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This paper introduces the Ninth Dialog System Technology Challenge (DSTC-9).
2002
Earlier work this paper cites.
S. Banerjee and A. Lavie, “Meteor: An automatic metric for mt evaluation with improved correlation with human judgments,” in Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and/or summarization , 2005, pp. 65–72
2005
Earlier work this paper cites.
J. Schatzmann, B. Thomson, K. Weilhammer, H. Ye, and S. Young, “Agenda-based user simulation for bootstrapping a pomdp dialogue system,” in Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Companion Volume, Short Papers , 2007, pp. 149–152
2007
Earlier work this paper cites.
H. Ai, A. Raux, D. Bohus, M. Eskenazi, and D. Litman, “Comparing spoken dialog corpora collected with recruited subjects versus real users,” in Proceedings of the 8th SIGdial Workshop on Discourse and Dialogue , 2007, pp. 124–131
2007
Earlier work this paper cites.
J. Williams, A. Raux, D. Ramachandran, and A. Black, “The dialog state tracking challenge,” in Proceedings of the SIGDIAL 2013 Conference , 2013, pp. 404–413
2013
Earlier work this paper cites.
M. Henderson, B. Thomson, and J. D. Williams, “The second dialog state tracking challenge,” in Proceedings of the 15th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL) , 2014, pp. 263–272
2014
Earlier work this paper cites.
——, “The third dialog state tracking challenge,” in Spoken Language Technology Workshop (SLT), 2014 IEEE . IEEE, 2014, pp. 324–329
2014
Earlier work this paper cites.
O. Vinyals and Q. Le, “A neural conversational model,” arXiv preprint arXiv:1506.05869 , 2015
2015
Earlier work this paper cites.
S. Kim, L. F. D’Haro, R. E. Banchs, J. D. Williams, M. Henderson, and K. Yoshino, “The fifth dialog state tracking challenge,” in Spoken Language Technology Workshop (SLT), 2016 IEEEover . IEEE, 2016, pp. 511–517
2016
Earlier work this paper cites.
T. Zhao, K. Lee, and M. Eskenazi, “Dialport: Connecting the spoken dialog research community to real user data,” in 2016 IEEE Spoken Language Technology Workshop (SLT) . IEEE, 2016, pp. 83–90
2016
Earlier work this paper cites.
S. Kim, L. F. D’Haro, R. E. Banchs, J. D. Williams, and M. Henderson, “The fourth dialog state tracking challenge,” in Dialogues with Social Robots . Springer, 2017, pp. 435–449
2017
Earlier work this paper cites.
N. Mrksic, I. Vulic, D. Ó. Séaghdha, I. Leviant, R. Reichart, M. Gasic, A. Korhonen, and S. Young, “Semantic specialization of distributional word vector spaces using monolingual and cross-lingual constraints,” Transactions of the Association for Computational Linguistics , vol. 5, pp. 309–324, 2017
2017
Earlier work this paper cites.
2017
Earlier work this paper cites.
C. Hori, J. Perez, R. Higasinaka, T. Hori, Y.-L. Boureau, M. Inaba, Y. Tsunomori, T. Takahashi, K. Yoshino, and S. Kim, “Overview of the sixth dialog system technology challenge: Dstc6,” 2018
2018
Earlier work this paper cites.
H. Alamri, C. Hori, T. K. Marks, D. Batr, and D. Parikh, “Audio visual scene-aware dialog (avsd) track for natural language generation in dstc7,” in DSTC7 at AAAI2019 Workshop , vol. 2, 2018
2018
Earlier work this paper cites.
P. Budzianowski, T. Wen, B. Tseng, I. Casanueva, S. Ultes, O. Ramadan, and M. Gasic, “Multiwoz - A large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling,” 2018, pp. 5016–5026
2018
Earlier work this paper cites.
2018
Earlier work this paper cites.
P.-E. Mazaré, S. Humeau, M. Raison, and A. Bordes, “Training millions of personalized dialogue agents,” in Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing . Brussels, Belgium: Association for Computational Linguistics, Oct.-Nov. 2018, pp. 2775–2779. [Online]. Available: https://www.aclweb.org/anthology/D18-1298
2018
Earlier work this paper cites.
2019
Cited alongside, same era.
C. Gunasekara, J. K. Kummerfeld, L. Polymenakos, , and W. S. Lasecki, “Dstc7 task 1: Noetic end-to-end response selection,” in 7th Edition of the Dialog System Technology Challenges at AAAI 2019 , January 2019. [Online]. Available: http://workshop.colips.org/dstc7/papers/dstc7_task1_final_report.pdf
2019
Cited alongside, same era.
C. Gunasekara, J. K. Kummerfeld, L. Polymenakos, and W. Lasecki, “Dstc7 task 1: Noetic end-to-end response selection,” in Proceedings of the First Workshop on NLP for Conversational AI , 2019, pp. 60–67
2019
Cited alongside, same era.
