1 citations · 2 across the 24 of their papers we have counts for
6 papers · 1 filter
Last Translation Benchmark
Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263
For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…
Asymmetric Within-Document Predictive Learning for Scientific Document Representation
You Zuo, Éric de la Clergerie, Benoît Sagot
We study predictive pretraining for scientific document representation using the discourse structure of papers. We propose SciJEPA, a citation-free framework that learns through as…
Sparse Coverage: Semantic Center Representations for Patent Prior-Art Retrieval
You Zuo, Kim Gerdes, Éric de la Clergerie +1
Patent prior-art retrieval is a recall-oriented search task over long and highly structured technical documents. Dense retrieval improves semantic matching, but single-vector repre…
Testing the Deliteralization Hypothesis in Human and Machine Translation
Malik Marmonier, Rachel Bawden, Benoît Sagot
The recent shift from dedicated NMT systems to general-purpose LLMs has reshaped machine translation, with LLMs reported to produce more fluent, less literal output than their pred…
Hindsight Quality Prediction Experiments in Multi-Candidate Human-Post-Edited Machine Translation
Malik Marmonier, Benoît Sagot, Rachel Bawden
This paper investigates two complementary paradigms for predicting machine translation (MT) quality: source-side difficulty prediction and candidate-side quality estimation (QE). T…
Translation Heads: Disentangling meaning from language in LLM-based machine translation
Théo Lasnier, Armel Zebaze, Djamé Seddah +2
Mechanistic Interpretability (MI) seeks to explain how neural networks implement their capabilities, but the scale of Large Language Models (LLMs) has limited prior MI work in Mach…