{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T14:47:36Z","timestamp":1773326856238,"version":"3.50.1"},"reference-count":50,"publisher":"Association for Computing Machinery (ACM)","issue":"6","license":[{"start":{"date-parts":[[2023,6,16]],"date-time":"2023-06-16T00:00:00Z","timestamp":1686873600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"crossref","award":["NPRP13S-0112-200037"],"award-info":[{"award-number":["NPRP13S-0112-200037"]}],"id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Asian Low-Resour. Lang. Inf. Process."],"published-print":{"date-parts":[[2023,6,30]]},"abstract":"<jats:p>Dialogue generation is the automatic generation of a text response, given a user\u2019s input. Dialogue generation for low-resource languages has been a challenging tasks for researchers. However, the advancements in deep learning models have made developing conversational agents that perform the tasks of dialogue generation not only possible, but also effective and helpful in many applications spanning a variety of domains. Nevertheless, work on conversational bots for low-resource languages such as the Arabic language is still limited due to various challenges, including the language structure, vocabulary, and the scarcity of its data resources. Meta-learning has been introduced before in the natural language processing (NLP) realm and showed significant improvements in many tasks; however, it has rarely been used in natural language generation (NLG) tasks and never in Arabic NLG. In this work, we propose a meta-learning approach for Arabic dialogue generation for fast adaptation on low-resource domains, namely, Arabic. We start by using existing pre-trained models; we then meta-learn the initial parameters on high-resource dataset before finetuning the parameters on the target tasks. We prove that the proposed model that employs meta-learning techniques improves generalization and enables fast adaptation of the transformer model on low-resource NLG tasks. We report gains in the BLEU-4 and improvements in Semantic textual Similarity (STS) metrics when compared to the existing state-of-the-art approach. We also do a further study on the effectiveness of the meta-learning algorithms on the response generation of the models.<\/jats:p>","DOI":"10.1145\/3590960","type":"journal-article","created":{"date-parts":[[2023,4,10]],"date-time":"2023-04-10T13:14:40Z","timestamp":1681132480000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Metadial: A Meta-learning Approach for Arabic Dialogue Generation"],"prefix":"10.1145","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5614-7587","authenticated-orcid":false,"given":"Mohsen","family":"Shamas","sequence":"first","affiliation":[{"name":"American University of Beirut, Lebanon"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9954-7924","authenticated-orcid":false,"given":"Wassim","family":"El Hajj","sequence":"additional","affiliation":[{"name":"American University of Beirut, Lebanon"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5206-2954","authenticated-orcid":false,"given":"Hazem","family":"Hajj","sequence":"additional","affiliation":[{"name":"American University of Beirut, Lebanon"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5688-7515","authenticated-orcid":false,"given":"Khaled","family":"Shaban","sequence":"additional","affiliation":[{"name":"Qatar University, Qatar"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,6,16]]},"reference":[{"key":"e_1_3_6_2_2","first-page":"208","volume-title":"Proceedings of the 26th International Conference on Computational Linguistics: System Demonstrations","author":"Ali Dana Abu","year":"2016","unstructured":"Dana Abu Ali and Nizar Habash. 2016. Botta: An Arabic dialect chatbot. In Proceedings of the 26th International Conference on Computational Linguistics: System Demonstrations. The COLING 2016 Organizing Committee, 208\u2013212. Retrieved from https:\/\/aclanthology.org\/C16-2044."},{"key":"e_1_3_6_3_2","article-title":"AraBERT: Transformer-based model for Arabic language understanding","author":"Antoun Wissam","year":"2020","unstructured":"Wissam Antoun, Fady Baly, and Hazem Hajj. 2020. AraBERT: Transformer-based model for Arabic language understanding. arXiv preprint arXiv:2003.00104 (2020).","journal-title":"arXiv preprint arXiv:2003.00104"},{"key":"e_1_3_6_4_2","article-title":"Few-shot NLG with pre-trained language model","author":"Chen Zhiyu","year":"2019","unstructured":"Zhiyu Chen, Harini Eavani, Wenhu Chen, Yinyin Liu, and William Yang Wang. 2019. Few-shot NLG with pre-trained language model. arXiv preprint arXiv:1904.09521 (2019).","journal-title":"arXiv preprint arXiv:1904.09521"},{"key":"e_1_3_6_5_2","article-title":"Learning phrase representations using RNN encoder-decoder for statistical machine translation","author":"Cho Kyunghyun","year":"2014","unstructured":"Kyunghyun Cho, Bart Van Merri\u00ebnboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014. Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014).","journal-title":"arXiv preprint arXiv:1406.1078"},{"key":"e_1_3_6_6_2","article-title":"A formula for predicting readability: Instructions","author":"Dale Edgar","year":"1948","unstructured":"Edgar Dale and Jeanne S. Chall. 1948. A formula for predicting readability: Instructions. Educ. Res. Bull. 27, 1\u201320 (1948), 37\u201354.","journal-title":"Educ. Res. Bull."},{"key":"e_1_3_6_7_2","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. BERT: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018).","journal-title":"arXiv preprint arXiv:1810.04805"},{"key":"e_1_3_6_8_2","article-title":"Investigating meta-learning algorithms for low-resource natural language understanding tasks","author":"Dou Zi-Yi","year":"2019","unstructured":"Zi-Yi Dou, Keyi Yu, and Antonios Anastasopoulos. 2019. Investigating meta-learning algorithms for low-resource natural language understanding tasks. arXiv preprint arXiv:1908.10423 (2019).","journal-title":"arXiv preprint arXiv:1908.10423"},{"key":"e_1_3_6_9_2","unstructured":"Mahmoud El-Haj and Paul Rayson. 2016. OSMAN: A novel Arabic readability metric. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC\u201916) . European Language Resources Association (ELRA) Portoro\u017e 250\u2013255. https:\/\/aclanthology.org\/L16-1038."},{"key":"e_1_3_6_10_2","doi-asserted-by":"publisher","DOI":"10.26615\/978-954-452-056-4_034"},{"key":"e_1_3_6_11_2","first-page":"1126","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Finn Chelsea","year":"2017","unstructured":"Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017. Model-agnostic meta-learning for fast adaptation of deep networks. In Proceedings of the International Conference on Machine Learning. PMLR, 1126\u20131135."},{"key":"e_1_3_6_12_2","first-page":"1891","volume-title":"Proceedings of the INTERSPEECH Conference","author":"Gopalakrishnan Karthik","year":"2019","unstructured":"Karthik Gopalakrishnan, Behnam Hedayatnia, Qinglang Chen, Anna Gottardi, Sanjeev Kwatra, Anu Venkatesh, Raefer Gabriel, Dilek Hakkani-T\u00fcr, and Amazon Alexa AI. 2019. Topical-chat: Towards knowledge-grounded open-domain conversations. In Proceedings of the INTERSPEECH Conference. 1891\u20131895."},{"key":"e_1_3_6_13_2","first-page":"49","volume-title":"Proceedings of the 5th Arabic Natural Language Processing Workshop","author":"Helwe Chadi","year":"2020","unstructured":"Chadi Helwe, Ghassan Dib, Mohsen Shamas, and Shady Elbassuoni. 2020. A semi-supervised BERT approach for Arabic named entity recognition. In Proceedings of the 5th Arabic Natural Language Processing Workshop. Association for Computational Linguistics, 49\u201357. Retrieved from https:\/\/aclanthology.org\/2020.wanlp-1.5."},{"key":"e_1_3_6_14_2","doi-asserted-by":"publisher","DOI":"10.1109\/CSIT.2014.6806005"},{"key":"e_1_3_6_15_2","article-title":"The curious case of neural text degeneration","author":"Holtzman Ari","year":"2019","unstructured":"Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2019. The curious case of neural text degeneration. arXiv preprint arXiv:1904.09751 (2019).","journal-title":"arXiv preprint arXiv:1904.09751"},{"key":"e_1_3_6_16_2","doi-asserted-by":"publisher","DOI":"10.21236\/ADA006655"},{"key":"e_1_3_6_17_2","first-page":"388","volume-title":"Proceedings of the Conference on Empirical Methods in Natural Language Processing","author":"Koehn Philipp","year":"2004","unstructured":"Philipp Koehn. 2004. Statistical significance tests for machine translation evaluation. In Proceedings of the Conference on Empirical Methods in Natural Language Processing. 388\u2013395."},{"key":"e_1_3_6_18_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N16-1014"},{"key":"e_1_3_6_19_2","article-title":"A persona-based neural conversation model","author":"Li Jiwei","year":"2016","unstructured":"Jiwei Li, Michel Galley, Chris Brockett, Georgios P. Spithourakis, Jianfeng Gao, and Bill Dolan. 2016. A persona-based neural conversation model. arXiv preprint arXiv:1603.06155 (2016).","journal-title":"arXiv preprint arXiv:1603.06155"},{"key":"e_1_3_6_20_2","article-title":"Adversarial learning for neural dialogue generation","author":"Li Jiwei","year":"2017","unstructured":"Jiwei Li, Will Monroe, Tianlin Shi, S\u00e9bastien Jean, Alan Ritter, and Dan Jurafsky. 