Jev发布帖
Diogo Almeida介绍了Jev,即TypeSafe的结构化决策模型。观看发布影片,并探索原始帖子了解该模型的方法、示例和作者报告的性能。
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Recent activityDiogo Almeida介绍了Jev,即TypeSafe的结构化决策模型。观看发布影片,并探索原始帖子了解该模型的方法、示例和作者报告的性能。
TypeSafe的正式发布公告介绍了实验室,并引导开发者使用Jev。公告包含Diogo Almeida的发布影片和原始介绍。
TypeSafe宣布Jev向公众开放,无需等待列表。官方控制台是将类型化决策应用于自己应用程序的起点。
TypeSafe强调Jev的类型化输出方法:应用程序提供状态和问题,然后根据概率、选择或评分进行操作。相关公告还介绍了Venice API集成。
Start with the Launch Post. Explore four official signals.
114 项资源
AI-assisted summaries and translations. Check original sources for context and performance claims.
Offline Obsidian search with optional Jev reranking of results, requiring user approval before reranking.
JEVLAB ARTSource-linked curation
Open alternative to Jev: typed, calibrated decisions from any open-weights LLM in one forward pass (HF + vLLM), with benchmarks.
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A real-time tool to analyze and categorize tweets for viral potential.
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A YouTube guide discussing Jev's functionality, pricing, and performance comparisons with Astra, including benchmarking and parallel decision analysis.

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A collection of research papers and open reproductions supporting System One models.
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A small open decision model: state + typed questions -> calibrated probabilities. A Jev / System One re-creation on Qwen3.5.
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Tool for systematic reviewers to extract information from research articles efficiently.
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A PostgreSQL extension enabling natural language queries across databases.
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A community project using Jev to customize Hacker News content preferences.
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Utilizes Jev as a decision engine to manage and coordinate multiple bot agents for complex tasks.
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Jev (TypeSafe) exploratory thread: claim audit, live demos, and runnable code.
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Open-source BYOK arena for Jev and other AI judges. Find failures, compare quality, cost, and latency.
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Directory of Jev-based projects including repositories, SDKs, and benchmarks.
JEVLAB ARTSource-linked curation
Reproducible benchmark for measuring Jev reranking quality, latency, and cost in RAG.
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Papers, open reproductions and independent evaluations behind System One models and Jev.
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Feedback on your paper in seconds.
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A small second eval for shadcn-ui/lint that uses TypeSafe's Jev to judge the linter's own output.
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A small reproducible MuJoCo pilot comparing Jev, Claude Haiku, and reactive rules for pick-and-place.
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Experiments with openjev, an open Jev-style option-logit runner, on local models.
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JevBench v1 - a benchmark for Jev-class typed decision models: smart, cheap, fast, reliable, open.
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Jev AI performs quality checks on action labels for physical AI training data at high speed.
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Can Jev pick the winner of a real headline A/B test? 64.5% across 10,984 Upworthy randomized experiments, 74.7% when the difference was decisive.
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A Jev-inspired decision interface for existing LLMs. Explicit choices, scores, calibration, and review thresholds.
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Can a decision model beat dedicated rerankers? TypeSafe Jev vs Cohere Rerank 4 vs ZeroEntropy zerank-2 vs a chat-model baseline: 14 datasets, every raw API response, bootstrap ranges on every gap.
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Eval of Jev turning free-text player intent into typed server actions: 96% agreement, 317 ms median.
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Measures how well TypeSafe's RLCD-Jev model spots real secret credentials in file snippets.
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Sort by meaning: order lines along a plain-English dimension, from pairwise comparisons judged by TypeSafe's Jev model.
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Jev versus a hand-built regex on 544 public data-protection resolutions: 98.2% agreement for about five cents.
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Rust port of TypeSafe system-one-adapter (LLM-backed system_one evaluations).
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A chatbot from typed Jev decisions: hierarchical speculative decoding over System One probabilities.
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Reproducible early-access evaluation of Jev on Korean understanding and medical text, with runtime and cost evidence.
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Jev integrates into a recommendation engine, providing 70+ personalized suggestions per user at 0.0019$ per user.
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A research project enabling SQL queries with real type responses.
