Large language models (LLMs) have changed the game for machine translation (MT). LLMs vary in architecture, ranging from decoder-only designs to encoder-decoder frameworks. Encoder-decoder models, ...

The encoder processes the input sequence and generates a contextualized ... with increasing the number of experts or total parameter size showing significant performance improvements. Decoder-Only ...

A hardware decoder would still beat any software-only library by a wide margin, of course. One of the apps already using libdav1d is YouTube, though the server-side change forcing AV1 videos onto ...

Natural Language Processing (NLP) tasks heavily rely on text embedding models as they translate the semantic meaning of text into vector representations. These representations make it possible to ...

Abstract: End-to-end (E2E) models, including the attention-based encoder-decoder (AED) models, have achieved promising performance on the automatic speech recognition (ASR) task. However, the ...

the proposed model takes 5-adjacent slices as the input but only outputs the prediction for the centering slice of the multichannel input. Figure 3. An overview of the proposed HED-Net, which is a ...