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Author

Thomas Gerald

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Open access 2026

Format Matters: A Critical Evaluation of Output Formats for Prompting LLMs in SLU and NER

It is shown that measured performance and reliability depend on the requested format (JSON, XML or inline Key-Values) and a lightweight selection procedure is proposed to determine the best format per model-dataset combination using only a small development slice; thus reducing trial-and-error in practice.

Pierre Lepagnol, Sahar Ghannay, Thomas Gerald et al. · 1 citation
Open access 2026

Can Multimodal LLMs Generate Pedagogical Questions?

This work investigates whether multimodal LLMs may generate pedagogical questions, and whether they can judge a question as pedagogical or not, in English and French and shows that while LLMs as a judge is an efficient framework, many problems could arise and that aligning prediction with human annotators is a difficul...

Thomas Gerald, Sahar Ghannay, Julie Lascar et al. · 0 citations
#artificial intelligence Open access Sep 2026

Can We Do Interpretable NLI with Graphs Based on Atomic Propositions?

This paper introduces a fully graph-based pipeline where the classifier never directly processes the input text, and reveals that graphs and text are complementary: combining both modalities achieves 92.1% accuracy on SNLI.

Younes Boufouss, Luc Pommeret, Thomas Gerald et al. · 0 citations

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