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Hits 101 – 120 of 20.397

101
How Well Do LSTM Language Models Learn Filler-gap Dependencies?
In: Proceedings of the Society for Computation in Linguistics (2022)
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102
A split-gesture, competitive, coupled oscillator model of syllable structure predicts the emergence of edge gemination and degemination
In: Proceedings of the Society for Computation in Linguistics (2022)
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103
Linguistic Complexity and Planning Effects on Word Duration in Hindi Read Aloud Speech
In: Proceedings of the Society for Computation in Linguistics (2022)
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104
Learning Argument Structures with Recurrent Neural Network Grammars
In: Proceedings of the Society for Computation in Linguistics (2022)
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105
MaxEnt Learners are Biased Against Giving Probability to Harmonically Bounded Candidates
In: Proceedings of the Society for Computation in Linguistics (2022)
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106
Evaluating Structural Economy Claims in Relative Clause Attachment
In: Proceedings of the Society for Computation in Linguistics (2022)
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107
A Model Theoretic Perspective on Phonological Feature Systems
In: Proceedings of the Society for Computation in Linguistics (2022)
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108
Representing Multiple Dependencies in Prosodic Structures
In: Proceedings of the Society for Computation in Linguistics (2022)
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109
Incremental Acquisition of a Minimalist Grammar using an SMT-Solver
In: Proceedings of the Society for Computation in Linguistics (2022)
Abstract: We introduce a novel procedure that uses the Z3 SMT-solver, an interactive theorem prover, to incrementally infer a Minimalist Grammar (MG) from an input sequence of paired interface conditions, which corresponds to the primary linguistic data (PLD) a child is exposed to. The procedure outputs an MG lexicon, consisting of a set of (word, feature-sequence) pairings, that yields, for each entry in the PLD, a derivation that satisfies the listed interface conditions; the output MG lexicon corresponds to the Knowledge of Language that the child acquires from processing the PLD. We use the acquisition procedure to infer an MG lexicon from a PLD consisting of 39 simple sentences with at most one level of embedding. Notably, the inferred lexicon can generate a countably infinite set of derivations, including derivations with n-levels of embedding for any n>0, thereby generalizing beyond the input PLD. The acquisition procedure allows us to focus on specifying the learner’s initial state and conditions on the learner’s final state (imposed by the PLD), and leave to the solver questions of how the language-acquisition device goes from the initial state to the final state and what that final state is.
Keyword: Computational Linguistics; Derivation; Inference; Interface Conditions; Language Acquisition; Lexicon; MG; Minimalist Grammar; Minimalist Program; Minimalist Syntax; Modeling; Satisfiability Modulo Theories; SMT; SMT solver; Syntax; Z3
URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1248&context=scil
https://scholarworks.umass.edu/scil/vol5/iss1/20
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110
Concurrent hidden structure & grammar learning
In: Proceedings of the Society for Computation in Linguistics (2022)
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111
Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructions
In: Proceedings of the Society for Computation in Linguistics (2022)
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112
Universal Dependencies and Semantics for English and Hebrew Child-directed Speech
In: Proceedings of the Society for Computation in Linguistics (2022)
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113
Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives
In: Proceedings of the Society for Computation in Linguistics (2022)
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114
Learning Constraints on Wh-Dependencies by Learning How to Efficiently Represent Wh-Dependencies: A Developmental Modeling Investigation With Fragment Grammars
In: Proceedings of the Society for Computation in Linguistics (2022)
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115
Typological Implications of Tier-Based Strictly Local Movement
In: Proceedings of the Society for Computation in Linguistics (2022)
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116
Parsing Early Modern English for Linguistic Search
In: Proceedings of the Society for Computation in Linguistics (2022)
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117
When Classifying Arguments, BERT Doesn't Care About Word Order. Except When It Matters
In: Proceedings of the Society for Computation in Linguistics (2022)
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118
Remodelling complement coercion interpretation
In: Proceedings of the Society for Computation in Linguistics (2022)
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119
Inferring Inferences: Relational Propositions for Argument Mining
In: Proceedings of the Society for Computation in Linguistics (2022)
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120
ANLIzing the Adversarial Natural Language Inference Dataset
In: Proceedings of the Society for Computation in Linguistics (2022)
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