{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T04:16:47Z","timestamp":1750220207867,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":35,"publisher":"ACM","license":[{"start":{"date-parts":[[2022,8,14]],"date-time":"2022-08-14T00:00:00Z","timestamp":1660435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2022,8,14]]},"DOI":"10.1145\/3534678.3539162","type":"proceedings-article","created":{"date-parts":[[2022,8,12]],"date-time":"2022-08-12T19:06:12Z","timestamp":1660331172000},"page":"3849-3857","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Semantic Aware Answer Sentence Selection Using Self-Learning Based Domain Adaptation"],"prefix":"10.1145","author":[{"given":"Rajdeep","family":"Sarkar","sequence":"first","affiliation":[{"name":"National University of Ireland Galway, Galway, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sourav","family":"Dutta","sequence":"additional","affiliation":[{"name":"Huawei Research, Dublin, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haytham","family":"Assem","sequence":"additional","affiliation":[{"name":"Amazon Alexa AI, Cambridge, United Kingdom"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mihael","family":"Arcan","sequence":"additional","affiliation":[{"name":"National University of Ireland Galway, Galway, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"John","family":"McCrae","sequence":"additional","affiliation":[{"name":"National University of Ireland Galway, Galway, Ireland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,8,14]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P19-1620"},{"key":"e_1_3_2_2_2_1","doi-asserted-by":"crossref","unstructured":"Giambattista Amati. 2009. BM25. Springer US Boston MA 257--260.","DOI":"10.1007\/978-0-387-39940-9_921"},{"key":"e_1_3_2_2_3_1","volume-title":"Qasar: Self-Supervised Learning Framework for Extractive Question Answering. In 2021 IEEE International Conference on Big Data (Big Data)","author":"Assem Haytham","year":"2021","unstructured":"Haytham Assem, Rajdeep Sarkar, and Sourav Dutta. 2021. Qasar: Self-Supervised Learning Framework for Extractive Question Answering. In 2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA. IEEE, 1797--1808."},{"volume-title":"Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP. The Association for Computational Linguistics, 632--642","author":"Bowman Samuel R.","key":"e_1_3_2_2_4_1","unstructured":"Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015. A large annotated corpus for learning natural language inference. In Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP. The Association for Computational Linguistics, 632--642."},{"key":"e_1_3_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-5821"},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3457533"},{"key":"e_1_3_2_2_7_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.wnut-1.20"},{"key":"e_1_3_2_2_8_1","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American","author":"Devlin Jacob","year":"2019","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT. Association for Computational Linguistics, 4171--4186."},{"key":"e_1_3_2_2_9_1","volume-title":"DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. In Proceedings of the 2019 Conference of the North American","author":"Dua Dheeru","year":"2019","unstructured":"Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. 2019. DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT. Association for Computational Linguistics, 2368--2378."},{"key":"e_1_3_2_2_10_1","volume-title":"ECIR (Lecture Notes in Computer Science","volume":"286","author":"Gao Luyu","year":"2021","unstructured":"Luyu Gao, Zhuyun Dai, and Jamie Callan. 2021. Rethink Training of BERT Rerankers in Multi-stage Retrieval Pipeline. In Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR (Lecture Notes in Computer Science, Vol. 12657). Springer, 280--286."},{"key":"e_1_3_2_2_11_1","volume-title":"TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI","author":"Garg Siddhant","year":"2020","unstructured":"Siddhant Garg, Thuy Vu, and Alessandro Moschitti. 2020. TANDA: Transfer and Adapt Pre-Trained Transformer Models for Answer Sentence Selection. In The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty- Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI. AAAI Press, 7780--7788."},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.eacl-main.261"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.5281\/zenodo.1212303"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00300"},{"key":"e_1_3_2_2_15_1","volume-title":"Textbook Question Answering for Multimodal Machine Comprehension. In 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR","author":"Kembhavi Aniruddha","year":"2017","unstructured":"Aniruddha Kembhavi, Min Joon Seo, Dustin Schwenk, Jonghyun Choi, Ali Farhadi, and Hannaneh Hajishirzi. 2017. Are You Smarter Than a Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension. In 2017 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017. IEEE Computer Society, 5376--5384."},{"volume-title":"Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR.","author":"Diederik","key":"e_1_3_2_2_16_1","unstructured":"Diederik P. Kingma and Jimmy Ba. 2015. Adam: A Method for Stochastic Optimization. In 3rd International Conference on Learning Representations, ICLR."},{"volume-title":"Proceedings of The 12th Language Resources and Evaluation Conference, LREC. European Language Resources Association, 5505--5514","key":"e_1_3_2_2_17_1","unstructured":"Md. Tahmid Rahman Laskar, Jimmy Xiangji Huang, and Enamul Hoque. 