Page: 1 2 3 4 5 6 7 8 9 10... 1.020
| 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)
|
|
Abstract:
In targeted syntactic evaluations, the syntactic competence of LMs has been investigated through various syntactic phenomena, among which one of the important domains has been argument structure. Argument structures in head-initial languages have been exclusively tested in the previous literature, but may be readily predicted from lexical information of verbs, potentially overestimating the syntactic competence of LMs. In this paper, we explore whether argument structures can be learned by LMs in head-final languages, which could be more challenging given that argument structures must be predicted before encountering verbs during incremental sentence processing, so that the relative weight of syntactic information should be heavier than lexical information. Specifically, we examined double accusative constraint and double dative constraint in Japanese with the sequential and hierarchical LMs: n-gram model, LSTM, GPT-2, and RNNG. Our results demonstrated that the double accusative constraint is captured by all LMs, whereas the double dative constraint is successfully explained only by the hierarchical model. In addition, we probed incremental sentence processing by LMs through the lens of surprisal, and suggested that the hierarchical model may capture deep semantic roles that verbs assign to arguments, while the sequential models seem to be influenced by surface case alignments.
|
|
Keyword:
acceptability; argument structure; Computational Linguistics; grammaticality; Japanese; language model; probability; structure
|
|
URL: https://scholarworks.umass.edu/cgi/viewcontent.cgi?article=1258&context=scil
https://scholarworks.umass.edu/scil/vol5/iss1/9
|
|
BASE
|
|
Hide 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)
|
|
BASE
|
|
Show 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... 1.020 |
|
