Hugging Face Trending Papers
Discovering Adaptive Transmission Programs for Collective Innovation
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arXiv AI
Aug 26
Discovering Adaptive Transmission Programs for Collective Innovation
The paper presents a method for designing state‑aware transmission protocols that guide how information and resources are shared among agents in a collective discovery task. Using LLM‑guided evolutionary search, the authors evolve protocols that outperform existing baselines by up to 37%, and show that the advantage stems from conditioning on content and agent states rather than just network topology. The evolved protocols also generalize across different domains and agent populations, indicating that such protocols can be discovered in silico and may inform AI‑assisted coordination systems for human collective intelligence.
arXiv AI
Jun 30
HyphaeDB: A Living Knowledge Topology for Agent-First Memory
arXiv:2606. 28781v1 Announce Type: new Abstract: Every existing vector database and agent memory framework treats memory as passive storage that agents query explicitly.
arXiv AI
Jun 2
Scaling Behavior of Single LLM-Driven Multi-Agent Systems
arXiv:2606. 00655v1 Announce Type: cross Abstract: The burgeoning field of LLM-based Multi-Agent Systems (MAS) promises to tackle complex tasks through collaborative intelligence, yet fundamental questions regarding their scaling behavior and intrinsic collective dynamics remain underexplored.
arXiv AI
Jun 6
Benchmarking Emergent Coordination in Large-Scale LLM Populations: An Evaluation Framework on the MoltBook Archive
arXiv:2603. 03555v3 Announce Type: replace-cross Abstract: As multi-agent Large Language Model (LLM) systems scale, evaluating their emergent coordination dynamics becomes increasingly critical.
arXiv Computation and Language
Aug 27
SwarmWorld: Stigmergic technological evolution in societies of language-model agents
SwarmWorld demonstrates that homogeneous language‑model agents can self‑organize into evolving technological societies without assigned roles or direct communication. In a spatial environment, agents explore, process resources, construct artifacts, and write executable controllers that are later evaluated by a deterministic simulator. The resulting societies develop broader, more resilient technological portfolios than isolated search, with agents differentiating into exploration, construction, maintenance, and coordination roles as the world matures.
Hugging Face Trending Papers
Aug 21
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,...