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Output verifiers versus process verifiers
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Classroom Contents
Test Time Compute: Verifiers and Parallel Sampling - Part 2
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- 1 Sampling and Verification
- 2 Training Compute vs Test Time Compute
- 3 Part 1 Recap: Sampling and Chain of Thought
- 4 Video Overview: Parallel Sampling and Filtering with Verifiers
- 5 How to sample multiple answers in parallel
- 6 Verifier Methods
- 7 Improving verifiers with fine-tuning or prompt optimisation
- 8 Output verifiers versus process verifiers
- 9 Majority Voting and Monte Carlo MCTS
- 10 Notebook Setup - Trelis.com/advanced-inference
- 11 Installation of vLLM with guided decoding
- 12 Loading Llama 3.2 1B as opposed to 3B in Part 1
- 13 Baseline Single-shot approach
- 14 Parallel sampling approach Pass@n / perfect verifier
- 15 Parallel sampling with a voting verifier using vLLM guided decoding
- 16 Prompt optimisation for verifiers
- 17 Parallel sampling with a scoring verifier 1-10
- 18 Parallel sampling with a binary true/false scoring verifier
- 19 Llama 3.2 1B Results
- 20 Literature Review Let’s Verify Step by Step, Large Language Monkeys, Are more LLM calls all you need? Tree of Thought
- 21 Resources
