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Found 4 papers, 3 papers with code
Question Translation Training for Better Multilingual Reasoning
A typical solution is to translate instruction data into all languages of interest, and then train on the resulting multilingual data, which is called translate-training.
MAPO: Advancing Multilingual Reasoning through Multilingual Alignment-as-Preference Optimization
To enhance reasoning abilities in non-dominant languages, we propose a Multilingual-Alignment-as-Preference Optimization framework (MAPO), aiming to align the reasoning processes in other languages with the dominant language.
Exploring the Factual Consistency in Dialogue Comprehension of Large Language Models
For answering the factual questions, which is more challenging, the average error rate of all evaluated LLMs is 36. 1%.
CoP: Factual Inconsistency Detection by Controlling the Preference
To separate the preference for factual consistency, we propose an unsupervised framework named CoP by controlling the preference of the generation model with the help of prompt.
