Fran{\c{c}}ois Yvon — accepted AI-conference papers

2025

An Interdisciplinary Approach to Human-Centered Machine Translation

Marine Carpuat, Omri Asscher, Kalika Bali, Luisa Bentivogli, Fr{\'e}d{\'e}ric Blain, Lynne Bowker +14

EMNLP 2025

Machine Translation (MT) tools are widely used today, often in contexts where professional translators are not present. Despite progress in MT technology, a gap persists between system development and real-world usage, particularly for non-expert users who may struggle to assess translation reliabil

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2025

How Sampling Affects the Detectability of Machine-written texts: A Comprehensive Study

Matthieu Dubois, Fran{\c{c}}ois Yvon, Pablo Piantanida

EMNLP 2025

As texts generated by Large Language Models (LLMs) are ever more common and often indistinguishable from human-written content, research on automatic text detection has attracted growing attention. Many recent detectors report near-perfect accuracy, often boasting AUROC scores above 99%. However, th

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2025

On Relation-Specific Neurons in Large Language Models

Yihong Liu, Runsheng Chen, Lea Hirlimann, Ahmad Dawar Hakimi, Mingyang Wang, Amir Hossein Kargaran +3

EMNLP 2025

In large language models (LLMs), certain neurons can store distinct pieces of knowledge learned during pretraining. While factual knowledge typically appears as a combination of relations and entities, it remains unclear whether some neurons focus on a relation itself – independent of any entity. We

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