Papers by Tomohide Shibata

6 papers
Entity-Centric Joint Modeling of Japanese Coreference Resolution and Predicate Argument Structure Analysis (P18-1)

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Challenge: Existing methods for predicate argument structure analysis are difficult and difficult . a Japanese model can detect a zero pronoun and identify a referent of the zero pronominator .
Approach: They propose a model that performs coreference resolution and predicate argument structure analysis simultaneously.
Outcome: The proposed model can improve the performance of the inter-sentential zero anaphora resolution drastically.
A Benchmark Suite of Japanese Natural Questions (2024.starsem-1)

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Challenge: Existing studies to solve QA tasks in an integrated manner are not available in other languages because of the lack of QA datasets.
Approach: They build a Japanese version of Natural Questions using natural questions from query logs of a search engine and crowdsource it using crowdsourcing.
Outcome: The proposed datasets are based on natural questions from Japanese search engines and crowdsourced.
JGLUE: Japanese General Language Understanding Evaluation (2022.lrec-1)

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Challenge: There is no benchmark for Japanese to evaluate and analyze NLU ability from different perspectives.
Approach: They build a Japanese NLU benchmark from scratch without translation to measure general NLU ability in Japanese.
Outcome: a Japanese NLU benchmark is built from scratch without translation to measure general NLU ability in Japanese.
Machine Comprehension Improves Domain-Specific Japanese Predicate-Argument Structure Analysis (D19-58)

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Challenge: a lack of gold datasets and knowledge about PAS analysis makes it difficult to create accurate PAS analyses.
Approach: They construct a Japanese blog-QA dataset and a reading comprehension QA dataset using crowdsourcing.
Outcome: The proposed method is most effective, pre-training model to acquire domain knowledge and fine-tuning model based on PAS-QA dataset.
Diverse and Non-redundant Answer Set Extraction on Community QA based on DPPs (2020.coling-main)

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Challenge: Community-based question answering platforms take time to get useful information from among many answers.
Approach: They propose a method to select a diverse and non-redundant answer set rather than ranking the answers.
Outcome: The proposed method outperforms baseline methods on a Japanese CQA site . it calculates the answer importance and similarity between answers by using BERT .
Building Japanese Creativity Benchmarks and Applying them to Enhance LLM Creativity (2025.acl-srw)

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Challenge: a recent study evaluated the creativity of large language models (LLMs) in Japanese based on a Torrance test of creative thinking . previous research on LLM creativity focused on English, but differences exist in how it manifests and is evaluated across languages and cultures.
Approach: They construct three benchmarks to evaluate LLM creativity in Japanese . they use Japanese Creativity Questions (JCQ), Divergent Association Task (DAT) and Story Alteration Task (SAT)
Outcome: The benchmarks evaluate the creativity of large language models (LLMs) in Japanese . the benchmarks are Japanese Creativity Questions (JCQ), Divergent Association Task (DAT), and Story Alteration Task (SAT).

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