第一步:什么是Truthful QA Benchmark评价指标? TruthfulQA指的是系统需要回答真实和准确的问题。而Benchmark评价指标是用来衡量系统在特定任务上的性能的指标。Truthful QA Benchmark评价指标就是为了评估真实性问答系统在任务上的表现而设计的一系列指标。 第二步:哪些是Truthful QA Benchmark评价指标的主要组成部分?
TL;DR 一个用来评判语言模型生成的答案是否真实的benchmark,精心设计了800+个问题,这些问题包含一些类似于流行的错误观念等,且容易被错误回答。为了表现得好,模型必须避免从人类文本中学到一些错误答案。 Dataset/Algorithm/Model/Experiment Detail 作者认为目前模型的错误回答有几类:1. 意外误用 2. 在专业知识上的谬...
注意:还是包含了一些exemplars的,和传统的zero-shot有所不同。 Conclusion 对大模型真实性的有效评估值得进一步思考,特别在中文领域还没有真实性评估的benchmark? 人工评估质量最高,但费时费力,文中提到的自动化评估方式可能更加高效。 发布于 2023-07-04 11:40・IP 属地浙江...
We propose a benchmark to measure whether a language model is truthful in generating answers to questions. The benchmark comprises 817 questions that span 38 categories, including health, law, finance and politics. We crafted questions that some humans would answer falsely due to a false belief ...
This repository contains code for evaluating model performance on the TruthfulQA benchmark. The full set of benchmark questions and reference answers is contained in TruthfulQA.csv. The paper introducing the benchmark can be found here. Authors: Stephanie Lin, University of Oxford (sylin07@gmail...
Traceback (most recent call last): File "c:\aigc\llama\ipex-llm\python\llm\dev\benchmark\harness\lm-evaluation-harness\lm_eval\tasks_init_.py", line 369, in get_task return TASK_REGISTRY[task_name] ~~~^^^ KeyError: 'tru...
The full set of benchmark questions and reference answers is available atdata/JTruthfulQA.csv. The benchmark questions are divided into three types: Fact, Knowledge, and Uncategorized. Task The task is to answer the given questions. To make it easier to evaluate the answers that were generated...
This repository contains code for evaluating model performance on the TruthfulQA benchmark. The full set of benchmark questions and reference answers is contained inTruthfulQA.csv. The paper introducing the benchmark can be foundhere. Authors: Stephanie Lin, University of Oxford (sylin07@gmail.com...