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When Is Collective Intelligence a Lottery? Multi-Agent Scaling Laws for Memetic

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25 Mar
Beyond Preset Identities: How Agents Form Stances and Boundaries in Generative Societies

arXiv:2603.23406v1 Announce Type: new Abstract: While large language models simulate social behaviors, their capacity for stable stance formation and identity negotiation during

REPORT · HOW · ArXiv CS.AIOPEN STORY
27 Apr
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

arXiv:2604.22748v1 Announce Type: new Abstract: As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment

REPORT · WHAT · ArXiv CS.AIOPEN STORY
6 May
12 Angry AI Agents: Evaluating Multi-Agent LLM Decision-Making Through Cinematic Jury Deliberation

arXiv:2605.01986v1 Announce Type: new Abstract: What if the twelve jurors of Sidney Lumet's 12 Angry Men (1957) were not men, but large language models? Would the one juror who

REPORT · WHO · ArXiv CS.AIOPEN STORY
27 Apr
Superminds Test: Actively Evaluating Collective Intelligence of Agent Society via Probing Agents

arXiv:2604.22452v1 Announce Type: new Abstract: Collective intelligence refers to the ability of a group to achieve outcomes beyond what any individual member can accomplish

REPORT · HOW · ArXiv CS.AIOPEN STORY
2 Apr
"Who Am I, and Who Else Is Here?" Behavioral Differentiation Without Role Assignment in Multi-Agent LLM Systems

arXiv:2604.00026v1 Announce Type: cross Abstract: When multiple large language models interact in a shared conversation, do they develop differentiated social roles or converge

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31 Mar
AutoMS: Multi-Agent Evolutionary Search for Cross-Physics Inverse Microstructure Design

arXiv:2603.27195v1 Announce Type: new Abstract: Designing microstructures that satisfy coupled cross-physics objectives is a fundamental challenge in material science. This

REPORT · WHERE · ArXiv CS.AIOPEN STORY
16 Oct
Kolab: Benchmarking Human-Agent Collaboration in Long-Horizon Workflows

arXiv:2610.21109v1 Announce Type: new Abstract: When humans collaborate with AI agents on long-horizon tasks, what happens to the agents' contributions? For solving long-horizon

REPORT · WHEN · ArXiv CS.AIOPEN STORY
25 Mar
MemCollab: Cross-Agent Memory Collaboration via Contrastive Trajectory Distillation

arXiv:2603.23234v1 Announce Type: new Abstract: Large language model (LLM)-based agents rely on memory mechanisms to reuse knowledge from past problem-solving experiences.

REPORT · HOW · ArXiv CS.AIOPEN STORY
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