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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 Hits 1 – 20 of 54 1 A Feasibility Study of Answer-Agnostic Question Generation for Education ... Dugan, Liam; Miltsakaki, Eleni; Upadhyay, Shriyash. - : arXiv, 2022 BASE Show details 2 BiSECT: Learning to Split and Rephrase Sentences with Bitexts ... Kim, Joongwon; Maddela, Mounica; Kriz, Reno. - : arXiv, 2021 BASE Show details 3 "Wikily" Supervised Neural Translation Tailored to Cross-Lingual Tasks ... Rasooli, Mohammad Sadegh; Callison-Burch, Chris; Wijaya, Derry Tanti. - : arXiv, 2021 BASE Show details 4 Is "my favorite new movie" my favorite movie? Probing the Understanding of Recursive Noun Phrases ... Lyu, Qing; Zheng, Hua; Li, Daoxin. - : arXiv, 2021 BASE Show details 5 Goal-Oriented Script Construction ... Lyu, Qing; Zhang, Li; Callison-Burch, Chris. - : arXiv, 2021 BASE Show details 6 Visual Goal-Step Inference using wikiHow ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Callison-Burch, Chris; Lyu, Qing. - : Underline Science Inc., 2021 BASE Show details 7 Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Callison-Burch, Chris; Rasooli, Mohammad Sadegh. - : Underline Science Inc., 2021 BASE Show details 8 BUSINESS MEETING ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bender, Emily M.; Callison-Burch, Chris. - : Underline Science Inc., 2021 BASE Show details 9 BiSECT: Learning to Split and Rephrase Sentences with Bitexts ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Callison-Burch, Chris; Kim, Joongwon. - : Underline Science Inc., 2021 BASE Show details 10 Resolving pronouns in Twitter streams: context can help! Wijaya, Derry Tanti; Andy, Anietie; Callison-Burch, Chris. - : Association for Computational Linguistics, 2020 BASE Show details 11 Intent Detection with WikiHow ... Zhang, Li; Lyu, Qing; Callison-Burch, Chris. - : arXiv, 2020 BASE Show details 12 Resolving Pronouns in Twitter Streams: Context can Help! ... The 28th International Conference on Computational Linguistics 2020; Andy, Anietie; Callison-Burch, Chris. - : Underline Science Inc., 2020 BASE Show details 13 Artificial Intelligence in mental health and the biases of language based models Straw, Isabel; Callison-Burch, Chris In: PLoS One (2020) BASE Show details 14 Winter is here: summarizing Twitter streams related to pre-scheduled events Andy, Anietie; Wijaya, Derry Tanti; Callison-Burch, Chris. - : Association for Computational Linguistics, 2019 BASE Show details 15 Bilingual is At Least Monolingual (BALM): A Novel Translation Algorithm that Encodes Monolingual Priors ... Cheng, Jeffrey; Callison-Burch, Chris. - : arXiv, 2019 BASE Show details 16 Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims ... Chen, Sihao; Khashabi, Daniel; Yin, Wenpeng. - : arXiv, 2019 BASE Show details 17 Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification ... Kriz, Reno; Sedoc, João; Apidianaki, Marianna; Zheng, Carolina; Kumar, Gaurav; Miltsakaki, Eleni; Callison-Burch, Chris. - : arXiv, 2019 Abstract: Sentence simplification is the task of rewriting texts so they are easier to understand. Recent research has applied sequence-to-sequence (Seq2Seq) models to this task, focusing largely on training-time improvements via reinforcement learning and memory augmentation. One of the main problems with applying generic Seq2Seq models for simplification is that these models tend to copy directly from the original sentence, resulting in outputs that are relatively long and complex. We aim to alleviate this issue through the use of two main techniques. First, we incorporate content word complexities, as predicted with a leveled word complexity model, into our loss function during training. Second, we generate a large set of diverse candidate simplifications at test time, and rerank these to promote fluency, adequacy, and simplicity. Here, we measure simplicity through a novel sentence complexity model. These extensions allow our models to perform competitively with state-of-the-art systems while generating simpler ... : 11 pages, North American Association of Computational Linguistics (NAACL 2019) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1904.02767 https://arxiv.org/abs/1904.02767 BASE Hide details 18 Comparison of Diverse Decoding Methods from Conditional Language Models ... Ippolito, Daphne; Kriz, Reno; Kustikova, Maria. - : arXiv, 2019 BASE Show details 19 Paraphrase-Sense-Tagged Sentences Cocos, Anne; Callison-Burch, Chris In: Transactions of the Association for Computational Linguistics, Vol 7, Pp 714-728 (2019) (2019) BASE Show details 20 Learning translations via images with a massively multilingual image dataset Callison-Burch, Chris; Wijaya, Derry; Kriz, Reno. - : Association for Computational Linguistics, 2018 BASE Show details Page: 1 2 3

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