Papers by Nicolas Le Roux

1 papers
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models (2025.emnlp-main)

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Challenge: Large language models (LLMs) can be used to solve new tasks by inducing high-level strategies from example solutions to similar problems and adapting these strategies to solve unseen problems.
Approach: They propose a foundation-model-based Latent Semantic Analysis method that iteratively clusters and tags document segments based on document-level contexts.
Outcome: The proposed method is more informative in reconstructing the original texts than existing tagging methods.

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