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Found 6 papers, 3 papers with code
How Distributed are Distributed Representations? An Observation on the Locality of Syntactic Information in Verb Agreement Tasks
This work addresses the question of the localization of syntactic information encoded in the transformers representations.
Les représentations distribuées sont-elles vraiment distribuées ? Observations sur la localisation de l’information syntaxique dans les tâches d’accord du verbe en français (How Distributed are Distributed Representations ? An Observation on the Locality of Syntactic)
Ce travail aborde la question de la localisation de l’information syntaxique qui est encodée dans les représentations de transformers.
SLOG: A Structural Generalization Benchmark for Semantic Parsing
The goal of compositional generalization benchmarks is to evaluate how well models generalize to new complex linguistic expressions.
Assessing the Capacity of Transformer to Abstract Syntactic Representations: A Contrastive Analysis Based on Long-distance Agreement
The long-distance agreement, evidence for syntactic structure, is increasingly used to assess the syntactic generalization of Neural Language Models.
Are Transformers a Modern Version of ELIZA? Observations on French Object Verb Agreement
Many recent works have demonstrated that unsupervised sentence representations of neural networks encode syntactic information by observing that neural language models are able to predict the agreement between a verb and its subject.
Are Neural Networks Extracting Linguistic Properties or Memorizing Training Data? An Observation with a Multilingual Probe for Predicting Tense
We evaluate the ability of Bert embeddings to represent tense information, taking French and Chinese as a case study.
