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- arXiv:2502. 14902v1 [cs. CL] 18 Feb 2025
Abstract Retrieval-augmented generation (RAG) im-proves the response quality of large language models (LLMs) by retrieving knowledge from external databases Typical RAG approaches split the text database into chunks, organizing them in a flat structure for eficient searches To better capture the inherent dependencies and structured relationships across the text database, researchers propose
- GemNet: Universal Directional Graph Neural Networks for Molecules
Effectively predicting molecular interactions has the potential to accelerate molecular dynamics by multiple orders of magnitude and thus revolutionize chemical simulations Graph neural networks (GNNs) have recently shown great successes for this task, overtaking classical methods based on fixed molecular kernels However, they still appear very limited from a theoretical perspective, since
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