Media is too big
VIEW IN TELEGRAM
✨ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development
📝 Summary:
ComfyUI-Copilot is an LLM and multi-agent system that enhances ComfyUI's usability. It provides intelligent recommendations and automated one-click workflow construction, lowering entry barriers for beginners and boosting efficiency for experienced users.
🔹 Publication Date: Published on Jun 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.05010
• PDF: https://arxiv.org/pdf/2506.05010
• Project Page: https://x.com/wangly0229/status/1923515826713526583
• Github: https://github.com/AIDC-AI/ComfyUI-Copilot
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #MultiAgent #ComfyUI #AI #WorkflowAutomation
📝 Summary:
ComfyUI-Copilot is an LLM and multi-agent system that enhances ComfyUI's usability. It provides intelligent recommendations and automated one-click workflow construction, lowering entry barriers for beginners and boosting efficiency for experienced users.
🔹 Publication Date: Published on Jun 5
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2506.05010
• PDF: https://arxiv.org/pdf/2506.05010
• Project Page: https://x.com/wangly0229/status/1923515826713526583
• Github: https://github.com/AIDC-AI/ComfyUI-Copilot
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #MultiAgent #ComfyUI #AI #WorkflowAutomation
✨Solving a Million-Step LLM Task with Zero Errors
📝 Summary:
MAKER solves million-step LLM tasks with zero errors. It uses extreme task decomposition for microagents and applies error correction at each step with multi-agent voting. This offers a new scalable approach for complex LLM processes.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09030
• PDF: https://arxiv.org/pdf/2511.09030
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #AI #ErrorCorrection #MultiAgent #TaskDecomposition
📝 Summary:
MAKER solves million-step LLM tasks with zero errors. It uses extreme task decomposition for microagents and applies error correction at each step with multi-agent voting. This offers a new scalable approach for complex LLM processes.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09030
• PDF: https://arxiv.org/pdf/2511.09030
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #AI #ErrorCorrection #MultiAgent #TaskDecomposition
❤1
✨QuantAgent: Price-Driven Multi-Agent LLMs for High-Frequency Trading
📝 Summary:
QuantAgent is a multi-agent LLM framework for high-frequency trading. It uses specialized agents for indicators, patterns, trends, and risk to make rapid decisions. It outperforms existing neural and rule-based systems in accuracy and returns.
🔹 Publication Date: Published on Sep 12, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09995
• PDF: https://arxiv.org/pdf/2509.09995
• Project Page: https://Y-Research-SBU.github.io/QuantAgent/
• Github: https://github.com/Y-Research-SBU/QuantAgent
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #MultiAgent #HighFrequencyTrading #FinTech #AlgorithmicTrading
📝 Summary:
QuantAgent is a multi-agent LLM framework for high-frequency trading. It uses specialized agents for indicators, patterns, trends, and risk to make rapid decisions. It outperforms existing neural and rule-based systems in accuracy and returns.
🔹 Publication Date: Published on Sep 12, 2025
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2509.09995
• PDF: https://arxiv.org/pdf/2509.09995
• Project Page: https://Y-Research-SBU.github.io/QuantAgent/
• Github: https://github.com/Y-Research-SBU/QuantAgent
==================================
For more data science resources:
✓ https://xn--r1a.website/DataScienceT
#LLM #MultiAgent #HighFrequencyTrading #FinTech #AlgorithmicTrading
❤2