Publications 📗

@inproceedings{Rzepka_MINSC26,

title = { Beyond Description: Comparing AI and Human Interpretation of Visual Art in Social Communication Contexts},

author = {Rafal Rzepka and Jin Hosono and Jun Nakamura},

year  = {2026},

date = {2026-08-10},

booktitle = {Proceedings of the 13th Multidisciplinary International Social Networks Conference (MISNC 2026), August 10-12, 2026, Danang, Vietnam},

keywords = {},

pubstate = {forthcoming},

tppubtype = {inproceedings}

}

@inproceedings{rzepka2026dataset,

title = {A Dataset and Benchmark for Resolving Legal Cross-References in Japanese Export Control Regulations},

author = {Rafal Rzepka and Shinji Muraji and Akihiko Obayashi},

year  = {2026},

date = {2026-06-01},

urldate = {2026-06-01},

booktitle = {Proceedings of the Twentieth International Workshop on Juris-informatics (JURISIN 2026) associated with JSAI International Symposia on AI 2026 (IsAI-2026)},

address = {Gunma, Japan},

keywords = {},

pubstate = {forthcoming},

tppubtype = {inproceedings}

}

@inproceedings{MurajiLaCATODA26,

title = {Evaluation of Emotion-Conditioned Response Generation for Role-Playing Agents Using Large Language Models: A Case Study with Facial Expression Labels from Visual Novel Data},

author = {Shinji Muraji and Rafal Rzepka and Toshihiko Itoh},

url = {https://ceur-ws.org/Vol-4178/},

year  = {2026},

date = {2026-01-27},

urldate = {2026-01-27},

booktitle = {CEUR Proceedings of the 10th Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA 2026), AAAI 2026 Workshop, Singapore, 2026},

pages = {144--159},

publisher = {WS-CEUR},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{RzepkaLaCATODA2026,

title = {Evaluating Lightweight Embedding Guardrails for Cost-Effective Misalignment Mitigation in Export Control Dialog Systems},

author = {Rafal Rzepka and Shinji Muraji and Akihiko Obayashi},

url = {https://ceur-ws.org/Vol-4178/},

year  = {2026},

date = {2026-01-27},

urldate = {2026-01-27},

booktitle = {CEUR Proceedings of the 10th Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA 2026), AAAI 2026 Workshop, Singapore, 2026.},

pages = {132--143},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{JETHICS2026,

title = {JETHICS: Japanese Ethics Understanding Evaluation Dataset},

author = {Masashi Takeshita and Rafal Rzepka},

year  = {2026},

date = {2026-01-27},

booktitle = {To appear in the Proceedings of Machine Ethics: from Formal Methods to Emergent Machine Ethics, AAAI 2026 Workshop, Singapore, 2026 },

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{RzepkaLaCATODA2026b,

title = {A Novel Neuro-symbolic Approach to Irony Detection Based on Structural Components of Ironic Statements},

author = {Hiroshi Shigenobu and Michal Ptaszynski and Shunsuke Dan and Fumito Masui and Yuzu Uchida and Rafal Rzepka},

url = {https://ceur-ws.org/Vol-4178/},

year  = {2026},

date = {2026-01-27},

urldate = {2026-01-27},

booktitle = {CEUR Proceedings of the 10th Linguistic and Cognitive Approaches to Dialog Agents (LaCATODA 2026), AAAI 2026 Workshop, Singapore, 2026.},

pages = {172-183},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{10.1145/3765766.3765822,

title = {Predicting Cooperative Overlap Timing to Enhance Human-likeness in Spoken Dialogue},

author = {Ryusei Hachiya and Toshihiko Itoh},

url = {https://doi.org/10.1145/3765766.3765822},

doi = {10.1145/3765766.3765822},

isbn = {9798400721786},

year  = {2026},

date = {2026-01-01},

booktitle = {Proceedings of the 13th International Conference on Human-Agent Interaction},

pages = {389–391},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {HAI '25},

abstract = {Cooperative overlap is a conversational behavior that expresses engagement and supports smooth communication, yet it is rarely addressed in dialogue systems. In this study, we extracted instances of cooperative overlap from a Japanese casual conversation corpus and explored the feasibility of predicting their timing using a lightweight classifier. The model showed learning tendencies that indicate potential for distinguishing cooperative overlaps from other utterances. Our findings suggest that this behavior can be implemented in dialogue agents. This work opens up new possibilities for designing systems that interact more naturally and responsively with users.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ShintoAACL2025,

title = {To What Extent Can In-Context Learning Solve Unseen Tasks?},

author = {Ryoma Shinto and Masashi Takeshita and Rafal Rzepka and Toshihiko Itoh},

url = {https://aclanthology.org/2025.ijcnlp-srw.23/},

year  = {2025},

date = {2025-12-20},

urldate = {2025-12-20},

booktitle = {IJCNLP-AACL Student Research Workshop, Mumbai, 2025 (Best Paper Award🏆) },

