OpenJev-RLCD: A Working RLCD Implementation

arXiv:2609.38850 · cs.AI, cs.CL · Submitted 2026-09-30 · Read on arXiv

cs.AI, cs.CL

Submitted: 2026-09-30

Updated: 2026-09-30

Code: https://github.com/ZimmyGao/openjev-rlcd

Terminology

• GRPO — 19× in this paper · explained in 6 episodes
• Accuracy — 16× in this paper · explained in 1 episode
• Calibration — 7× in this paper · explained in 7 episodes
• Reinforcement Learning — 6× in this paper · explained in 4 episodes
• Benchmark — 3× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Trace — 3× in this paper · explained in 2 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Adam — 2× in this paper · explained in 2 episodes
• Aleatoric Uncertainty — 2× in this paper · explained in 5 episodes
• AI Agents — 1× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Adaptation — 1× in this paper · explained in 1 episode
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• Epistemic Uncertainty — 1× in this paper · explained in 10 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Latent Reasoning — 1× in this paper · explained in 2 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Thinking mode — 1× in this paper · explained in 2 episodes
• Verifiable Rewards — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
• Training Verifiers to Solve Math Word Problems
• Beyond Binary Rewards: Training LMs to Reason About Their Uncertainty
• Language Models (Mostly) Know What They Know
• Qwen3 Technical Report
• DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

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