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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 – 11 of 11 1 On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers ... 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; Balasubramanian, Niranjan; Ferdman, Michael. - : Underline Science Inc., 2021 BASE Show details 2 Don't Let Discourse Confine Your Model: Sequence Perturbations for Improved Event Language Models ... 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; Balasubramanian, Niranjan; Chambers, Nathanael; Durrett, Greg; Koupaee, Mahnaz. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-short.76 Abstract: Event language models represent plausible sequences of events. Most existing approaches train autoregressive models on text, which successfully capture event co-occurrence but unfortunately constrain the model to follow the discourse order in which events are presented. Other domains may employ different discourse orders, and for many applications, we may care about different notions of ordering (e.g., temporal) or not care about ordering at all (e.g., when predicting related events in a schema). We propose a simple yet surprisingly effective strategy for improving event language models by perturbing event sequences so we can relax model dependence on text order. Despite generating completely synthetic event orderings, we show that this technique improves the performance of the event language models on both applications and out-of-domain events data. ... Keyword: Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics URL: https://dx.doi.org/10.48448/yhx9-pa72 https://underline.io/lecture/25651-don't-let-discourse-confine-your-model-sequence-perturbations-for-improved-event-language-models BASE Hide details 3 TellMeWhy: A Dataset for Answering Why-Questions in Narratives ... 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; Balasubramanian, Niranjan; Chambers, Nathanael. - : Underline Science Inc., 2021 BASE Show details 4 IrEne: Interpretable Energy Prediction for Transformers ... 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; ., Harsh; Balasubramanian, Niranjan. - : Underline Science Inc., 2021 BASE Show details 5 On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers ... 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; Balasubramanian, Niranjan; Ferdman, Michael. - : Underline Science Inc., 2021 BASE Show details 6 Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Harsh; Balasubramanian, Niranjan. - : Underline Science Inc., 2021 BASE Show details 7 Modeling Label Semantics for Predicting Emotional Reactions ... Gaonkar, Radhika; Kwon, Heeyoung; Bastan, Mohaddeseh. - : arXiv, 2020 BASE Show details 8 Residualized Factor Adaptation for Community Social Media Prediction Tasks ... Zamani, Mohammadzaman; Schwartz, H. Andrew; Lynn, Veronica E.. - : arXiv, 2018 BASE Show details 9 The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models ... Weber, Noah; Shekhar, Leena; Balasubramanian, Niranjan. - : arXiv, 2018 BASE Show details 10 Generating Coherent Event Schemas at Scale Balasubramanian, Niranjan; Soderland,Stephen; Mausam,. - 2013 BASE Show details 11 Improved Document Representation for Classification Tasks for the Intelligence Community Liddy, Elizabeth D.; Yilmazel, Ozgur; Symonenko, Svetlana... In: School of Information Studies - Faculty Scholarship (2005) BASE Show details

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