LM agents' changeable modules prevent persistent identity and sanction sensitivity, making reputation mechanisms structurally inapplicable and requiring protocol-based behavioral harnesses instead.
Agentic web: weaving the next web with
7 Pith papers cite this work. Polarity classification is still indexing.
7
Pith papers citing it
years
2026 7verdicts
UNVERDICTED 7representative citing papers
GRAIL achieves over 79 times lower latency than LLM-parsing baselines and higher Recall@10 than vector search by combining SLM-enhanced prediction, pseudo-document expansion, and MaxSim resonance on the new AgentTaxo-9K dataset of 9,240 agents.
AI-Sinkhole uses AI classification with quantized LLMs and Pi-Hole DNS blocking to dynamically prevent access to LLM services during student evaluations, reporting F1 scores above 0.83.
A framework structures AI-generated content with prompt-aware metadata and verifiable credentials to support reliable assessment and reuse by agents.
Proposes ten design principles for an agent-first web with changes to access (agent identification and dual content), economics (intent-based tiers and tokens), and content (ATML and provenance chains) to address blocking and epistemic recursion.
WebUncertainty improves web agent performance on benchmarks by adaptively selecting planning modes based on task uncertainty and using confidence-induced action uncertainty in MCTS to quantify aleatoric and epistemic uncertainty for better decisions.
Position paper proposing 'scaling the harness' as the next bottleneck in agentic AI, with three core system challenges and an open-source reference implementation called CheetahClaws.
citing papers explorer
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Dissociative Identity: Language Model Agents Lack Grounding for Reputation Mechanisms
LM agents' changeable modules prevent persistent identity and sanction sensitivity, making reputation mechanisms structurally inapplicable and requiring protocol-based behavioral harnesses instead.
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GRAIL: A Deep-Granularity Hybrid Resonance Framework for Real-Time Agent Discovery via SLM-Enhanced Indexing
GRAIL achieves over 79 times lower latency than LLM-parsing baselines and higher Recall@10 than vector search by combining SLM-enhanced prediction, pseudo-document expansion, and MaxSim resonance on the new AgentTaxo-9K dataset of 9,240 agents.
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Fighting AI with AI: AI-Agent Augmented DNS Blocking of LLM Services during Student Evaluations
AI-Sinkhole uses AI classification with quantized LLMs and Pi-Hole DNS blocking to dynamically prevent access to LLM services during student evaluations, reporting F1 scores above 0.83.
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A Prompt-Aware Structuring Framework for Reliable Reuse of AI-Generated Content in the Agentic Web
A framework structures AI-generated content with prompt-aware metadata and verifiable credentials to support reliable assessment and reuse by agents.
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Towards an Agent-First Web: Redesigning the Web for AI Agents
Proposes ten design principles for an agent-first web with changes to access (agent identification and dual content), economics (intent-based tiers and tokens), and content (ATML and provenance chains) to address blocking and epistemic recursion.
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WebUncertainty: Dual-Level Uncertainty Driven Planning and Reasoning For Autonomous Web Agent
WebUncertainty improves web agent performance on benchmarks by adaptively selecting planning modes based on task uncertainty and using confidence-induced action uncertainty in MCTS to quantify aleatoric and epistemic uncertainty for better decisions.
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From Model Scaling to System Scaling: Scaling the Harness in Agentic AI
Position paper proposing 'scaling the harness' as the next bottleneck in agentic AI, with three core system challenges and an open-source reference implementation called CheetahClaws.