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cs.CL2026

LEDGER: A Long-Context Benchmark of Corporate Annual Reports for Grounded Financial Retrieval and Extraction

Charles Moslonka, Amaury de Vitry, Arthur Garnier +2

Finance reporting is a natural proving ground for large language models, and the very-long-context capabilities of recent models across all sizes make rigorous evaluation in this d…

cs.CL2026

EuroBERT: Scaling Multilingual Encoders for European Languages

Nicolas Boizard, Hippolyte Gisserot-Boukhlef, Duarte M. Alves +16

General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirectional encoder models. Despite their w…

cs.CL2026

Should We Still Pretrain Encoders with Masked Language Modeling?

Hippolyte Gisserot-Boukhlef, Nicolas Boizard, Manuel Faysse +5

Learning high-quality text representations is fundamental to a wide range of NLP tasks. While encoder pretraining has traditionally relied on Masked Language Modeling (MLM), recent…

cs.CL2026

BERT-as-a-Judge: A Robust Alternative to Lexical Methods for Efficient Reference-Based LLM Evaluation

Hippolyte Gisserot-Boukhlef, Nicolas Boizard, Emmanuel Malherbe +2

Accurate evaluation is central to the large language model (LLM) ecosystem, guiding model selection and downstream adoption across diverse use cases. In practice, however, evaluati…

cs.CL2024

Is Preference Alignment Always the Best Option to Enhance LLM-Based Translation? An Empirical Analysis

Hippolyte Gisserot-Boukhlef, Ricardo Rei, Emmanuel Malherbe +3

Neural metrics for machine translation (MT) evaluation have become increasingly prominent due to their superior correlation with human judgments compared to traditional lexical met…