A Succinct Summary of Reinforcement Learning. 11 of 11
@dair_ai
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Integrated Decomposition Improves Science Q&A with Human-in-Loop
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Proposes integrated decomposition, an approach to improve Science Q&A through a human-in-the-loop workflow for refining compositional LM programs. 10 of 11
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Deep Learning Memorization: Understanding Overfitting Phenomena
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This work aims to better understand how deep learning models overfit or memorize examples; interesting phenomena observed; important work toward a mechanistic theory of memorization. 8 of 11
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StitchNet: Novel Neural Network Paradigm Through Pretrained Fragment Reuse
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StitchNet is a novel paradigm to create new coherent neural networks by reusing pretrained fragments of existing NNs. 9 of 11
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ConvNeXt V2: Performant CNN Model with Masked Autoencoder Framework
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ConvNeXt V2 is a performant model based on a fully convolutional masked autoencoder framework and other architectural improvements. CNNs are sticking back! 6 of 11
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Large Language Models Used for Corporate Lobbying Activities
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With more capabilities, we are starting to see a wider range of applications with LLMs. This paper utilized large language models for conducting corporate lobbying activities. 7 of 11