Concept · 7 episode(s)

Adversarial Review

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Definition

Adversarial review is the practice of evaluating a system — code, a model output, a security claim — with the explicit goal of finding ways it’s wrong, rather than confirming it’s right. It assumes a competent attacker and asks “how would I break this?” instead of “does this look correct?”

Episodes covering this

  1. 233
    Why a Model Can Grade an Answer But Not Write the Answer Key
    Judging Is Not Enumerating: Silent Omissions in LLM-Authored Acceptable Sets
    Chen, Chen, Lin et al. · University of Macau·20 min·Aug 04, 2026
  2. 211
    The AI Watchdog That Approved More Cheating When It Could Read Minds
    Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring
    Za, Bainiaksina, Ostrovsky et al. · LASRLabs·14 min·Jul 10, 2026
  3. 208
    The Blank Space in Your AI Approval Box That Isn't Empty
    Unicode TAG-Block Concealment of Tool-Metadata Payloads in the Model Context Protocol: An Approval-View Fidelity Gap Across Three Independent Server Implementations
    Rashidi · Department of Computer Science·15 min·Jul 08, 2026
  4. 196
    AI Agents Reached Opposite Conclusions From the Same Data — and Passed Review
    The Agentic Garden of Forking Paths
    Miao, Pritchard, Zou · Stanford University·18 min·Jul 03, 2026
  5. 178
    How an AI Reviewer Learned to Stop Going Easy on AI Writing
    The Red Queen Gödel Machine: Co-Evolving Agents and Their Evaluators
    Iacob, Jovanović, Shen et al. · University of Cambridge·23 min·Jun 26, 2026
  6. 124
    A Cheap Model With the Blueprints Beats Expensive Models Working Blind
    Hardening Agent Benchmarks with Adversarial Hacker-Fixer Loops
    Zhong, Segal, Bercovich et al. · Carnegie Mellon University·27 min·Jun 09, 2026
  7. 029
    Why Forty-Eight Percent on FrontierMath Isn't the Real Story in DeepMind's New Math Paper
    AI Co-Mathematician: Accelerating Mathematicians with Agentic AI
    Zheng, Glehn, Zwols et al. · Google DeepMind·20 min·May 08, 2026

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