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@@ -88,14 +88,14 @@ out = generate(model, tokenizer, prompt=prompt, max_tokens=4096,
 ### HumanEval+ (code generation)
 
 - **Dataset**: `evalplus/humanevalplus` test split (164 prompts, harder tests than HumanEval).
-- **Protocol**: greedy pass@1 baseline + pass@5 retry on failures.
-- **Sampling for pass@5**: temp=1.0, top_p=0.95, top_k=40 (MiniMax official); k=5 samples per failed problem, early stop on first pass.
+- **Protocol**: sampled pass@1 baseline + pass@5 retry on failures.
+- **Sampling for both pass@1 and pass@5 retry**: temp=1.0, top_p=0.95, top_k=40 (MiniMax official); max_tokens=5000 on pass@1, 1200 on pass@5; k=5 samples per failed problem, early stop on first pass.
 - **Grading**: each candidate run with 20s subprocess timeout; must pass ALL EvalPlus tests.
 
 | Metric | Score |
 |--------|-------|
-| **pass@1 (greedy)** | **71.95%** (118/164) |
-| **pass@5 (greedy + sampled retry)** | **89.02%** (146/164) |
+| **pass@1 (sampled, temp=1.0)** | **71.95%** (118/164) |
+| **pass@5 (sampled, retry of failures)** | **89.02%** (146/164) |
 
 28 of 46 greedy failures recovered via sampling; 18 residual failures are genuine logic errors or prompts where 1200 tokens ran out mid-reasoning.