Papers by Tatiana Passali

2 papers
LARD: Large-scale Artificial Disfluency Generation (2022.lrec-1)

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Challenge: Existing datasets suffer from class imbalance issues, causing performance problems . Disfluency detection is a critical task in real-time dialogue systems .
Approach: They propose a method for generating complex and realistic artificial disfluencies with little effort using a large-scale dataset.
Outcome: The proposed method can handle repetitions, replacements, and restarts on a large-scale dataset with disfluencies.
Topic-Controllable Summarization: Topic-Aware Evaluation and Transformer Methods (2024.lrec-main)

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Challenge: Existing methods for topic-controllable summarization are limited by their recurrent architectures and require modifications to the model's architecture for controlling the topic.
Approach: They propose a new topic-oriented evaluation measure to automatically evaluate the generated summaries based on the topic affinity between the generated summary and the desired topic.
Outcome: The proposed method achieves better performance compared to more complicated embedding-based approaches while also being significantly faster.

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