EQ-Bench

Emotional Intelligence Benchmark for LLMs

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Model Params EQ-Bench* MAGI-Hard† Combined

* EQ-Bench v2 scoring system has superseded v1. Scores are not directly comparable between v1 and v2. More info.

† MAGI-Hard is a custom subset of MMLU and AGIEval which is highly discriminative amongst the top models (and weakly discriminative lower down). Read more here.

Cite EQ-Bench:

@misc{paech2023eqbench,
	title={EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models}, 
	author={Samuel J. Paech},
	year={2023},
	eprint={2312.06281},
	archivePrefix={arXiv},
	primaryClass={cs.CL}
}
MAGI draws from the MMLU and AGIEval tests. Click to show citations 

@article{hendryckstest2021,
		title={Measuring Massive Multitask Language Understanding},
		author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
		journal={Proceedings of the International Conference on Learning Representations (ICLR)},
		year={2021}
}

@article{hendrycks2021ethics,
		title={Aligning AI With Shared Human Values},
		author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt},
		journal={Proceedings of the International Conference on Learning Representations (ICLR)},
		year={2021}
}

@misc{zhong2023agieval,
		title={AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models},
		author={Wanjun Zhong and Ruixiang Cui and Yiduo Guo and Yaobo Liang and Shuai Lu and Yanlin Wang and Amin Saied and Weizhu Chen and Nan Duan},
		year={2023},
		eprint={2304.06364},
		archivePrefix={arXiv},
		primaryClass={cs.CL}
}

@inproceedings{ling-etal-2017-program,
		title = "Program Induction by Rationale Generation: Learning to Solve and Explain Algebraic Word Problems",
		author = "Ling, Wang  and
		Yogatama, Dani  and
		Dyer, Chris  and
		Blunsom, Phil",
		booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
		month = jul,
		year = "2017",
		address = "Vancouver, Canada",
		publisher = "Association for Computational Linguistics",
		url = "https://aclanthology.org/P17-1015",
		doi = "10.18653/v1/P17-1015",
		pages = "158--167",
}

@inproceedings{hendrycksmath2021,
		title={Measuring Mathematical Problem Solving With the MATH Dataset},
		author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt},
		journal={NeurIPS},
		year={2021}
}

@inproceedings{Liu2020LogiQAAC,
		title={LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning},
		author={Jian Liu and Leyang Cui and Hanmeng Liu and Dandan Huang and Yile Wang and Yue Zhang},
		booktitle={International Joint Conference on Artificial Intelligence},
		year={2020}
}

@inproceedings{zhong2019jec,
		title={JEC-QA: A Legal-Domain Question Answering Dataset},
		author={Zhong, Haoxi and Xiao, Chaojun and Tu, Cunchao and Zhang, Tianyang and Liu, Zhiyuan and Sun, Maosong},
		booktitle={Proceedings of AAAI},
		year={2020},
}

@article{Wang2021FromLT,
		title={From LSAT: The Progress and Challenges of Complex Reasoning},
		author={Siyuan Wang and Zhongkun Liu and Wanjun Zhong and Ming Zhou and Zhongyu Wei and Zhumin Chen and Nan Duan},
		journal={IEEE/ACM Transactions on Audio, Speech, and Language Processing},
		year={2021},
		volume={30},
		pages={2201-2216}
}