aisingapore/MultiTurn-Chat-MT-Bench-Judge

SEA-MT-Bench-Judge

SEA-MT-Bench-Judge expands on the original SEA-MTBench through the use of a criteria-based evaluation framework. We use GPT-OSS-120B as the judge model.

The prompts are based on MT-Bench and was manually translated by native speakers. Furthermore, some prompts were modified to be more suitable for the criteria-based judgments.

Supported Tasks and Leaderboards

SEA-MT-Bench-Judge is designed for evaluating chat or instruction-tuned large language models (LLMs). It is part of the SEA-HELM leaderboard from AI Singapore.

Languages

• English (en)
• Indonesian (id)
• Thai (th)
• Vietnamese (vi)
• Malay (ms)
• Filipino (tl)
• Tamil (ta)

Dataset Details

SEA-MT-Bench-Judge is split by language. Below are the statistics for this dataset. The number of tokens only refer to the strings of text found within the prompts column.

Split	# of examples
en	58
id	58
th	58
vi	58
ms	58
tl	58
ta	58

Data Sources

Data Source	License	Language/s	Split/s
MT-Bench	CC BY 4.0	English	en
SEA-MTBench^	CC BY 4.0	Indonesian, Thai, Vietnamese, Malay, Filipino, Tamil	id, th, vi, ms, tl, ta

^ manually translated from MT-Bench

License

For the license/s of the dataset/s, please refer to the data sources table above.

We endeavor to ensure data used is permissible and have chosen datasets from creators who have processes to exclude copyrighted or disputed data.

Acknowledgement

This project is supported by the National Research Foundation Singapore and Infocomm Media Development Authority (IMDA), Singapore under its National Large Language Model Funding Initiative.

References

@misc{zheng2023judgingllmasajudgemtbenchchatbot,
      title={Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena}, 
      author={Lianmin Zheng and Wei-Lin Chiang and Ying Sheng and Siyuan Zhuang and Zhanghao Wu and Yonghao Zhuang and Zi Lin and Zhuohan Li and Dacheng Li and Eric P. Xing and Hao Zhang and Joseph E. Gonzalez and Ion Stoica},
      year={2023},
      eprint={2306.05685},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2306.05685}, 
}