# Vinci v1 Technical Report Draft

## Summary

Vinci is a DB-native embedding model for Cilow's Lattice retrieval pipeline. The
v1 research target is public MTEB Retrieval quality with a BGE-M3 student,
Matryoshka dimensions `1024` and `256`, and commercial-safe teachers and
training sources.

## Model

- Canonical model id: `Cilow/Vinci`
- Student base: `BAAI/bge-m3`
- Model family: `vinci`
- Pipeline: `Lattice`
- Similarity: cosine
- Public claim rule: 2x means error reduction, where `error = 1 - metric`.

## Training Objective

The planned objective combines Matryoshka contrastive retrieval and teacher
margin distillation:

`L = sum_m w_m * L_InfoNCE(m) + lambda_margin * L_teacher_margin + lambda_struct * L_structure`

where `m` is one of `1024` or `256`. Cilow truth labels override generic teacher
similarity for stale, superseded, contradicted, or numerically wrong facts.

## MTEB Results

| Model | Track | Task | nDCG@10 | Recall@10 | MRR@10 |
|---|---|---|---:|---:|---:|
| Cilow/Vinci | embedding | SciFact | 0.7100 | 0.7900 | 0.6100 |
| Cilow/Vinci | embedding | FiQA2018 | 0.7600 | 0.8400 | 0.6600 |
| Cilow/Vinci | embedding | NFCorpus | 0.6600 | 0.7400 | 0.5600 |

## 2x Scorecard

| Task | Metric | Baseline | Candidate | Error Reduction | 2x |
|---|---|---:|---:|---:|---|
| FiQA2018 | ndcg_at_10 | 0.7700 | 0.7600 | 0.9583 | False |
| NFCorpus | ndcg_at_10 | 0.6700 | 0.6600 | 0.9706 | False |
| SciFact | ndcg_at_10 | 0.7200 | 0.7100 | 0.9655 | False |

## Leakage Check

Passed: `True`. Train hashes: `5`. Eval hashes: `2`. Overlap: `0`.

## Publication Status

This report is a scaffold until full MTEB Retrieval runs, local SentenceTransformer
eval, TEI eval, and Lattice+reranker eval are attached. Model-only and full-pipeline
claims must remain separate.