Agentic AI: Top Papers on Reasoning, Tools & Behavior

If you're interested in agentic AI, there are key papers that explain how these systems work. One foundational paper is "ReAct: Synergizing Reasoning and Acting in Language Models." It shows how AI agents can combine thinking and action by alternating between reasoning steps and interacting with external environments. This helps them plan, track progress, and learn from mistakes. Another important paper is "Toolformer: Language Models Can Teach Themselves to Use Tools." This research demonstrates how language models can learn to use external tools like calculators or search engines on their own. This moves AI beyond just generating text to deciding when outside help is useful. Finally, "Generative Agents: Interactive Simulacra of Human Behavior" introduces AI agents that simulate human behavior in interactive environments. These papers offer a clear look at the core ideas behind modern AI agents.