Reasoning with LLMs (UdS; Summer 2025/26)

Seminar on reasoning with large language models, covering inference, learning, and analysis.

Instructor: Yuekun Yao

Term: Summer

Course Description

Large language models are now capable of a wide range of human-like tasks, but reasoning, planning, and systematic generalization remain major open problems. This seminar surveys recent work on reasoning with LLMs, including prompting strategies, verification, learning-based approaches, and analyses of what these models are actually doing.

Prerequisites

Students should have a solid background in NLP and machine learning. Familiarity with language models, transformer architectures, in-context learning, and supervised fine-tuning is assumed.

Registration

Please contact me by email if you are interested in presenting a paper. Students should indicate their top paper preferences from the schedule readings.

Course Format

The seminar is discussion-driven. Each week we focus on one or more recent papers. Students are expected to come prepared to discuss the central ideas, assumptions, limitations, and open questions.

Each participant leads one session during the semester. Session leaders should:

  • present the paper’s main goal, method, and contributions;
  • raise discussion points about strengths, weaknesses, and implications;
  • engage actively with questions from the group.

Evaluation

For students taking the seminar for 4 credits:

  • Presentation: 60%
  • Participation in discussion: 40%

For students taking the seminar for 7 credits:

  • Presentation: 30%
  • Participation in discussion: 20%
  • Term paper: 50%

Term Paper

Students taking the 7-credit version may write either a survey paper or a replication paper. The expected paper length is at most 8 pages in ACL, ICLR, or NeurIPS format, excluding references.

Contact

Please email ykyao.cs@gmail.com with questions about the seminar.

Schedule

Week Date Topic Materials
1 2025-04-15 Course logistics
2 2025-04-22 Overview
3 2025-04-29 Chain-of-thought prompting
4 2025-05-06 Rationale exploration
5 2025-05-13 Task decomposition
6 2025-05-13 Chain-of-thought reasoning without prompting
7 2025-05-20 Verification
8 2025-05-27 Step-by-step verification
9 2025-06-03 Supervised fine-tuning
10 2025-06-10 Bootstrapping
11 2025-06-17 Reinforcement tuning
12 2025-06-24 Test-time scaling
13 2025-07-01 Latent reasoning
14 2025-07-08 Multi-hop reasoning analysis
15 2025-07-15 Reasoning or reciting?