decision-models

Research design for a Jev-native agent system:enable more options than jev provided with virtulization and paging, tool integration, external helper logits Top-k proposals with Jev-controlled fallback ,decision-aware hierarchical memory, and dependency-aware replanning.

Run fast, typed AI decision models behind one API. Choice, score and yes/no decisions with multiple engines and hardware backends.

ReflexBench — open benchmark and evaluation harness for System One models and typed decision engines

Self-hosted, Jev-compatible decision-model API — one /v1/systemone endpoint, open weights (Laya, kev), one Docker image per engine.

Black-box reverse engineering research archive for the Jev decision model

Train lightweight language backbones for typed decisions and candidate probabilities. CE/Brier training, evaluation, and an offline end-to-end demo.

Seven decision models, measured as the candidate list grows, the option order changes, and the wrong answers stop being obvious.

Your hardware. Local decision models. Turn messy state into typed choices, scores, and yes-no calls over TypeSafe-compatible HTTP and MCP. No cloud bill.

Code for JevOut: Natural Context Can Flip Decision Models

Finite-sample guarantees for Jev (TypeSafe's System One). Conformal risk control turns calibrated probabilities into certified routing thresholds; prediction-powered inference audits them. 2,412 decisions on CLINC150 for $0.23 — including the shift and prevalence cases where the guarantee breaks.

Seems: Python, plus judgment, answered locally by Laya. A variant of kavehmz/seems-lang with the open-weight decision model swapped in for TypeSafe Jev.

1,000-decision behavioral benchmark of Jev across 25 deterministic reasoning families.

Open models, libraries, tools, and applications for Jev and System One decisions.

Train and inspect a small decision model on your Mac. Public data, full fine-tuning, honest evaluation, and downloadable weights.

Convert any causal LM into a Jev-style typed decision model — no training, no new weights. Measured honestly against JevBench, negative results included.

Benchmarking decision models under attack, starting with Jev, Shieldstral, Prompt Guard 2 and SemIf. 2,000 paired cases; 95% confidence intervals on every number.

Batched, judged, efficiency-first RL for Pollen's Microduck: many small attempts on one 4 GB GPU, pruned by a pre-registered kill order, with decision models (Jev, GLiNER2.5-Decide) measured as judges.

A small decision model improved through a Bittensor training competition.

Benchmark for typed System One decision models (Jev, Laya, and whatever comes next): calibration against a noise floor, framing sensitivity, selective prediction, ordinal fidelity, interference, robustness. pip install sys1bench.

Curated, evidence-graded list of System One models (typed probabilistic decision models), with genealogy, open and hosted models, datasets, tooling, graded evidence, a failure atlas and design patterns.