Papers by Gaël Guibon

5 papers
QUARTZ: QA-based Unsupervised Abstractive Refinement for Task-oriented Dialogue Summarization (2025.findings-emnlp)

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Challenge: a framework for task-oriented utility-based dialogue summarization is proposed . QUARTZ is a tool for task summarizing dialogues, but its outputs lack task-specific focus.
Approach: They propose a framework for task-oriented utility-based dialogue summarization . QUARTZ generates summaries and question-answer pairs from a dialogue in a zero-shot manner .
Outcome: The proposed framework achieves competitive results in zero-shot settings, rivaling fully-supervised State-of-the-Art methods.
Few-Shot Emotion Recognition in Conversation with Sequential Prototypical Networks (2021.emnlp-main)

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Challenge: Existing studies on dyadic human-human interactions focus on conversations without specific business objectives.
Approach: They propose a method to detect emotions in a live chat customer service . they propose 'ProtoSeq' for conversational emotion classification using different languages .
Outcome: The proposed method is competitive even when applied to other ones.
OFrLex: A Computational Morphological and Syntactic Lexicon for Old French (2020.lrec-1)

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Challenge: Using heterogeneous language resources, we extract structured and exploitable information from a large-coverage morphological and syntactic Old French lexicon.
Approach: They propose to use a large-coverage morphological and syntactic Old French lexicon to extract structured and exploitable information from heterogeneous language resources.
Outcome: The proposed extension technique will be validated manually in the near future and take advantage of OFrLex’s viewing, searching and editing interface.
EZCAT: an Easy Conversation Annotation Tool (2022.lrec-1)

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Challenge: EZCAT is an annotation tool for textual conversations, but it is not customizable.
Approach: They propose an easy-to-use interface to annotate conversations in a configurable schema . they use it to annnotate private chats and chats, and they use the schema to test it .
Outcome: The proposed interface allows users to control data and annotate conversations in two levels . it eliminates the need for a server and accounts management, and allows users access to data .
When Collaborative Treebank Curation Meets Graph Grammars (2020.lrec-1)

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Challenge: Arborator-Grew is a collaborative annotation tool for treebank development.
Approach: They present a collaborative annotation tool for treebank development that combines the features of Arborator and Grew.
Outcome: The proposed tool is a complete redevelopment and modernization of Arborator, replacing its internal database storage by a new Grew API.

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