logbook.json

{
  "schema_version": 1,
  "title": "Repro - Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training",
  "emoji": "🎯",
  "space_id": "rdubwiley/spurious-correlation-learning-in-preference-repro",
  "paper": {
    "arxiv_id": "2605.11134"
  },
  "tags": [
    "icml2026-repro",
    "paper-Hpfybj9wkd"
  ],
  "updated_at": "2026-07-18T02:52:37+00:00",
  "root": {
    "slug": "index",
    "title": "Repro - Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training",
    "file": "pages/index.md",
    "children": [
      {
        "slug": "conclusion",
        "title": "Conclusion",
        "file": "pages/conclusion/page.md",
        "children": []
      },
      {
        "slug": "claim-1-standard-preference-learning-objectives-induce-reliance-on-spurious-features-through-mean-spurious-bias-and-causal-spurious-correlation-leakage",
        "title": "Claim 1: Standard preference-learning objectives induce reliance on spurious features through mean spurious bias and causal-spurious correlation leakage",
        "file": "pages/claim-1-standard-preference-learning-objectives-induce-reliance-on-spurious-features-through-mean-spurious-bias-and-causal-spurious-correlation-leakage/page.md",
        "children": []
      },
      {
        "slug": "claim-2-irreducible-vulnerability-to-distribution-shift-more-data-from-same-training-distribution-fails-to-reduce-model-dependence-on-spurious-features",
        "title": "Claim 2: Irreducible vulnerability to distribution shift: more data from same training distribution fails to reduce model dependence on spurious features",
        "file": "pages/claim-2-irreducible-vulnerability-to-distribution-shift-more-data-from-same-training-distribution-fails-to-reduce-model-dependence-on-spurious-features/page.md",
        "children": []
      },
      {
        "slug": "claim-3-tie-training-using-equal-utility-preference-pairs-selectively-reduces-spurious-learning-without-degrading-causal-learning",
        "title": "Claim 3: Tie training using equal-utility preference pairs selectively reduces spurious learning without degrading causal learning",
        "file": "pages/claim-3-tie-training-using-equal-utility-preference-pairs-selectively-reduces-spurious-learning-without-degrading-causal-learning/page.md",
        "children": []
      }
    ]
  },
  "agent_view_tokens": 5747,
  "revision": "1784343157793148899"
}