21 citations · 21 across the 3 of their papers we have counts for
3 papers
Are Language Models Efficient Reasoners? A Perspective from Logic Programming
Andreas Opedal, Yanick Zengaffinen, Haruki Shirakami +5
Modern language models (LMs) exhibit strong deductive reasoning capabilities, yet standard evaluations emphasize correctness while overlooking a key aspect of reasoning: efficiency…
MathGAP: Out-of-Distribution Evaluation on Problems with Arbitrarily Complex Proofs
Andreas Opedal, Haruki Shirakami, Bernhard Schölkopf +2
Large language models (LLMs) can solve arithmetic word problems with high accuracy, but little is known about how well they generalize to more complex problems. This is difficult t…
Do Language Models Exhibit the Same Cognitive Biases in Problem Solving as Human Learners?
Andreas Opedal, Alessandro Stolfo, Haruki Shirakami +5
There is increasing interest in employing large language models (LLMs) as cognitive models. For such purposes, it is central to understand which properties of human cognition are w…