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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...
This work formalizes multi-model human evaluation as a best-arm identification problem in a multi-armed bandit setup with correlated arms, where pulling an arm corresponds to human-evaluating a model, and proves the optimality of the proposed algorithms and shows that it improves discrimination between top-performing m...
The empirical results indicate that the reported gains depend heavily on the experiment setup and the choice of random seed, although the trend of stable gains is confirmed with 128-Dyck pretraining of small models with the Llama tokenizer for most of the examined languages.
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