UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification

arXiv:2405.03714v1 Announce Type: new
Abstract: Extreme Multi-label Classification (XMC) involves predicting a subset of relevant labels from an extremely large label space, given an input query and labels with textual features. Models developed for this problem have conventionally used modular approach with (i) a Dual Encoder (DE) to embed the queries and label texts, (ii) a One-vs-All classifier to rerank the shortlisted labels mined through meta-classifier training. While such methods have shown empirical success, we observe two key uncharted aspects, …

abstract arxiv classification classifier cs.ai cs.lg encoder features labels modular query space textual training type