PostHog/jeeves

Jeeves – Reasoning improves Jev-like decision models

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A reasoning Jev-style classifier with a diffusion drafter, trained with SFT and CISPO. Inspired by Kev. Jev-like models give calibrated decision probabilities, but at low accuracy. A lot of pipelines therefore rely on a reasoning model as a fallback. Jeeves trains a Jev-like Qwen3.5-9B (LoRA and a pointer head) using CISPO to reason before it decides. This results in better performance on out of domain tasks, and outperforms Jev in JevBench hard (public). Accuracy with thinking, greedy, 2,560-token cap. The Kev-9B and Jev columns are the numbers Kev publishes. \ No Kev-9B JevBench result is published. These are Kev-8B (Qwen3). All JevBench numbers are on the public easy, standard and hard tiers (231 items). The sealed judge tier is not included, and the Jev and Kev numbers are restricted to the same public items. Without thinking the same checkpoint scores 0.804 on our test split (2,962 items), against 0.840 with…

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Inside the original README — Document outline
  1. Jeeves – Reasoning improves Jev-like decision models
  2. Acknowledgements
  3. Highlights
  4. Problem
  5. Results
  6. Quickstart
  7. Python
  8. Options
  9. How it works
  10. Training
  11. Diffusion drafter
  12. Reproduce

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What this repository does

Jeeves – Reasoning improves Jev-like decision models

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Owner
PostHog
Primary language
Python
Stars
320
Forks
12
Open issues + pull requests
6
License
MIT
Archived
No
Default branch
master
Created
2026-09-29T09:56:47.000Z
Last push
2026-09-30T08:51:49.000Z

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