9 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.CL2024★ 9 cited
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
Miruna Beţianu, Abele Mălan, Marco Aldinucci +2
Large language models (LLMs) increasingly serve as the backbone for classifying text associated with distinct domains and simultaneously several labels (classes). When encountering…
cs.CV2021★ 1 cited
Multi-Label Gold Asymmetric Loss Correction with Single-Label Regulators
Cosmin Octavian Pene, Amirmasoud Ghiassi, Taraneh Younesian +2
Multi-label learning is an emerging extension of the multi-class classification where an image contains multiple labels. Not only acquiring a clean and fully labeled dataset in mul…