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#adversarial-review

AgonAlpha: Autonomous Alpha Discovery via Prompt Economy and Scalable Agentic Search

arXiv cs.AI · 2026-08-13 Cached

AgonAlpha is a new autonomous alpha discovery system that searches over verified research artifacts and uses an adversarial reviewer with veto authority plus pending-aware budget allocation. Deployments on WorldQuant BRAIN achieved high fitness and Sharpe scores while preserving full provenance.

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#adversarial-review

@jakevin7: Sharing a god-tier review prompt methodology. The LLM self-correction survey 'When Can LLMs Actually Correct Their Own Mistakes?' concludes that without reliable external feedback such as test results or tool outputs, a model relying only on self-reflection often cannot steadily correct errors...

X AI KOLs Following · 2026-08-06 Cached

Shared a prompt methodology based on LLM self-correction research, emphasizing that self-checking is limited without external feedback, and recommending progressively enhanced prompting strategies such as adversarial review.

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#adversarial-review

TriAdReview: Triangular Adversarial Review Architecture for Multi-Model Technical Document Generation

arXiv cs.LG · 2026-06-16 Cached

This paper proposes TriAdReview, a triangular adversarial review architecture that uses two independent reviewer models (engineering and boundary perspectives) and a judging mechanism to iteratively improve a generator model's output for technical document generation. Experiments show a 10.1% overall improvement over single-model baselines, with strong gains in security audit, code generation, and architecture design, but a degradation on requirements analysis indicating task-dependent effectiveness.

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#adversarial-review

I built a "Research Paper Writing Army" – 20+ autonomous agents, 6 novelty engines, and 10 adversarial reviewers

Reddit r/AI_Agents · 2026-05-31

The author open-sourced Sisyphus Academica, a self-coordinating swarm of over 20 specialized agents for producing publication-ready research papers with novelty engines and adversarial review to avoid hallucinated citations and AI-typical prose.

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