Page: 1 2 3 4 5 6 7 8 9 10... 992
101 |
How Well Do LSTM Language Models Learn Filler-gap Dependencies?
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
103 |
Linguistic Complexity and Planning Effects on Word Duration in Hindi Read Aloud Speech
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
104 |
Learning Argument Structures with Recurrent Neural Network Grammars
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
105 |
MaxEnt Learners are Biased Against Giving Probability to Harmonically Bounded Candidates
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
106 |
Evaluating Structural Economy Claims in Relative Clause Attachment
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
107 |
A Model Theoretic Perspective on Phonological Feature Systems
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
108 |
Representing Multiple Dependencies in Prosodic Structures
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
109 |
Incremental Acquisition of a Minimalist Grammar using an SMT-Solver
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
110 |
Concurrent hidden structure & grammar learning
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
112 |
Universal Dependencies and Semantics for English and Hebrew Child-directed Speech
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
113 |
Learning Input Strictly Local Functions: Comparing Approaches with Catalan Adjectives
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
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)
|
|
Abstract:
It’s hotly contested how children learn constraints on wh-dependencies, called syntactic islands. When learning this knowledge, a prerequisite is knowing how to represent wh-dependencies so that constraints can be hypothesized over those representations. Previous work has explained disparate sets of syntactic island constraints by assuming different wh-dependency representations, without a unified dependency representation capturing all these constraints. We implement a modeled learner who learns a Fragment Grammar (FG) representation of wh-dependencies–a representation comprised of potentially different-sized fragments that combine to form full dependencies–that best accounts for the input while being as compact as possible. This efficient wh-dependency representation can then be used to generate any wh-dependency’s probability, and so predict acceptability patterns for stimuli sets that reveal syntactic island knowledge. We find that the identified FG can generate the attested acceptability judgment patterns for all syntactic islands previously investigated, highlighting how implicit knowledge of wh-dependency constraints can emerge from trying to learn to efficiently represent wh-dependencies more generally. We additionally compare the FG representation’s performance against baselines inspired by previous proposals, finding that one baseline also yields equivalent performance. We discuss how this baseline is similar to and different from the FG representation.
|
|
Keyword:
Computational Linguistics; developmental modeling; efficient representation; First and Second Language Acquisition; Fragment Grammar; syntactic islands; Syntax; wh-dependencies
|
|
URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1255&context=scil https://scholarworks.umass.edu/scil/vol5/iss1/22
|
|
BASE
|
|
Hide details
|
|
115 |
Typological Implications of Tier-Based Strictly Local Movement
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
116 |
Parsing Early Modern English for Linguistic Search
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
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)
|
|
BASE
|
|
Show details
|
|
118 |
Remodelling complement coercion interpretation
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
119 |
Inferring Inferences: Relational Propositions for Argument Mining
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
120 |
ANLIzing the Adversarial Natural Language Inference Dataset
|
|
|
|
In: Proceedings of the Society for Computation in Linguistics (2022)
|
|
BASE
|
|
Show details
|
|
Page: 1 2 3 4 5 6 7 8 9 10... 992
|
|