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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 The statistical advantage of automatic NLG metrics at the system level ... 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; Jia, Robin; Wei, Johnny. - : Underline Science Inc., 2021 BASE Show details 2 Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? ... 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; ., Jordan; Barrow, Joe; Hoyle, Alexander; Jia, Robin; Lalor, John; Rodriguez, Pedro. - : Underline Science Inc., 2021 Abstract: Read paper: https://www.aclanthology.org/2021.acl-long.346 Abstract: Leaderboards are widely used in NLP and push the field forward. While leaderboards are a straightforward ranking of NLP models, this simplicity can mask nuances in evaluation items (examples) and subjects (NLP models). Rather than replace leaderboards, we advocate a re-imagining so that they better highlight if and where progress is made. Building on educational testing, we create a Bayesian leaderboard model where latent subject skill and latent item difficulty predict correct responses. Using this model, we analyze the ranking reliability of leaderboards. Afterwards, we show the model can guide what to annotate, identify annotation errors, detect overfitting, and identify informative examples. We conclude with recommendations for future benchmark tasks. ... 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/zre7-ng29 https://underline.io/lecture/26059-evaluation-examples-are-not-equally-informative-how-should-that-change-nlp-leaderboardsquestion BASE Hide details 3 Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Bartolo, Max; Jia, Robin. - : Underline Science Inc., 2021 BASE Show details 4 The statistical advantage of automatic NLG metrics at the system level ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Jia, Robin; Wei, Johnny. - : Underline Science Inc., 2021 BASE Show details 5 Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality ... Lee, Mina; Donahue, Chris; Jia, Robin. - : arXiv, 2021 BASE Show details 6 Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality ... NAACL 2021 2021; Donahue, Chris; Iyabor, Alexander. - : Underline Science Inc., 2021 BASE Show details 7 Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Dieuwke; Jia, Robin. - : Underline Science Inc., 2021 BASE Show details

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