In today’s episode of Hugging Face Trending Papers, we explore three cutting-edge ideas reshaping how we interact with AI and research.

First, we dive into Paper2Agent, a framework that transforms static research papers into interactive AI agents, making findings more transparent and usable. Next, we look at Scaling Agents via Continual Pre-training, which pushes the boundaries of agent reliability by teaching them through lifelong learning. Finally, we cover Documenting Machine Learning with AI Partners, a vision of AI tools that act as collaborative lab partners to capture, explain, and even co-author machine learning workflows.

Listen in for benchmarks, methods, and real-world implications — and discover how these papers could change the way we do science.

Papers discussed:

• Paper2Agent: Reimagining Research Papers As Interactive and Reliable AI Agents

• Scaling Agents via Continual Pre-training

• Documenting Machine Learning with AI Partners