Author

Timothee Mickus

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Preprint Aug 2026

Can Humans Dream of Electric Sheep? Human-Written Samples for Fine-Grained Vision-and-Language Hallucination Benchmarking

In an age of rapid model turnover, how do we make hallucination evaluation more perennial? We explore whether human-written hallucination samples could take the place of model-generated hallucinations, in order to make benchmarking detection independent of particular models. To this end, we construct a dataset of 1,600...

Timothee Mickus, Claudio Savelli, Eduardo Calò et al. · 3 citations

#machine learning Preprint Feb 2026

Is Knowledge Distillation Actually Greener? A Case Study in Machine Translation

This work evaluates representative KD methods both on bespoke MT models and LLMs, by considering both translation quality and computational cost, using the Machine Learning Life Cycle Assessment tool, which accounts for costs throughout the KD model life cycle.

Joseph Attieh, Timothee Mickus, Anne-Laure Ligozat et al. · 0 citations

#natural language process... Review Aug 2026

Overview of SHROOM-Visions 2026: A Shared Task on Hallucination Detection in Large Vision-Language Models

This time, the SHROOM-Visions task aims to tackle hallucinations through a model-agnostic detection task focused on large vision-language models, building on the recently introduced SHEEP dataset.

Raúl Vázquez, Aman Sinha, Chuyuan Li et al. · 0 citations