VeriGraphi introduces a knowledge-graph-anchored multi-agent pipeline that produces reliable hierarchical synthesizable Verilog for complex designs such as RISC-V processors.
Autogen: Enabling next-gen llm applications via multi-agent conversations,
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
years
2026 4verdicts
UNVERDICTED 4representative citing papers
AgentGate decomposes routing into action decision and structural grounding stages, allowing small 3B-7B models to dispatch queries competitively on a curated benchmark after targeted fine-tuning.
ROSClaw is a hierarchical framework that unifies vision-language model control with e-URDF-based sim-to-real mapping and closed-loop data collection to enable semantic-physical collaboration among heterogeneous multi-agent robots.
CyberAId is a proposed on-premise multi-agent system that coordinates LLM subagents with classical security tools to improve threat response and regulatory alignment in financial services.
citing papers explorer
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VeriGraphi: A Multi-Agent Framework of Hierarchical RTL Generation for Large Hardware Designs
VeriGraphi introduces a knowledge-graph-anchored multi-agent pipeline that produces reliable hierarchical synthesizable Verilog for complex designs such as RISC-V processors.
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AgentGate: A Lightweight Structured Routing Engine for the Internet of Agents
AgentGate decomposes routing into action decision and structural grounding stages, allowing small 3B-7B models to dispatch queries competitively on a curated benchmark after targeted fine-tuning.
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ROSClaw: A Hierarchical Semantic-Physical Framework for Heterogeneous Multi-Agent Collaboration
ROSClaw is a hierarchical framework that unifies vision-language model control with e-URDF-based sim-to-real mapping and closed-loop data collection to enable semantic-physical collaboration among heterogeneous multi-agent robots.
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CyberAId: AI-Driven Cybersecurity for Financial Service Providers
CyberAId is a proposed on-premise multi-agent system that coordinates LLM subagents with classical security tools to improve threat response and regulatory alignment in financial services.