5 papers · 1 filter
Adaptive Mutual Distillation for Balanced Multi-Task Post-Training of Large Language Models
Baohang Li, Xiaocheng Feng, Yichong Huang +6
Multi-task post-training of large language models (LLMs) aims to improve performance across tasks with unequal amounts of training data. Existing methods focus primarily on balanci…
CRISP: Cultural Reward Modeling for Implicit Situated Propriety
Zekun Yuan, Yangfan Ye, Baohang Li +6
As large language models (LLMs) are increasingly deployed across countries and regions, the ability to recognize and respond appropriately to diverse cultural contexts becomes incr…
Culture-Aware Machine Translation in Large Language Models: Benchmarking and Investigation
Zekun Yuan, Yangfan Ye, Xiaocheng Feng +5
Large language models (LLMs) have achieved strong performance in general machine translation, yet their ability in culture-aware scenarios remains poorly understood. To bridge this…
x1: Learning to Think Adaptively Across Languages and Cultures
Yangfan Ye, Xiaocheng Feng, Xiachong Feng +8
Languages encode distinct abstractions and inductive priors, yet most large language models (LLMs) overlook this diversity by reasoning in a single dominant language. In this work,…
CC-Tuning: A Cross-Lingual Connection Mechanism for Improving Joint Multilingual Supervised Fine-Tuning
Yangfan Ye, Xiaocheng Feng, Zekun Yuan +11
Current large language models (LLMs) often exhibit imbalanced multilingual capabilities due to their English-centric training corpora. To address this, existing fine-tuning approac…