TLDR Tech / Dev
Language Models for Text Classification: From Bag-of-Words to Jev
This visual history traces text classification from bag-of-words and recurrent networks through transformers and Jev-style decision APIs. Jev is positioned between narrow specialist classifiers and general-purpose language models, offering broad zero-shot classification with lower latency and cost. The practical opportunity is to use calibrated decision models for routing, screening, evaluation, and other bounded choices inside agent systems.
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