{ "schema_version": 2, "title": "Learning $U$-Statistics with Active Inference", "emoji": "🎯", "space_id": "SabaPivot/repro-learning-u-statistics-with-active-inference", "paper": { "arxiv_id": "2605.11638" }, "tags": [ "icml2026-repro", "paper-BwufLjXbMO" ], "updated_at": "2026-08-02T16:31:38.256984+00:00", "root": { "slug": "index", "title": "Learning $U$-Statistics with Active Inference", "file": "pages/index.md", "children": [ { "slug": "executive-summary", "title": "Executive summary", "file": "pages/executive-summary/page.md", "children": [] }, { "slug": "claim-1-aipw-u-statistic-estimator-is-unbiased", "title": "Claim 1: AIPW U-statistic estimator is unbiased", "file": "pages/claim-1-aipw-u-statistic-estimator-is-unbiased/page.md", "children": [] }, { "slug": "claim-2-optimal-sampling-rule-from-hoeffding-projection", "title": "Claim 2: optimal sampling rule from Hoeffding projection", "file": "pages/claim-2-optimal-sampling-rule-from-hoeffding-projection/page.md", "children": [] }, { "slug": "claim-3-clt-and-computable-cis-under-adaptive-sampling", "title": "Claim 3: CLT and computable CIs under adaptive sampling", "file": "pages/claim-3-clt-and-computable-cis-under-adaptive-sampling/page.md", "children": [] }, { "slug": "claim-4-acs-gini-budget-reduction", "title": "Claim 4: ACS Gini budget reduction", "file": "pages/claim-4-acs-gini-budget-reduction/page.md", "children": [] }, { "slug": "claim-5-vitaldb-wilcoxon-budget-reduction", "title": "Claim 5: VitalDB Wilcoxon budget reduction", "file": "pages/claim-5-vitaldb-wilcoxon-budget-reduction/page.md", "children": [] }, { "slug": "claim-6-political-bias-kendall-budget-reduction", "title": "Claim 6: political-bias Kendall budget reduction", "file": "pages/claim-6-political-bias-kendall-budget-reduction/page.md", "children": [] }, { "slug": "claim-99-fresh-independent-cpu-audit", "title": "Fresh independent CPU audit", "file": "pages/claim-99-fresh-independent-cpu-audit/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] }, "traces": [], "workspace": { "file": "workspace.json", "file_count": 0, "total_size": 0, "bucket_id": null }, "agent_view_tokens": 6289, "trace_view_tokens": 23978, "workspace_view_tokens": 1044, "revision": "36bdce7650b68d08adc1", "traces_ref": { "repo_id": "Srishti280992/repro-learning-u-statistics-with-active-inference-traces", "repo_type": "dataset", "repo_url": "https://huggingface.co/datasets/Srishti280992/repro-learning-u-statistics-with-active-inference-traces", "private": true }, "trace_dataset": "https://huggingface.co/datasets/Srishti280992/repro-learning-u-statistics-with-active-inference-traces", "workspace_ref": { "repo_id": "Srishti280992/repro-learning-u-statistics-with-active-inference-artifacts", "repo_type": "bucket", "repo_url": "https://huggingface.co/buckets/Srishti280992/repro-learning-u-statistics-with-active-inference-artifacts", "private": true }, "workspace_bucket": "https://huggingface.co/buckets/Srishti280992/repro-learning-u-statistics-with-active-inference-artifacts" }