On 272 family-category analogy questions from a fairytales corpus, averaging random-indexing vectors over a top-50 PPMI graph raised accuracy from 19.4% to 30.7% across five seeds, while the same averaging hurt stronger baselines.
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Sparse Mutual Information Graph Averaging for Improving Random Indexing Embeddings
On 272 family-category analogy questions from a fairytales corpus, averaging random-indexing vectors over a top-50 PPMI graph raised accuracy from 19.4% to 30.7% across five seeds, while the same averaging hurt stronger baselines.