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.
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Transcendence: Generative Models Can Outperform The Experts That Train Them
Neural Information Processing Systems
Therefore, when trained on data generated by humans, we may not expect the artificial model to outperform the humans on their original objectives.
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Guiding Large Language Models via Directional Stimulus Prompting
Neural Information Processing Systems
T5) to generate an auxiliary directional stimulus prompt for each input instance.
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Reducing Transformer Key-Value Cache Size with Cross-Layer Attention William Brandon
Neural Information Processing Systems
Key-value (KV) caching plays an essential role in accelerating decoding for transformer-based autoregressive large language models (LLMs).
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