Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
649adc59afdef2a8b9e943f94a04b02f-Paper.pdf
Neural Information Processing Systems
But these methods are unable to improve throughput (frames-per-second) on real-life hardware while simultaneously preserving robustness toadversarial perturbations.
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RRHF: Rank Responses to Align Language Models with Human Feedback
Neural Information Processing Systems
InstructGPT implements RLHF through several stages, including Supervised Fine-Tuning (SFT), reward model training, and Proximal Policy Optimization (PPO).
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