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  • Update wiki for current v1 retrieval data

    @GiulioDER GiulioDER committed Aug 10, 2026
    4459ac2
  • docs(wiki): reranking is the largest gain, not a redundancy — and a settings guide Two pages told readers to skip the single highest-value setting. Installation-and-Setup called the rerank extra "redundant on an easy corpus with a strong embedder"; Evidence-Map listed "reranking, candidate pool and chunk size are NOT the lever". Both came from an early ablation on a small internal corpus. PR #103 measured the opposite on the standard public benchmark, with the DEFAULT local embedder: the largest single retrieval gain anywhere in this project, intervals disjoint from the baseline. The wiki was advising against it. Corrected on both pages, with a note saying why the old framing existed rather than deleting it — it was published advice and someone may have acted on it. The FINDINGS §7 null is kept and scoped to the corpus it was measured on, because it is still true there. New page, Embedders-and-Rerankers: the choice these two settings actually present. Five embedders (Retrieval-Pipeline said four — OpenAI-compatible was missing) and two rerankers, each with when to pick it, what it costs, what it breaks, and a link to the measurement. It also documents the interaction nothing else does: a candidate pool no wider than k hands the cross-encoder exactly the list it is meant to reorder. The flag is set, the model loads, the latency is paid, and the result is identical to having no reranker — with nothing reporting it. Canonical-source rule held: the new page states no figure and no default. A digit scan finds only section references and a numbered list. Verified across the wiki: 76 repo URLs all resolve, zero broken wikilinks.

    @GiulioDER GiulioDER committed Jul 29, 2026
    5c72fb0
  • docs(wiki): filtered-ANN tuning is a truncation fix, not a recall win Both pages described the HNSW filtered-path tuning as fixing "poor recall". PR #57 measured it twice: truncation is eliminated in both, recall improves only on a fixture corpus the test rebuilds until it reproduces the pathology, and moves the other way on a normally-built one. relaxed_order fills to k with approximate matches — the trade is truncation for approximation. Same correction landing in README / FINDINGS / CHANGELOG. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

    @GiulioDER GiulioDER committed Jul 23, 2026
    3b51c87
  • docs(wiki): 14 pages — reference, architecture and evidence routing The repo already carries the narrative (README, docs/, results/). What it lacked was a reference surface: nothing documented the 28 RECALL_* variables or the 8 CLI subcommands in one place, and nothing mapped the modules. Organised by topic with audience-specific entry paths on Home, so the trust layer is written once rather than three times. No page states a measured figure, a config default or a CLI flag value. Those live in the repo, versioned with the code that produced them, and a second copy in a wiki — no CI, no review, no commit link — is somewhere for them to go stale. That is the failure mode this project exists to prevent, so shipping it in the project's own docs would be self-refuting. Pages route to FINDINGS / .env.example / --help instead. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

    @GiulioDER GiulioDER committed Jul 23, 2026
    a703da2
  • Initial Home page

    @GiulioDER GiulioDER committed Jul 23, 2026
    80e8312