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Found 8 papers, 5 papers with code
KW-ATTN: Knowledge Infused Attention for Accurate and Interpretable Text Classification
Text classification has wide-ranging applications in various domains.
Active Learning Framework for Cost-Effective TCR-Epitope Binding Affinity Prediction
To reduce annotation cost, we present ActiveTCR, a framework that incorporates active learning and TCR-epitope binding affinity prediction models.
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
While argument mining has achieved significant success in classifying argumentative relations between statements (support, attack, and neutral), we have a limited computational understanding of logical mechanisms that constitute those relations.
Detecting Attackable Sentences in Arguments
Finding attackable sentences in an argument is the first step toward successful refutation in argumentation.
Dropout Prediction over Weeks in MOOCs via Interpretable Multi-Layer Representation Learning
Massive Open Online Courses (MOOCs) have become popular platforms for online learning.
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach
Briefness and comprehensiveness are necessary in order to provide a large amount of information concisely when explaining a black-box decision system.
Explaining a black-box using Deep Variational Information Bottleneck Approach
Briefness and comprehensiveness are necessary in order to provide a large amount of information concisely when explaining a black-box decision system.
Robust Multiple Kernel k-means Clustering using Min-Max Optimization
To address this problem and inspired by recent works in adversarial learning, we propose a multiple kernel clustering method with the min-max framework that aims to be robust to such adversarial perturbation.
