Reward Modeling on PrincipleBench benchmark leaderboard · SOTA2 Research

Reward Modeling on PrincipleBench

93.8ClarityLlama-3.1-Nemotron-70B-Reward

Evaluation Results

Method
Llama-3.1-Nemotron-70B-Reward2025.09	93.8	81.9	91.5	89.7	66.7	87.6	90.7	86	90	85.4	88.9	81.1	86.3	87.5
Flexible Principles ScalarRM2025.09	90.6	89.4	94.9	100	87.5	92.1	90	92.1	89	89.6	94.8	93.7	91.8	91.6
Llama-3.3-Nemotron-70B-Reward2025.09	87.5	90.4	93.2	89.7	66.7	89.9	92	87.1	92.8	87.5	89.6	84.2	88.5	89.7
Bradley-Terry2025.09	84.4	91.5	89.8	89.7	83.3	88.8	90.7	88.3	90.4	87.5	88.2	90.5	89.2	89.5
Flexible Principles GenRM2025.09	84.4	84	79.7	82.1	100	82	84	85.2	81.3	70.8	87.4	90.5	82.5	83.8
Llama-3.3-Nemotron-Super-49B-GenRM2025.09	81.2	80.9	81.4	89.7	62.5	85.4	82.7	80.5	83.3	66.7	88.1	78.9	79.3	82.1
RewardAnything-8B-v12025.09	78.1	61.7	62.7	82.1	87.5	80.9	75.3	75.5	68.9	66.7	76.3	83.2	73.8	73.5
RM-R1-DeepSeek-Distilled-Qwen-32B2025.09	78.1	73.4	64.4	82.1	50	76.4	77.3	71.7	69.9	75	80.7	72.6	74.6	73.9
R3-QWEN3-14B-LORA-4K2025.09	56.3	66	62.7	79.5	41.7	79.8	65.3	64.5	64.1	56.3	74.8	68.4	65.9	67.2