Jev Based Adaptive Thinking for LLMs

Reddit r/LocalLLaMA Tools
llm adaptive-thinking entropy-gating open-source reasoning local-models

Summary

An open-source experiment applying Jevons-style (JEV) logic to make LLM thinking adaptive: the model measures per-word entropy and triggers additional parallel thinking blocks only when uncertainty is high, selecting the best branch via tree search. Aimed especially at users running local models who can leverage parallel decoding streams.

Hi, I experimented with the following idea, using JEV logic to make the thinking process of LLMs adaptive. For every single word we measure the entropy and when the model is unsure we use a JEV like gate where we ask the model if it should trigger a thinking process. We have the opening thought that happens anyway, but then we may have additional thinking blocks, based on the logic above. For the thinking blocks we have some tree of parallel conversations where again we use JEV logic to define the best line. I hope it can inspire people, especially if you run local models and you have the ability to run multiple streams, anyway bottlenecked by RAM speed for decode. Github repo (open source): https://github.com/dimknaf/adaptive-thinking
Original Article

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