2025 Spring

2025 Spring Schedule

This Spring, we focus on understanding and developing AI agents that can autonomously perform tasks, make decisions, and interact with their environment. Our high school researchers will gain hands-on experience with cutting-edge AI technologies while developing critical research and programming skills.

Schedule & Information

• Feb 8: Hello

  • Setup for agent development environments

  • Git Repo: github.com/philmui/research2025

  • Notebook: [link]

  • Readings

    • Stanford AI Index Report. (link)

• Feb 15: Retrieval Augmented Generation (RAG) Agents

  • Recording [link]

  • Notebook: [link]

• Feb 22: SKI WEEK (no meeting)

• March 1: Agentic Tooling

  • Slides: [link]

  • Recording: [link]

  • Notebook: [link]

  • Readings

    • Alexander Meinke, Bronson Schoen, Jérémy Scheurer, Mikita Balesni, Rusheb Shah, Marius Hobbhahn.  Frontier Models are Capable of In-context Scheming.  arXiv:2412.04984, 14 Jan 2025. [link]

• March 9: Agentic Reasoning

  • Slides: [link]

  • Recording: [link]

  • Notebook: [link]

  • Readings:

    • Shreya Shankar, J.D. Zamfirescu-Pereira, Björn Hartmann, Aditya G. Parameswaran, Ian Arawjo.  Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences. arXiv:2404.12272 [cs.HC], 18, Apr 2025. [link]

• March 16: Image RAG

  • Slides: [link]

  • Recording: [link]

  • Notebook: [link]

  • Readings:

    • Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, Ilya Sutskever.  Learning Transferable Visual Models From Natural Language Supervision.  arXiv:2103.00020.  [link]

    • Yossi Gandelsman, Alexei A. Efros, and Jacob Steinhardt.  Interpreting CLIP's Image Representation via Text-based Decomposition.  arXiv:2310.05916.  [link]

•  March 22: Projects with Agents and LLMs

  • Slides: [link]

  • Recording: [link]

  • Research Project

    • Signup Spreadsheet [link]

    • Project Proposal Template: [link]

  • Readings:

    • Tom Ling.  What Elinor Ostrom Teaches Us About Avoiding the 'Tragedy of the Commons' in Delivering the Public Interest in the Post COVID-19 World, RAND Commentary, Jun 22, 2020. [link]

    • Kreps, David, Robert Wilson, Paul Milgrom, and John Roberts. “Rational Cooperation in the Finitely Repeated Prisoners’ Dilemma.” Journal of Economic Theory 27, no. 2 (August 1982): 245–252.

    • Milgrom, Paul. “Axelrod’s The Evolution of Cooperation.” RAND Journal of Economics 15, no. 2 (1984): 305–309.

•  March 29: Agent Evaluations

  • Slides: [link]

  • Recording: [link]

  • Readings:

    • Asaf Yehudai, Lilach Eden, Alan Li, Guy Uziel, Yilun Zhao, Roy Bar-Haim, Arman Cohan, Michal Shmueli-Scheuer.  "Survey on Evaluation of LLM-based Agents." arXiv:2503.16416, Mar 20, 2025 [link]

• April 5: Advanced Chunking

  • Notebook:[advanced RAG]

  • Recording: [link]

• April 12: Reasoning

  • Notebook: [HuatuoGPT & MedReason]

  • Recording: [link]

  • Readings:

    • Junying Chen and Zhenyang Cai and Ke Ji and Xidong Wang and Wanlong Liu and Rongsheng Wang and Jianye Hou and Benyou Wang (2025) HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs. arXiv:2412.18925 [link][ dataset]

    • Juncheng Wu, Wenlong Deng, Xingxuan Li, Sheng Liu, Taomian Mi, Yifan Peng, Ziyang Xu, Yi Liu, Hyunjin Cho, Chang-In Choi, Yihan Cao, Hui Ren, Xiang Li, Xiaoxiao Li, Yuyin Zhou (2025) MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs. arXiv:2504.00993, April 1, 2025. [link]

• April 19: Reflexion

  • Repo: [link]

  • Slides: [link]

  • Recording: [link]

•  b: BioReasoning Project

  • Repo: [link]

  • Slides: [link]

  • Reading:

    • Brian J Chan, Chao-Ting Chen, Jui-Hung Cheng, Hen-Hsen Huang (2024) Don’t Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks.  arXiv:2412.15605, December 20, 2024.  [link]

• May 3: EvoGames Project

  • Repo: [link]

  • Slides: [link]

  • Reading:

    • Alexander De Ridder (2025) Agent-Based Modeling and Game Theory: Simulating Strategic Interactions in Complex Systems, Smyth|OS.  [link]

• May 10: Research Project Q&A

  • Reading:

    • Circuit Tracing: Revealing Computational Graphs in Language Models [link]

• Research Project

  • Signup Spreadsheet [link]

  • Project Proposal Template: [link]

What are we covering this Spring?

Part 1: Foundations

- Introduction to AI Agents and their applications

- Setting up development environments and tools

- Understanding Large Language Models (LLMs)

- Prompt engineering and chain-of-thought reasoning

- Introduction to autonomous agents and decision-making

- Basic agent architectures and frameworks

Part 2: Applied Projects

- Building simple AI agents using popular frameworks

- Implementing goal-oriented behavior

- Working with APIs and external tools

- Collaborative project development

Part 3: Selecting Research Topics

- Multi-agent systems and communication

- Studying social phenomena with multi-agent systems

- Ethical considerations in AI agents

- Original research projects