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    <title>ILang on iLang (I Language) Research</title>
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    <description>Recent content in ILang on iLang (I Language) Research</description>
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      <title>I-Lang Conformance Results v1</title>
      <link>https://research.ilang.ai/datasets/ilang-conformance/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/datasets/ilang-conformance/</guid>
      <description>45 model runs against a 320-case deterministic conformance suite, 18–20 September 2026. Best weighted total 0.8417; no run reached the L1 gate. 93.5% of all execution-rule violations fall on a single rule: acting with authority the model does not hold. Every run&amp;rsquo;s per-track scores and per-rule failure counts are published.</description>
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      <title>IML — the I-Lang Machine Layer</title>
      <link>https://research.ilang.ai/protocol/machine-layer/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/protocol/machine-layer/</guid>
      <description>IML is a machine form of iLang v4.x declarations: fixed-width codes derived from the canon, for agent-to-agent transport. Experimental, versioned at 0.5.1, MIT.</description>
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      <title>Judgment Layer Audit v1</title>
      <link>https://research.ilang.ai/datasets/judgment-layer-audit/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/datasets/judgment-layer-audit/</guid>
      <description>Three days of a production agent&amp;rsquo;s messages judged twice — by a cheap always-on judge model and by the operator&amp;rsquo;s written rules. 7,940 messages judged, 2,648 scored against the reference. Agreement 68.4% → 75.1% → 80.9%; 87.2% in the judge&amp;rsquo;s top confidence band. Includes a worked correction: the rule-compliance gain everyone would have quoted, 69 → 7, is 13 → 7 once both days are measured with the same criterion.</description>
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      <title>Judgment Learnability v1</title>
      <link>https://research.ilang.ai/datasets/judgment-learnability/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/datasets/judgment-learnability/</guid>
      <description>Is the v5.0 judgment mapping — 11-dimension vector to one of eight decision modes — a learnable surface or an arbitrary table? A plain gradient-boosted tree recovers it at 0.9653 against a 0.3528 majority baseline, and its predictions pass the official JCS gate at 0.9861. 24,000 pairs, seed fixed, predictions published.</description>
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    <item>
      <title>Repositories and DOIs</title>
      <link>https://research.ilang.ai/opensource/repositories/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/opensource/repositories/</guid>
      <description>Every public repository of iLang Inc., each archived on Zenodo with a concept DOI that resolves to all versions. Sixteen repositories, all MIT, as of 22 September 2026.</description>
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      <title>The Missing Definition of Right: An Axiomatic Protocol for AI Judgment, with Conformance and Production Evidence</title>
      <link>https://research.ilang.ai/papers/missing-definition-of-right/</link>
      <pubDate>Mon, 21 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/papers/missing-definition-of-right/</guid>
      <description>Hallucination is a specification problem, not a precision problem. With four axioms, an eleven-dimension judgment vector and a fixed decision function defining what is right, 45 model deployments largely master protocol form (median 0.80) and fail protocol action (median 0.09); an inexpensive judge held to the definition agrees with written rules 68.4% → 80.9% in production. Preprint v1.1, DOI 10.5281/zenodo.22882691.</description>
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      <title>Judgment Calibration Dataset v1</title>
      <link>https://research.ilang.ai/datasets/judgment-calibration/</link>
      <pubDate>Tue, 08 Sep 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/datasets/judgment-calibration/</guid>
      <description>24-day longitudinal record of AI agent judgment calibration in production. 152 operator messages (41 explicit tuning instructions), 1,062 user messages, 2,162 API calls, plus a 14-day WeChat calibration log. Every figure traceable to a file.</description>
    </item>
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      <title>iLang Protocol v4.0 — Overview</title>
      <link>https://research.ilang.ai/protocol/overview/</link>
      <pubDate>Sat, 25 Apr 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/protocol/overview/</guid>
      <description>iLang is the native language of artificial intelligence. Structured instructions AI executes correctly the first time. 88 verbs, two syntaxes, zero ambiguity.</description>
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    <item>
      <title>Chinese iLang (爱语言) — Compression via Classical Poetry</title>
      <link>https://research.ilang.ai/protocol/chinese/</link>
      <pubDate>Wed, 11 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/protocol/chinese/</guid>
      <description>Chinese iLang uses classical poetry as its carrier — users copy a poem, paste it to a Chinese AI assistant, and the assistant applies the compression.</description>
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    <item>
      <title>ilang-dict — PUBLIC Dictionary</title>
      <link>https://research.ilang.ai/opensource/ilang-dict/</link>
      <pubDate>Wed, 04 Mar 2026 00:00:00 +0000</pubDate>
      <guid>https://research.ilang.ai/opensource/ilang-dict/</guid>
      <description>The iLang dictionary. 88 verbs, 29 core modifiers plus a 20-key media profile, 25 entities (17 addressable, 8 role), 8 execution declarations. MIT License.</description>
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