A survey of knowledge enhanced pre-trained language models
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-
supervised learning method, have yielded promising performance on various tasks in …
supervised learning method, have yielded promising performance on various tasks in …
Generating anomalies for video anomaly detection with prompt-based feature map**
Anomaly detection in surveillance videos is a challenging computer vision task where only
normal videos are available during training. Recent work released the first virtual anomaly …
normal videos are available during training. Recent work released the first virtual anomaly …
[HTML][HTML] Knowledge injected prompt based fine-tuning for multi-label few-shot icd coding
Abstract Automatic International Classification of Diseases (ICD) coding aims to assign
multiple ICD codes to a medical note with average length of 3,000+ tokens. This task is …
multiple ICD codes to a medical note with average length of 3,000+ tokens. This task is …
Re4: Learning to re-contrast, re-attend, re-construct for multi-interest recommendation
Effectively representing users lie at the core of modern recommender systems. Since users'
interests naturally exhibit multiple aspects, it is of increasing interest to develop multi-interest …
interests naturally exhibit multiple aspects, it is of increasing interest to develop multi-interest …
Improving deep learning with prior knowledge and cognitive models: A survey on enhancing explainability, adversarial robustness and zero-shot learning
F Mumuni, A Mumuni - Cognitive Systems Research, 2024 - Elsevier
We review current and emerging knowledge-informed and brain-inspired cognitive systems
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
for realizing adversarial defenses, eXplainable Artificial Intelligence (XAI), and zero-shot or …
Kept: Knowledge enhanced prompt tuning for event causality identification
Event causality identification (ECI) aims to identify causal relations of event mention pairs in
text. Despite achieving certain accomplishments, existing methods are still not effective due …
text. Despite achieving certain accomplishments, existing methods are still not effective due …
Combining prompt learning with contextual semantics for inductive relation prediction
Inductive relation prediction for knowledge graphs aims to predict missing relations between
two new entities. Most previous studies on relation prediction are limited to the transductive …
two new entities. Most previous studies on relation prediction are limited to the transductive …