← Search

Jonathan Shaki

3 accepted papers

2025

Out-of-Context Reasoning in Large Language Models

EMNLP 2025

We study how large language models (LLMs) reason about memorized knowledge through simple binary relations such as equality ( = ), inequality ( < ), and inclusion ( ⊂ ). Unlike in-context reasoning, the axioms (e.g., a < b, b < c ) are only seen during training and not provided in the task prompt (e

Cited by 0SourcePDFScholar