Advances and challenges in meta-learning: A technical review

A Vettoruzzo, MR Bouguelia… - IEEE transactions on …, 2024 - ieeexplore.ieee.org
Meta-learning empowers learning systems with the ability to acquire knowledge from
multiple tasks, enabling faster adaptation and generalization to new tasks. This review …

Recent advances in deep learning based dialogue systems: A systematic survey

J Ni, T Young, V Pandelea, F Xue… - Artificial intelligence review, 2023 - Springer
Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …

Recent advances and challenges in task-oriented dialog systems

Z Zhang, R Takanobu, Q Zhu, ML Huang… - Science China …, 2020 - Springer
Due to the significance and value in human-computer interaction and natural language
processing, task-oriented dialog systems are attracting more and more attention in both …

PLACES: Prompting language models for social conversation synthesis

M Chen, A Papangelis, C Tao, S Kim… - ar** artificial learning systems that can understand and generate natural language
has been one of the long-standing goals of artificial intelligence. Recent decades have …

Zero-shot cross-lingual transfer with meta learning

F Nooralahzadeh, G Bekoulis, J Bjerva… - arxiv preprint arxiv …, 2020 - arxiv.org
Learning what to share between tasks has been a topic of great importance recently, as
strategic sharing of knowledge has been shown to improve downstream task performance …

Low-resource domain adaptation for compositional task-oriented semantic parsing

X Chen, A Ghoshal, Y Mehdad, L Zettlemoyer… - arxiv preprint arxiv …, 2020 - arxiv.org
Task-oriented semantic parsing is a critical component of virtual assistants, which is
responsible for understanding the user's intents (set reminder, play music, etc.). Recent …

Meta learning for natural language processing: A survey

H Lee, SW Li, NT Vu - arxiv preprint arxiv:2205.01500, 2022 - arxiv.org
Deep learning has been the mainstream technique in natural language processing (NLP)
area. However, the techniques require many labeled data and are less generalizable across …