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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. - : arXiv, 2020 BASE Show 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.; Chaudhary, Aditi; Celano, Giuseppe G. A.; Ponti, Edoardo M.; Vylomova, Ekaterina; Cotterell, Ryan; Augenstein, Isabelle. - : arXiv, 2020 Abstract: Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages. They have been shown to be useful for downstream applications, including cross-lingual transfer learning and linguistic probing. A major drawback hampering broader adoption of typological KBs is that they are sparsely populated, in the sense that most languages only have annotations for some features, and skewed, in that few features have wide coverage. As typological features often correlate with one another, it is possible to predict them and thus automatically populate typological KBs, which is also the focus of this shared task. Overall, the task attracted 8 submissions from 5 teams, out of which the most successful methods make use of such feature correlations. However, our error analysis reveals that even the strongest submitted systems struggle with predicting feature values for languages where few features are known. ... : SigTyp 2020 Shared Task Description Paper @ EMNLP 2020 ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2010.08246 https://dx.doi.org/10.48550/arxiv.2010.08246 BASE Hide 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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