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      <title>Paper Roundup: LLM Safety &amp; RLHF at NeurIPS 2025 and ICLR 2026</title>
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      <pubDate>Wed, 29 Apr 2026 00:00:00 +0700</pubDate>
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      <description>A curated list of papers on alignment, preference optimization, mechanistic interpretability, and reasoning from the two biggest ML conferences this cycle — with personal takes on the ones that matter most.</description>
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      <title>Ara: What If Research Papers Were Executable?</title>
      <link>https://learning-notes-dz2.pages.dev/posts/2026-04-28/</link>
      <pubDate>Tue, 28 Apr 2026 00:00:00 +0700</pubDate>
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      <description>A deep look at Agent-Native Research Artifacts (Ara) — a proposed replacement for academic PDFs that packages research as machine-executable knowledge bundles. What it gets right, what it gets wrong, and why it matters for AI-assisted research.</description>
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      <title>Sparse Autoencoders: The Swiss Army Knife of Interpretability</title>
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      <pubDate>Wed, 08 Apr 2026 00:00:00 +0700</pubDate>
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      <description>SAEs went from niche interpretability tool to dominant research theme in one year. Where they&amp;rsquo;re being applied, what they reveal, and the fundamental limitations nobody has solved yet.</description>
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      <title>A Curated Guide to LLMs, Reinforcement Learning, and AI Safety</title>
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      <description>Books, papers, conferences, and researchers — a personal resource list for anyone going deep into LLMs, RL, and AI safety.</description>
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