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Functional Correctness on HumanEval (p@k and Precision)

71.57Pass@1

Dense

Updated 1mo ago

Evaluation Results

Method	Links
Dense 2026.06		71.57	85.58	89.63	100
SecRL-Prune 2026.06		54.79	73.18	84.21	85.3
PruneNet 2026.06		46.43	62.08	70.34	72
SecRL-Prune 2026.06		41.95	60.78	78.65	72.5
SecRL-Prune 2026.06		38.16	57.38	75.14	68.1
Dense 2026.06		36.7	68.3	87.8	100
SecRL-Prune 2026.06		34.37	53.98	71.63	63.7
Dense 2026.06		27.67	60.04	83.53	100
SecRL-Prune 2026.06		26.2	53.5	78.04	79.5
SecRL-Prune 2026.06		21.37	46.91	72.25	80.6
PruneNet 2026.06		21.3	38.57	51.05	43.9
SecRL-Prune 2026.06		18.94	35.93	58.39	56.9
PruneNet 2026.06		18.7	34.71	47.29	39.8
PruneNet 2026.06		16.1	30.85	43.53	35.7
SecRL-Prune 2026.06		15.32	31.58	53.68	49.7
SecRL-Prune 2026.06		15.06	33.78	60.97	61.2
PruneNet 2026.06		14.96	33.07	49.85	56.3
PruneNet 2026.06		14.16	30.09	42.4	43.6
SecRL-Prune 2026.06		11.91	27.72	55.33	51.8
SecRL-Prune 2026.06		11.7	27.23	48.97	42.5
PruneNet 2026.06		10.55	20.77	33.1	32.3
SecRL-Prune 2026.06		8.75	20.65	49.69	41.8
PruneNet 2026.06		7.98	20.5	37.19	35.8
PruneNet 2026.06		7.9	15.04	23.8	23.6
PruneNet 2026.06		5.96	14.73	29.88	27.3
PruneNet 2026.06		5.8	10	17.6	16.8
PruneNet 2026.06		4.2	9.7	23.85	20