4 citations · 12 across the 5 of their papers we have counts for
5 papers
MoDS: Model-oriented Data Selection for Instruction Tuning
Qianlong Du, Chengqing Zong, Jiajun Zhang
Instruction tuning has become the de facto method to equip large language models (LLMs) with the ability of following user instructions. Usually, hundreds of thousands or millions…
Life-long Learning for Multilingual Neural Machine Translation with Knowledge Distillation
Yang Zhao, Junnan Zhu, Lu Xiang +4
A common scenario of Multilingual Neural Machine Translation (MNMT) is that each translation task arrives in a sequential manner, and the training data of previous tasks is unavail…
Discrete Cross-Modal Alignment Enables Zero-Shot Speech Translation
Chen Wang, Yuchen Liu, Boxing Chen +4
End-to-end Speech Translation (ST) aims at translating the source language speech into target language text without generating the intermediate transcriptions. However, the trainin…
Other Roles Matter! Enhancing Role-Oriented Dialogue Summarization via Role Interactions
Haitao Lin, Junnan Zhu, Lu Xiang +3
Role-oriented dialogue summarization is to generate summaries for different roles in the dialogue, e.g., merchants and consumers. Existing methods handle this task by summarizing e…
Instance-aware Prompt Learning for Language Understanding and Generation
Feihu Jin, Jinliang Lu, Jiajun Zhang +1
Recently, prompt learning has become a new paradigm to utilize pre-trained language models (PLMs) and achieves promising results in downstream tasks with a negligible increase of p…