·
DataBubble
  • Home
  • Models
  • News
  • Compare
  • Boards
  • Pricing
  • About
  • Newsletter
  • Methodology
  • Contact
Latest
Vision Hopfield Memory Networks3h◆Stable Deep Reinforcement Learning via Isotropic Gaussian Representations3h◆Insurance of Agentic AI3h◆Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation3h◆MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery3h◆Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory3h◆Residual Modeling for High-Fidelity Learned Compression of Scientific Data3h◆Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution3h◆LatentWave: JEPA Pretraining for Wireless Foundation Models3h◆An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)3h◆Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models3h◆SciVisAgentSkills: Design and Evaluation of Agent Skills for Scientific Data Analysis and Visualization3h◆Beyond Similarity: Trustworthy Memory Search for Personal AI Agents3h◆Assessing the Geographic Diversity of AI's Platial Representations in Image Generation3h◆Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads3h◆Harnessing Structural Context for Entity Alignment Foundation Models3h◆ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models3h◆Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature3h◆Personal AI Agent for Camera Roll VQA3h◆LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models3h◆Vision Hopfield Memory Networks3h◆Stable Deep Reinforcement Learning via Isotropic Gaussian Representations3h◆Insurance of Agentic AI3h◆Do Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation3h◆MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery3h◆Uncertainty Aware Functional Behavior Prediction and Material Fatigue Assessment for Circular Factory3h◆Residual Modeling for High-Fidelity Learned Compression of Scientific Data3h◆Mutation Without Variation: Convergence Dynamics in LLM-Driven Program Evolution3h◆LatentWave: JEPA Pretraining for Wireless Foundation Models3h◆An interpretable and trustworthy AI framework for large-scale longitudinal structure-pain association studies using data from the Osteoarthritis Initiative (OAI)3h◆Minimizing the Hidden Cost of Scales: Graph-Guided Ultra-Low-Bit Quantization for Large Language Models3h◆SciVisAgentSkills: Design and Evaluation of Agent Skills for Scientific Data Analysis and Visualization3h◆Beyond Similarity: Trustworthy Memory Search for Personal AI Agents3h◆Assessing the Geographic Diversity of AI's Platial Representations in Image Generation3h◆Mechanistic Insights into Functional Sparsity in Multimodal LLMs via CoRe Heads3h◆Harnessing Structural Context for Entity Alignment Foundation Models3h◆ReTreVal: Reasoning Tree with Validation and Cross-Problem Memory for Large Language Models3h◆Ontology-constrained multi-LLM scoring of hypothesis support in the predictive processing literature3h◆Personal AI Agent for Camera Roll VQA3h◆LLMCodec: Adapting Video Codecs for Efficient Weight Compression of Large Language Models3h◆
News/Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs
arxiv
PublishedMay 13, 2026 at 4:00 AM
—neutral

Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2605.08686v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems often rely on a controller to coordinate a pool of heterogeneous models, yet existing controllers are typically limited to one-shot routing: they select a model once and return its output directly. Such ro

Stay posted· Newsletter

A 5-min weekly brief — top movers, price watch, story of the week.

// no spam · unsubscribe one-click · free forever

Discussion
Source
↗
arxiv
Read original ↗All from arxiv →

No replies yet. Be first.

Source
↗
arxiv
Read original ↗All from arxiv →

Related coverage

More from ARXIV
arxivVision Hopfield Memory Networks3harxivStable Deep Reinforcement Learning via Isotropic Gaussian Representations3harxivInsurance of Agentic AI3harxivDo Models Share Safety Representations? Cross-Model Steering for Safe Visual Generation3h
The Bubble Brief
WEEKLY

Read AI insights every Tuesday — top movers, new releases, story of the week.

// no spam · unsubscribe one-click · free forever

Originally published on arxiv ↗
HomeModelsNews