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Found 5 papers, 2 papers with code
Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models
These LoRA modules can be aligned with the expert design principles observed in Mixture-of-Experts (MoE).
A Two-Stage Framework in Cross-Spectrum Domain for Real-Time Speech Enhancement
Two-stage pipeline is popular in speech enhancement tasks due to its superiority over traditional single-stage methods.
Magnitude-and-phase-aware Speech Enhancement with Parallel Sequence Modeling
In speech enhancement (SE), phase estimation is important for perceptual quality, so many methods take clean speech's complex short-time Fourier transform (STFT) spectrum or the complex ideal ratio mask (cIRM) as the learning target.
VSANet: Real-time Speech Enhancement Based on Voice Activity Detection and Causal Spatial Attention
The deep learning-based speech enhancement (SE) methods always take the clean speech's waveform or time-frequency spectrum feature as the learning target, and train the deep neural network (DNN) by reducing the error loss between the DNN's output and the target.
HIT-SCIR at SemEval-2020 Task 5: Training Pre-trained Language Model with Pseudo-labeling Data for Counterfactuals Detection
In this task, we dedicate to detecting causation, especially counterfactuals from texts.
