Papers by Matteo Manica

2 papers
Zero-Shot-BERT-Adapters: a Zero-Shot Pipeline for Unknown Intent Detection (2023.findings-emnlp)

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Challenge: Intent discovery remains a crucial task in natural language processing . identifying novel, unseen intents remains one of the biggest challenges in this field .
Approach: They propose a multi-language approach to intent discovery using Adapters and a Transformer architecture.
Outcome: The proposed pipeline outperforms baselines in two zero-shot settings for intent classification and unseen intent discovery.
Hierarchical Pre-training for Sequence Labelling in Spoken Dialog (2020.findings-emnlp)

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Challenge: Sequence labelling tasks like Dialog Act and Emotion/Sentiment identification are a key component of spoken dialog systems.
Approach: They propose a new approach to learn generic representations adapted to spoken dialog using a hierarchical encoder based on transformer architectures.
Outcome: The proposed model is model-agnostic and contains 10 datasets of various sizes.

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