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A reproducible, contamination-resistant large language model testing suite that not only evaluates models' capability metrics but also focuses on behavioral traits such as instruction following, sycophantic behavior, and excessive refusal, providing a comprehensive model profile
Section 01
A reproducible, contamination-resistant large language model testing suite that not only evaluates models' capability metrics but also focuses on behavioral traits such as instruction following, sycophantic behavior, and excessive refusal, providing a comprehensive model profile
Section 02
Section 03
The current landscape of large language model evaluation has obvious limitations. Most public leaderboards only focus on two dimensions: correctness (whether the test is passed) and human preference (which answer is more popular). However, these metrics cannot capture the real performance of models in actual use: Does it follow instructions? Is the answer concise? Can it admit ignorance when uncertain? Will it cater to users' wrong opinions?
The model-eval-suite developed by fireball-industries is designed to address this pain point. It integrates capability benchmarking and behavioral benchmarking into an ordered evaluation protocol and provides public result records.
Section 04
This project defines seven core evaluation dimensions, forming a comprehensive profile of language models:
Section 05
Evaluates the model's ability to generate, understand, and debug code. This includes not only grammatical correctness but also code style, readability, and adherence to best practices.
Section 06
Tests the model's performance in logical reasoning, mathematical calculation, causal inference, etc. This is a core indicator of the model's "intelligence" level.
Section 07
Evaluates the model's ability to understand and execute user instructions. This includes complex scenarios such as format requirements, constraints, and multi-step tasks.
Section 08
Measures the model's tendency to cater to users' opinions, even when the users' views are clearly wrong. This is an important behavioral safety indicator.
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