1 citations · 2 across the 5 of their papers we have counts for
9 papers
CASSANDRA: Programmatic and Probabilistic Learning and Inference for Stochastic World Modeling
Panagiotis Lymperopoulos, Abhiramon Rajasekharan, Ian Berlot-Attwell +2
Building world models is essential for planning in real-world domains such as businesses. Since such domains have rich semantics, we can leverage world knowledge to effectively mod…
Mini Amusement Parks (MAPs): A Testbed for Modelling Business Decisions
Stéphane Aroca-Ouellette, Ian Berlot-Attwell, Panagiotis Lymperopoulos +5
Despite rapid progress in artificial intelligence, current systems struggle with the interconnected challenges that define real-world decision making. Practical domains such as bus…
A Compute-Matched Re-Evaluation of TroVE on MATH
Tobias Sesterhenn, Ian Berlot-Attwell, Janis Zenkner +1
Reusing established theorems and formulas is central to mathematical problem solving, serving as essential building blocks for tackling increasingly complex challenges. Recent work…
LLM Library Learning Fails: A LEGO-Prover Case Study
Ian Berlot-Attwell, Frank Rudzicz, Xujie Si
Recent advancements in the coding, reasoning, and tool-using abilities of LLMs have spurred interest in library learning (i.e., online learning through the creation, storage, and r…
Library Learning Doesn't: The Curious Case of the Single-Use "Library"
Ian Berlot-Attwell, Frank Rudzicz, Xujie Si
Advances in Large Language Models (LLMs) have spurred a wave of LLM library learning systems for mathematical reasoning. These systems aim to learn a reusable library of tools, suc…
Attribute Diversity Determines the Systematicity Gap in VQA
Ian Berlot-Attwell, Kumar Krishna Agrawal, A. Michael Carrell +2
Although modern neural networks often generalize to new combinations of familiar concepts, the conditions that enable such compositionality have long been an open question. In this…