Papers by Rémy Portelas

    1 papers
    Recursive Training Loops in LLMs: How training data properties modulate distribution shift in generated data? (2025.emnlp-main)

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    Challenge: Large language models (LLMs) are increasingly used in the creation of online content, creating feedback loops as future generations of models will be trained on this synthetic data.
    Approach: They propose to use large language models to create feedback loops as future models are trained on this data.
    Outcome: The proposed model collapse effects are found to be detrimental to the results of recursive training on human datasets.

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