Collective Intelligence
No mentions found
This entity hasn't been tracked yet, or Iris is still building its knowledge base.
Related Articles from SNS
OpenHospital: A Thing-in-itself Arena for Evolving and Benchmarking LLM-based Collective Intelligence
arXiv:2603.14771v3 Announce Type: replace Abstract: Large Language Model (LLM)-based Collective Intelligence (CI) presents a promising approach to overcoming the data wall and continuously boosting the capabilities of LLM agents. However, there is currently no dedicated arena for evolving and benchmarking LLM-based CI. To address this gap, we introduce OpenHospital, an interactive arena where physician agents can evolve CI through interactions with patient agents.
Evolved Collectives Combine Complex Internal Representations with Simple Outputs
Announce Type: new Abstract: Collective intelligence emerges from local interactions among agents with limited information, yet how internal controller organization relates to emergent collective order remains unclear. Here, we study evolved swarms with shallow neural controllers under explicit sensory and actuation constraints and compare collective order with hidden-layer complexity and output nonlinearity across 3024 conditions. Under these constraints, the most ordered regimes exhibit...
Economy of Minds: Emerging Multi-Agent Intelligence with Economic Interactions
Announce Type: new Abstract: How can a population of agents self-orchestrate and self-adapt into stronger collective intelligence without centralized control? Inspired by Friedrich Hayek's economic theory of decentralized coordination in markets, we study this question through an agent economy in which agents compete via auctions for the right to act, exchange payments, and accumulate wealth from environmental rewards. These simple economic signals induce decentralized credit assignment,...
Design and Evaluation of Multi-Agent AI Oracle Systems for Prediction Market Resolution
Announce Type: new Abstract: Prediction markets aggregate collective intelligence to forecast uncertain events, but their utility depends on reliable outcome resolution. Existing oracle systems tradeoff fast but brittle automation against accurate but costly human arbitration. Single-LLM oracles achieve meaningful accuracy but inherit all failure modes of their underlying model with no self-correction mechanism.
Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
arXiv:2603.19294v4 Announce Type: replace Abstract: While post-training has successfully improved large language models (LLMs) across a variety of domains, these gains heavily rely on human-labeled data or external verifiers. Existing data has already been exploited, and new data is expensive to collect. Moreover, true intelligence goes far beyond verifiable tasks.
AI Has Come for Serif Fonts
As public backlash to the seeming omnipresence of artificial intelligence intensifies, the collective quest to weed out—and reject—telltale signs of its use continues. One of the first casualties, to my dismay, was em dashes—which are a great, and very human form of punctuation, by the way! There's also the “rule of threes,” which is meant to scan as rhythmic, but often comes across predictable, hackish, and stale.
CHALIS: A Challenge Dataset for Language Identification in Difficult Scenarios
Announce Type: new Abstract: We present CHALIS (Challenging Language Identification Samples), a new benchmark dataset explicitly designed to address difficult cases in language identification: cousin languages and orthographic noise. Our dataset has two parts: First, we collected sentences shared across mutually intelligible language pairs (Czech/Slovak, Spanish/Catalan, Portuguese/Galician, Danish/Norwegian). The second part tests for orthography noise: we transliterate text across multiple...
China-linked spy site expansion in Cuba raises alarms near key US military bases
As the Trump administration ramps up pressure on Cuba, renewed scrutiny is falling on expanding intelligence infrastructure on the island that analysts say could help China and Russia monitor sensitive U.S. military activity near Florida.New reporting and satellite analysis of a major Cuban signals intelligence facility outside Havana have intensified concerns about foreign surveillance capabilities positioned near Key West naval operations, Homestead Air Reserve Base and launches from Cape...
Europe pours money into ocean research as Trump guts science funding
PARIS — The European Union wants to plug a gaping hole in ocean research left behind by the administration of U.S. President Donald Trump. The trouble is, it has a lot less cash to splash. Last week, the European Commission launched the “OceanEye” program, which aims to make the EU “a global leader in ocean intelligence” by investing in critical ocean observation technologies and data collection on how oceans evolve. It came two weeks after the...
Robots Need More than VLA and World Models
arXiv:2606.06556v1 Announce Type: new Abstract: Generalist robot intelligence is often framed as a policy-scaling problem: collect more robot demonstrations, train larger Vision-Language-Action (VLA) models, and expect broader generalisation. In this position paper, we argue that this framing is incomplete. The central bottleneck is not only policy learning, but the absence of mechanisms that convert the world's abundant unstructured behavioural data into grounded robot supervision.