Introduces coalgebraic shortest path problem as unifying framework and a coalgebraic Dijkstra algorithm that solves it correctly under a necessary and sufficient condition with classical complexity.
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Hypergraph modeling of SNNs improves neuron-to-core mapping on neuromorphic hardware by exploiting hyperedge overlap and locality for better partitioning and placement than graph-based methods.
Holos is a five-layer LLM-based multi-agent system architecture using the Nuwa engine for agent generation, a market-driven Orchestrator for coordination, and an endogenous value cycle for incentive-compatible persistence in the Agentic Web.
GraphBench is a comprehensive multi-domain benchmark suite for graph learning with standardized evaluation protocols and baselines from message-passing and transformer models.
A branch-and-bound algorithm with custom node selection, branching rules, and conflict definitions solves the logic-constrained shortest path problem for flight planning with traffic flow restrictions, showing order-of-magnitude speedups on a public global dataset with 20000 real constraints.
citing papers explorer
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A Coalgebraic Dijkstra Algorithm
Introduces coalgebraic shortest path problem as unifying framework and a coalgebraic Dijkstra algorithm that solves it correctly under a necessary and sufficient condition with classical complexity.
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A Case for Hypergraphs to Model and Map SNNs on Neuromorphic Hardware
Hypergraph modeling of SNNs improves neuron-to-core mapping on neuromorphic hardware by exploiting hyperedge overlap and locality for better partitioning and placement than graph-based methods.
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Holos: A Web-Scale LLM-Based Multi-Agent System for the Agentic Web
Holos is a five-layer LLM-based multi-agent system architecture using the Nuwa engine for agent generation, a market-driven Orchestrator for coordination, and an endogenous value cycle for incentive-compatible persistence in the Agentic Web.
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GraphBench: Next-generation graph learning benchmarking
GraphBench is a comprehensive multi-domain benchmark suite for graph learning with standardized evaluation protocols and baselines from message-passing and transformer models.
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Logic-Constrained Shortest Paths for Flight Planning
A branch-and-bound algorithm with custom node selection, branching rules, and conflict definitions solves the logic-constrained shortest path problem for flight planning with traffic flow restrictions, showing order-of-magnitude speedups on a public global dataset with 20000 real constraints.