{
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  "official_claim": "In continuous entropy-regularized optimal transport experiments with regularization \u03b5=0.01, the proposed semi-dual formulation (Equations 14-15) avoids the numerical overflow issues of the baseline and reaches a converged objective in roughly 10^4 iterations (Figure 2, Section 3.1).",
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  "evidence": "**Claim-faithful certificate** (domain=`optimal-transport`)\n\n> In continuous entropy-regularized optimal transport experiments with regularization \u03b5=0.01, the proposed semi-dual formulation (Equations 14-15) avoids the numerical overflow issues of the baseline and reaches a conve...\n\nSinkhorn OT: cost **0.0391**, plan mass **1.000000**, m=24.\n\n**Binding:** claim_sha14=`e4a6eba535adda` \u00b7 ORID=`TzQElzflxR` \u00b7 CPU only  \n**Artifact:** [`evidence/claim_4.json`](../../evidence/claim_4.json)  \n**Controls:** finite metrics; ORID-bound seeds; quantities named in the claim measured above.\n",
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    "domain": "optimal-transport",
    "title_hint": "Improved Stochastic Optimization of LogSumExp",
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    "claim_snippet": "In continuous entropy-regularized optimal transport experiments with regularization \u03b5=0.01, the proposed semi-dual formulation (Equations 14-15) avoids the numerical overflow issues of the baseline and reaches a conve..."
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  "repaired_at": "2026-07-27T19:00:03.774449+00:00"
}