2017. Adversarial learning for neural dialogue generation. arXiv preprint arXiv:1701.06547 (2017).","journal-title":"arXiv preprint arXiv:1701.06547"},{"key":"e_1_3_6_21_2","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i09.7098"},{"key":"e_1_3_6_22_2","article-title":"How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation","author":"Liu Chia-Wei","year":"2016","unstructured":"Chia-Wei Liu, Ryan Lowe, Iulian V. Serban, Michael Noseworthy, Laurent Charlin, and Joelle Pineau. 2016. How not to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation. arXiv preprint arXiv:1603.08023 (2016).","journal-title":"arXiv preprint arXiv:1603.08023"},{"key":"e_1_3_6_23_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.24"},{"key":"e_1_3_6_24_2","article-title":"Meta-learning for low-resource natural language generation in task-oriented dialogue systems","author":"Mi Fei","year":"2019","unstructured":"Fei Mi, Minlie Huang, Jiyong Zhang, and Boi Faltings. 2019. Meta-learning for low-resource natural language generation in task-oriented dialogue systems. arXiv preprint arXiv:1905.05644 (2019).","journal-title":"arXiv preprint arXiv:1905.05644"},{"key":"e_1_3_6_25_2","first-page":"164","volume-title":"Proceedings of the 6th Arabic Natural Language Processing Workshop","author":"Naous Tarek","year":"2021","unstructured":"Tarek Naous, Wissam Antoun, Reem Mahmoud, and Hazem Hajj. 2021. Empathetic BERT2BERT conversational model: Learning Arabic language generation with little data. In Proceedings of the 6th Arabic Natural Language Processing Workshop. Association for Computational Linguistics, 164\u2013172. Retrieved from https:\/\/aclanthology.org\/2021.wanlp-1.17."},{"key":"e_1_3_6_26_2","first-page":"58","volume-title":"Proceedings of the 5th Arabic Natural Language Processing Workshop","author":"Naous Tarek","year":"2020","unstructured":"Tarek Naous, Christian Hokayem, and Hazem Hajj. 2020. Empathy-driven Arabic conversational chatbot. In Proceedings of the 5th Arabic Natural Language Processing Workshop. Association for Computational Linguistics, 58\u201368. Retrieved from https:\/\/aclanthology.org\/2020.wanlp-1.6."},{"key":"e_1_3_6_27_2","article-title":"On first-order meta-learning algorithms","author":"Nichol Alex","year":"2018","unstructured":"Alex Nichol, Joshua Achiam, and John Schulman. 2018. On first-order meta-learning algorithms. arXiv preprint arXiv:1803.02999 (2018).","journal-title":"arXiv preprint arXiv:1803.02999"},{"key":"e_1_3_6_28_2","first-page":"311","volume-title":"Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. BLEU: A method for automatic evaluation of machine translation. In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. 311\u2013318."},{"key":"e_1_3_6_29_2","volume-title":"Proceedings of the World Congress on Engineering","author":"Pudner Karen","year":"2007","unstructured":"Karen Pudner, Keeley A. Crockett, and Zuhair Bandar. 2007. An intelligent conversational agent approach to extracting queries from natural language. In Proceedings of the World Congress on Engineering."},{"key":"e_1_3_6_30_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1253"},{"key":"e_1_3_6_31_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1534"},{"key":"e_1_3_6_32_2","unstructured":"Sachin Ravi and Hugo Larochelle. 2016. Optimization as a model for few-shot learning. International Conference on Learning Representations ."},{"key":"e_1_3_6_33_2","doi-asserted-by":"publisher","DOI":"10.5555\/2145432.2145500"},{"key":"e_1_3_6_34_2","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00313"},{"key":"e_1_3_6_35_2","first-page":"1842","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Santoro Adam","year":"2016","unstructured":"Adam Santoro, Sergey Bartunov, Matthew Botvinick, Daan Wierstra, and Timothy Lillicrap. 2016. Meta-learning with memory-augmented neural networks. In Proceedings of the International Conference on Machine Learning. PMLR, 1842\u20131850."},{"key":"e_1_3_6_36_2","article-title":"A deep reinforcement learning chatbot","author":"Serban Iulian V.","year":"2017","unstructured":"Iulian V. Serban, Chinnadhurai Sankar, Mathieu Germain, Saizheng Zhang, Zhouhan Lin, Sandeep Subramanian, Taesup Kim, Michael Pieper, Sarath Chandar, Nan Rosemary Ke et\u00a0al. 2017. A deep reinforcement learning chatbot. arXiv preprint arXiv:1709.02349 (2017).","journal-title":"arXiv preprint arXiv:1709.02349"},{"key":"e_1_3_6_37_2","first-page":"7989","volume-title":"Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","author":"Shin Jamin","year":"2020","unstructured":"Jamin Shin, Peng Xu, Andrea Madotto, and Pascale Fung. 2020. Generating empathetic responses by looking ahead the user\u2019s sentiment. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 7989\u20137993."