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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 Hits 1 – 20 of 35 1 Eye Movement Traces of Linguistic Knowledge Berzak, Yevgeni; Levy, Roger In: Proceedings of the Annual Meeting of the Cognitive Science Society, vol 43, iss 43 (2021) BASE Show details 2 Eye Movement Traces of Linguistic Knowledge ... Berzak, Yevgeni. - : Open Science Framework, 2021 BASE Show details 3 Universal Dependencies 2.9 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 4 Universal Dependencies 2.8.1 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 5 Universal Dependencies 2.8 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 6 Eye Movement Traces of Linguistic Knowledge ... 43rd Annual Meeting of the Cognitive Science Society 2021; Berzak, Yevgeni; Levy, Roger. - : Underline Science Inc., 2021 BASE Show details 7 Assessing Language Proficiency from Eye Movements in Reading Berzak, Yevgeni; Katz, Boris; Levy, Roger P In: Association for Computational Linguistics (2021) BASE Show details 8 STARC: Structured Annotations for Reading Comprehension Berzak, Yevgeni; Malmaud, Jonathan; Levy, Roger In: Association for Computational Linguistics (2021) Abstract: We present STARC (Structured Annotations for Reading Comprehension), a new annotation framework for assessing reading comprehension with multiple choice questions. Our framework introduces a principled structure for the answer choices and ties them to textual span annotations. The framework is implemented in OneStopQA, a new high-quality dataset for evaluation and analysis of reading comprehension in English. We use this dataset to demonstrate that STARC can be leveraged for a key new application for the development of SAT-like reading comprehension materials: automatic annotation quality probing via span ablation experiments. We further show that it enables in-depth analyses and comparisons between machine and human reading comprehension behavior, including error distributions and guessing ability. Our experiments also reveal that the standard multiple choice dataset in NLP, RACE (Lai et al., 2017), is limited in its ability to measure reading comprehension. 47% of its questions can be guessed by machines without accessing the passage, and 18% are unanimously judged by humans as not having a unique correct answer. OneStopQA provides an alternative test set for reading comprehension which alleviates these shortcomings and has a substantially higher human ceiling performance. URL: https://hdl.handle.net/1721.1/138279 BASE Hide details 9 Bridging Information-Seeking Human Gaze and Machine Reading Comprehension Malmaud, Jonathan; Levy, Roger; Berzak, Yevgeni In: Association for Computational Linguistics (2021) BASE Show details 10 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 11 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 12 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni... In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019) BASE Show details 13 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 14 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 15 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing ... Ponti, Edoardo; O'Horan, Helen; Berzak, Yevgeni. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 16 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Reichart, Roi; Shutova, Ekaterina; Korhonen, Anna-Leena. - : MIT Press - Journals, 2019. : COMPUTATIONAL LINGUISTICS, 2019 BASE Show details 17 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni... In: Computational Linguistics, Vol 45, Iss 3, Pp 559-601 (2019) (2019) BASE Show details 18 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo,; O 'horan, Helen; Berzak, Yevgeni... In: https://hal.archives-ouvertes.fr/hal-01856176 ; 2018 (2018) BASE Show details 19 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 20 Second language learning from a multilingual perspective Berzak, Yevgeni. - : Massachusetts Institute of Technology, 2018 BASE Show details Page: 1 2

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