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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 – 10 of 10 1 Formal Language Recognition by Hard Attention Transformers: Perspectives from Circuit Complexity ... Hao, Yiding; Angluin, Dana; Frank, Robert. - : arXiv, 2022 BASE Show details 2 An Adversarial Benchmark for Fake News Detection Models ... Flores, Lorenzo Jaime Yu; Hao, Yiding. - : arXiv, 2022 BASE Show details 3 Attribution Analysis of Grammatical Dependencies in LSTMs ... Hao, Yiding. - : arXiv, 2020 BASE Show details 4 Probabilistic Predictions of People Perusing: Evaluating Metrics of Language Model Performance for Psycholinguistic Modeling ... Hao, Yiding; Mendelsohn, Simon; Sterneck, Rachel; Martinez, Randi; Frank, Robert. - : arXiv, 2020 Abstract: By positing a relationship between naturalistic reading times and information-theoretic surprisal, surprisal theory (Hale, 2001; Levy, 2008) provides a natural interface between language models and psycholinguistic models. This paper re-evaluates a claim due to Goodkind and Bicknell (2018) that a language model's ability to model reading times is a linear function of its perplexity. By extending Goodkind and Bicknell's analysis to modern neural architectures, we show that the proposed relation does not always hold for Long Short-Term Memory networks, Transformers, and pre-trained models. We introduce an alternate measure of language modeling performance called predictability norm correlation based on Cloze probabilities measured from human subjects. Our new metric yields a more robust relationship between language model quality and psycholinguistic modeling performance that allows for comparison between models with different training configurations. ... : To appear in the proceedings of the Cognitive Modeling and Computational Linguistics workshop (CMCL) at EMNLP 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Neural and Evolutionary Computing cs.NE URL: https://dx.doi.org/10.48550/arxiv.2009.03954 https://arxiv.org/abs/2009.03954 BASE Hide details 5 Rhythmic Syncope in Subregular Phonology Bowers, Dustin; Hao, Yiding In: University of Pennsylvania Working Papers in Linguistics (2020) BASE Show details 6 Metrical Grids and Generalized Tier Projection Hao, Yiding In: Proceedings of the Society for Computation in Linguistics (2020) BASE Show details 7 Computing Vowel Harmony: The Generative Capacity of Search & Copy Andersson, Samuel; Dolatian, Hossep; Hao, Yiding In: Proceedings of the Annual Meetings on Phonology; Proceedings of the 2019 Annual Meeting on Phonology ; 2377-3324 (2020) BASE Show details 8 Action-Sensitive Phonological Dependencies ... Hao, Yiding; Bowers, Dustin. - : arXiv, 2019 BASE Show details 9 Finding Syntactic Representations in Neural Stacks ... Merrill, William; Khazan, Lenny; Amsel, Noah. - : arXiv, 2019 BASE Show details 10 Learnability and Overgeneration in Computational Syntax Hao, Yiding In: Proceedings of the Society for Computation in Linguistics (2019) BASE Show details

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