datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Agentic-Long-Context-Understanding-QA 📖 Agentic Long Context Understanding 📖
Self-Taught Agentic Long Context Understanding (Arxiv).
AgenticLU refines complex, long-context queries through self-clarifications and contextual grounding, enabling robust long-document understanding in a single pass.
Installation Requirements
This codebase is largely based on OpenRLHF and Helmet, kudos to them.
The requirements are the same
pip install openrlhf
pip install -r ./HELMET/requirements.txt… See the full description on the dataset page: https://huggingface.co/datasets/yzhuang/Agentic-Long-Context-Understanding-QA.Multi-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/snorkelai/Multi-Turn-Insurance-Underwriting.un-digital-library
United Nations Digital Library (UNDL) Comprehensive Master Dataset
1. Executive Summary
Welcome to the United Nations Digital Library (UNDL) Comprehensive Master Dataset repository. This dataset represents a monumental effort to harvest, normalize, enrich, and democratize access to the vast archives of the United Nations. By leveraging advanced web harvesting techniques, robust state management, and modern big-data formats, this repository provides researchers… See the full description on the dataset page: https://huggingface.co/datasets/AdhyanshVerma/un-digital-library.Multi-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/dennis-panos/Multi-Turn-Insurance-Underwriting.ArabicMMLU_undiac
Fajri Koto, Haonan Li, Sara Shatnawi, Jad Doughman, Abdelrahman Boda Sadallah, Aisha Alraeesi, Khalid Almubarak, Zaid Alyafeai, Neha Sengupta, Shady Shehata, Nizar Habash, Preslav Nakov, and Timothy Baldwin
MBZUAI, Prince Sattam bin Abdulaziz University, KFUPM, Core42, NYU Abu Dhabi, The University of Melbourne
Introduction
We present ArabicMMLU, the first multi-task language understanding benchmark for Arabic language, sourced from school exams across diverse… See the full description on the dataset page: https://huggingface.co/datasets/go-inoue/ArabicMMLU_undiac.Multi-Turn-Insurance-Underwriting
Dataset Card for Multi-Turn-Insurance-Underwriting
Dataset Summary
This dataset includes sample traces and associated metadata from multi-turn interactions between a commercial underwriter and AI assistant. We built the system in langgraph with model context protocol and ReAct agents. In each sample, the underwriter has a specific task to solve related to a recent application for insurance by a small business. We created a diverse sample dataset covering 6 distinct types… See the full description on the dataset page: https://huggingface.co/datasets/AliDjl/Multi-Turn-Insurance-Underwriting.