add paper

Author: kadubon

works.html

@@ -70,6 +70,26 @@
         "https://huggingface.co/kadubon"
       ],
       "publication": [
+        {
+          "@type": "ScholarlyArticle",
+          "name": "AI Benchmark Half-Life in Recursive Corpora: A Theory of Validity Decay under Semantic Leakage and Regeneration",
+          "genre": "Preprint",
+          "url": "https://doi.org/10.5281/zenodo.18954286",
+          "datePublished": "2026-03-11",
+          "author": [
+            {
+              "@type": "Person",
+              "name": "K Takahashi"
+            }
+          ],
+          "isPartOf": {
+            "@type": "Periodical",
+            "name": "Zenodo"
+          },
+          "citation": "K Takahashi (2026-03-11). AI Benchmark Half-Life in Recursive Corpora: A Theory of Validity Decay under Semantic Leakage and Regeneration. Zenodo. https://doi.org/10.5281/zenodo.18954286",
+          "abstract": "This preprint develops a theory of AI benchmark half-life in recursive corpora under semantic leakage and regeneration, yielding validity-decay bounds and monitoring rules for evaluation systems whose items and solution traces re-enter public data. It models benchmark validity through discriminative power and construct validity, and derives jump-aware lifetime bounds, partial-identification results, portfolio design criteria, and safe sequential control under ambiguity and partial observability.",
+          "keywords": "AI benchmark half-life, recursive corpora, semantic leakage, validity decay, benchmark contamination, construct validity, discriminative power, dynamic benchmarks, partial identification, sequential monitoring, lineage observability, model metrology"
+        },
         {
           "@type": "ScholarlyArticle",
           "name": "When Should Inference Be Split? A Fixed-Budget Theory of Predictable Multi-Agent Advantage under Local Context Ceilings",
@@ -3737,6 +3757,27 @@ <h1>
        Machine-readable endpoints: <a href="https://kadubon.github.io/github.io/feed.xml">RSS feed</a>, <a href="https://kadubon.github.io/github.io/CITATION.cff">CITATION.cff</a>, <a href="https://kadubon.github.io/github.io/robots.txt">robots.txt</a>, and <a href="https://kadubon.github.io/github.io/sitemap.xml">sitemap.xml</a>.
       </p>
       <ol class="publication-list">
+       <li>
+        <div class="publication-item">
+         <h3>
+          AI Benchmark Half-Life in Recursive Corpora: A Theory of Validity Decay under Semantic Leakage and Regeneration
+         </h3>
+         <p>
+          <span class="publication-meta">
+           Preprint | Published: 2026-03-11
+          </span>
+          <a href="https://doi.org/10.5281/zenodo.18954286" target="_blank">
+           DOI: 10.5281/zenodo.18954286
+          </a>
+         </p>
+         <p class="publication-abstract">
+          Abstract: This preprint develops a theory of AI benchmark half-life in recursive corpora under semantic leakage and regeneration, yielding validity-decay bounds and monitoring rules for evaluation systems whose items and solution traces re-enter public data. It models benchmark validity through discriminative power and construct validity, and derives jump-aware lifetime bounds, partial-identification results, portfolio design criteria, and safe sequential control under ambiguity and partial observability.
+         </p>
+         <p class="publication-keywords">
+          Keywords: AI benchmark half-life, recursive corpora, semantic leakage, validity decay, benchmark contamination, construct validity, discriminative power, dynamic benchmarks, partial identification, sequential monitoring, lineage observability, model metrology
+         </p>
+        </div>
+       </li>
        <li>
         <div class="publication-item">
          <h3>