2020. Contextualized Embeddings based Transformer Encoder for Sentence Similarity Modeling in Answer Selection Task. In Proceedings of The 12th Language Resources and Evaluation Conference, LREC. European Language Resources Association, 5505--5514."},{"key":"e_1_3_2_2_18_1","volume-title":"ECIR (Lecture Notes in Computer Science","volume":"312","author":"Lauriola Ivano","year":"2021","unstructured":"Ivano Lauriola and Alessandro Moschitti. 2021. Answer Sentence Selection Using Local and Global Context in Transformer Models. In Advances in Information Retrieval - 43rd European Conference on IR Research, ECIR (Lecture Notes in Computer Science, Vol. 12656). Springer, 298--312."},{"volume-title":"Specification searches: Ad hoc inference with nonexperimental data","author":"Leamer Edward E","key":"e_1_3_2_2_19_1","unstructured":"Edward E Leamer. 1978. Specification searches: Ad hoc inference with nonexperimental data. Vol. 53. John Wiley & Sons Incorporated."},{"key":"e_1_3_2_2_20_1","volume-title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach. CoRR abs\/1907.11692","author":"Liu Yinhan","year":"2019","unstructured":"Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019. RoBERTa: A Robustly Optimized BERT Pretraining Approach. CoRR abs\/1907.11692 (2019). arXiv:1907.11692 http:\/\/arxiv.org\/abs\/1907.11692"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.492"},{"key":"e_1_3_2_2_22_1","volume-title":"Machine Learning and Knowledge Discovery in Databases - InternationalWorkshops of ECML PKDD (Communications in Computer and Information Science","volume":"568","author":"Nentidis Anastasios","year":"2019","unstructured":"Anastasios Nentidis, Konstantinos Bougiatiotis, Anastasia Krithara, and Georgios Paliouras. 2019. Results of the Seventh Edition of the BioASQ Challenge. In Machine Learning and Knowledge Discovery in Databases - InternationalWorkshops of ECML PKDD (Communications in Computer and Information Science, Vol. 1168), Peggy Cellier and Kurt Driessens (Eds.). Springer, 553--568."},{"key":"e_1_3_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330677"},{"key":"e_1_3_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.emnlp-main.468"},{"key":"e_1_3_2_2_25_1","unstructured":"Alec Radford JeffreyWu Rewon Child David Luan Dario Amodei Ilya Sutskever et al. 2019. Language models are unsupervised multitask learners. OpenAI blog 1 8 (2019) 9."},{"key":"e_1_3_2_2_26_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D16-1264"},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D19-1410"},{"key":"e_1_3_2_2_28_1","volume-title":"a distilled version of BERT: smaller, faster, cheaper and lighter. CoRR abs\/1910.01108","author":"Sanh Victor","year":"2019","unstructured":"Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019. DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter. CoRR abs\/1910.01108 (2019)."},{"key":"e_1_3_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/2766462.2767738"},{"key":"e_1_3_2_2_30_1","doi-asserted-by":"crossref","unstructured":"Luca Soldaini and Alessandro Moschitti. 2020. The Cascade Transformer: an Application for Efficient Answer Sentence Selection. In ACL. 5697--5708.","DOI":"10.18653\/v1\/2020.acl-main.504"},{"key":"e_1_3_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2017.2785283"},{"key":"e_1_3_2_2_32_1","volume-title":"Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems. 5998--6008","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All you Need. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems. 5998--6008."},{"key":"e_1_3_2_2_33_1","volume-title":"Manning","author":"Yang Zhilin","year":"2018","unstructured":"Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, and Christopher D. Manning. 2018. HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, EMNLP. Association for Computational Linguistics, 2369--2380."},{"key":"e_1_3_2_2_34_1","volume-title":"Proceedings of The 12th Language Resources and Evaluation Conference, LREC. European Language Resources Association, 5400--5407","author":"Yoon Seunghyun","year":"2020","unstructured":"Seunghyun Yoon, Franck Dernoncourt, Doo Soon Kim, Trung Bui, and Kyomin Jung. 2020. Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks. In Proceedings of The 12th Language Resources and Evaluation Conference, LREC. European Language Resources Association, 5400--5407."},{"key":"e_1_3_2_2_35_1","volume-title":"Deep Learning for Answer Sentence Selection. In NIPS Deep Learning Workshop.","author":"Yu Lei","year":"2014","unstructured":"Lei Yu, Karl Moritz Hermann, Phil Blunsom, and Stephen Pulman. 2014. Deep Learning for Answer Sentence Selection. In NIPS Deep Learning Workshop."}],"event":{"name":"KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGKDD ACM Special Interest Group on Knowledge Discovery in Data"],"location":"Washington DC USA","acronym":"KDD '22"},"container-title":["Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539162","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3534678.3539162","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T19:02:58Z","timestamp":1750186978000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3534678.3539162"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,14]]},"references-count":35,"alternative-id":["10.1145\/3534678.3539162","10.1145\/3534678"],"URL":"https:\/\/doi.org\/10.1145\/3534678.3539162","relation":{},"subject":[],"published":{"date-parts":[[2022,8,14]]},"assertion":[{"value":"2022-08-14","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}