---
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 the GitHub repository: https://github.com/allison-stack/embedding-migration

## License

MIT