Sunday Lab #2: ICPC Primer, Academic Reading Circle (LLMs Using External Tools), and Social

Sunday Lab #2 continues ACM ASU’s full-day academic and community experience, integrating problem-solving, research literacy, and technical networking into a single immersive Sunday program.
The day begins with an ICPC Primer, where participants collaboratively solve two Codeforces problems under guided mentorship, sharpening algorithmic thinking, competitive programming patterns, and live problem-solving strategies.
This flows into a Lunch and Social hour, creating a relaxed space for students across ASU’s technical organizations to connect, exchange ideas, and build relationships beyond formal classrooms and projects.
The afternoon concludes with the Academic Reading Circle, featuring a deep-dive into Toolformer: Language Models Can Teach Themselves to Use Tools. Participants will examine how modern language models learn to invoke external tools such as calculators, search engines, and APIs, and why this marks a shift from static language modeling toward tool-augmented reasoning systems.
Sunday Labs is designed for students who want to strengthen their technical foundations while engaging in thoughtful, research-driven community.

Date: Sunday, February 08, 2026
Time: 11:00 AM – 5:00 PM​
Location: Durham Hall 106 (DH 106), Tempe campus​
For more info and RSVP: https://asu.acm.org/rsvp
Virtual Location via Zoom: https://asu.acm.org/attend

Session Breakdown:
11:00 AM–1:00 PM: ICPC Primer - Problem set
Solve two Codeforces problems with guided instruction from Souradeep Banerjee.
1:00 PM–2:00 PM: Lunch and Social
Network with students from other clubs and enjoy food in a relaxed, collaborative environment.
2:00 PM–4:00 PM: Academic Reading Circle – “Toolformer: Language Models Can Teach Themselves to Use Tools”
Explore how Toolformer enables LLMs to learn, in a self-supervised way, when and how to call external APIs (calculator, search, QA, etc.), illustrating a concrete step from static language modeling to tool-augmented reasoning systems.​

Paper: https://arxiv.org/abs/2302.04761

Academic Outcomes:
Students will:
Build foundational competitive programming skills aligned with ICPC-style problem solving.
Develop structured approaches to reading and analyzing modern AI research papers.
Strengthen interdisciplinary communication and collaboration through social networking.
Gain exposure to both technical depth and community leadership within ACM.

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