M. Galley, C. Brockett, X. Gao, J. Gao, and B. Dolan, “Grounded response generation task at dstc7,” in AAAI Dialog System Technology Challenges Workshop , 2019
2019
S. Kim, M. Eric, K. Gopalakrishnan, B. Hedayatnia, Y. Liu, and D. Hakkani-Tur, “Beyond domain APIs: Task-oriented conversational modeling with unstructured knowledge access,” in Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue . 1st virtual meeting: Association for Computational Linguistics, Jul. 2020, pp. 278–289. [Online]. Available: https://www.aclweb.org/anthology/2020.sigdial-1.35
2020
Closest in time.
K. Gopalakrishnan, B. Hedayatnia, L. Wang, Y. Liu, and D. Hakkani-Tür, “Are neural open-domain dialog systems robust to speech recognition errors in the dialog history? an empirical study,” INTERSPEECH , pp. 911–915, 2020
2020
Closest in time.
J. Li, B. Peng, S. Lee, J. Gao, R. Takanobu, Q. Zhu, M. Huang, H. Schulz, A. Atkinson, and M. Adada, “Results of the multi-domain task-completion dialog challenge,” in Proceedings of the 34th AAAI Conference on Artificial Intelligence, Eighth Dialog System Technology Challenge Workshop , 2020
2020
Closest in time.
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Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
2019
Cited alongside, same era.
A. Radford, J. Wu, R. Child, D. Luan, D. Amodei, and I. Sutskever, “Language models are unsupervised multitask learners,” OpenAI blog , vol. 1, no. 8, p. 9, 2019
2019
Cited alongside, same era.
S. Lee, Q. Zhu, R. Takanobu, Z. Zhang, Y. Zhang, X. Li, J. Li, B. Peng, X. Li, M. Huang, and J. Gao, “Convlab: Multi-domain end-to-end dialog system platform,” in Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28 - August 2, 2019, Volume 3: System Demonstrations , 2019, pp. 64–69
2019
Cited alongside, same era.
J. Devlin, M. Chang, K. Lee, and K. Toutanova, “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 2019, Minneapolis, MN, USA, June 2-7, 2019, Volume 1 (Long and Short Papers) , pp. 4171–4186
2019
Cited alongside, same era.
S. Schuster, S. Gupta, R. Shah, and M. Lewis, “Cross-lingual transfer learning for multilingual task oriented dialog,” in NAACL-HLT , 2019
2019
Cited alongside, same era.
H. Lee, J. Lee, and T.-Y. Kim, “Sumbt: Slot-utterance matching for universal and scalable belief tracking,” 2019
2019
Cited alongside, same era.
R. Takanobu, Q. Zhu, J. Li, B. Peng, J. Gao, and M. Huang, “Is your goal-oriented dialog model performing really well? empirical analysis of system-wise evaluation,” in Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue , Jul. 2020, pp. 297–310
2020
Closest in time.
D. Ham, J.-G. Lee, Y. Jang, and K.-E. Kim, “End-to-end neural pipeline for goal-oriented dialogue systems using gpt-2.” ACL, 2020
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
Q. Zhu, Z. Zhang, Y. Fang, X. Li, R. Takanobu, J. Li, B. Peng, J. Gao, X. Zhu, and M. Huang, “Convlab-2: An open-source toolkit for building, evaluating, and diagnosing dialogue systems,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations, ACL 2020, Online, July 5-10, 2020 , pp. 142–149
2020
Closest in time.
2020
Closest in time.
S. Gururangan, A. Marasovic, S. Swayamdipta, K. Lo, I. Beltagy, D. Downey, and N. A. Smith, “Don’t stop pretraining: Adapt language models to domains and tasks,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020 , pp. 8342–8360
2020
Closest in time.
Y. Shan, Z. Li, J. Zhang, F. Meng, Y. Feng, C. Niu, and J. Zhou, “A contextual hierarchical attention network with adaptive objective for dialogue state tracking,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Online: Association for Computational Linguistics, Jul. 2020, pp. 6322–6333. [Online]. Available: https://www.aclweb.org/anthology/2020.acl-main.563
2020
Closest in time.
S. Kim, S. Yang, G. Kim, and S.-W. Lee, “Efficient dialogue state tracking by selectively overwriting memory,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Online: Association for Computational Linguistics, Jul. 2020, pp. 567–582. [Online]. Available: https://www.aclweb.org/anthology/2020.acl-main.53
2020
Closest in time.
2020
Closest in time.
2020
Closest in time.
2020
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S. Moon, S. Kottur, P. A. Crook, A. De, S. Poddar, T. Levin, D. Whitney, D. Difranco, A. Beirami, E. Cho, R. Subba, and A. Geramifard, “Situated and interactive multimodal conversations,” The 28th International Conference on Computational Linguistics (COLING) , 2020
2020
Closest in time.
M. Lewis, Y. Liu, N. Goyal, M. Ghazvininejad, A. Mohamed, O. Levy, V. Stoyanov, and L. Zettlemoyer, “BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension,” in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics . Online: Association for Computational Linguistics, Jul. 2020, pp. 7871–7880. [Online]. Available: https://www.aclweb.org/anthology/2020.acl-main.703
2020
Closest in time.
S. Humeau, K. Shuster, M. Lachaux, and J. Weston, “Poly-encoders: Architectures and pre-training strategies for fast and accurate multi-sentence scoring,” in 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020 . OpenReview.net, 2020. [Online]. Available: https://openreview.net/forum?id=SkxgnnNFvH
2020
Closest in time.