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Found 11 papers, 1 papers with code
That Looks Hard: Characterizing Linguistic Complexity in Humans and Language Models
We then show the effectiveness of linguistic features when explicitly leveraged by a regression model for predicting sentence complexity and compare its results with the ones obtained by a fine-tuned neural language model.
Sentence Complexity in Context
We study the influence of context on how humans evaluate the complexity of a sentence in English.
What Makes My Model Perplexed? A Linguistic Investigation on Neural Language Models Perplexity
This paper presents an investigation aimed at studying how the linguistic structure of a sentence affects the perplexity of two of the most popular Neural Language Models (NLMs), BERT and GPT-2.
SemEval-2022 Task 3: PreTENS-Evaluating Neural Networks on Presuppositional Semantic Knowledge
We report the results of the SemEval 2022 Task 3, PreTENS, on evaluation the acceptability of simple sentences containing constructions whose two arguments are presupposed to be or not to be in an ordered taxonomic relation.
Linguistic Profiling of a Neural Language Model
In this paper we investigate the linguistic knowledge learned by a Neural Language Model (NLM) before and after a fine-tuning process and how this knowledge affects its predictions during several classification problems.
Tracking the Evolution of Written Language Competence in L2 Spanish Learners
In this paper we present an NLP-based approach for tracking the evolution of written language competence in L2 Spanish learners using a wide range of linguistic features automatically extracted from students{'} written productions.
Profiling-UD: a Tool for Linguistic Profiling of Texts
In this paper, we introduce Profiling{--}UD, a new text analysis tool inspired to the principles of linguistic profiling that can support language variation research from different perspectives.
Is this Sentence Difficult? Do you Agree?
In this paper, we present a crowdsourcing-based approach to model the human perception of sentence complexity.
