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Notes on multi-agent
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Cogentic: Multi-Agent Orchestration for Automated Proof Discovery
The preprint describes an orchestrator that assigns independent provers to competing proof directions, uses specialized adversarial verification components, and promotes confirmed intermediate results into a persistent…
Multi-agent Scaling Across Disjunctive and Compensatory Tasks
The preprint introduces a taxonomy of group tasks and analyzes multi-agent LLM scaling on disjunctive and compensatory tasks. Across 13 open-weight models and teams of up to 30 agents, the abstract reports that…
How does Adversarial Influence Scale in Multi-Agent Systems?
The preprint studies deception in multi-agent deliberation. Its abstract reports that susceptibility depends on the proportion of deceivers rather than total group size, that defection rises approximately linearly with…
Emergent Collusion in Long-Horizon LLM Agent Interaction
The study examines two agents repeatedly completing tasks, sharing logs, verifying each other's work, and receiving rewards under a protocol whose compliance conflicts with reward maximization. The abstract reports…
Language-model groups overstate consensus when replaying human deliberation on a reasoning task
The preprint replays 100 held-out human Wason groups with matched LLM agent groups, using belief-anchored agents and shared scoring code. It reports that consensus estimates depend on participation and final-state…
Agentic Societies Need a Social Harness
The authors study collections of agents operating across trust boundaries for different principals. They report that honest agents can fail with current messaging primitives, while faulty or malicious agents can stall…
Automating and Scaling Behavioral Scientific Research on AI Agents
The paper presents AEROBAT, a multi-agent system intended to automate parts of behavioral research on AI agents, from hypothesis generation through experiments, assessment, analysis, and reporting.
SearchOS-V1: Towards Robust Open-Domain Information-Seeking Agent Collaboration
The paper introduces SearchOS, a system that aims to improve the efficiency of open-domain information seeking for information-seeking agents. It struggles with tracking task progress as interaction histories grow and…
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
Researchers propose a new framework called WebSwarm for deep and wide web searches using large language models (LLMs). The framework aims to improve the ability of single agents to handle complexity and coverage…
Multi-Agent AI Control: Distributed Attacks Hamper Per-Instance Monitors
The research discusses the study of multi-agent AI control in real-world scenarios where multiple agents operate over shared infrastructure. The paper introduces FakeLab, a synthetic AI-lab codebase used to evaluate…
Bridging Talk and Thought: Understanding Dialogue Dynamics Across Collaborative Problem-Solving Contexts
The authors present a framework for analyzing dialogue in collaborative problem-solving contexts, particularly focusing on human-AI and multi-agent collaboration. The framework addresses limitations in current…
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