1 citations · 1 across the 5 of their papers we have counts for
8 papers
Knowledge-Graph Based Augmentation versus Retrieval Augmented Generation for Cultural-Related Question Answering
Pablo Poulenard, Yannis Karmim, Valentin Barrière
Large language models (LLMs) suffer from a long-tail deficit: culturally specific facts, particularly those concerning underrepresented regions such as Latin America, appear too ra…
Multi-Hop Knowledge Composition is Bound by Pretraining Exposure
Yannis Karmim, Luis Marti, Djamé Seddah +1
Large Language Models fail at implicit multi-hop reasoning: a model answers "When was born?" and "Who is 's closest friend?" correctly but fails on "When was 's closest f…
Leveraging Wikidata for Geographically Informed Sociocultural Bias Dataset Creation: Application to Latin America
Yannis Karmim, Renato Pino, Hernan Contreras +6
Large Language Models (LLMs) exhibit inequalities with respect to various cultural contexts. Most prominent open-weights models are trained on Global North data and show prejudicia…
Building Specialized Software-Assistant ChatBot with Graph-Based Retrieval-Augmented Generation
Mohammed Hilel, Yannis Karmim, Jean De Bodinat +2
Digital Adoption Platforms (DAPs) have become essential tools for helping employees navigate complex enterprise software such as CRM, ERP, or HRMS systems. Companies like LemonLear…
ViLU: Learning Vision-Language Uncertainties for Failure Prediction
Marc Lafon, Yannis Karmim, Julio Silva-Rodríguez +6
Reliable Uncertainty Quantification (UQ) and failure prediction remain open challenges for Vision-Language Models (VLMs). We introduce ViLU, a new Vision-Language Uncertainty quant…
Supra-Laplacian Encoding for Transformer on Dynamic Graphs
Yannis Karmim, Marc Lafon, Raphael Fournier S'niehotta +1
Fully connected Graph Transformers (GT) have rapidly become prominent in the static graph community as an alternative to Message-Passing models, which suffer from a lack of express…
Temporal receptive field in dynamic graph learning: A comprehensive analysis
Yannis Karmim, Leshanshui Yang, Raphaël Fournier S'Niehotta +3
Dynamic link prediction is a critical task in the analysis of evolving networks, with applications ranging from recommender systems to economic exchanges. However, the concept of t…
ITEM: Improving Training and Evaluation of Message-Passing based GNNs for top-k recommendation
Yannis Karmim, Elias Ramzi, Raphaël Fournier-S'niehotta +1
Graph Neural Networks (GNNs), especially message-passing-based models, have become prominent in top-k recommendation tasks, outperforming matrix factorization models due to their a…