livebench_coding

# Dataset Card for "livebench/coding"
LiveBench is a benchmark for LLMs designed with test set contamination and objective evaluation in mind. It has the following properties:
- LiveBench is designed to limit potential contamination by releasing new questions monthly, as well as having questions based on recently-released datasets, arXiv papers, news articles, and IMDb movie synopses.
- Each question has verifiable, objective ground-truth answers, allowing hard questions to be scored accurately and automatically, without the use of an LLM judge.
- LiveBench currently contains a set of 18 diverse tasks across 6 categories, and we will release new, harder tasks over time.
This is the instruction_following category of livebench.

See more in our [paper](https://arxiv.org/abs/2406.19314), [leaderboard](https://livebench.ai/), and [datasheet](https://github.com/LiveBench/LiveBench/blob/main/docs/DATASHEET.md).

# 「livebench/coding」数据集卡片
LiveBench是一款专为大语言模型（Large Language Model，LLM）设计的基准测试套件，其研发充分考量了测试集污染问题与客观评估需求，具备以下特性：
- LiveBench通过每月发布全新问题、以及基于近期公开数据集、arXiv论文、新闻文章和IMDb电影剧情简介构建问题，以此限制潜在的测试集污染。
- 每个问题均配有可验证的客观标准答案，即便高难度问题也可实现精准自动评分，无需借助大语言模型作为评判工具。
- 当前LiveBench共涵盖6个类别下的18项多样化任务，后续将持续发布难度更高的全新任务。
本数据集为LiveBench的指令遵循（instruction_following）子类别。

如需了解更多信息，请参阅我们的[论文](https://arxiv.org/abs/2406.19314)、[排行榜](https://livebench.ai/)以及[数据集说明文档](https://github.com/LiveBench/LiveBench/blob/main/docs/DATASHEET.md)。