1 citations · 1 across the 5 of their papers we have counts for
6 papers
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…
Breaking the Curse of Multilinguality in Many-to-Many Speech-to-Text Translation via a Resource-Aware Mixture of Speech Encoders
Yexing Du, Kaiyuan Liu, Youcheng Pan +4
Multimodal large language models (MLLMs) have achieved significant success in speech-to-text translation (S2TT). However, when processing multilingual speech inputs, a single speec…
Enhancing Non-English Capabilities of English-Centric Large Language Models through Deep Supervision Fine-Tuning
Wenshuai Huo, Xiaocheng Feng, Yichong Huang +9
Large language models (LLMs) have demonstrated significant progress in multilingual language understanding and generation. However, due to the imbalance in training data, their cap…
Ensuring Consistency for In-Image Translation
Chengpeng Fu, Xiaocheng Feng, Yichong Huang +9
The in-image machine translation task involves translating text embedded within images, with the translated results presented in image format. While this task has numerous applicat…
Relay Decoding: Concatenating Large Language Models for Machine Translation
Chengpeng Fu, Xiaocheng Feng, Yichong Huang +5
Leveraging large language models for machine translation has demonstrated promising results. However, it does require the large language models to possess the capability of handlin…
Aligning Translation-Specific Understanding to General Understanding in Large Language Models
Yichong Huang, Baohang Li, Xiaocheng Feng +4
Large Language models (LLMs) have exhibited remarkable abilities in understanding complex texts, offering a promising path towards human-like translation performance. However, this…