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Found 6 papers, 3 papers with code
How Multimodal Integration Boost the Performance of LLM for Optimization: Case Study on Capacitated Vehicle Routing Problems
Recently, large language models (LLMs) have notably positioned them as capable tools for addressing complex optimization challenges.
Asynchronous and Segmented Bidirectional Encoding for NMT
With the rapid advancement of Neural Machine Translation (NMT), enhancing translation efficiency and quality has become a focal point of research.
Efficient Reinforcemen Learning via Decoupling Exploration and Utilization
OPARL employs a unique dual-actor approach: an optimistic actor dedicated to exploration and a pessimistic actor focused on utilization, thereby effectively differentiating between exploration and utilization strategies.
CIGAN: A Python Package for Handling Class Imbalance using Generative Adversarial Networks
A key challenge in Machine Learning is class imbalance, where the sample size of some classes (majority classes) are much higher than that of the other classes (minority classes).
Powerful Graph Convolutioal Networks with Adaptive Propagation Mechanism for Homophily and Heterophily
To address this problem, in this paper we design a novel propagation mechanism, which can automatically change the propagation and aggregation process according to homophily or heterophily between node pairs.
On the Discovery of Feature Importance Distribution: An Overlooked Area
We then propose a feature importance model to capture a high-resolution distribution of feature importance across feature values.
