Publications

2023

Heydar Soudani, Evangelos Kanoulas, Faegheh Hasibi, “Data Augmentation for Conversational AI,” Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023, October 2023, vol. , pp. 5220–5223. DOI: 10.1145/3583780.3615291. URL: https://dl.acm.org/doi/10.1145/3583780.3615291. Open Access: Yes.

Jirui Qi, Raquel Fernández, Arianna Bisazza, “Cross-Lingual Consistency of Factual Knowledge in Multilingual Language Models,” Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, December 2023, vol. long/658, pp. 10650–10666. DOI: 10.18653/v1/2023.emnlp-main.658. URL: https://aclanthology.org/2023.emnlp-main.658/. Open Access: Yes.

Suzan Verberne, “Service-Chatbots voor het Nederlands: De Onderzoeksagenda van het LESSEN Project,” DIXIT magazine, December 2023, vol. , pp. 32-33. DOI: No DOI. URL: https://notas.nl/dixit/dixit_2023_conversational_ai.pdf. Open Access: Yes.

2024

Mert Yazan, Frederik Situmeang, Ruilin Xiao, “Rethinking Conversation Styles of Chatbots from the Customer Perspective: Relationships between Conversation Styles of Chatbots, Chatbot Acceptance, and Perceived Tie Strength and Perceived Risk,” International Journal of Human–Computer Interaction, February 2024, vol. , pp. . DOI: 10.1080/10447318.2024.2314348. URL: https://www.tandfonline.com/doi/figure/10.1080/10447318.2024.2314348?scroll=top&needAccess=true. Open Access: No.

Mohanna Hoveyda, Arjen de Vries, Maarten de Rijke, Faegheh Hasibi, “Real World Conversational Entity Linking Requires More Than Zero-Shots,” Findings of the Association for Computational Linguistics ACL 2024, May 2024, vol. , pp. . DOI: 10.18653/v1/2024.findings-acl.829. URL: https://aclanthology.org/2024.findings-acl.829.pdf. Open Access: Yes.

Heydar Soudani, Roxana Petcu, Evangelos Kanoulas, and Faegheh Hasibi., “Data Augmentation for Conversational AI,” Proceedings of the ACM Web Conference 2024 (WWW ’24), May 2024, vol. , pp. . DOI: https://doi.org/10.1145/3589335.3641238. URL: https://dl.acm.org/doi/10.1145/3589335.3641238. Open Access: Yes.

Andreas Paraskeva, Joao Pedro Reis, Suzan Verberne, Jan N. van Rijn, “Resource-constrained Neural Architecture Search on Language Models: A Case Study,” WANT@ICML2024 workshop, June 2024, vol. , pp. . DOI: No DOI. URL: https://openreview.net/forum?id=ksdbauVu00¬eId=ksdbauVu00. Open Access: Yes.

Mert Yazan, Frederik Situmeang, Suzan Verberne, “The Impact of Quantization on Retrieval-Augmented Generation: An Analysis of Small LLMs,” IR-RAG@SIGIR’24, July 2024, vol. 3784, pp. 77-81. DOI: https://doi.org/10.48550/arXiv.2406.10251. URL: https://ceur-ws.org/Vol-3784/. Open Access: Yes.

Nonkes, N., Agaronian, S., Kanoulas, E., Petcu, R., “Leveraging graph structures to detect hallucinations in large language models.,” Proceedings of the TextGraphs-17 Workshop, ACL 2024, August 2024, vol. , pp. 93–104. DOI: https://doi.org/10.48550/arXiv.2407.04485. URL: https://aclanthology.org/2024.textgraphs-1.7/. Open Access: Yes.

Vera Neplenbroek, Arianna Bisazza, Raquel Fernández, “MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs,” Conference on Language Modeling (COLM), October 2024, vol. , pp. . DOI: https://doi.org/10.48550/arXiv.2406.07243. URL: https://openreview.net/forum?id=X9yV4lFHt4#discussion. Open Access: Yes.

Jirui Qi, Gabriele Sarti, Raquel Fernández, Arianna Bisazza, “Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation,” Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, December 2024, vol. , pp. . DOI: https://doi.org/10.48550/arXiv.2406.13663. URL: https://arxiv.org/abs/2406.13663. Open Access: Yes.

Xinyi Chen, Baohao Liao, Jirui Qi, Panagiotis Eustratiadis, Christof Monz, Arianna Bisazza, Maarten de Rijke, “The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models,” Findings of the 2024 Conference on Empirical Methods in Natural Language Processing, December 2024, vol. , pp. . DOI: https://doi.org/10.48550/arXiv.2406.19999. URL: https://arxiv.org/abs/2406.19999. Open Access: Yes.

I-Fan Lin, Faegheh Hasibi, Suzan Verberne, “Generate then Refine: Data Augmentation for Zero-shot Intent Detection,” Findings of the 2024 Conference on Empirical Methods in Natural Language Processing, December 2024, vol. , pp. . DOI: https://aclanthology.org/2024.findings-emnlp.768. URL: https://aclanthology.org/2024.findings-emnlp.768/. Open Access: Yes.

Heydar Soudani, Evangelos Kanoulas, Faegheh Hasibi, “Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge,” Proceedings of International ACM SIGIR Conference on Information Retrieval in the Asia Pacific, December 2024, vol. , pp. . DOI: https://doi.org/10.1145/3673791.369841. URL: https://arxiv.org/abs/2403.01432. Open Access: Yes.