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Notes on multi-agent system
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Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering
Researchers have developed an adaptive memory and reflection multi-agent system for medical question answering. This system, which uses specialized agents with dedicated memory and feedback, aims to improve the…
Adaptive Memory and Reflection Multi-Agent System for Medical Question Answering
Researchers introduce a new multi-agent system called Adaptive Memory and Reflection (AMR) for medical question answering. This system aims to address the limitations of existing systems by using specialized agents…
NeuroRefiner: Morphology-Aware Multi-Agent Refinement for 3D Fluorescence Microscopy Neuron Segmentation
The study introduces a new method called NeuroRefiner for accurately segmenting neurons in 3D fluorescence microscopy images. The method overcomes challenges posed by the sparse and elongated morphology of neurons…
BrainPilot: Automating Brain Discovery with Agentic Research
BrainPilot is a multi-agent system developed by researchers for accelerating brain science research using AI agents. It includes a coordinating principal investigator (PI) agent, specialist agents grounded in curated…
Copewell: A Multi-Agent Swarm Architecture for Equitable Mental Wellness Support
The paper introduces Copewell, a novel multi-agent swarm system designed to improve mental health support, particularly for people in low- and middle-income countries where access is limited due to various factors. The…
TreeAgent: A Generalizable Multi-Agent Framework for Automated Bias Labeling in Forestry via Compiled Expert Rules and Vision-Language Models
Researchers propose a system called TreeAgent that uses artificial intelligence (AI) to classify tree heights in forestry remote sensing. The system combines decision trees created by experts with Vision-Language…
COHORT: Collaborative Orchestration for Hardening via Offensive Replay on Emulated Topologies
The COHORT framework is an automated solution that aims to mitigate cyber attacks in enterprise networks more efficiently. It uses a multi-agent system and a high-fidelity GNS3 emulator to generate, implement, and…
PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement
The paper introduces PAPERCLAW, a multi-agent system that automates the research process from start to finish. It uses a large language model as its core, which can drive the entire pipeline and also allows for human…
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