让同一论点在不同世界观下显现不同结论，揭示隐性假设差异
TruthSplit: Operationalizing Conditional Validity in Arguments Through Multi-Perspective Reasoning
- 基于多视角世界观分析论点逻辑与价值一致性
- 通过三阶段NLI识别观点分歧的深层原因
- 适合需要批判性思维或跨立场沟通的研究者
我们提出TruthSplit，一个支持多视角论点分析的交互式系统。现有论点分析工具通常关注论证结构、质量、立场或说服力等内部属性，而将视角相关的背景知识隐含处理。TruthSplit弥补这一缺口，支持探索同一主张在不同世界观的价值观、假设和概念定义下导致不同结论的现象，我们称之为条件有效性。给定输入论点文本，TruthSplit提取主张与前提，采用三层自然语言推理（NLI）方法评估逻辑一致性和世界观特异性规范一致性，并以结构化世界观档案（包含核心价值观与决策原则）为条件，引导大语言模型推理。系统生成各视角下的解释，识别价值冲突与假设缺口，并通过交互式界面可视化分歧。
原文摘要 · Abstract (English)
We present TruthSplit, an interactive system for multi-perspective argument analysis. Existing argumentation tools typically analyze properties of the argument itself, such as structure, quality, stance, or persuasiveness, while leaving perspective-specific background knowledge implicit. TruthSplit addresses this gap by supporting an exploratory analysis of how the same claim can lead to different conclusions when interpreted through worldview-specific values, assumptions, and conceptual definitions. We refer to this perspective-dependent analysis as conditional validity. Given an input argumentative text, TruthSplit extracts claims and premises, applies a three-layer natural language inference (NLI) approach to assess both logical and worldview-specific normative consistency, and conditions large language model (LLM) reasoning on structured worldview profiles that encode core values and decision principles. The system then generates perspective-specific interpretations, identifies value conflicts and assumption gaps, and visualizes divergence through interactive analytical interfaces.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。