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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 Hits 1 – 13 of 13 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; Zhang, Li; Apidianaki, Marianna; Callison-Burch, Chris. - : arXiv, 2021 Abstract: Recursive noun phrases (NPs) have interesting semantic properties. For example, "my favorite new movie" is not necessarily "my favorite movie", whereas "my new favorite movie" is. This is common sense to humans, yet it is unknown whether pre-trained language models have such knowledge. We introduce the Recursive Noun Phrase Challenge (RNPC), a challenge set targeting the understanding of recursive NPs. When evaluated on our dataset, state-of-the-art Transformer models only achieve around chance performance. Still, we show that such knowledge is learnable with appropriate data. We further probe the models for relevant linguistic features that can be learned from our tasks, including modifier semantic category and modifier scope. Finally, models trained on RNPC achieve strong zero-shot performance on an extrinsic Harm Detection task, showing the usefulness of the understanding of recursive NPs in downstream applications. All code and data will be released at https://github.com/veronica320/Recursive-NPs. ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2112.08326 https://arxiv.org/abs/2112.08326 BASE Hide details 5 Goal-Oriented Script Construction ... Lyu, Qing; Zhang, Li; Callison-Burch, Chris. - : arXiv, 2021 BASE Show details 6 Intent Detection with WikiHow ... Zhang, Li; Lyu, Qing; Callison-Burch, Chris. - : arXiv, 2020 BASE Show details 7 Bilingual is At Least Monolingual (BALM): A Novel Translation Algorithm that Encodes Monolingual Priors ... Cheng, Jeffrey; Callison-Burch, Chris. - : arXiv, 2019 BASE Show details 8 Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims ... Chen, Sihao; Khashabi, Daniel; Yin, Wenpeng. - : arXiv, 2019 BASE Show details 9 Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification ... Kriz, Reno; Sedoc, João; Apidianaki, Marianna. - : arXiv, 2019 BASE Show details 10 Comparison of Diverse Decoding Methods from Conditional Language Models ... Ippolito, Daphne; Kriz, Reno; Kustikova, Maria. - : arXiv, 2019 BASE Show details 11 Use of Modality and Negation in Semantically-Informed Syntactic MT ... Baker, Kathryn; Bloodgood, Michael; Dorr, Bonnie J.. - : arXiv, 2015 BASE Show details 12 Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation ... Bloodgood, Michael; Callison-Burch, Chris. - : arXiv, 2014 BASE Show details 13 Semantically-Informed Syntactic Machine Translation: A Tree-Grafting Approach ... Baker, Kathryn; Bloodgood, Michael; Callison-Burch, Chris. - : arXiv, 2014 BASE Show details

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