3 citations · 4 across the 13 of their papers we have counts for
5 papers · 2 filters
Boosting LLM Translation Skills without General Ability Loss via Rationale Distillation
Junhong Wu, Yang Zhao, Yangyifan Xu +2
Large Language Models (LLMs) have achieved impressive results across numerous NLP tasks but still encounter difficulties in machine translation. Traditional methods to improve tran…
Language Imbalance Driven Rewarding for Multilingual Self-improving
Wen Yang, Junhong Wu, Chen Wang +2
Large Language Models (LLMs) have achieved state-of-the-art performance across numerous tasks. However, these advancements have predominantly benefited "first-class" languages such…
Hit the Sweet Spot! Span-Level Ensemble for Large Language Models
Yangyifan Xu, Jianghao Chen, Junhong Wu +1
Ensembling various LLMs to unlock their complementary potential and leverage their individual strengths is highly valuable. Previous studies typically focus on two main paradigms:…
BLSP-Emo: Towards Empathetic Large Speech-Language Models
Chen Wang, Minpeng Liao, Zhongqiang Huang +3
The recent release of GPT-4o showcased the potential of end-to-end multimodal models, not just in terms of low latency but also in their ability to understand and generate expressi…
F-MALLOC: Feed-forward Memory Allocation for Continual Learning in Neural Machine Translation
Junhong Wu, Yuchen Liu, Chengqing Zong
In the evolving landscape of Neural Machine Translation (NMT), the pretrain-then-finetune paradigm has yielded impressive results. However, the persistent challenge of Catastrophic…