Reasoning Models
Test-time compute, process reward models, the o-series, DeepSeek-R1 and contamination.
9concepts
46flashcards
74minutes of reading
- 01 Chain-of-Thought Faithfulness Whether a model's stated reasoning is the reasoning that produced its answer, how the hint-injection test measures it, and why unfaithful CoT undermines monitoring more than it undermines accuracy.
- 02 DeepSeek-R1 and the Open Reasoning Recipe How DeepSeek's R1 pipeline produced o1-class reasoning with an open paper, an open model, and a recipe other labs could replicate within weeks.
- 03 Inference-Time Scaling Laws and Thinking Budgets How accuracy trades against tokens spent at inference, why the optimal strategy depends on question difficulty, and what a thinking budget actually buys.
- 04 Process Reward Models and Verifiable Rewards Why scoring every step of a reasoning trace beats scoring only the final answer, and how Ai2 and DeepSeek replaced PRMs entirely with programmatic correctness checks.
- 05 The Limits of Self-Correction Why asking a model to review its own answer often makes it worse, what separates intrinsic from extrinsic correction, and the oracle-label leak that inflated the early results.