ParamTatva/rlm-small-v1
Text Generation
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Language Dexterity Benchmark
I am working on a new benchmark to establish human language dexterity. My hypothesis is that certain language allow for more accurate dexterous behaviour - Pointed, unambigous, and confusion-free references of parts of speech in small and large contexts. There are certain languages with high degree of accurate grammar like Sanskrit, Esperanto, and Turkish. I am native Sanskrit speaker.
I have plans to establish this benchmark and test this hypothesis across 100 langauges. I have created 25 task prompts for text, image, video and robotics manipulation. We can test langauges across multiple popular models. Here is the github link: https://github.com/ParamTatva-org/Linguistic-Dexterity-Benchmark
I am working on a new benchmark to establish human language dexterity. My hypothesis is that certain language allow for more accurate dexterous behaviour - Pointed, unambigous, and confusion-free references of parts of speech in small and large contexts. There are certain languages with high degree of accurate grammar like Sanskrit, Esperanto, and Turkish. I am native Sanskrit speaker.
I have plans to establish this benchmark and test this hypothesis across 100 langauges. I have created 25 task prompts for text, image, video and robotics manipulation. We can test langauges across multiple popular models. Here is the github link: https://github.com/ParamTatva-org/Linguistic-Dexterity-Benchmark
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