2 citations · 8 across the 45 of their papers we have counts for
5 papers · 2 filters
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…
Ladders in Chaos: When, How, (and Perhaps Why) Does Test-Time Scaling Improve LLM Machine Translation
Di Wu, Sergey Troshin, Christof Monz +2
Two forms of test-time scaling for Large Language Models (LLMs) have emerged as effective and widely adopted paradigms: sequential, in which later answer attempts depend on earlier…
On the Limits of Model Merging for Multilinguality in Pre-Training
Seth Aycock, Fedor Vitiugin, Aleksandr Umnov +2
Endowing models with consistent multilingual performance can be achieved by mixing pre-training data, or post-training approaches such as language-specific model merging. In this w…
When Contextual Inference Fails: Cancelability in Interactive Instruction Following
Natalia Bila, Kata Naszádi, Alexandra Mayn +1
We investigate the separation of literal interpretation from contextual inference in a collaborative block-building tasks, where an agent must resolve underspecified instructions u…
Do Language Models Reason Across Languages?
Yan Meng, Wafaa Mohammed, Christof Monz
The real-world information sources are inherently multilingual, which naturally raises a question about whether language models can synthesize information across languages. In this…