Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,87 @@
+---
+license: mit
+task_categories:
+  - feature-extraction
+language:
+  - en
+tags:
+  - embeddings
+  - vector-database
+  - migration
+  - retrieval
+  - ms-marco
+  - beir
+pretty_name: Embedding Migration Results
+size_categories:
+  - n<1K
+---
+
+# Embedding Migration Results
+
+Experimental results from testing whether vector databases can be migrated to new embedding models **without re-embedding the entire corpus**.
+
+## Overview
+
+We embedded ~1M MS MARCO passages with 6 embedding models across 3 dimensionalities (768, 1024, 2560), trained linear translators between every pair of embedding spaces, and measured recall@10 ratio (translated / native ceiling).
+
+## Models
+
+| Model | Dim | Prefix |
+|---|---|---|
+| intfloat/e5-base-v2 | 768 | query/passage |
+| BAAI/bge-base-en-v1.5 | 768 | query only |
+| Alibaba-NLP/gte-base-en-v1.5 | 768 | none |
+| nomic-ai/nomic-embed-text-v1.5 | 768 | search_query/search_document |
+| Qwen/Qwen3-Embedding-0.6B | 1024 | instruction format |
+| Qwen/Qwen3-Embedding-4B | 2560 | instruction format |
+
+## Files
+
+| File | Evaluations | Description |
+|---|---|---|
+| `msmarco_procrustes.json` | 30 | Orthogonal Procrustes / least-squares on MS MARCO 1M |
+| `msmarco_ridge.json` | 30 | Ridge regression on MS MARCO 1M |
+| `beir_scifact_procrustes.json` | 30 | Procrustes/LS evaluated on BEIR SciFact |
+| `beir_scifact_ridge.json` | 30 | Ridge evaluated on BEIR SciFact |
+| `beir_fiqa_procrustes.json` | 30 | Procrustes/LS evaluated on BEIR FiQA |
+| `beir_fiqa_ridge.json` | 30 | Ridge evaluated on BEIR FiQA |
+| `beir_nfcorpus_procrustes.json` | 30 | Procrustes/LS evaluated on BEIR NFCorpus |
+| `beir_nfcorpus_ridge.json` | 30 | Ridge evaluated on BEIR NFCorpus |
+| `fewshot_curve.json` | 84 | Few-shot learning curve (50-5000 training examples) |
+| `relative_repr.json` | 30 | Relative representations baseline (Moschella et al. 2023) |
+
+**Total: 354 evaluations**
+
+## Key Results
+
+- **50 paired examples** is enough for 95%+ native performance on compatible model pairs
+- **Prefix mismatch** (not dimension mismatch) is the dominant failure mode
+- **Ridge regression** rescues prefix-mismatched pairs (E5→GTE: 0.090 → 0.814)
+- **Cross-domain generalization** holds for same-family pairs, degrades 10-30% for mismatched pairs
+- **Relative representations** fail at retrieval scale (negative result)
+
+## Schema
+
+Each JSON file contains an array of evaluation records. Common fields:
+
+```json
+{
+  "source": "model/name",
+  "target": "model/name",
+  "method": "procrustes|ridge|relative_repr",
+  "src_dim": 768,
+  "tgt_dim": 768,
+  "recall@10_translated": 0.862,
+  "recall@10_native_target": 0.885,
+  "ratio": 0.974,
+  "train_size": 5000
+}
+```
+
+## Citation
+
+If you use these results, please link to the GitHub repository.
+
+## License
+
+MIT