Papers by Georgios Spithourakis
EVI: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification (2022.findings-naacl)
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| Challenge: | Knowledge-based authentication is crucial for task-oriented spoken dialogue systems that offer personalised and privacy-focused services . e-learning systems should be able to enrol, identify, and verify new and recurring users based on their personal information . |
| Approach: | They propose to formalise three authentication tasks and their evaluation protocols . they propose to use a spoken multilingual dataset with 5,506 spoken dialogues . |
| Outcome: | The proposed models set the first competitive benchmarks and set directions for future research. |
Multi-Label Intent Detection via Contrastive Task Specialization of Sentence Encoders (2022.emnlp-main)
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Ivan Vulić, Iñigo Casanueva, Georgios Spithourakis, Avishek Mondal, Tsung-Hsien Wen, Paweł Budzianowski
| Challenge: | a novel framework for task-oriented dialog ToD systems is proposed . a task of recognizing the user's intent or goal from their utterance is a crucial component of any TOD system. |
| Approach: | They propose to transform general-purpose sentences into task-specialized SEs by contrastive fine-tuning on annotated multi-label data. |
| Outcome: | The proposed framework yields effective mID models with large gains over non-specialized models across a spectrum of different m ID datasets. |
Training Neural Response Selection for Task-Oriented Dialogue Systems (P19-1)
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Matthew Henderson, Ivan Vulić, Daniela Gerz, Iñigo Casanueva, Paweł Budzianowski, Sam Coope, Georgios Spithourakis, Tsung-Hsien Wen, Nikola Mrkšić, Pei-Hao Su
| Challenge: | Despite their popularity, retrieval-based models have had modest impact on task-oriented dialogue systems . main obstacle to their application is the low-data regime of most task-orientated dialogue tasks . e-commerce, banking, and other domains are applications of retrieval models . |
| Approach: | They propose a method which pretrains a retrieval-based model on large general-domain conversational corpora and fine-tunes it for the target dialogue domain. |
| Outcome: | The proposed method is evaluated on five diverse domains, ranging from e-commerce to banking. |
Numeracy for Language Models: Evaluating and Improving their Ability to Predict Numbers (P18-1)
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| Challenge: | Numeracy is the ability to understand and work with numbers. |
| Approach: | They propose a neural architecture that uses a continuous probability density function to model numerals from an open vocabulary using hierarchical models. |
| Outcome: | The proposed model reduces errors by 18% and 54% on clinical and scientific datasets compared to the second best model for each dataset . |
PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking (D19-3)
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Matthew Henderson, Ivan Vulić, Iñigo Casanueva, Paweł Budzianowski, Daniela Gerz, Sam Coope, Georgios Spithourakis, Tsung-Hsien Wen, Nikola Mrkšić, Pei-Hao Su
| Challenge: | a task-oriented dialogue system is based on task-specific ontologies that constrain slots to specific values . we present a conversational search engine that can be used to search for restaurant reservations . |
| Approach: | They propose a conversational search engine that supports task-oriented dialogue . the polyresponse engine is trained on hundreds of millions of examples extracted from real conversations . |
| Outcome: | The proposed system is available in 8 different languages. |
NLU++: A Multi-Label, Slot-Rich, Generalisable Dataset for Natural Language Understanding in Task-Oriented Dialogue (2022.findings-naacl)
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| Challenge: | NLU++ provides a more challenging evaluation environment for dialogue NLU models . Typical ToD systems still rely on a modular design . |
| Approach: | They propose to use NLU++ to provide a more challenging evaluation environment for dialogue NLU models. |
| Outcome: | The proposed dataset improves existing datasets and provides a much more challenging evaluation environment for dialogue NLU models. |