encoder-decoder

by Synced 2022-06-20 3

Meta AI’s LegoNN Builds Decoder Modules That Are Reusable Across Diverse Language Tasks Without Fine-Tuning

In the new paper LegoNN: Building Modular Encoder-Decoder Models, Meta AI researchers propose LegoNN, a procedure for building encoder-decoder architectures with decoder modules that can be shared across different tasks without finetuning or significant performance reductions.

by Synced 2017-08-17 1

Global News Research

History and Frontier of the Neural Machine Translation

Compared to SMT, NMT can train multiple features jointly and does not need prior domain knowledge, enabling zero-shot translation. In addition to higher BLEU score and better sentence structure, NMT can also help reduce morphology errors, syntax errors, and word order errors of SMT.

by Synced 2017-08-15 2

China Research

30 Years of Devotion to Natural Language Processing Based on Concepts

We interviewed Mr. Qiang Dong, chief scientist of Beijing YuZhi Language Understanding Technology Co. Ltd. and learned more about their YuZhi NLU Platform that conducts its unique semantic analysis based on concepts rather than words.

by Synced 2017-08-01 0

Research

Achieving Open Vocabulary Neural Machine Translation with Hybrid Word-Character Models

The paper proposes a hybrid neural machine translation model concerning both words and characters, which mainly contributes to the translation of rare or unknown words.