Search Results for author:
Found 2 papers, 2 papers with code
Unseen Classes at a Later Time? No Problem
Secondly, we introduce a unified feature-generative framework for CGZSL that leverages bi-directional incremental alignment to dynamically adapt to addition of new classes, with or without labeled data, that arrive over time in any of these CGZSL settings.
Unsupervised Identification of Relevant Prior Cases
Based on the comparative analysis, we found that the TF-IDF score multiplied by the BM25 score gives the best result.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
