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Full research and publication inventory · Structured citation/source inventory · Reproducible benchmarks · Raw benchmark evidence

These are existing public manuscripts, research PDFs, and implementations. An authored arXiv submission has not been independently verified; see the inventory for status and attribution.

Directly measured reranking (2026-10-29): Directly timed three-host rerank benchmark · reproduction and caveats. 45 measured runs across three Linux CPU hosts and 15 distinct synthetic seed/distribution cases. With 160 candidates, exact top-five matches were recovered on all tested cases, while direct end-to-end CPU latency was lower than an exact float32 scan. Quantization setup is measured separately, and actual dashcam embeddings, GPU and production DB retrieval remain unmeasured.

Two-stage reranking study (2026-10-29): Six-host, five-seed shortlist results · clustered/temporal stress results · benchmark methods. Reranking 20 int8 candidates restored 100% top-5 recall on independent synthetic vectors but only 97.33% on the clustered control; 160 candidates reached 100% on those five clustered seeds. Synthetic CPU evidence only, not real dashcam or GPU benchmarks.

October 2026: high-dimensional quantization replication. 768D multi-seed results (30 runs) · Methods and GPU readiness. Five independent synthetic seeds across six Linux hosts; int8 recall@5 averaged 84.0% versus float32. CPU only.

Fleet benchmark replication (2026-10-29): Eight-host results, methods and code · Machine-readable comparison · Compiled C benchmark. Eight CPU hosts completed the synthetic Python and compiled vector tests; no production location data or GPU inference was benchmarked.

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32,768-vector CPU scale-up (2026-10-29): Ten directly timed trials · validated methodology. At 768 dimensions, int8 scanning plus float32 reranking of 160 candidates measured ~4.89 ms median versus ~14.06 ms exact float32 on clustered synthetic data, with 100% top-5 recall on these five seeds only; quantization incurred ~79 ms one-time cost and is excluded from query latency.

Held-out benchmark validation (2026-10-29): 80-trial frozen-policy study · 40-trial disjoint second validation · methods, source and caveats. Initial 99% recall calibration failed on both 32,768-vector held-out distributions (98.67%/98.33%). A separately precommitted, more conservative M20/M80 policy reached 99.83%/99.92% on a second synthetic CPU-only holdout. These are not actual dashcam or GPU results.

Query-only adaptive retrieval (2026-10-29): 300-query calibration · 960 held-out queries · 40 matched fixed160 comparisons · methods. A fixed quantized-score margin threshold of 0.0064 yielded 99.58–100% top-five recall across five unseen synthetic CPU groups without a distribution-label oracle. Critical negative control: adaptation yielded only ~2–9% additional median paired speedup over fixed160, much smaller than the ~2.9× ratio versus full float32 search. No real dashcam, SensorGraft production query, GPU, or arXiv publication is claimed.

Per-vector int8 scaling replication (2026-10-29): 60 held-out synthetic CPU trials · 25 cross-fleet CPU trials · methods and memory caveats. At 768 dimensions, per-vector absmax int8 + float32 rerank 20 restored 100% observed top-five recall across six tested synthetic workloads versus fixed-scale int8 recall of 96.83% / 95.50% on clustered 8K/32K vectors. Peer replication on Deathstar, Lenovo and Raspberry Pi confirmed deterministic hit totals. This is not a guarantee for real embeddings or a GPU result. Retaining the original float32 representations plus int8 and scale costs 25.1% more raw vector memory than float32 alone.

Secondary-storage reranking (2026-10-29): 100 raw synthetic CPU trials · file-backed C benchmark · full methodology. With 32,768 768D clustered vectors, float32 rerank candidates fetched via warm-cache pread used 26.4 MiB measured process RSS versus 122.3 MiB for float32 in process RAM, at 4.70 ms versus 4.67 ms median query time (M20). Cache-drop hints significantly increased latency; Linux page cache means process RSS reductions are not whole-system memory savings. This is synthetic CPU evidence, not deployed SensorGraft or ROCm.

Contiguous float32 candidate-read benchmark (2026-10-29): 280-run raw evidence · C source · full reproducibility and caveats. Sorting selected float32 candidate IDs and combining adjacent records cut pread calls 99.3% for the 32,768-vector temporal/M160 synthetic CPU workload, but 0% for clustered data with scattered IDs. Correctness parity passed on all 40 seeded dataset/M cases across seven modes. Latency gains are locality-dependent and noisy; cache-hint results do not prove cold-device latency. This is not production SensorGraft or ROCm performance.

Synchronized concurrency benchmark (2026-10-29): 48 gated groups / 112 low-priority worker processes / 10,752 timed synthetic queries · compiled worker · methods and limitations. For 32,768 temporal 768D vectors per worker, four independent warm file-backed coalesced workers delivered 574 completed queries/s with 7.66 ms pooled p95; for clustered data, 688 queries/s and 7.14 ms pooled p95. Cache-hinted clustered retrieval fell to 219 queries/s and 21.48 ms p95. All synthetic exact top-5 checks passed. These are independent per-process indexes and files, not a shared production SensorGraft service; summed process RSS excludes kernel page cache.

Shared-index concurrency and backpressure (2026-10-29): 72 synchronized groups / 4,992 exact synthetic client requests · 18 overload groups / 432 explicit response receipts · shared C Unix-socket server · methods and caveats. One shared read-only synthetic 32,768 × 768D index was served by 1 or 4 threads to 1/4/8 concurrent clients. At eight clients, four-worker file-backed coalesced retrieval delivered about 656–666 QPS with 14.7–14.8 ms client p95, versus 186–198 QPS and 47–54 ms p95 on one worker; queue delay drove the difference. Server ready-state process RSS was ~27 MiB file-backed vs ~125 MiB float32 RAM; Linux page cache remains unaccounted. Under deliberate overload, a one-worker/two-slot queue returned 378 explicit BUSY replies and 54 exact successful responses. This is synthetic UDS research, not production SensorGraft or ROCm.