Papers by Camille Guinaudeau
Bazinga! A Dataset for Multi-Party Dialogues Structuring (2022.lrec-1)
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Paul Lerner, Juliette Bergoënd, Camille Guinaudeau, Hervé Bredin, Benjamin Maurice, Sharleyne Lefevre, Martin Bouteiller, Aman Berhe, Léo Galmant, Ruiqing Yin, Claude Barras
| Challenge: | a dataset of 16 TV and movie series is filled with challenging multi-party dialogues. |
| Approach: | They propose a dataset built around 16 TV and movie series with challenging multi-party dialogues. |
| Outcome: | The proposed dataset is a step towards better multi-party dialogue structuring and understanding. |
Mitigating the Impact of Reference Quality on Evaluation of Summarization Systems with Reference-Free Metrics (2024.emnlp-main)
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| Challenge: | Existing metrics for summarization are reference-based and correlate poorly with relevance . fluency, faithfulness, coherence and relevance are all measures of human evaluation . |
| Approach: | They propose a reference-free metric that correlates well with human evaluated relevance . n-gram importance weighting is used to weight a summary's importance . |
| Outcome: | The proposed metric can be used along reference-based metrics to improve their robustness in low quality reference settings. |