We observe that pre-trained large language models (LLMs) are capable of autoregressively
completing complex token sequences--from arbitrary ones procedurally generated by …

GPT (Generative Pre-trained Transformer) represents advanced language models that have
significantly reshaped the academic writing landscape. These sophisticated language …

Inductive reasoning is a core problem-solving capacity: humans can identify underlying
principles from a few examples, which can then be robustly generalized to novel scenarios …

The ability to derive underlying principles from a handful of observations and then
generalize to novel situations--known as inductive reasoning--is central to human …

We explore the abstract reasoning abilities of text-only and multimodal versions of GPT-4,
using the ConceptARC benchmark [10], which is designed to evaluate robust understanding …

We propose a novel framework that leverages LLMs for full causal graph discovery. While
previous LLM-based methods have used a pairwise query approach, this requires a …

The study explores the capabilities of OpenAI's ChatGPT in solving different types of physics
problems. ChatGPT (with GPT-4) was queried to solve a total of 40 problems from a college …

Large language models are increasingly solving tasks that are commonly believed to
require human-level reasoning ability. However, these models still perform very poorly on …

This paper introduces ARCLE, an environment designed to facilitate reinforcement learning
research on the Abstraction and Reasoning Corpus (ARC). Addressing this inductive …

We attempt to solve the Abstraction and Reasoning Corpus (ARC) Challenge using Large
Language Models (LLMs) as a system of multiple expert agents. Using the flexibility of LLMs …