Papers with BARThez

2 papers
Effectiveness of French Language Models on Abstractive Dialogue Summarization Task (2022.lrec-1)

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Challenge: Pre-trained language models have established the state-of-the-art on various natural language processing tasks, including dialogue summarization.
Approach: They propose to use several language specific pre-trained models to summarize spontaneous oral dialogues in French using several language-specific pre-trainers: BARThez, BelGPT-2, mBARThes, and mT5.
Outcome: The proposed models outperform the existing models on the DECODA (Call Center) dialogue corpus and show that they are far superior to the current models.
BARThez: a Skilled Pretrained French Sequence-to-Sequence Model (2021.emnlp-main)

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Challenge: Inductive transfer learning has taken the entire NLU field by storm, with models such as BERT and BART setting new state-of-the-art on countless tasks.
Approach: They introduce a large-scale pretrained seq2seq model for French that is very competitive with state-of-the-art BERT-based French language models such as CamemBERT and FlauBERT.
Outcome: The proposed model outperforms existing models on discriminative and generative tasks on a French summarization dataset.

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