Victor Guimarães
2024
Reliable LLM-based User Simulator for Task-Oriented Dialogue Systems
Ivan Sekulic
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Silvia Terragni
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Victor Guimarães
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Nghia Khau
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Bruna Guedes
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Modestas Filipavicius
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Andre Ferreira Manso
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Roland Mathis
Proceedings of the 1st Workshop on Simulating Conversational Intelligence in Chat (SCI-CHAT 2024)
In the realm of dialogue systems, user simulation techniques have emerged as a game-changer, redefining the evaluation and enhancement of task-oriented dialogue (TOD) systems. These methods are crucial for replicating real user interactions, enabling applications like synthetic data augmentation, error detection, and robust evaluation. However, existing approaches often rely on rigid rule-based methods or on annotated data. This paper introduces DAUS, a Domain-Aware User Simulator. Leveraging large language models, we fine-tune DAUS on real examples of task-oriented dialogues. Results on two relevant benchmarks showcase significant improvements in terms of user goal fulfillment. Notably, we have observed that fine-tuning enhances the simulator’s coherence with user goals, effectively mitigating hallucinations—a major source of inconsistencies in simulator responses.
2015
Boosting Named Entity Recognition with Neural Character Embeddings
Cícero dos Santos
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Victor Guimarães
Proceedings of the Fifth Named Entity Workshop
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Co-authors
- Cicero dos Santos 1
- Ivan Sekulić 1
- Silvia Terragni 1
- Nghia Khau 1
- Bruna Guedes 1
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