6 papers · 1 filter
XL-Suite: Cross-Lingual Synthetic Training and Evaluation Data for Open-Ended Generation
Vivek Iyer, Pinzhen Chen, Ricardo Rei +1
Cross-lingual open-ended generation - responding in a language different from that of the query - is an important yet understudied problem. This work proposes XL-Instruct, a novel…
Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning
Wenhao Zhu, Pinzhen Chen, Hanxu Hu +4
Long-context modelling for large language models (LLMs) has been a key area of recent research because many real world use cases require reasoning over longer inputs such as docume…
The Power of Question Translation Training in Multilingual Reasoning: Broadened Scope and Deepened Insights
Wenhao Zhu, Shujian Huang, Fei Yuan +3
Bridging the significant gap between large language model's English and non-English performance presents a great challenge. While some previous studies attempt to mitigate this gap…
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation
Vivek Iyer, Bhavitvya Malik, Pavel Stepachev +3
Despite the recent popularity of Large Language Models (LLMs) in Machine Translation (MT), their performance in low-resource languages (LRLs) still lags significantly behind Neural…
Cultural Adaptation of Menus: A Fine-Grained Approach
Zhonghe Zhang, Xiaoyu He, Vivek Iyer +1
Machine Translation of Culture-Specific Items (CSIs) poses significant challenges. Recent work on CSI translation has shown some success using Large Language Models (LLMs) to adapt…
Question Translation Training for Better Multilingual Reasoning
Wenhao Zhu, Shujian Huang, Fei Yuan +3
Large language models show compelling performance on reasoning tasks but they tend to perform much worse in languages other than English. This is unsurprising given that their trai…