2 citations · 9 across the 9 of their papers we have counts for
9 papers
G2CP: A Graph-Grounded Communication Protocol for Verifiable and Efficient Multi-Agent Reasoning
Karim Ben Khaled, Davy Monticolo
Multi-agent systems powered by Large Language Models face a critical challenge: agents communicate through natural language, leading to semantic drift, hallucination propagation, a…
Using AI to Help in the Semantic Lexical Database to Evaluate Ideas
Pedro Chávez Barrios, Davy Monticolo, Sahbi Sidhom
Inside a challenge of ideas there are several phases in a Creative Support System (CSS), they are problem analysis, ideation, evaluation, and implementation. Our problem: we need a…
Do Similar Entities have Similar Embeddings?
Nicolas Hubert, Heiko Paulheim, Armelle Brun +1
Knowledge graph embedding models (KGEMs) developed for link prediction learn vector representations for entities in a knowledge graph, known as embeddings. A common tacit assumptio…
PyGraft: Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips
Nicolas Hubert, Pierre Monnin, Mathieu d'Aquin +2
Knowledge graphs (KGs) have emerged as a prominent data representation and management paradigm. Being usually underpinned by a schema (e.g., an ontology), KGs capture not only fact…
Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInE
Nicolas Hubert, Heiko Paulheim, Pierre Monnin +2
Knowledge graph embedding models (KGEMs) have gained considerable traction in recent years. These models learn a vector representation of knowledge graph entities and relations, a.…
Treat Different Negatives Differently: Enriching Loss Functions with Domain and Range Constraints for Link Prediction
Nicolas Hubert, Pierre Monnin, Armelle Brun +1
Knowledge graph embedding models (KGEMs) are used for various tasks related to knowledge graphs (KGs), including link prediction. They are trained with loss functions that consider…
Sem@: Is my knowledge graph embedding model semantic-aware?
Nicolas Hubert, Pierre Monnin, Armelle Brun +1
Using knowledge graph embedding models (KGEMs) is a popular approach for predicting links in knowledge graphs (KGs). Traditionally, the performance of KGEMs for link prediction is…
Use of Bayesian Network characteristics to link project management maturity and risk of project overcost
Felipe Sanchez, Davy Monticolo, Eric Bonjour +1
The project management field has the imperative to increase the project probability of success. Experts have developed several project management maturity models to assets and impr…
Results of multi-agent system and ontology to manage ideas and represent knowledge in a challenge of creativity
Pedro Barrios, Davy Monticolo, Sahbi Sidhom
This article is about an intelligent system to support ideas management as a result of a multi-agent system used in a distributed system with heterogeneous information as ideas and…