ai-research-survey

Systematic scan of agentic development research. What's signal, what's noise.
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paper_type.json (328B)


      1 {
      2   "paper_type": "empirical",
      3   "reason": "Primary contribution is quantitative experimental findings on LLM judge performance (80%+ agreement rates, bias identification, and mitigation strategies) across controlled and crowdsourced settings, with MT-Bench serving as an evaluation vehicle rather than the main contribution."
      4 }

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