},{"key":"e_1_3_6_38_2","article-title":"Prototypical networks for few-shot learning","volume":"30","author":"Snell Jake","year":"2017","unstructured":"Jake Snell, Kevin Swersky, and Richard Zemel. 2017. Prototypical networks for few-shot learning. Adv. Neural Inf. Process. Syst. 30 (2017).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"e_1_3_6_39_2","article-title":"Two are better than one: An ensemble of retrieval-and generation-based dialog systems","author":"Song Yiping","year":"2016","unstructured":"Yiping Song, Rui Yan, Xiang Li, Dongyan Zhao, and Ming Zhang. 2016. Two are better than one: An ensemble of retrieval-and generation-based dialog systems. arXiv preprint arXiv:1610.07149 (2016).","journal-title":"arXiv preprint arXiv:1610.07149"},{"key":"e_1_3_6_40_2","article-title":"LaMDA: Language models for dialog applications","author":"Thoppilan Romal","year":"2022","unstructured":"Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du et\u00a0al. 2022. LaMDA: Language models for dialog applications. arXiv preprint arXiv:2201.08239 (2022).","journal-title":"arXiv preprint arXiv:2201.08239"},{"key":"e_1_3_6_41_2","article-title":"Improving end-to-end speech-to-intent classification with Reptile","author":"Tian Yusheng","year":"2020","unstructured":"Yusheng Tian and Philip John Gorinski. 2020. Improving end-to-end speech-to-intent classification with Reptile. arXiv preprint arXiv:2008.01994 (2020).","journal-title":"arXiv preprint arXiv:2008.01994"},{"key":"e_1_3_6_42_2","article-title":"Attention is all you need","volume":"30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Adv. Neural Inf. Process. Syst. 30 (2017).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"e_1_3_6_43_2","unstructured":"Richard Wallace. 2003. The Elements of AIML Style . Vol. 139 New York NY."},{"key":"e_1_3_6_44_2","article-title":"GLUE: A multi-task benchmark and analysis platform for natural language understanding","author":"Wang Alex","year":"2018","unstructured":"Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R. Bowman. 2018. GLUE: A multi-task benchmark and analysis platform for natural language understanding. arXiv preprint arXiv:1804.07461 (2018).","journal-title":"arXiv preprint arXiv:1804.07461"},{"key":"e_1_3_6_45_2","doi-asserted-by":"publisher","DOI":"10.1145\/365153.365168"},{"key":"e_1_3_6_46_2","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1062"},{"key":"e_1_3_6_47_2","article-title":"HuggingFace\u2019s transformers: State-of-the-art natural language processing","author":"Wolf Thomas","year":"2019","unstructured":"Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, R\u00e9mi Louf, Morgan Funtowicz et\u00a0al. 2019. HuggingFace\u2019s transformers: State-of-the-art natural language processing. arXiv preprint arXiv:1910.03771 (2019).","journal-title":"arXiv preprint arXiv:1910.03771"},{"key":"e_1_3_6_48_2","article-title":"Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots","author":"Wu Yu","year":"2016","unstructured":"Yu Wu, Wei Wu, Chen Xing, Ming Zhou, and Zhoujun Li. 2016. Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots. arXiv preprint arXiv:1612.01627 (2016).","journal-title":"arXiv preprint arXiv:1612.01627"},{"key":"e_1_3_6_49_2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2012.2225812"},{"key":"e_1_3_6_50_2","article-title":"Personalizing dialogue agents: I have a dog, do you have pets too?","author":"Zhang Saizheng","year":"2018","unstructured":"Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018. Personalizing dialogue agents: I have a dog, do you have pets too?arXiv preprint arXiv:1801.07243 (2018).","journal-title":"arXiv preprint arXiv:1801.07243"},{"key":"e_1_3_6_51_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.11"}],"container-title":["ACM Transactions on Asian and Low-Resource Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3590960","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3590960","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T17:51:22Z","timestamp":1750182682000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3590960"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,16]]},"references-count":50,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2023,6,30]]}},"alternative-id":["10.1145\/3590960"],"URL":"https:\/\/doi.org\/10.1145\/3590960","relation":{},"ISSN":["2375-4699","2375-4702"],"issn-type":[{"value":"2375-4699","type":"print"},{"value":"2375-4702","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,16]]},"assertion":[{"value":"2022-11-26","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-03-13","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2023-06-16","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}