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2 papers
Proofread: Fixes All Errors with One Tap (2024.acl-demos)

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Challenge: Extensive experiments on a human-labeled golden set showed our tuned PaLM2-XS model achieved 85.56% good ratio.
Approach: They propose a two-stage tuning approach to acquire the dedicated Large Language Model for the feature, followed by a reinforcement learning approach for targeted refinement.
Outcome: The proposed model achieves 85.56% good quality on Rewrite and proofread tasks on human-labeled golden sets.
An Automatic Learning of an Algerian Dialect Lexicon by using Multilingual Word Embeddings (L18-1)

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Challenge: a study on the Algerian Arabic dialect aims to build a lexicon of words written in Arabic or Latin script . multilinguality of the corpus is due to the fact that people use several languages to post comments . stretched letters, misspelled words, emoticons, condensed writing are among the problems .
Approach: They propose to build automatically from a social network an Algerian dialect lexicon.
Outcome: The proposed method leads to a score of 73% on a test lexicon . the study is based on analyzing a lexical corpus of an Algerian dialect .

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