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ShintoDemo2025,

title = {Live Demonstration: Fingerspelling Recognition in Quantized Neural Networks with Emulated Memristors for 2D/3D Camera Applications},

author = {Yoshinari Wada and Rei Kusunose and Ryoma Shinto and Ayane Matsuzaki and Seiji Adachi and Kota Ando and Tetsuya Asai and Takao Marukame},

year  = {2025},

date = {2025-10-16},

booktitle = {Proceedings of 2025 IEEE Biomedical Circuits and Systems Conference, Abu Dhabi, UAE},

keywords = {},

pubstate = {forthcoming},

tppubtype = {inproceedings}

}

@inproceedings{nokey,

title = {Rethinking Continual Learning with Pre-Trained Models: Knowledge-Preserving Approach},

author = {Makoto Misaizu and Koshi Watanabe and Keisuke Maeda and Takahiro Ogawa and Rafal Rzepka and Toshihiko Itoh and Miki Haseyama},

year  = {2025},

date = {2025-09-23},

urldate = {2025-09-23},

booktitle = {Proceedings of 2025 IEEE 14th Global Conference on Consumer Electronics (GCCE)},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{ICAAI2024,

title = {Effectiveness of Security Export Control Ontology for Predicting Answer Type and Regulation Categories},

author = {Rafal Rzepka and Akihiko Obayashi},

url = {https://doi.org/10.1145/3704137.3704180},

doi = {10.1145/3704137.3704180},

isbn = {9798400718014},

year  = {2025},

date = {2025-01-01},

urldate = {2025-01-01},

booktitle = {Proceedings of the 2024 8th International Conference on Advances in Artificial Intelligence},

pages = {156–161},

publisher = {Association for Computing Machinery},

address = {New York, NY, USA},

series = {ICAAI '24},

abstract = {In this paper we present results of our experiments investigating if an expert knowledge graph can improve Large Language Models accuracy in predicting correct answer labels and regulations related to the topic of security export control. As the lack of related data prevents machine-learning or fine-tuning approaches, we implement prompt expansion by searching most relevant nodes of the graph and adding the expanded context to the prompt. Results of our experiments show that the addition improved answer type selection but clearly hamper the capability of finding a correct regulation category.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Muraji_LACATODA2024,

title = {Evaluation of active generation of interlocutor profiling sentences from utterances and their implicit context},

author = {Shinji Muraji and Rafal Rzepka and Toshihiko Itoh},

editor = {Rafal Rzepka and Michal Ptaszynski and Pawel Dybala and Siaw-Fong Chung and Jordi Vallverdu},

year  = {2024},

date = {2024-11-19},

urldate = {2024-11-19},

booktitle = {Proceedings of the 9th Linguistic and Cognitive Approaches To Dialog Agents Workshop - LaCATODA 2024 co-located with the Pacific Rim International Conference on Artificial Intelligence (PRICAI 2024)},

pages = {45-55},

publisher = {WS-CEUR},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}

@inproceedings{Ji2024pricai,

title = {Fame Bias -- Large Language Models Change Their Judgement Depending on Personal Name},

author = {Huizhong Ji and Rafal Rzepka},

editor = {Rafik Hadfi, Patricia Anthony, Alok Sharma, Takayuki Ito, Quan Bai},

doi = {https://doi.org/10.1007/978-981-96-0122-6},

year  = {2024},

date = {2024-11-18},

urldate = {2024-11-18},

booktitle = {PRICAI 2024: Trends in Artificial Intelligence, Lecture Notes LNAI 15283, 21st Pacific Rim International Conference on Artificial Intelligence, PRICAI 2024, Kyoto, Japan, November 18–24, 2024, Proceedings, Part III},

pages = {15--20},

series = {Lecture Notes in Computer Science},

abstract = {This paper focuses on bias caused by changing personal names in the input of proprietary LLMs, fine-tuned language models, and lexicon-based sentiment analysis tool. It extracts examples from NLI and story cloze task datasets with personal names, replaces them with names of celebrities, ordinary people or mixtures. Results show that altered names significantly influence model assessments, especially with more than two choices, indicating potential real-world application hazards. A mitigation method for “fame bias” is proposed but the problem requires further research.},

keywords = {},

pubstate = {published},

tppubtype = {inproceedings}

}