A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities

Y Song, T Wang, P Cai, SK Mondal… - ACM Computing Surveys, 2023 - dl.acm.org
Few-shot learning (FSL) has emerged as an effective learning method and shows great
potential. Despite the recent creative works in tackling FSL tasks, learning valid information …

Efficient utilization of pre-trained models: A review of sentiment analysis via prompt learning

K Bu, Y Liu, X Ju - Knowledge-Based Systems, 2024 - Elsevier
Sentiment analysis is one of the traditional well-known tasks in Natural Language
Processing (NLP) research. In recent years, Pre-trained Models (PMs) have become one of …

Fill in the blank: Context-aware automated text input generation for mobile gui testing

Z Liu, C Chen, J Wang, X Che, Y Huang… - 2023 IEEE/ACM 45th …, 2023 - ieeexplore.ieee.org
Automated GUI testing is widely used to help ensure the quality of mobile apps. However,
many GUIs require appropriate text inputs to proceed to the next page, which remains a …

PLACES: Prompting language models for social conversation synthesis

M Chen, A Papangelis, C Tao, S Kim… - ar** plms sauce: Bridging structure and text for effective knowledge graph completion via conditional soft prompting
C Chen, Y Wang, A Sun, B Li, KY Lam - arxiv preprint arxiv:2307.01709, 2023 - arxiv.org
Knowledge Graph Completion (KGC) often requires both KG structural and textual
information to be effective. Pre-trained Language Models (PLMs) have been used to learn …

Language-guided music recommendation for video via prompt analogies

D McKee, J Salamon, J Sivic… - Proceedings of the …, 2023 - openaccess.thecvf.com
We propose a method to recommend music for an input video while allowing a user to guide
music selection with free-form natural language. A key challenge of this problem setting is …

Let gpt be a math tutor: Teaching math word problem solvers with customized exercise generation

Z Liang, W Yu, T Rajpurohit, P Clark, X Zhang… - arxiv preprint arxiv …, 2023 - arxiv.org
In this paper, we present a novel approach for distilling math word problem solving
capabilities from large language models (LLMs) into smaller, more efficient student models …

Label-specific feature augmentation for long-tailed multi-label text classification

P Xu, L **ao, B Liu, S Lu, L **g, J Yu - Proceedings of the AAAI …, 2023 - ojs.aaai.org
Multi-label text classification (MLTC) involves tagging a document with its most relevant
subset of labels from a label set. In real applications, labels usually follow a long-tailed …

Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning

P Chen, J Wang, H Lin, D Zhao, Z Yang - Bioinformatics, 2023 - academic.oup.com
Motivation Few-shot learning that can effectively perform named entity recognition in low-
resource scenarios has raised growing attention, but it has not been widely studied yet in the …