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Found 5 papers, 2 papers with code
STMGF: An Effective Spatial-Temporal Multi-Granularity Framework for Traffic Forecasting
Accurate Traffic Prediction is a challenging task in intelligent transportation due to the spatial-temporal aspects of road networks.
Position-Aware Parameter Efficient Fine-Tuning Approach for Reducing Positional Bias in LLMs
Recent advances in large language models (LLMs) have enhanced their ability to process long input contexts.
RHCO: A Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning for Large-scale Graphs
To address these problems, we propose a novel Relation-aware Heterogeneous Graph Neural Network with Contrastive Learning (RHCO) for large-scale heterogeneous graph representation learning.
LightXML: Transformer with Dynamic Negative Sampling for High-Performance Extreme Multi-label Text Classification
In LightXML, we use generative cooperative networks to recall and rank labels, in which label recalling part generates negative and positive labels, and label ranking part distinguishes positive labels from these labels.
Exploiting Processing in Non-Volatile Memory for Binary Neural Network Accelerators
Recently, binary neural networks have shown impressive efficiency and accuracy on image recognition data sets.
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