arXiv AI
Jun 30
Robust Multi-Agent LLMs under Byzantine Faults
arXiv:2605. 09076v2 Announce Type: replace-cross Abstract: Large language model (LLM) agents increasingly collaborate over peer-to-peer networks to improve their reliability.
Resilient Consensus in Agentic AI
arXiv:2606. 15024v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed in multi-agent systems where they must coordinate and agree on shared decisions.
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arXiv AI
Aug 10
Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On
arXiv:2605. 19035v2 Announce Type: replace Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution.
arXiv Machine Learning
Sep 23
Fully Byzantine-Resilient Multi-Agent Reinforcement Learning
arXiv:2609.25701v1 Announce Type: new Abstract: We study distributed Byzantine-resilient actor-critic multi-agent reinforcement learning (AC-MARL), where agents collectively learn policies through lo...
arXiv Machine Learning
4d ago
Bregman Consensus
arXiv:2609.35930v1 Announce Type: cross Abstract: Consider a community of agents who are seeking consensus on a set of parameters. The agents agree to use the same Bregman-type divergence to quantify...
arXiv Machine Learning
Jul 7
Social Networks of LLM Agents
arXiv:2607. 03695v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly deployed in interacting populations, raising the question of what such populations come to believe collectively.
arXiv AI
Aug 6
Is Monitoring Enough? Strategic Agent Selection For Stealthy Attack in Multi-Agent Discussions
arXiv:2603. 21194v2 Announce Type: replace-cross Abstract: Multi-agent discussions have been widely adopted, motivating growing efforts to develop attacks that expose their vulnerabilities.
arXiv Machine Learning
Jul 15
When and Why Does Multi-Agent Debate Fail and Does It Really Underperform?
arXiv:2510. 20963v2 Announce Type: replace Abstract: Multi-agent debate (MAD) was proposed as a promising approach for ensembling the wisdom of multiple large language models (LLMs) to improve reasoning and provide effective supervision to superhuman LLMs.
arXiv AI
Sep 25
Epistemic-Probabilistic Model for Guarded Multi-Agent LLM Coordination
The paper introduces Epistemic Probabilistic Language Agents (EPLA), a neuro‑symbolic architecture designed to enable coordination among multi‑agent large language models (LLMs) under uncertainty. EPLA employs a Symbolic Guard that provides structured diagnostic feedback, allowing the LLM to generate typed actions while the Guard controls their execution against an authoritative symbolic state. The authors formalize an epistemic layer using gossip testbeds and epistemic lottery gossip models, combining view‑based call histories with agent‑indexed probability weights to address gaps in social behavior and coordination mechanisms for agentic LLMs.
arXiv AI
Jun 29
Seven Security Challenges That Must be Solved in Cross-domain Multi-agent LLM Systems
arXiv:2505. 23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disaster response, supply-chain optimization, and other tasks that demand decentralized expertise without surrendering data ownership.
arXiv Machine Learning
5d ago
Reinforcement Learning of Communication in a Mesh of Small Language Models
The paper introduces TalkMesh, a decentralized network of small language model agents that learn to communicate effectively during inference. Each agent proposes an answer, scores it with a confidence head, and the most confident agent broadcasts a hint; lower‑confidence agents revise their proposals if a new suggestion scores higher. This gossip‑based consensus, trained via group relative policy optimization, enables a mesh of three agents to match the accuracy of majority voting over 32 samples, and scales to larger meshes to significantly boost performance on benchmarks like GSM8K and MATH-500.
arXiv AI
Sep 16
Agentic Societies Need a Social Harness
arXiv:2609.17527v1 Announce Type: cross Abstract: An agentic society is a collection of AI agents that coordinate autonomously across trust boundaries, on behalf of different principals whose objecti...
arXiv AI
Jun 4
SMAC-Talk: A Natural Language Extension of the StarCraft Multi-Agent Challenge for Large Language Models
arXiv:2606. 04202v1 Announce Type: new Abstract: As LLMs become more widely deployed, they are increasingly expected to work alongside other AI agents rather than operating in isolation.