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"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"
} |