25 citations · 76 across the 8 of their papers we have counts for
8 papers
MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
Tongliang Li, Zixiang Wang, Linzheng Chai +8
Cross-lingual open information extraction aims to extract structured information from raw text across multiple languages. Previous work uses a shared cross-lingual pre-trained mode…
MIT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning
Lei Li, Yuwei Yin, Shicheng Li +9
Instruction tuning has significantly advanced large language models (LLMs) such as ChatGPT, enabling them to align with human instructions across diverse tasks. However, progress i…
TTIDA: Controllable Generative Data Augmentation via Text-to-Text and Text-to-Image Models
Yuwei Yin, Jean Kaddour, Xiang Zhang +4
Data augmentation has been established as an efficacious approach to supplement useful information for low-resource datasets. Traditional augmentation techniques such as noise inje…
HanoiT: Enhancing Context-aware Translation via Selective Context
Jian Yang, Yuwei Yin, Shuming Ma +7
Context-aware neural machine translation aims to use the document-level context to improve translation quality. However, not all words in the context are helpful. The irrelevant or…
UM4: Unified Multilingual Multiple Teacher-Student Model for Zero-Resource Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +5
Most translation tasks among languages belong to the zero-resource translation problem where parallel corpora are unavailable. Multilingual neural machine translation (MNMT) enable…
HLT-MT: High-resource Language-specific Training for Multilingual Neural Machine Translation
Jian Yang, Yuwei Yin, Shuming Ma +3
Multilingual neural machine translation (MNMT) trained in multiple language pairs has attracted considerable attention due to fewer model parameters and lower training costs by sha…