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    "headline": "Police Academy Students Deliver Aid to NTT Earthquake Victims",
    "dek": "Master's students from the Indonesian National Police Academy distributed essential goods and trauma counseling to earthquake survivors in East Nusa Tenggara.",
    "prose": "According to BNPB data updated on August 29, 2026, the earthquake caused 111 deaths and displaced hundreds of thousands of people across seven regencies in NTT. [^1]\n\nMaster's students from the Sekolah Tinggi Ilmu Kepolisian (STIK) Lemdiklat Polri, 16th cohort, distributed social aid to earthquake victims in East Nusa Tenggara (NTT) on August 29, 2026. [^2]\n\nThe study demonstrates that behaviorally effective LoRA writes are sparse, structured, and far more concentrated than the raw low-rank parameterization suggests. [^3]\n\nAgustinus Nong Viles, a camp coordinator in Dusun Wairhabi, received the aid on behalf of 159 households from three villages: Dusun Wairhabi, Dusun Habigahar, and Kelurahan Waiot. [^4]\n\nThe aid was delivered to displacement camps in Dusun Wairhabi, Desa Habi, Kecamatan Kangae, Kabupaten Sikka, and via Lorens Say port to Pelabuhan Palue. [^5]\n\nAcross GSM8K, MathQA, and AQuA benchmarks, per-module top-k continuation reached its optimum at k in {2, 4} in all twelve seed-level cases tested. [^6]\n\nResearchers used Learned-Basis LoRA, a learned-basis continuation recipe, to expose the structure of LoRA writes. [^7]\n\nThe Learned-Basis LoRA recipe warms up an unconstrained adapter, converts its learned write columns into a module-wise orthonormal basis, freezes that basis, and continues training inside the constrained parameterization. [^8]",
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