How Research Agentic Systems Are Actually Built: From ReAct to the AI Scientist
🌟 Important Notice
To maximize engagement, participants are encouraged to read the material in advance and come prepared to discuss technical and methodological details during the session. If you have relevant research or came across articles, blog posts, or other resources that contribute to the topic, please share!
AI agents have transitioned from basic reasoning loops to sophisticated systems capable of querying external knowledge, utilizing tools, learning from failures, executing code, and even attempting comprehensive research pipelines. This session aims to demystify the design principles enabling this evolution and what it signifies for AI's role in actual research processes.
The discussion will center on the principal paper titled "Towards End-to-End Automation of AI Research" (Nature, 2026) and will be supported by four foundational papers:
- ReAct: Grounding reasoning in action
- Toolformer: Enabling autonomous tool and API usage
- Reflexion: Facilitating learning from failures through feedback
- SWE-agent: Functioning in real code execution environments
Together, these papers encapsulate the capabilities that construct the AI Scientist's comprehensive research pipeline.
We will also critically review the achievements of the main paper and the concerns it raises regarding research integrity, overload in review systems, and the future of scientific training.
Suggested Pre-Reading:
- Main Paper: Towards End-to-End Automation of AI Research
- Lineage Papers: ReAct, Toolformer, Reflexion, SWE-agent
- Optional Context Articles:
About the Hosts
👩💻 Anshu Singh: An AI and Data Privacy Research Engineer at the Government Technology Agency (GovTech), Singapore. With a Master’s in AI from the National University of Singapore, she specializes in user-centric solutions and translating research into practice.
👨💻 Keshav Nath: A Master of Computing graduate from the National University of Singapore. His experience spans applied AI and research, including time at the UCLA Smart Energy Lab and internship at MITACS, leading to three publications. He has worked as a Junior AI Engineer and a Graduate Teaching Assistant, focusing on Advanced Analytics.
About the Series
📚 Paper Club: A community-driven initiative by Lorong AI, where members gather to discuss and analyze significant papers, articles, or developments in artificial intelligence.
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