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GenderBench – Evaluation suite for gender biases in LLMs

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GenderBench – Evaluation suite for gender biases in LLMs

GenderBench is an open-source evaluation benchmark that measures gender biases in large language models. This is my attempt to decompose this pretty complex and difficult topic into interpretable measures. My goal was to systematize the evaluation of unfair behavior in LLMs and help other developer and researchers do their own tests. What is linked here is the report that is generated from GenderBench logs that quantifies how LLMs behave in various situations when gender can be considered. Links: Repository - https://github.com/matus-pikuliak/genderbench Report - https://genderbench.readthedocs.io/latest/_static/reports/ge...

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73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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Hacker NewsStrong engagement from HN community · Strong signals: lua, ide, io · Missing: https docs, excited, just released
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nativeThis product was originally launched on this platform.
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AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
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3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

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