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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 3 Hits 1 – 20 of 50 1 Probing for the Usage of Grammatical Number ... Lasri, Karim; Pimentel, Tiago; Lenci, Alessandro. - : arXiv, 2022 BASE Show details 2 Estimating the Entropy of Linguistic Distributions ... Arora, Aryaman; Meister, Clara; Cotterell, Ryan. - : arXiv, 2022 BASE Show details 3 A Latent-Variable Model for Intrinsic Probing ... Stańczak, Karolina; Hennigen, Lucas Torroba; Williams, Adina. - : arXiv, 2022 BASE Show details 4 On Homophony and Rényi Entropy ... Pimentel, Tiago; Meister, Clara; Teufel, Simone. - : arXiv, 2021 BASE Show details 5 Towards Zero-shot Language Modeling ... Ponti, Edoardo Maria; Vulić, Ivan; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 6 Differentiable Generative Phonology ... Wu, Shijie; Ponti, Edoardo Maria; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 7 Finding Concept-specific Biases in Form--Meaning Associations ... Pimentel, Tiago; Roark, Brian; Wichmann, Søren. - : arXiv, 2021 BASE Show details 8 Quantifying Gender Bias Towards Politicians in Cross-Lingual Language Models ... Stańczak, Karolina; Choudhury, Sagnik Ray; Pimentel, Tiago. - : arXiv, 2021 BASE Show details 9 Probing as Quantifying Inductive Bias ... Immer, Alexander; Hennigen, Lucas Torroba; Fortuin, Vincent. - : arXiv, 2021 BASE Show details 10 Revisiting the Uniform Information Density Hypothesis ... Meister, Clara; Pimentel, Tiago; Haller, Patrick. - : arXiv, 2021 BASE Show details 11 How (Non-)Optimal is the Lexicon? ... Pimentel, Tiago; Nikkarinen, Irene; Mahowald, Kyle. - : arXiv, 2021 BASE Show details 12 Disambiguatory Signals are Stronger in Word-initial Positions ... Pimentel, Tiago; Cotterell, Ryan; Roark, Brian. - : arXiv, 2021 BASE Show details 13 A Cognitive Regularizer for Language Modeling ... Wei, Jason; Meister, Clara; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 14 Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ... Maudslay, Rowan Hall; Cotterell, Ryan. - : arXiv, 2021 BASE Show details 15 On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ... Williams, Adina; Cotterell, Ryan; Wolf-Sonkin, Lawrence. - : arXiv, 2020 BASE Show details 16 Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ... Leung, Jun Yen; Emerson, Guy; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 17 SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ... Vylomova, Ekaterina; White, Jennifer; Salesky, Elizabeth; Mielke, Sabrina J.; Wu, Shijie; Ponti, Edoardo; Maudslay, Rowan Hall; Zmigrod, Ran; Valvoda, Josef; Toldova, Svetlana; Tyers, Francis; Klyachko, Elena; Yegorov, Ilya; Krizhanovsky, Natalia; Czarnowska, Paula; Nikkarinen, Irene; Krizhanovsky, Andrew; Pimentel, Tiago; Hennigen, Lucas Torroba; Kirov, Christo; Nicolai, Garrett; Williams, Adina; Anastasopoulos, Antonios; Cruz, Hilaria; Chodroff, Eleanor; Cotterell, Ryan; Silfverberg, Miikka; Hulden, Mans. - : arXiv, 2020 Abstract: A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from just one language such as English. The SIGMORPHON 2020 shared task on morphological reinflection aims to investigate systems' ability to generalize across typologically distinct languages, many of which are low resource. Systems were developed using data from 45 languages and just 5 language families, fine-tuned with data from an additional 45 languages and 10 language families (13 in total), and evaluated on all 90 languages. A total of 22 systems (19 neural) from 10 teams were submitted to the task. All four winning systems were neural (two monolingual transformers and two massively multilingual RNN-based models with gated attention). Most teams demonstrate utility of data hallucination and augmentation, ensembles, and multilingual training for low-resource languages. Non-neural learners and manually designed grammars showed ... : 39 pages, SIGMORPHON ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.2006.11572 https://arxiv.org/abs/2006.11572 BASE Hide details 18 Intrinsic Probing through Dimension Selection ... Hennigen, Lucas Torroba; Williams, Adina; Cotterell, Ryan. - : arXiv, 2020 BASE Show details 19 SIGTYP 2020 Shared Task: Prediction of Typological Features ... Bjerva, Johannes; Salesky, Elizabeth; Mielke, Sabrina J.. - : arXiv, 2020 BASE Show details 20 Information-Theoretic Probing for Linguistic Structure ... Pimentel, Tiago; Valvoda, Josef; Maudslay, Rowan Hall. - : arXiv, 2020 BASE Show details Page: 1 2 3

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