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ENTITY bidirectional encoder representations from transformers

bidirectional encoder representations from transformers

PulseAugur coverage of bidirectional encoder representations from transformers — every cluster mentioning bidirectional encoder representations from transformers across labs, papers, and developer communities, ranked by signal.

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  1. TOOL · CL_139607 ·

    New method fuses graph and text for patent entity alignment

    This paper introduces a novel method for aligning entities within science and technology patent knowledge graphs. The proposed approach leverages a graph convolution network combined with the BERT model to fuse structur…

  2. TOOL · CL_107686 ·

    LLM-annotated data boosts e-commerce search retrieval performance

    Researchers have developed a novel method for generating high-quality training data for dense retrieval models, particularly for e-commerce sponsored search. This approach leverages disagreements between multiple retrie…

  3. RESEARCH · CL_84501 ·

    New RePAIR architecture learns chess concepts via self-supervised learning

    Researchers have developed a new self-supervised learning architecture called RePAIR, which combines elements of MAE, JEPA, and BERT. This architecture is designed to encode sequential data, such as chess positions, int…

  4. TOOL · CL_66107 ·

    GNNs and score-based models enhance wireless beamforming with better CSI

    Researchers have developed a novel approach for robust hybrid beamforming in wireless communications by leveraging Graph Neural Networks (GNNs) and score-based generative models. This method aims to improve the accuracy…