交互式工具，透明化验证生成文本事实准确性
FACTS&EVIDENCE: An Interactive Tool for Transparent Fine-Grained Factual Verification of Machine-Generated Text
- 用户驱动的细粒度事实核查，分解复杂文本中的每项主张
- 可视化展示每条主张的可信度、模型决策依据与多源证据
- 适合关注内容可信度的读者，提升对生成文本的掌控力
随着人工智能生成内容的广泛传播，自动化事实核查工具的重要性日益凸显。然而，现有研究和工具将事实核查简化为二分类或线性回归问题，虽可作为系统自动防护机制，但缺乏预测推理的透明度和证据来源的多样性，难以建立用户信任。本文提出 Facts&Evidence——一款交互式、透明的事实核查工具，支持用户对复杂文本进行自主验证。该工具能将输入文本拆解为多个独立主张，可视化呈现每个主张的可信度，解释模型判断依据，并关联多种多样化的证据来源。通过提供可追溯的推理过程和多源支撑，Facts&Evidence 旨在赋予机器生成内容消费者以知情权和选择权，实现可信、可控的内容使用。
原文摘要 · Abstract (English)
With the widespread consumption of AI-generated content, there has been an increased focus on developing automated tools to verify the factual accuracy of such content. However, prior research and tools developed for fact verification treat it as a binary classification or a linear regression problem. Although this is a useful mechanism as part of automatic guardrails in systems, we argue that such tools lack transparency in the prediction reasoning and diversity in source evidence to provide a trustworthy user experience. We develop Facts&Evidence - an interactive and transparent tool for user-driven verification of complex text. The tool facilitates the intricate decision-making involved in fact-verification, presenting its users a breakdown of complex input texts to visualize the credibility of individual claims along with an explanation of model decisions and attribution to multiple, diverse evidence sources. Facts&Evidence aims to empower consumers of machine-generated text and give them agency to understand, verify, selectively trust and use such text.
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