datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DEBATE
DEBATE: Diverse Multi-Agent Debates
This dataset is presented in the paper "MALLM: Multi-Agent Large Language Models Framework".
Citation
comming soon.
MultiAgentFraudBench
MultiAgentFraudBench Dataset
中文 | English
🌐 Project Page
| 📄 Paper
| 📦 Code
This directory contains the MultiAgentFraudBench dataset, a comprehensive collection of synthetic financial fraud posts designed for multi-agent fraud simulation research. The dataset is generated through a multi-agent simulation framework built on OASIS, capturing realistic fraud lifecycle from initial posts, trust-building through collusion, to victim-fraudster dialogues. All content… See the full description on the dataset page: https://huggingface.co/datasets/ninty-seven/MultiAgentFraudBench.MultiAgent-X
MultiAgent-X: Multilingual Agentic Function-Calling Benchmark
Created with Adaptive Data by Adaption
The first open-source multilingual function-calling training and evaluation dataset targeting under-resourced languages. 10,551 records across 12 languages, 7 unique writing systems, and 5 life-critical agentic domains covering 1.3 billion speakers that mainstream AI has never been optimised for.
The Gap This Fills
MASSIVE-Agents (EMNLP 2025) evaluated multilingual… See the full description on the dataset page: https://huggingface.co/datasets/Saurabh-66/MultiAgent-X.multi_agent_handoff
Multi-Agent Handoff Synthetic Dataset
The Multi-Agent Handoff Synthetic Dataset is a fully synthetic dataset designed to support research and development in multi-agent systems.
Specifically, it focuses on agent handoffs (https://openai.github.io/openai-agents-python/handoffs/) — scenarios where a central language model delegates specialized tasks to sub-agents based on user prompts.
The domian, sys_prompts and subagents design:… See the full description on the dataset page: https://huggingface.co/datasets/JayYz/multi_agent_handoff.smfr-dataset
Synthetic Multi-Hop Financial Reasoning (SMFR) Dataset
Dataset Description
The Synthetic Multi-Hop Financial Reasoning (SMFR) dataset contains synthetic stock trading analysis problems designed to evaluate multi-step reasoning and computational capabilities of large language models. Each problem presents historical stock price data for multiple companies and asks questions about investor trading strategies and portfolio performance.
Dataset Structure
The… See the full description on the dataset page: https://huggingface.co/datasets/the-illusion-of-multi-agent-advantages/smfr-dataset.factual-multiagent-roleplay-ft-ru
march228/factual-multiagent-roleplay-ft-ru
Небольшой русскоязычный synthetic finetuning dataset для обучения модели следованию ролевым системным инструкциям личности при сохранении фактической опоры на контекст.
Что это за датасет
Этот набор сделан как instruction / finetuning dataset, а не как benchmark.
В каждой записи есть:
плотный system с персоной и тоном;
context, на который нужно опираться;
пользовательский question;
внутренние thoughts;
финальный answer.… See the full description on the dataset page: https://huggingface.co/datasets/march228/factual-multiagent-roleplay-ft-ru.