{ "schema_version": 1, "title": "Repro - Instance-Level Costs for Nuanced Classifier Evaluation", "emoji": "🎯", "space_id": "vbabenko97/repro-instance-level-costs", "paper": { "arxiv_id": "2605.03135", "openreview_id": "qMI1xD8O3x" }, "tags": [ "icml2026-repro", "paper-qMI1xD8O3x" ], "updated_at": "2026-07-18T18:43:23+00:00", "root": { "slug": "index", "title": "Repro - Instance-Level Costs for Nuanced Classifier Evaluation", "file": "pages/index.md", "children": [ { "slug": "paper-claims", "title": "Paper & claims", "file": "pages/paper-claims/page.md", "children": [] }, { "slug": "feasibility-gates", "title": "Feasibility gates", "file": "pages/feasibility-gates/page.md", "children": [] }, { "slug": "claim-1-jigsaw-nec-vs-error-3x-gap", "title": "Claim 1: Jigsaw NEC vs error (3x gap)", "file": "pages/claim-1-jigsaw-nec-vs-error-3x-gap/page.md", "children": [] }, { "slug": "claim-2-divergence-across-modalities", "title": "Claim 2: Divergence across modalities", "file": "pages/claim-2-divergence-across-modalities/page.md", "children": [] }, { "slug": "claim-3-cost-derivation-sources", "title": "Claim 3: Cost derivation sources", "file": "pages/claim-3-cost-derivation-sources/page.md", "children": [] }, { "slug": "claim-4-fine-tuned-results-toy", "title": "Claim 4: Fine-tuned results (toy)", "file": "pages/claim-4-fine-tuned-results-toy/page.md", "children": [] }, { "slug": "claim-5-cost-weighted-training-is-inconsistent", "title": "Claim 5: Cost-weighted training is inconsistent", "file": "pages/claim-5-cost-weighted-training-is-inconsistent/page.md", "children": [] }, { "slug": "claim-6-delta-regression-calibration-not-accuracy", "title": "Claim 6: Delta-regression = calibration, not accuracy", "file": "pages/claim-6-delta-regression-calibration-not-accuracy/page.md", "children": [] }, { "slug": "conclusion", "title": "Conclusion", "file": "pages/conclusion/page.md", "children": [] } ] }, "agent_view_tokens": 13862, "revision": "1784400203588636000" }