jevbooks

← All projects

llm-memory-audit

lizhuojunx86/llm-memory-audit

Pre-registered tests of whether language models remember market outcomes.

Evaluation & Benchmarking0.94Runner-up: Calibration & ResearchCheck-up
Automated README summary

Automatically summarized from the README on 27 Sept 2026; not a run by jevbooks. Run instructions and author-reported outcomes still need verification.

What it is

A repository of pre-registered studies testing whether language models remember how market events turned out, so that backtests measure memory rather than judgment. It publishes code, per-call probabilities, and freeze proofs, but withholds licensed data.

How it uses Jev

In the Jev study, TypeSafe Jev (`jev-1.13-20260917`) is asked to predict whether each of 12,533 US earnings announcements beat expectations, comparing each company only with itself. The README does not say how Jev is called or how its probabilities are used in code.

Technique worth stealing

Pre-registering the protocol and anchoring a freeze file in Bitcoin before any model call.

View on GitHub

Start using Jev: API key and your first request →

Model judgments from README excerpts

Project signals use repository metadata, an existing summary and the first 700 README characters, not the full project. “Not found” means not detected in that material; it does not establish absence. These are the original judgments with recorded models and dates, not source audits or run results.

Models & evaluation dates

Inclusion gate
jev-1.13.0
Project signals
jev-1.13.0
Category
jev-1.13.0
Pattern tags
jev-1.13.0

Evidence

These signals use repository metadata, an existing summary and at most 700 cleaned README characters. ≥ 0.60 means reported in that excerpt; ≤ 0.40 means not found there. The middle band is inconclusive. None is a source-code audit or a test result. The runnable-tool question excludes research experiments; the recommendation question asks for a learning shortlist, not a quality verdict.

  • Jev is core to the projectnot found in the excerpt0.25
  • Shows a System One patternnot found in the excerpt0.15
  • Describes handling uncertaintynot found in the excerpt0.04
  • Reports measured numbersFound in material0.96
  • Is a runnable toolnot found in the excerpt0.06
  • Top-10 learning shortlist signalnot found in the excerpt0.28
  • Is a replica of the modelnot found in the excerpt0.06
  • Solves a common problem (0–2)score on a 0–2 scale0.83 / 2
  • About JevFound in material0.96
Signals
Jev is core to the project0.25Shows a System One pattern0.15Describes handling uncertainty0.04Reports measured numbers0.96Is a runnable tool0.06Top-10 learning shortlist signal0.28Is a replica of the model0.0600.51Solves a common problem (0–2)0.83 / 2012

no-judgment band (0.40–0.60)

Design patterns
Check-up0.85Viewfinder0.3200.51

no-judgment band (0.40–0.60)

The Jev model and date for each judgment stage are listed above. Card written by DeepSeek V4.1 Flash from the README on 27 Sept 2026.