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发明 RLHF 的人,这次做了个不会说话的模型:Jev 独立研究报告。52 页 PDF + 50 条中文实测复现包 + 143 条可回溯数据表.
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PadFlow(土地开发SaaS)的类型化决策基准:模式、匿名化标记行和用于信心校准模型的运行器,如TypeSafe Jev。
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Independent, evidence-based map of when TypeSafe's Jev actually holds up vs. breaks down — real API-call receipts, not a leaderboard. 中文為主的雙語 repo。
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Independent calibration test of TypeSafe's Jev on a task it cannot have seen: 900 rule-generated support tickets (choice / score / boolean) plus 3 public benchmarks via Vercel AI Gateway. Raw responses, ECE with noise floor, temperature refit, per-type sign of miscalibration. Reproducible for ~$0.06.
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Jev-style calibrated decision model (Choice/Score/Noul) on Qwen3.5-0.8B.
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Jev-style parallel constrained decisions for any MLX model on Apple Silicon. Typed, schema-valid JSON in one forward pass.
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Evidence-backed index of real-world Jev (TypeSafe AI System One) use cases: repos, patterns, benchmarks, and measured results.
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A word-level language model whose output layer is Jev: n-gram drafter, Noul chunk verification, bits-per-token eval.
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Check whether each cited paper supports the sentence citing it. Claude proves the quote, TypeSafe's Jev scores it, a human decides.
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Typed JSON inference with DiffusionGemma, with Every and Jev benchmark results.
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Blind security benchmarks for Jev, TypeSafe's System One model: prompt injection and vulnerable code detection, built on jev-go.
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Decision harness for TypeSafe Jev — confidence gates, shadow mode, recipes, and evals. Claude CLI 48.9s → Jev 1.3s on the same row-filter job.
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Open, Jev-compatible System One decision server on DiffusionGemma.
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A spatial reference explorer for creators. Local Jev query choices, metadata highlights and source-linked collections.
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Jev enables fast search of physical library indexes.
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Ongoing Japanese research deck on Jev and System One models, maintained as Markdown slides.
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Never confidently wrong: a TLA+-verified consensus kernel around TypeSafe's Jev, run through 1,680 chaos-tested pharmacy decisions with zero wrong verdicts. Film, code, and every captured call.
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AI benchmark on Japan's 2026 Common Test: Jev vs luna-none vs luna-low (static dashboard).
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Replicating Jev with a local LLM.
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A research project featuring an English–Icelandic dictionary that uses Jev to rerank results for better accuracy.
JEVLAB ARTSource-linked curation
Jevals is a local testing environment for evaluating Jev requests and improving results through primitive operations.
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A chatbot built on a model that cannot generate text (TypeSafe AI's Jev, driven autoregressively).
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Jev monitors 25 WhatsApp customer groups in real time, alerting an LLM only when urgent issues arise.
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An open-source project aiming to develop a Jev-class decision model for research purposes.
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Zero-shot spam filtering with TypeSafe Jev Noul questions, compared with TF-IDF baselines.
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Jev 1.13 reward-model evaluation across 8 benchmark tracks, with an interactive report and 54-row SOTA comparison.
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Curated catalog of System One / Decision Models — contributions for modelsystem.one.
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A free open-source search tool powered by Jev and a search API for plain language queries.
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A small, type-safe client for asking AI questions about your data, powered by TypeSafe Jev.
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Batched single-token choice inference for open language models, compatible with TypeSafe.
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Semantic test matchers for Vitest and Jest, powered by TypeSafe's Jev model. Write expectations in plain English, get calibrated probabilities back.
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This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
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A research project auditing Jev's performance with the Spanish language.
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Local bilingual probability decisions from context, questions, and candidate answers. Independent research preview inspired by TypeSafe Jev.
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Open replica of TypeSafe's Jev: typed calibrated decisions in one forward pass, on Gemma 4 E2B / Gemma 3 270M (Modal).
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The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.
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Nushell module for the TypeSafe System One API: typed decisions with calibrated probabilities.
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A reproduction of Jev that turns any Qwen model into a fast decision model, serving the same /v1/systemone schema (Choice, Score, Noul) with no training and no generated answer text.
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Jev (TypeSafe) vs Claude Haiku 4.5 on 2 000 phishing emails: accuracy, calibration, latency, cost. Reproducible benchmark.
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