2 citations · 4 across the 10 of their papers we have counts for
11 papers
Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?
Younes Boufouss, Luc Pommeret, Thomas Gerald +2
While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable structures. This paper explore…
LLM-based Atomic Propositions help weak extractors: Evaluation of a Propositioner for triplet extraction
Luc Pommeret, Thomas Gerald, Patrick Paroubek +3
Knowledge Graph construction from natural language requires extracting structured triplets from complex, information-dense sentences. In this paper, we investigate if the decomposi…
Evaluation of Clinical Trials Reporting Quality using Large Language Models
Mathieu Laï-king, Patrick Paroubek
Reporting quality is an important topic in clinical trial research articles, as it can impact clinical decisions. In this article, we test the ability of large language models to a…
Pre-training data selection for biomedical domain adaptation using journal impact metrics
Mathieu Laï-king, Patrick Paroubek
Domain adaptation is a widely used method in natural language processing (NLP) to improve the performance of a language model within a specific domain. This method is particularly…
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada +11
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However,…
Chitchat as Interference: Adding User Backstories to Task-Oriented Dialogues
Armand Stricker, Patrick Paroubek
During task-oriented dialogues (TODs), human users naturally introduce chitchat that is beyond the immediate scope of the task, interfering with the flow of the conversation. To ad…
A Unified Approach to Emotion Detection and Task-Oriented Dialogue Modeling
Armand Stricker, Patrick Paroubek
In current text-based task-oriented dialogue (TOD) systems, user emotion detection (ED) is often overlooked or is typically treated as a separate and independent task, requiring ad…
Searching for Snippets of Open-Domain Dialogue in Task-Oriented Dialogue Datasets
Armand Stricker, Patrick Paroubek
Most existing dialogue corpora and models have been designed to fit into 2 predominant categories : task-oriented dialogues portray functional goals, such as making a restaurant re…
Enhancing Task-Oriented Dialogues with Chitchat: a Comparative Study Based on Lexical Diversity and Divergence
Armand Stricker, Patrick Paroubek
As a recent development, task-oriented dialogues (TODs) have been enriched with chitchat in an effort to make dialogues more diverse and engaging. This enhancement is particularly…
Emotion Recognition based on Psychological Components in Guided Narratives for Emotion Regulation
Gustave Cortal, Alain Finkel, Patrick Paroubek +1
Emotion regulation is a crucial element in dealing with emotional events and has positive effects on mental health. This paper aims to provide a more comprehensive understanding of…
Natural Language Processing for Cognitive Analysis of Emotions
Gustave Cortal, Alain Finkel, Patrick Paroubek +1
Emotion analysis in texts suffers from two major limitations: annotated gold-standard corpora are mostly small and homogeneous, and emotion identification is often simplified as a…