A comprehensive survey of few-shot learning: Evolution, applications, challenges, and opportunities
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 …
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 …
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
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 …
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
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 …
information to be effective. Pre-trained Language Models (PLMs) have been used to learn …
Localized symbolic knowledge distillation for visual commonsense models
Instruction following vision-language (VL) models offer a flexibleinterface that supports a
broad range of multimodal tasks in a zero-shot fashion. However, interfaces that operate on …
broad range of multimodal tasks in a zero-shot fashion. However, interfaces that operate on …
Knowledge is flat: A seq2seq generative framework for various knowledge graph completion
Knowledge Graph Completion (KGC) has been recently extended to multiple knowledge
graph (KG) structures, initiating new research directions, eg static KGC, temporal KGC and …
graph (KG) structures, initiating new research directions, eg static KGC, temporal KGC and …