Logical reasoning, ie, deductively inferring the truth value of a conclusion from a set of
premises, is an important task for artificial intelligence with wide potential impacts on …

Large language models have shown astonishing performance on a wide range of reasoning
tasks. In this paper, we investigate whether they could reason about real-world events and …

Large language models (LLMs) have achieved impressive human-like performance across
various reasoning tasks. However, their mastery of underlying inferential rules still falls short …

While large language models (LLMs) are proficient at question-answering (QA), it is not
always clear how (or even if) an answer follows from their latent" beliefs". This lack of …

A growing body of work studies how to answer a question or verify a claim by generating a
natural language" proof": a chain of deductive inferences yielding the answer based on a set …

Answering complex questions often requires multi-step reasoning in order to obtain the final
answer. Most research into decompositions of complex questions involves open-domain …

Maintaining logical consistency in structured explanations is critical for understanding and
troubleshooting the reasoning behind a system's decisions. However, existing methods for …

Large language models (LLMs) are growing highly adept at language-guided program
synthesis: translating natural language specifications into code to solve programming tasks …