Develops a semantic signaling game for LLMs with awareness types modeling systematic blindness, Gaussian approximations for decisions, Perfect Bayesian Nash equilibria, and mechanism design for benign outcomes via awareness shaping.
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4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
Outlines a vision and key research challenges for scalable networks of autonomous AI agents drawing on multi-agent systems, networks, and security.
Develops a framework linking token-level technical costs to workflow-level economic value and market design in AI foundation models.
Synthesizes mechanisms of LLM censorship across the model lifecycle and argues that the key issue is making moderation proportionate, accountable, pluralistic, and auditable rather than debating whether moderation should occur.
citing papers explorer
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LLM Semantic Signaling Game and Mechanism Design: Systematic Blindness, Awareness Shaping, and Mindset Dynamics
Develops a semantic signaling game for LLMs with awareness types modeling systematic blindness, Gaussian approximations for decisions, Perfect Bayesian Nash equilibria, and mechanism design for benign outcomes via awareness shaping.
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The Internet of Agentic AI: Communication, Coordination, and Collective Intelligence at Scale
Outlines a vision and key research challenges for scalable networks of autonomous AI agents drawing on multi-agent systems, networks, and security.
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AI Tokenomics: The Economics of Tokens, Computation, and Pricing in Foundation Models
Develops a framework linking token-level technical costs to workflow-level economic value and market design in AI foundation models.
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Understanding Censorship in Large Language Models: From Mechanisms to Governance
Synthesizes mechanisms of LLM censorship across the model lifecycle and argues that the key issue is making moderation proportionate, accountable, pluralistic, and auditable rather than debating whether moderation should occur.