Papers by Laurent Charlin

2 papers
Optimizing User Profiles via Contextual Bandits for Retrieval-Augmented LLM Personalization (2026.acl-long)

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Challenge: Existing approaches for personalizing large language models require modifying parameters.
Approach: They propose a lightweight approach to personalizing large language models via retrieval augmentation . relevance serves as an unreliable proxy for utility, they argue .
Outcome: The proposed framework outperforms strong heuristic and retrieval-augmented baselines on nine personalization tasks.
Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles (2020.emnlp-main)

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Challenge: Multi-XScience is a dataset construction protocol that favours abstractive modeling approaches.
Approach: They propose a large-scale multi-document summarization dataset that is based on articles and lexical databases and WordNet synonymy information to generate related-work sections of a paper.
Outcome: The proposed method is based on lexical databases and WordNet synonymy information to write related work sections of a paper based upon their abstract and the articles they reference.

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