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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 – 7 of 7 1 Contrastive Explanations for Model Interpretability ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Choi, Yejin; Elazar, Yanai. - : Underline Science Inc., 2021 BASE Show details 2 Provable Limitations of Acquiring Meaning from Ungrounded Form: What will Future Language Models Understand? ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Merrill, William. - : Underline Science Inc., 2021 BASE Show details 3 Measuring and Improving Consistency in Pretrained Language Models ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Elazar, Yanai; Goldberg, Yoav. - : Underline Science Inc., 2021 BASE Show details 4 Aligning Faithful Interpretations with their Social Attribution ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Jacovi, Alon. - : Underline Science Inc., 2021 BASE Show details 5 Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Merrill, William. - : Underline Science Inc., 2021 BASE Show details 6 Asking It All: Generating Contextualized Questions for any Semantic Role ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Dagan, Ido; Goldberg, Yoav; Michael, Julian; Pyatkin, Valentina; Roit, Paul; Tsarfaty, Reut. - : Underline Science Inc., 2021 Abstract: Anthology paper link: https://aclanthology.org/2021.emnlp-main.108/ Abstract: Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention and a passage, requires producing a set of questions asking about all possible semantic roles of the predicate. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage. Unlike most existing approaches to question generation, our approach does not require conditioning on existing answers in the text. Instead, we condition on the type of information to inquire about, regardless of whether the answer appears explicitly in the text, could be inferred from it, or should be sought elsewhere. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage ontology of predicates and roles. ... Keyword: Language Models; Natural Language Processing; Semantic Evaluation; Sociolinguistics URL: https://dx.doi.org/10.48448/endb-5y94 https://underline.io/lecture/37784-asking-it-all-generating-contextualized-questions-for-any-semantic-role BASE Hide details 7 Counterfactual Interventions Reveal the Causal Effect of Relative Clause Representations on Agreement Prediction ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Goldberg, Yoav; Linzen, Tal. - : Underline Science Inc., 2021 BASE Show details

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