Compile real-world Claude Code and Codex trajectories into verified, tradable post-training assets.
Procedural data generators for verifiable reasoning, synthetic pretraining, post-training, evaluation, and RL.
Context & Guide For Reinforcement Learning with Verifiable Rewards with Large Language Models
Score the trustworthiness of outputs from any LLM in real-time
🐀 Fuzz your verifier before an RL agent does. Static + dynamic LLM security auditor to detect reward-hacking in RL post-training environments (OpenEnv, verifiers-spec, Gymnasium).
A curated list of rubrics, checklists, criteria sets, principles, and scoring guides used to score, rank, verify, filter, or train modern generative models.
Open Arena: SLM verifiers across observability platforms, dataset and model catalogs, and value scenarios for LLM, agentic and harness evals.
Write loops, not prompts. The loop is easy — the verifier is the whole game. VCN night one at Network School.
An RL Enviorment for AES Inversion
A verifiers RLM environment for testing whether adaptive recursive search outperforms brittle manual RAG choreography on long synthetic corpora.
Adversarial QA for LLM-RL environments: find out what reward an empty answer earns. Model-free, zero API cost.
An open reinforcement-learning (RL) environment that trains LLM agents to use the current fact, not the stale one — verifiable reward for temporal fact-currency, built on verifiers / prime-rl (GRPO, LoRA).
Reproducible verifier audits, datasheets, agreement metrics, and release gates
Typed asset shapes + visual + headless views for AI agents. One asset definition. Three rendering targets (HTML / Markdown / Text).
Research proposal for verifier-gated on-policy distillation with explicit evaluation and claim boundaries
Running, reproducing, and testing AI agent environments to understand how they work.
RLVR coding environment for training and evaluating LLM agents on automated code-fixing tasks.
Verifiers hello world repo
Deterministic three.js frontier game and Prime Intellect Verifiers v1 agent environment
Deterministic SRT captioning environment for LLM evaluation and reinforcement learning.
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