OMNIX Benchmarks 是一个用于评估和基准测试大型语言模型性能的数据集。它旨在通过一套标准化的指标对模型进行综合比较，涵盖格式遵循、逻辑推理、知识回忆、约束遵循、成功率（首次通过和最终）以及推理延迟等多个关键维度。该数据集支持文本生成和问答任务类别，并提供了对多个流行模型（如 Qwen、Gemma、Llama 等系列的不同版本）在上述维度上的量化评分和排名分析，帮助研究人员和开发者了解

Hugging Face2026-07-07 更新100

A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions

可解释性机器学习

信息论

This dataset was produced by simulations done in "A General Framework for Interpretable Neural Learning based on Local Information-Theoretic Goal Functions"

DataCite Commons2024-07-02 更新60

Additional file 10 of Development and internal validation of an interpretable machine learning model to predict coagulopathy following extracorporeal membrane oxygenation: a retrospective multicenter study

ECMO后凝血病预测

可解释性机器学习

Supplementary Material 10.

NIAID Data Ecosystem50

next-tat/MMDocBench

视觉文档理解

模型基准测试

--- license: cc-by-sa-4.0 task_categories: - question-answering - visual-question-answering - table-question-answering language: - en pretty_name: MMDocBench size_categories: - 1K<n<10K tags: - LVLMs

Hugging Face2024-10-30 更新90

CROSS-DOMAIN DYNAMIC VOCABULARY IN METROLOGICAL USE CASES: LINKAGE, AUTOMATIZATION AND IMPLEMENTATION

计量学术语整合

数据互操作性

IMEKO 2024 Conference Paper

科学数据银行2025-12-17 更新50