✨Scaling Agents via Continual Pre-training
📝 Summary:
Current agentic LLMs underperform due to training tensions. This paper proposes Agentic Continual Pre-training CPT to build powerful agentic foundation models. Their AgentFounder model achieves state-of-the-art performance on benchmarks with strong tool-use.
🔹 Publication Date: Published on Sep 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2502.06589
• PDF: https://arxiv.org/pdf/2509.13310
• Project Page: https://tongyi-agent.github.io/blog/
• Github: https://tongyi-agent.github.io/blog/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMAgents #ContinualPretraining #FoundationModels #AIResearch #ToolUse
📝 Summary:
Current agentic LLMs underperform due to training tensions. This paper proposes Agentic Continual Pre-training CPT to build powerful agentic foundation models. Their AgentFounder model achieves state-of-the-art performance on benchmarks with strong tool-use.
🔹 Publication Date: Published on Sep 16
🔹 Paper Links:
• arXiv Page: https://arxiv.org/pdf/2502.06589
• PDF: https://arxiv.org/pdf/2509.13310
• Project Page: https://tongyi-agent.github.io/blog/
• Github: https://tongyi-agent.github.io/blog/
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLMAgents #ContinualPretraining #FoundationModels #AIResearch #ToolUse
✨In-the-Flow Agentic System Optimization for Effective Planning and Tool Use
📝 Summary:
AgentFlow is a trainable agentic framework that optimizes its planner in-the-flow within multi-turn interactions. It uses Flow-GRPO to train its modules and significantly outperforms top baselines and GPT-4o on various reasoning and tool-use tasks.
🔹 Publication Date: Published on Oct 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05592
• PDF: https://arxiv.org/pdf/2510.05592
• Project Page: https://agentflow.stanford.edu/
• Github: https://github.com/lupantech/AgentFlow
✨ Spaces citing this paper:
• https://huggingface.co/spaces/AgentFlow/agentflow
• https://huggingface.co/spaces/bioliveir4/agentflow2
• https://huggingface.co/spaces/bioliveir4/agentflow
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #MachineLearning #AIagents #ToolUse #Planning
📝 Summary:
AgentFlow is a trainable agentic framework that optimizes its planner in-the-flow within multi-turn interactions. It uses Flow-GRPO to train its modules and significantly outperforms top baselines and GPT-4o on various reasoning and tool-use tasks.
🔹 Publication Date: Published on Oct 7
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2510.05592
• PDF: https://arxiv.org/pdf/2510.05592
• Project Page: https://agentflow.stanford.edu/
• Github: https://github.com/lupantech/AgentFlow
✨ Spaces citing this paper:
• https://huggingface.co/spaces/AgentFlow/agentflow
• https://huggingface.co/spaces/bioliveir4/agentflow2
• https://huggingface.co/spaces/bioliveir4/agentflow
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#AI #MachineLearning #AIagents #ToolUse #Planning
✨LoopTool: Closing the Data-Training Loop for Robust LLM Tool Calls
📝 Summary:
LoopTool is an automated framework that closes the data-training loop for LLMs. It iteratively refines data and models to improve tool-use capabilities, achieving state-of-the-art results and surpassing larger models cost-effectively.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09148
• PDF: https://arxiv.org/pdf/2511.09148
• Github: https://github.com/Rednote-ExperienceAI-Lab/LoopTool
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLM #AI #MachineLearning #DataScience #ToolUse
📝 Summary:
LoopTool is an automated framework that closes the data-training loop for LLMs. It iteratively refines data and models to improve tool-use capabilities, achieving state-of-the-art results and surpassing larger models cost-effectively.
🔹 Publication Date: Published on Nov 12
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.09148
• PDF: https://arxiv.org/pdf/2511.09148
• Github: https://github.com/Rednote-ExperienceAI-Lab/LoopTool
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#LLM #AI #MachineLearning #DataScience #ToolUse