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Summary
Submission paths (new tasks):
task-submissions/bingyu/1-x-1Category / Implementation or Optimization / CPU or GPU: 1 / Implementation / CPU
Authors and coauthors: bingyu
Adds a Faiss metadata-filtered ANN retrieval task based on YFCC-10M.
The task includes 10 public queries and 10 hidden queries. Hidden queries are
scored individually, and their scores are averaged.
Index building has a 600-second deadline. Once the service reports ready,
each query has a 15 ms deadline.
The verifier checks result correctness, index persistence, and consistency
after index relocation and reloading, and performs an independent trajectory audit.
Validation evidence
Completed checks:
python -B scripts/check_submission.py task-submissions/bingyu/1-x-1Result: 0 errors; submission review-stage static checks passed.
python -B scripts/check_release.pyResult: 0 errors, 0 warnings.
python -B scripts/download_assets.py --task-path task-submissions/bingyu/1-x-1 --verify-onlyResult: size and SHA-256 verification passed for all 9 data files.
git show --format= --check HEADResult: no whitespace errors in the commit.
service loading timeout.
process exits were handled as expected. Injecting 3 failures among 10 queries
produced a retrieval score of 0.7, with subsequent queries still evaluated.
Earlier full-corpus reference implementation validation:
relocation and reloading: 20 requests in total against the full 10-million-vector corpus.
approximately 5.67 ms. The retrieval score was 1.0.
timeout. The 13 regression tests passed after that change, but the full-corpus
reference implementation validation has not been rerun.
task README.
Development dataset:
Cooki-e/search-swe-developmentContributor checklist
task.toml; commit email associated with my GitHub account.Maintainer merge checklist (new tasks)
git mvand reviewed finalization commits per task, in this PR.SOURCES and license updated, all old assets preserved; official SHA pinned in
assets.json.every task is promoted and no submission
task.tomlremains.