New benchmark results and documentation parity. Central Intelligence's v2 hybrid retrieval pipeline (pgvector HNSW + BM25 + RRF fusion + bge-reranker-v2-m3 cross-encoder) scores among the top results published on both LifeBench and LongMemEval.
Benchmark Results
LongMemEval (ICLR 2025) — 75.0%
Conversational memory across 500 questions: single-session recall, multi-session reasoning, temporal reasoning, knowledge updates, preference tracking.
| Overall | Single-session | Multi-session | Temporal | Preference |
|---|---|---|---|---|
| 75.0% | 91.9% | 66.2% | 69.9% | 76.7% |
Answer model: gpt-5.4-mini. Judge: gpt-4o.
LifeBench (2026) — 52.2%
Long-term multi-source memory: 2,003 questions across 10 users, 51K real-world events (messages, calendar, health records, notes, calls). The hardest published memory benchmark.
| Overall | Info Extraction | Multi-hop | Temporal | Nondeclarative |
|---|---|---|---|---|
| 52.2% | 47.2% | 52.9% | 46.4% | 64.1% |
Answer model: gpt-5.4-mini. Judge: gpt-4.1-mini.
Evaluation harness: lifebench-eval.
What Got Us Here (since v1.2.1)
The journey from v1.2.1 to v1.2.2, measured on LongMemEval:
| Change | Delta |
|---|---|
Reranker upgrade: MiniLM → bge-reranker-v2-m3 + top-K=10 |
~+18pp |
Answer model: gpt-4o-mini → gpt-5.4-mini |
~+5pp |
| Answer prompt: CoT counting + factual precision + multi-hop grounding | ~+3pp |
| Infrastructure fixes (ef_search, performance CPU, 4GB RAM) | enabler |
Attribution is approximate — each step was measured through the benchmark's run-to-run variance. The architecture that reached 75% is the clean v2 pipeline: pgvector HNSW + BM25 with RRF fusion, temporal decay, and a cross-encoder reranker. No fact extraction or graph traversal during recall.
Changes Since v1.2.1
Retrieval
- Upgraded reranker to
bge-reranker-v2-m3(8K context, +14% nDCG@10 over MiniLM) - top-K=10 retrieval (NeurIPS 2024 finding: accuracy saturates at k=10, degrades with more docs)
- Set
hnsw.ef_search = 400globally (was silently capped at ~40 results) - Reverted to v2 architecture (vector + BM25 + reranker) — removed query decomposition and fact-path that regressed multi-session scores
Benchmark infrastructure
- Added
--answer-modelparameter to benchmark entrypoint - Performance CPU on benchmark VM (fixes extraction stalls under shared-CPU throttling)
- DB-driven extraction queue (removed in-memory queue that caused zombie processes)
Documentation
- README Benchmarks section now includes full category tables for both LifeBench and LongMemEval
- Landing page at centralintelligence.online matches README numbers exactly
- Answer/judge model attribution documented inline for reproducibility
Try It
npx central-intelligence-local signupFull docs: README · Benchmarks: live results