Datasets:
| task_categories: | |
| - graph-ml | |
| license: mit | |
| tags: | |
| - multi-agent-systems | |
| - benchmark | |
| - llms | |
| dataset_info: | |
| features: | |
| - name: 'Unnamed: 0' | |
| dtype: int64 | |
| - name: graph_generator | |
| dtype: string | |
| - name: num_nodes | |
| dtype: int64 | |
| - name: index | |
| dtype: int64 | |
| - name: graph | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 517975 | |
| num_examples: 117 | |
| download_size: 127270 | |
| dataset_size: 517975 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| # AgentsNet | |
| This repository contains the graph instances used in the [AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs](https://huggingface.co/papers/2507.08616) paper. | |
| AgentsNet is a new benchmark for multi-agent reasoning, designed to measure the ability of multi-agent systems to collaboratively form strategies for problem-solving, self-organization, and effective communication given a network topology. It draws inspiration from classical problems in distributed systems and graph theory. | |
| * **Paper**: [AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs](https://huggingface.co/papers/2507.08616) | |
| * **Project Page**: [https://agentsnet.graphben.ch](https://agentsnet.graphben.ch) | |
| * **GitHub Repository**: [https://github.com/ashleve/lightning-hydra-template](https://github.com/ashleve/lightning-hydra-template) | |
| ## Dataset | |
| The dataset consists of synthetic graphs generated using various random graph models. It serves as the input for all experiments in the benchmark. | |
| ## Citation | |
| If you use this dataset, please cite the associated paper: | |
| ```bibtex | |
| @misc{grötschla2025agentsnetcoordinationcollaborativereasoning, | |
| title={AgentsNet: Coordination and Collaborative Reasoning in Multi-Agent LLMs}, | |
| author={Florian Grötschla and Luis Müller and Jan Tönshoff and Mikhail Galkin and Bryan Perozzi}, | |
| year={2025}, | |
| eprint={2507.08616}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.MA}, | |
| url={https://arxiv.org/abs/2507.08616}, | |
| } | |
| ``` |