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cs.CL2026
ForMaT: Dataset for Visually-Grounded Multilingual PDF Translation
Michał Ciesiółka, Dawid Wiśniewski, Adrian Charkiewicz +1
We present ForMaT (Format-Preserving Multilingual Translation), a parallel corpus of 3,956 PDFs across 15 language pairs that preserves original layout metadata proposed for multim…
cs.CL2026
CompactQE: Interpretable Translation Quality Estimation via Small Open-Weight LLMs
Kamil Guttmann, Zofia Fraś, Artur Nowakowski +1
Current state-of-the-art Quality Estimation (QE) in machine translation relies on massive, proprietary LLMs, raising data privacy concerns. We demonstrate that smaller, open-source…