DOLORES, an agent using a formal language for meta-reasoning to construct adaptive scaffolds on the fly, outperforms prior scaffolding methods by 24.8% on average across four hard benchmarks and multiple model sizes.
arXiv preprint arXiv:2502.01635 , year =
5 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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ClawNet digitizes human collaborative relationships into a network of identity-governed AI agents that collaborate on behalf of their owners through a central orchestrator enforcing binding and verification.
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The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
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citing papers explorer
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Deep Reasoning in General Purpose Agents via Structured Meta-Cognition
DOLORES, an agent using a formal language for meta-reasoning to construct adaptive scaffolds on the fly, outperforms prior scaffolding methods by 24.8% on average across four hard benchmarks and multiple model sizes.
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ClawNet: Human-Symbiotic Agent Network for Cross-User Autonomous Cooperation
ClawNet digitizes human collaborative relationships into a network of identity-governed AI agents that collaborate on behalf of their owners through a central orchestrator enforcing binding and verification.
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The Agentic Web Requires New Normative Infrastructure
The web's anti-bot regime should be replaced by a framework that presumptively lets user-authorized AI agents act for their principals, requires platforms to disclose access policies, and permits agent blocking only when proportionate to concrete harms.
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The 2025 AI Agent Index: Documenting Technical and Safety Features of Deployed Agentic AI Systems
The 2025 AI Agent Index catalogs technical and safety details for 30 deployed AI agents and finds low developer transparency on safety, evaluations, and societal impacts.
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Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safety
Chain-of-thought monitorability provides a promising but fragile method for AI safety oversight that developers should actively preserve.