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Found 6 papers, 4 papers with code
Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Study
Experimental outcomes highlight LogCleaner's capability to reduce over 70% of log events in anomaly detection, accelerating the model's inference speed by approximately 300%, and universally improving the performance of models for anomaly detection.
LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
Recent advancements in large language models (LLMs) are propelling us toward artificial general intelligence with their remarkable emergent abilities and reasoning capabilities.
Fast and Controllable Post-training Sparsity: Learning Optimal Sparsity Allocation with Global Constraint in Minutes
Previous methods for finding sparsity rates mainly focus on the training-aware scenario, which usually fails to converge stably under the PTS setting with limited data and much less training cost.
Compressing Models with Few Samples: Mimicking then Replacing
Hence, previous methods optimize the compressed model layer-by-layer and try to make every layer have the same outputs as the corresponding layer in the teacher model, which is cumbersome.
Hate Speech Detection Based on Sentiment Knowledge Sharing
The wanton spread of hate speech on the internet brings great harm to society and families.
Design and implementation of smart cooking based on amazon echo
Smart cooking based on Amazon Echo uses the internet of things and cloud computing to assist in cooking food.
