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Found 4 papers, 0 papers with code
Minimizing Factual Inconsistency and Hallucination in Large Language Models
Large Language Models (LLMs) are widely used in critical fields such as healthcare, education, and finance due to their remarkable proficiency in various language-related tasks.
Synergistic Fusion of Graph and Transformer Features for Enhanced Molecular Property Prediction
While recent advances in Graph Neural Networks (GNNs) and Transformers have shown to be effective and promising, they face the following limitations: Transformer self-attention does not explicitly consider the underlying molecule structure while GNN feature representation alone is not sufficient to capture granular and hidden interactions and characteristics that distinguish similar molecules.
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Molecular Property Prediction
on ClinTox
Large-Scale Knowledge Synthesis and Complex Information Retrieval from Biomedical Documents
Recent advances in the healthcare industry have led to an abundance of unstructured data, making it challenging to perform tasks such as efficient and accurate information retrieval at scale.
3D Conditional Generative Adversarial Networks to enable large-scale seismic image enhancement
We propose GAN-based image enhancement models for frequency enhancement of 2D and 3D seismic images.
