Why Predicting Post-Edition is so Hard? Failure Analysis of LIMSI Submission to the APE Shared Task

Collection of a Large Database of French-English SMT Output Corrections

Corpus-based approaches to machine translation (MT) rely on the availability of parallel corpora. To produce user-acceptable translation outputs, such systems need high quality data to be efficiency trained, optimized an…

Overview of MediaEval 2020 Predicting Media Memorability Task: What Makes a Video Memorable?

This paper describes the MediaEval 2020 \textit{Predicting Media Memorability} task. After first being proposed at MediaEval 2018, the Predicting Media Memorability task is in its 3rd edition this year, as the prediction…

Reading or Guessing? Visual Grounding Failures of Vision-Language Models for OCR in Ancient Greek Editions

Recent work has shown that Vision-Language Models (VLMs) used for optical character recognition (OCR) can generate plausible but visually unsupported text, suggesting reliance on language priors. Comparing open-weight VL…

Large-scale End-of-Life Prediction of Hard Disks in Distributed Datacenters

On a daily basis, data centers process huge volumes of data backed by the proliferation of inexpensive hard disks. Data stored in these disks serve a range of critical functional needs from financial, and healthcare to a…

Post-\'edition statistique pour l'adaptation aux domaines de sp\'ecialit\'e en traduction automatique (Statistical Post-Editing of Machine Translation for Domain Adaptation) [in French]