Hugging Face Trending Papers
Rethinking Multi-Agent Collaboration: When More Is Less
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arXiv AI
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Rethinking Multi-Agent Collaboration: When More Is Less
arXiv:2609.19759v1 Announce Type: new Abstract: The rapid advancement of large language models and single-agent harnesses has reshaped the landscape of autonomous systems, raising a critical question...
Hugging Face Trending Papers
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Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence
LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms including Prompt Engineering to elicit model capabilities,...
arXiv AI
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Focus Is All You Need: Adaptive Goal-aware Attention Orchestration for Multi-Agent Graph Systems
arXiv:2607. 23678v1 Announce Type: new Abstract: Large language models (LLMs) enable autonomous agents for reasoning, planning, and tool use.
arXiv Machine Learning
Jul 22
Node-as-Agent: Graph Agentic Network
arXiv:2508. 00429v5 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have achieved remarkable success in graph-based learning by propagating information among neighbor nodes via predefined aggregation mechanisms.
arXiv AI
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AdaSTORM: Scaling LLM Reasoning on Dynamic Graphs via Adaptive Spatio-Temporal Multi-Agent Collaboration
arXiv:2606. 16328v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable potential in dynamic graph reasoning, but suffer from a scaling bottleneck: current models can only handle graphs with tens of nodes, constrained by exponential reasoning overhead and finite context windows.
arXiv AI
Jul 7
Optimal-Agent-Selection: State-Aware Routing Framework for Efficient Multi-Agent Collaboration
arXiv:2511. 02200v2 Announce Type: replace Abstract: The emergence of multi-agent systems powered by large language models (LLMs) has unlocked new frontiers in complex task-solving, enabling diverse agents to integrate unique expertise, collaborate flexibly, and address challenges unattainable for individual models.