Differentiable Product Quantization for End-to-End Embedding Compression
Table 9: Nearest neighbours of ‘_evolve’ in the embedding space.
['[BOLD] Baseline (Full) _evolve', '[BOLD] Dist 1.000', '[BOLD] DPQ-SX _evolve', '[BOLD] Dist 1.000', '[BOLD] DPQ-VQ _evolve', '[BOLD] Dist 1.000']
Distance between two sub-words is measured by the cosine similarity of their embedding vectors. Baseline is the original full embeddings model. DPQ variants were trained with K=D=128 with no subspace-sharing.