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Found 3 papers, 1 papers with code
Single image super-resolution based on trainable feature matching attention network
Furthermore, we integrate non-local and channel attention into our proposed Trainable Feature Matching Attention Network (TFMAN) to further enhance SR performance.
Lifelong Knowledge Editing for LLMs with Retrieval-Augmented Continuous Prompt Learning
Model editing aims to correct outdated or erroneous knowledge in large language models (LLMs) without the need for costly retraining.
R4: Reinforced Retriever-Reorder-Responder for Retrieval-Augmented Large Language Models
The reordering learning process is divided into two steps according to the quality of the generated responses: document order adjustment and document representation enhancement.
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