A publicly released dataset of 15,591 configuration artifacts for five agentic AI coding tools, drawn from 4,738 GitHub repositories along with associated files and AI-co-authored commits.
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Agentic AI: A Conceptual Taxonomy, Applications and Challenges
16 Pith papers cite this work, alongside 10 external citations. Polarity classification is still indexing.
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Assistive agents for BVI users need accessibility alignment as a core design goal, with a proposed lifecycle pipeline, because sighted assumptions cause unfixable failures in verification, risk, and interaction.
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.
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
A graph-based propagation model for error cascades in LLM multi-agent systems plus a genealogy-graph governance plugin that prevents final infection in at least 89% of runs across tested frameworks.
Integrates LLMs with domain ontologies and SHACL constraints to produce accurate, explainable structured outputs from cybersecurity logs for threat intelligence.
HAMLET is a hierarchical adaptive multi-agent framework that creates narrative blueprints and conducts autonomous live embodied theater performances with LLM agents that handle dialogue, decision-making, and physical prop interactions, evaluated via the introduced HAMLETJudge critic model.
Presents the Agents All the Way Down methodology with two preconditions and three repeatable practices for building and maintaining custom AI agents, distilled from a ten-day production implementation.
Systematic review of agentic AI in the SDLC finds output verifiability drives industrial adoption in later phases, with Planner-Executor-Reviewer as the dominant pattern, plus a new multi-agent LLM screening pipeline for high-volume SLRs.
The paper analyzes CPU bottlenecks in agentic AI serving, selects representative workloads, and demonstrates that CPU-aware scheduling optimizations COMB and MAS can reduce P50 latency by up to 1.7x and total latency by up to 2.49x on two hardware systems.
OntoLogX is a system that applies LLMs with ontology guidance, RAG, and iterative fixes to build valid knowledge graphs from cybersecurity logs and predict ATT&CK tactics from aggregated sessions.
Proposes a DLT-anchored architecture extending the A2A protocol with on-chain AgentCards and x402 micropayments to enable multi-agent economies.
The survey structures agentic reasoning for LLMs into foundational, self-evolving, and collective multi-agent layers while distinguishing in-context orchestration from post-training optimization and reviewing applications across domains.
Fall detection and prediction are reformulated as anomaly detection tasks within an agentic AI system to enable adaptive, proactive risk management in human movement.
Flowr is an agentic AI framework that decomposes retail supply chain workflows into coordinated LLM-based agents with human-in-the-loop oversight to automate operations in large supermarket chains.
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.
citing papers explorer
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A Dataset of Agentic AI Coding Tool Configurations
A publicly released dataset of 15,591 configuration artifacts for five agentic AI coding tools, drawn from 4,738 GitHub repositories along with associated files and AI-co-authored commits.
-
Position: Assistive Agents Need Accessibility Alignment
Assistive agents for BVI users need accessibility alignment as a core design goal, with a proposed lifecycle pipeline, because sighted assumptions cause unfixable failures in verification, risk, and interaction.
-
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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Agentic Business Process Management: A Research Manifesto
Agentic Business Process Management reframes BPM around autonomous agents that must exhibit framed autonomy, explainability, conversational actionability, and self-modification to keep their actions aligned with organizational objectives.
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From Spark to Fire: Modeling and Mitigating Error Cascades in LLM-Based Multi-Agent Collaboration
A graph-based propagation model for error cascades in LLM multi-agent systems plus a genealogy-graph governance plugin that prevents final infection in at least 89% of runs across tested frameworks.
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Enabling Transparent Cyber Threat Intelligence Combining Large Language Models and Domain Ontologies
Integrates LLMs with domain ontologies and SHACL constraints to produce accurate, explainable structured outputs from cybersecurity logs for threat intelligence.
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HAMLET: A Hierarchical and Adaptive Multi-Agent Framework for Live Embodied Theatrics
HAMLET is a hierarchical adaptive multi-agent framework that creates narrative blueprints and conducts autonomous live embodied theater performances with LLM agents that handle dialogue, decision-making, and physical prop interactions, evaluated via the introduced HAMLETJudge critic model.
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Agents All the Way Down; A Methodology for Building Custom AI Agents from Substrate to Production
Presents the Agents All the Way Down methodology with two preconditions and three repeatable practices for building and maintaining custom AI agents, distilled from a ten-day production implementation.
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Assistance to Autonomy: A Systematic Literature Review of Agentic AI across the Software Development Life Cycle
Systematic review of agentic AI in the SDLC finds output verifiability drives industrial adoption in later phases, with Planner-Executor-Reviewer as the dominant pattern, plus a new multi-agent LLM screening pipeline for high-volume SLRs.
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Towards Understanding, Analyzing, and Optimizing Agentic AI Execution: A CPU-Centric Perspective
The paper analyzes CPU bottlenecks in agentic AI serving, selects representative workloads, and demonstrates that CPU-aware scheduling optimizations COMB and MAS can reduce P50 latency by up to 1.7x and total latency by up to 2.49x on two hardware systems.
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OntoLogX: Ontology-Guided Knowledge Graph Extraction from Cybersecurity Logs with Large Language Models
OntoLogX is a system that applies LLMs with ontology guidance, RAG, and iterative fixes to build valid knowledge graphs from cybersecurity logs and predict ATT&CK tactics from aggregated sessions.
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Towards Multi-Agent Economies: Enhancing the A2A Protocol with Ledger-Anchored Identities and x402 Micropayments for AI Agents
Proposes a DLT-anchored architecture extending the A2A protocol with on-chain AgentCards and x402 micropayments to enable multi-agent economies.
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Agentic Reasoning for Large Language Models
The survey structures agentic reasoning for LLMs into foundational, self-evolving, and collective multi-agent layers while distinguishing in-context orchestration from post-training optimization and reviewing applications across domains.
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Integrating Anomaly Detection into Agentic AI for Proactive Risk Management in Human Activity
Fall detection and prediction are reformulated as anomaly detection tasks within an agentic AI system to enable adaptive, proactive risk management in human movement.
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Flowr -- Scaling Up Retail Supply Chain Operations Through Agentic AI in Large Scale Supermarket Chains
Flowr is an agentic AI framework that decomposes retail supply chain workflows into coordinated LLM-based agents with human-in-the-loop oversight to automate operations in large supermarket chains.
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AI Trust OS -- A Continuous Governance Framework for Autonomous AI Observability and Zero-Trust Compliance in Enterprise Environments
AI Trust OS is a proposed always-on operating layer that discovers undocumented AI systems via telemetry and produces continuous zero-trust compliance artifacts for regulations including ISO 42001, EU AI Act, SOC 2, GDPR, and HIPAA.