encoder-decoder architecture
This is a neural network architecture commonly used in tasks like machine translation and text generation. The encoder processes the input data to create a condensed representation, while the decoder uses this representation to produce an output sequence.
- BEAST: Efficient Tokenization of B-Splines Encoded Action Sequences for Imitation Learning
- BlockDecoder: Boosting ASR Decoders with Context and Merger Modules
- Encoder-Decoder Diffusion Language Models for Efficient Training and Inference
- Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification
- Mamba Only Glances Once (MOGO): A Lightweight Framework for Efficient Video Action Detection
- TimePerceiver: An Encoder-Decoder Framework for Generalized Time-Series Forecasting