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Found 6 papers, 4 papers with code
IFIR: A Comprehensive Benchmark for Evaluating Instruction-Following in Expert-Domain Information Retrieval
We introduce IFIR, the first comprehensive benchmark designed to evaluate instruction-following information retrieval (IR) in expert domains.
Self-Supervised Spatial-Temporal Normality Learning for Time Series Anomaly Detection
STEN is composed of a sequence Order prediction-based Temporal Normality learning (OTN) module that captures the temporal correlations within sequences, and a Distance prediction-based Spatial Normality learning (DSN) module that learns the relative spatial relations between sequences in a feature space.
Zero Stability Well Predicts Performance of Convolutional Neural Networks
We first give the interpretation of zero stability in the context of deep learning and then investigate the performance of existing first- and second-order CNNs under different zero-stable circumstances.
Activated Gradients for Deep Neural Networks
The experimental results also demonstrate that the proposed method is able to be adopted in various deep neural networks to improve their performance.
TempNodeEmb:Temporal Node Embedding considering temporal edge influence matrix
As a result, adjacency matrices cannot be directly used by machine learning models for making network or node level predictions.
Self-training semi-supervised classification based on density peaks of data
Having a multitude of unlabeled data and few labeled ones is a common problem in many practical ap- plications.
