SLSCom pre-trains a semantic encoder with contrastive and reconstruction pretext tasks on unlabeled data, then jointly fine-tunes it with JSCC and a classifier, improving accuracy under few labels and low SNR.
Learning task-oriented communication for edge inference: An information bottleneck approach,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
Task-Oriented Low-Label Semantic Communication With Self-Supervised Learning
SLSCom pre-trains a semantic encoder with contrastive and reconstruction pretext tasks on unlabeled data, then jointly fine-tunes it with JSCC and a classifier, improving accuracy under few labels and low SNR.