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Found 6 papers, 1 papers with code
ir_explain: a Python Library of Explainable IR Methods
The library is designed to make it easy to reproduce state-of-the-art ExIR baselines on standard test collections, as well as to explore new approaches to explaining IR models and methods.
Engineering software 2.0 by interpolating neural networks: unifying training, solving, and calibration
The evolution of artificial intelligence (AI) and neural network theories has revolutionized the way software is programmed, shifting from a hard-coded series of codes to a vast neural network.
A Comparative Analysis of CNN-Based Pretrained Models for the Detection and Prediction of Monkeypox
As a result, there is an urgent need for a novel technique to combat and anticipate the disease in the early phases of individual virus infection.
Explainability of Text Processing and Retrieval Methods: A Critical Survey
This article provides a broad overview of research on the explainability and interpretability of natural language processing and information retrieval methods.
An Introduction to Kernel and Operator Learning Methods for Homogenization by Self-consistent Clustering Analysis
However, for large-scale engineering problems such as concurrent multiscale simulation for mechanical properties, the training cost for the current operator learning methods is very high.
Bangla Image Caption Generation through CNN-Transformer based Encoder-Decoder Network
Automatic Image Captioning is the never-ending effort of creating syntactically and validating the accuracy of textual descriptions of an image in natural language with context.
