logbook.json

{
  "schema_version": 1,
  "title": "Repro - Balancing Learning Rates Across Layers",
  "emoji": "🎯",
  "space_id": "DineshAI/4vztmTrGhd",
  "paper": {
    "arxiv_id": "2606.00340",
    "openreview_id": "4vztmTrGhd"
  },
  "tags": [
    "icml2026-repro",
    "paper-4vztmTrGhd"
  ],
  "updated_at": "2026-07-18T09:00:58+00:00",
  "root": {
    "slug": "index",
    "title": "Repro - Balancing Learning Rates Across Layers",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "claim-1-asymmetry-then-balance",
        "title": "Claim 1 — asymmetry then balance",
        "file": "pages/claim-1-asymmetry-then-balance/page.md",
        "children": []
      },
      {
        "slug": "claim-2-exact-gradients-and-losses",
        "title": "Claim 2 — exact gradients and losses",
        "file": "pages/claim-2-exact-gradients-and-losses/page.md",
        "children": []
      },
      {
        "slug": "methods-environment",
        "title": "Methods & environment",
        "file": "pages/methods-environment/page.md",
        "children": []
      },
      {
        "slug": "negative-controls-falsification",
        "title": "Negative controls & falsification",
        "file": "pages/negative-controls-falsification/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
  "agent_view_tokens": 2956,
  "revision": "1784365258453726731"
}