{
  "schema_version": 2,
  "title": "Reproduction: Autoregressive Direct Preference Optimization",
  "emoji": "\ud83e\uddee",
  "space_id": "codemaivanngu/repro-autoregressive-direct-preference-optimization",
  "paper": {
    "arxiv_id": "2602.09533",
    "openreview_id": "DmeFAFUO6f"
  },
  "tags": [
    "icml2026-repro",
    "paper-DmeFAFUO6f"
  ],
  "updated_at": "2026-08-03T11:10:51.875114+00:00",
  "root": {
    "slug": "index",
    "title": "Reproduction: Autoregressive Direct Preference Optimization",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "executive-summary",
        "title": "Executive summary",
        "file": "pages/executive-summary/page.md",
        "children": []
      },
      {
        "slug": "claim-1-loss-structure",
        "title": "Claim 1: ADPO loss structure",
        "file": "pages/claim-1-loss-structure/page.md",
        "children": []
      },
      {
        "slug": "claim-2-length-measures",
        "title": "Claim 2: token and feedback length measures",
        "file": "pages/claim-2-length-measures/page.md",
        "children": []
      },
      {
        "slug": "claim-3-reduction-to-dpo",
        "title": "Claim 3: reduction to DPO",
        "file": "pages/claim-3-reduction-to-dpo/page.md",
        "children": []
      },
      {
        "slug": "claim-4-math-reasoning",
        "title": "Claim 4: mathematical reasoning benchmarks",
        "file": "pages/claim-4-math-reasoning/page.md",
        "children": []
      },
      {
        "slug": "claim-5-alpacaeval",
        "title": "Claim 5: AlpacaEval 2",
        "file": "pages/claim-5-alpacaeval/page.md",
        "children": []
      },
      {
        "slug": "claim-6-granularity",
        "title": "Claim 6: response granularity",
        "file": "pages/claim-6-granularity/page.md",
        "children": []
      },
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      }
    ]
  },
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    "file": "workspace.json",
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