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Directly optimizing internal reasoning from outcome feedback, GradCuit achieves a 6.6% accuracy boost over chain-of-thought prompting while enhancing robustness and interpretability.
Forget expensive human preference data: this new method uses the policy's own value function to self-supervise reward model training, boosting performance across diverse benchmarks and RL algorithms.
Can dynamically weighting opinions by the credibility of their proponents help online platforms recover from misinformation and resist manipulation better than simple voting or staking?
