3 citations · 3 across the 4 of their papers we have counts for
6 papers · 1 filter
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs
Zixuan Ren, Jinliang Lu, Junhong Wu +5
Model merging plays a crucial role in consolidating multiple specialized models into a single, unified model, especially in the era of large language models (LLMs). Recent research…
A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities
Lu Xiang, Yang Zhao, Yaping Zhang +1
Large Language Models (LLMs) have demonstrated their transformative potential across numerous disciplinary studies, reshaping the existing research methodologies and fostering inte…
Improving MLLM's Document Image Machine Translation via Synchronously Self-reviewing Its OCR Proficiency
Yupu Liang, Yaping Zhang, Zhiyang Zhang +5
Multimodal Large Language Models (MLLMs) have shown strong performance in document image tasks, especially Optical Character Recognition (OCR). However, they struggle with Document…
Single-to-mix Modality Alignment with Multimodal Large Language Model for Document Image Machine Translation
Yupu Liang, Yaping Zhang, Zhiyang Zhang +4
Document Image Machine Translation (DIMT) aims to translate text within document images, facing generalization challenges due to limited training data and the complex interplay bet…
SimulPL: Aligning Human Preferences in Simultaneous Machine Translation
Donglei Yu, Yang Zhao, Jie Zhu +3
Simultaneous Machine Translation (SiMT) generates translations while receiving streaming source inputs. This requires the SiMT model to learn a read/write policy, deciding when to…
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…