轻量级模型Paladin-mini高效判断文本中论断是否成立
Paladin-mini: A Compact and Efficient Grounding Model Excelling in Real-World Scenarios
- 3.8B参数小模型，专为真实场景下的论断验证设计
- 在新基准数据集上表现超越当前最先进水平
- 开源可复现，适合需要高效文本验证的落地应用
本文针对上下文中的论断是否具备支持证据这一问题提出两项贡献。所谓‘接地’（grounding），即给定文档和论断时，文档中至少存在一条支持该论断的证据。我们提出Paladin-mini，一个3.8亿参数的开源分类模型，用于标注论断是否具有支撑证据，其设计旨在真实场景下保持稳健性能；同时构建了grounding-benchmark，一个用于评估关键推理能力的新基准数据集。实验表明，Paladin-mini在多个基准测试中优于现有最先进方法，并提供清晰、可复现的结果。
原文摘要 · Abstract (English)
This paper introduces two significant contributions to address the issue of grounding claims in a given context. Grounding means that given a context (document) and a claim, there's at least one supportive evidence for the claim in the document. We will introduce Paladin-mini, a compact (3.8B parameters) open-source classifier model (used for labeling data as grounded or ungrounded) engineered for robust performance in real-world scenarios, and the grounding-benchmark, a new evaluation dataset designed to assess performance on critical reasoning tasks. We'll also demonstrate the results of Paladin-mini with benchmarks against the current State-of-the-art and share clear and reproducible results.
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