Open source Mamba 3 arrives to surpass Transformer architecture with nearly 4% improved language modeling, reduced latency

This release is good for developers building long-context applications, real-time reasoning agents, or those seeking to reduce GPU costs in high-volume production environments.
GitHub

Official implementation of "Disentanglement with Factor Quantized Variational Autoencoders"

blocks: Consists of building blocks of the architecture. configs/{dataset_name}: Consists of model specific configuration files for each dataset. data: Consists of data loader files. decoders: ...
IEEE

Leveraging NLP Techniques for Robust Emotion Recognition in Text

Abstract: This study introduces a novel emotion classification framework that harnesses the power of Bidirectional Encoders Representation from Transformer's (BERT)-based contextual embeddings in ...
IEEE

A Dual-Decoder Variational Auto-Encoder for Anomaly Detection

Abstract: Anomaly detection aims to identify patterns and events that deviate from the norm. However, current methods struggle to achieve high detection accuracy due to data complexity, i.e., ...
GitHub

custom-model-binding.md

Model binding allows controller actions to work directly with model types (passed in as method arguments), rather than HTTP requests. Mapping between incoming request data and application models is ...