MSEED features a hierarchical encoder-decoder architecture, a short-term-enhanced subnet, and a feature assembling layer that integrates spatial and temporal information across multivariate inputs. By ...

This transformation is important because it allows the model to “understand” the input. Then, the decoder uses the information of the encoder and generates an output, such as a translation of the ...

Travel route recommendation is an important part of electronic tour guides and map applications. It aims to recommend a sequence of points of interest (POIs) to users based on their interests. The ...

📢We are excited to introduce RAVEN, a retrieval-augmented encoder-decoder language model. Despite having substantially fewer parameters than top models, RAVEN delivers competitive results in ...

The model works quite well, but unfortunately its inference time is quite high (about 400ms to generate a sentence of about 7 tokens). We would like to reduce that time, and have opted for ONNX and ...

In this paper, we propose an encoder-decoder model which embeds the interaction between entities and relations, and adds a gate mechanism to control the attention mechanism. Experimental results show ...