Papers by VG Vinod Vydiswaran
HiCL: Hierarchical Contrastive Learning of Unsupervised Sentence Embeddings (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Existing methods that encode a sequence in its entirety for contrast with others often neglect local representation learning. |
| Approach: | They propose a hierarchical contrastive learning framework, HiCL, which considers local segment-level and global sequence-level relationships to improve training efficiency and effectiveness. |
| Outcome: | The proposed framework improves training efficiency and effectiveness by dividing a sequence into several segments and using local and global contrastive learning to model relationships. |