Are Machines Better at Complex Reasoning? Unveiling Human-Machine Inference Gaps in Entailment Verification

Understand

Making inferences in text comprehension to understand the meaning is essential in language processing.

• This work studies the entailment verification (EV) problem of multi-sentence premises that requires a system to make multiple inferences implicitly.
• Studying EV for such complex premises is important because modern NLP problems, such as detecting inconsistent model-generated rationales, require complex multi-hop reasoning.
• However, current textual inference datasets mostly contain short premises that only partially focus on these challenges.