OpenSubtitles2024, a massively parallel dataset compiled from translated subtitles, includes an extensive collection of aligned training data based on user-contributed subtitles derived from OpenSubtitles.org and a dedicated held-out dataset for development and evaluation of machine translation and multilingual languag...
Jörg Tiedemann, Hengyu Luo· International Conference on...· 2 citations
It is found that human-written samples result in higher agreement and allow greater control of dataset contents, while remaining distributionally similar to samples derived from vision-and-language samples and providing a reasonable portrayal of detection capabilities - suggesting that human data is a viable substitute...
Timothee Mickus, Claudio Savelli, Eduardo Calò et al.· 4 citations
This work shows that specialist optimization implicitly selects from this latent trajectory space, and establishes a new view of specialist training: when gold reasoning is absent, tuning choices directly control the latent supervision passed to downstream models.
Yi-Le Tu, Zi-Hao Li, Shao-Xiong Ji et al.· 0 citations
This work introduces MultiSynt/MT, an open synthetic parallel corpus with approximately 4.8 trillion target-language tokens across 36 languages, produced by translating 100 billion high-quality Nemotron-CC tokens with Tower+ and OPUS-MT/HPLT-MT systems, and releases the corpus to support controlled research on multilin...
Maximilian Idahl, Jörg Tiedemann, S. Pyysalo et al.· arXiv.org· 0 citations
The Last Translation Benchmark is introduced, a collection of human-authored and peer-reviewed examples that break leading machine translation models and a new evaluation approach: each example comes with handcrafted verification rules describing concrete failure cases on that example, therefore allowing reliable and a...
Vilém Zouhar, Niyati Bafna, Mukund Choudhary et al.· 0 citations
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
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