{ "schema_version": 2, "title": "Reproduction: FormulaCode: Evaluating Agentic Optimization on Large Codebases", "emoji": "🏎️", "space_id": "amkkk/repro-formulacode-evaluating-agentic-optimization-on-large-codebases", "paper": { "arxiv_id": "2603.16011", "orid": "WArbqRUsAe" }, "tags": [ "icml2026-repro", "paper-WArbqRUsAe" ], "updated_at": "2026-08-02T21:34:14+00:00", "root": { "slug": "index", "title": "Reproduction: FormulaCode: Evaluating Agentic Optimization on Large Codebases", "file": "pages/index.md", "children": [ { "slug": "executive-summary", "title": "executive-summary", "file": "pages/executive-summary/page.md", "children": [] }, { "slug": "claim-1-dataset-pipeline", "title": "Claim 1: dataset construction pipeline", "file": "pages/claim-1-dataset-pipeline/page.md", "children": [] }, { "slug": "claim-2-workload-patch-scale", "title": "Claim 2: workload & patch scale", "file": "pages/claim-2-workload-patch-scale/page.md", "children": [] }, { "slug": "claim-3-agent-performance", "title": "Claim 3: frontier-agent performance", "file": "pages/claim-3-agent-performance/page.md", "children": [] }, { "slug": "claim-4-optimization-scale", "title": "Claim 4: optimization scale", "file": "pages/claim-4-optimization-scale/page.md", "children": [] }, { "slug": "claim-5-repository-popularity", "title": "Claim 5: repository popularity", "file": "pages/claim-5-repository-popularity/page.md", "children": [] }, { "slug": "claim-6-strategy-performance", "title": "Claim 6: strategy performance", "file": "pages/claim-6-strategy-performance/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": 8186, "trace_view_tokens": 10, "workspace_view_tokens": 8, "revision": "d91128d651d678438800" }