25 citations · 26 across the 12 of their papers we have counts for
5 papers · 1 filter
CORGI: Efficient Pattern Matching With Quadratic Guarantees
Daniel Weitekamp
Rule-based systems must solve complex matching problems within tight time constraints to be effective in real-time applications, such as planning and reactive control for AI agents…
When Should Users Check? Modeling Confirmation Frequency in Multi-Step Agentic AI Tasks
Jieyu Zhou, Aryan Roy, Sneh Gupta +2
Existing AI agents typically execute multi-step tasks autonomously and only allow user confirmation at the end. During execution, users have little control, making the confirm-at-e…
Decomposed Inductive Procedure Learning: Learning Academic Tasks with Human-Like Data Efficiency
Daniel Weitekamp, Christopher MacLellan, Erik Harpstead +1
Human learning relies on specialization -- distinct cognitive mechanisms working together to enable rapid learning. In contrast, most modern neural networks rely on a single mechan…
TutorGym: A Testbed for Evaluating AI Agents as Tutors and Students
Daniel Weitekamp, Momin N. Siddiqui, Christopher J. MacLellan
Recent improvements in large language model (LLM) performance on academic benchmarks, such as MATH and GSM8K, have emboldened their use as standalone tutors and as simulations of h…
Beyond Final Answers: Evaluating Large Language Models for Math Tutoring
Adit Gupta, Jennifer Reddig, Tommaso Calo +2
Researchers have made notable progress in applying Large Language Models (LLMs) to solve math problems, as demonstrated through efforts like GSM8k, ProofNet, AlphaGeometry, and Mat…