5 papers
Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
Zheng Wei Lim, Nitish Gupta, Honglin Yu +1
Multilingual large language models (LLMs) are great translators, but this is largely limited to high-resource languages. For many LLMs, translating in and out of low-resource langu…
Language-Specific Latent Process Hinders Cross-Lingual Performance
Zheng Wei Lim, Alham Fikri Aji, Trevor Cohn
Large language models (LLMs) are demonstrably capable of cross-lingual transfer, but can produce inconsistent output when prompted with the same queries written in different langua…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
David Romero, Chenyang Lyu, Haryo Akbarianto Wibowo +73
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge pres…
Simpson's Paradox and the Accuracy-Fluency Tradeoff in Translation
Zheng Wei Lim, Ekaterina Vylomova, Trevor Cohn +1
A good translation should be faithful to the source and should respect the norms of the target language. We address a theoretical puzzle about the relationship between these object…