3 papers
cs.CL2026
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…
cs.CL2025
Leveraging Information Retrieval to Enhance Spoken Language Understanding Prompts in Few-Shot Learning
Pierre Lepagnol, Sahar Ghannay, Thomas Gerald +2
Understanding user queries is fundamental in many applications, such as home assistants, booking systems, or recommendations. Accordingly, it is crucial to develop accurate Spoken…
cs.AI2024
Small Language Models are Good Too: An Empirical Study of Zero-Shot Classification
Pierre Lepagnol, Thomas Gerald, Sahar Ghannay +2
This study is part of the debate on the efficiency of large versus small language models for text classification by prompting.We assess the performance of small language models in…