Core
Reward Models
A reward model scores a candidate output by how much a human would prefer it, learned from pairwise comparisons rather than absolute ratings. It is the signal that drives RLHF, ranks best-of-N samples, and guides test-time search, which is why FDE loops probe how it is trained, where it leaks, and the outcome-versus-process distinction.
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LLM & GenAI FundamentalsWalk through the RLHF pipeline (SFT, reward model, PPO) and explain how DPO simplifies it. →hard · PremiumAI Security, Privacy & GovernanceReproduce-from-paper: design a production-safe Constitutional-AI-style fine-tuning pipeline that aligns a chatbot to a set of rules →hard · PremiumLLM & GenAI FundamentalsGRPO vs PPO-based RLHF: how does group-relative reward let you drop the value model? →hard · PremiumLLM & GenAI FundamentalsTrain a reward model for a coding agent from 100K noisy human scores biased toward short solutions. →expert · PremiumLLM & GenAI FundamentalsWhat's the difference between a base model and an instruct model, and why would a customer care? →easy · FreeLLM & GenAI FundamentalsInstruction tuning: win-rate keeps rising but factual QA accuracy drops. What's happening and the immediate fix? →hard · Premium