3 papers
cs.AI2026
Belief or Circuitry? Causal Evidence for In-Context Graph Learning
Katharine Kowalyshyn, Timothy Duggan, Daniel Little +1
How do LLMs learn in-context? Is it by pattern-matching recent tokens, or by inferring latent structure? We probe this question using a toy graph random-walk across two competing g…
physics.ed-ph2026
Locating acts of mechanistic reasoning in student team conversations with mechanistic machine learning
Kaitlin Gili, Mainak Nistala, Kristen Wendell +1
STEM education researchers are often interested in identifying moments of students' mechanistic reasoning for deeper analysis, but have limited capacity to search through many team…
stat.ML2025
Discovering group dynamics in coordinated time series via hierarchical recurrent switching-state models
Michael T. Wojnowicz, Kaitlin Gili, Preetish Rath +7
We seek a computationally efficient model for a collection of time series arising from multiple interacting entities (a.k.a. "agents"). Recent models of temporal patterns across in…