Active Learning for Communication Structure Optimization in LLM-Based Multi-Agent Systems
cs.MA, cs.AI, cs.LG
Submitted: 2026-05-07
Updated: 2026-10-02
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Evaluating Large Language Models Trained on Code
- Diffusion Posterior Sampling for General Noisy Inverse Problems
- Training Verifiers to Solve Math Word Problems
- SciML Agents: Write the Solver, Not the Solution
- Bayesian optimal experimental design with Wasserstein information criteria
- Bayesian Active Learning for Classification and Preference Learning
- Agent Hospital: A Simulacrum of Hospital with Evolvable Medical Agents
- ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
- Score-Based Generative Modeling through Stochastic Differential Equations
- ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono
- Topological Structure Learning Should Be A Research Priority for LLM-Based Multi-Agent Systems
- G-Designer: Architecting Multi-agent Communication Topologies via Graph Neural Networks
- Multi-agent Architecture Search via Agentic Supernet
- AFlow: Automating Agentic Workflow Generation
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