Papers with zero-shot verification

2 papers
SYNTHVERIFY: Enhancing Zero-Shot Claim Verification through Step-by-Step Synthetic Data Generation (2025.findings-acl)

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Challenge: Existing methods for claim verification are inefficient or rely on external documents.
Approach: They propose a step-by-step prompting-based synthetic data generation framework to enhance zero-shot claim verification.
Outcome: The proposed framework bridges LLMs’ knowledge gaps in specialized domains without access to external corpora or sacrificing generalizability.
Prompt to be Consistent is Better than Self-Consistent? Few-Shot and Zero-Shot Fact Verification with Pre-trained Language Models (2023.findings-acl)

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Challenge: Existing methods for few-shot and zero-shot fact verification require a large set of training data.
Approach: They propose a method to prompt pre-trained language models to be consistent to improve the factuality assessment capability of PLMs.
Outcome: The proposed method outperforms state-of-the-art few-shot fact verification models with a small number of unlabeled instances on zero-shot verification.

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