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Found 15 papers, 4 papers with code
CEPOC: The Cambridge Exams Publishing Open Cloze dataset
Open cloze tests are a standard type of exercise where examinees must complete a text by filling in the gaps without any given options to choose from.
Language Variety Identification with True Labels
Research has shown that this is a problematic assumption, particularly in the case of very similar languages (e. g., Croatian and Serbian) and national language varieties (e. g., Brazilian and European Portuguese), where texts may contain no distinctive marker of the particular language or variety.
Constructing Open Cloze Tests Using Generation and Discrimination Capabilities of Transformers
This paper presents the first multi-objective transformer model for constructing open cloze tests that exploits generation and discrimination capabilities to improve performance.
A Crash Course in Automatic Grammatical Error Correction
Grammatical Error Correction (GEC) is the task of automatically detecting and correcting all types of errors in written text.
Entropy as a Proxy for Gap Complexity in Open Cloze Tests
To the best of our knowledge, this is the first unsupervised information-theoretical approach to evaluating the quality of cloze tests.
The BEA-2019 Shared Task on Grammatical Error Correction
This paper reports on the BEA-2019 Shared Task on Grammatical Error Correction (GEC).
Artificial Error Generation with Machine Translation and Syntactic Patterns
Shortage of available training data is holding back progress in the area of automated error detection.
Ranked #3 on
Grammatical Error Detection
on FCE
Automatic Annotation and Evaluation of Error Types for Grammatical Error Correction
Until now, error type performance for Grammatical Error Correction (GEC) systems could only be measured in terms of recall because system output is not annotated.
Automatic Extraction of Learner Errors in ESL Sentences Using Linguistically Enhanced Alignments
We propose a new method of automatically extracting learner errors from parallel English as a Second Language (ESL) sentences in an effort to regularise annotation formats and reduce inconsistencies.
