by BERT without a Question Are Less Effective in MRC Model Training (2020.aacl-srw)
Copied to clipboard
| Challenge: | Existing models for Machine Reading Comprehension (MRC) are unable to predict answers from a question and its related context. |
| Approach: | They propose a method that splits the training examples into those that are “easy to answer” or “hard to answer”. |
| Outcome: | The proposed model outperforms the previous models on a large-scale English MRC dataset. |