Zhirui Zhang

Regularizing End-to-End Speech Translation with Triangular Decomposition Agreement

2021 · arXiv (Cornell University)

End-to-end speech-to-text translation (E2E-ST) is becoming increasingly popular due to the potential of its less error propagation, lower latency, and fewer parameters. Given the triplet training corpus $\langle speech, transcription, translation\rangle$, the conventional high-quality E2E-ST …

Nearest Neighbor Machine Translation is Meta-Optimizer on Output Projection Layer

2023 · arXiv (Cornell University)

Nearest Neighbor Machine Translation ($k$NN-MT) has achieved great success in domain adaptation tasks by integrating pre-trained Neural Machine Translation (NMT) models with domain-specific token-level retrieval. However, the reasons underlying its success have not been thoroughly …

OpsEval: A Comprehensive IT Operations Benchmark Suite for Large Language Models

2023 · arXiv (Cornell University)

Information Technology (IT) Operations (Ops), particularly Artificial Intelligence for IT Operations (AIOps), is the guarantee for maintaining the orderly and stable operation of existing information systems. According to Gartner's prediction, the use of AI technology …

Rethinking Word-Level Auto-Completion in Computer-Aided Translation

2023 · arXiv (Cornell University)

Word-Level Auto-Completion (WLAC) plays a crucial role in Computer-Assisted Translation. It aims at providing word-level auto-completion suggestions for human translators. While previous studies have primarily focused on designing complex model architectures, this paper takes a …

Achieving Human Parity on Automatic Chinese to English News Translation

2018 · arXiv (Cornell University)

Machine translation has made rapid advances in recent years. Millions of people are using it today in online translation systems and mobile applications in order to communicate across language barriers. The question naturally arises whether …

Style Transfer as Unsupervised Machine Translation

2018 · arXiv (Cornell University)

Language style transferring rephrases text with specific stylistic attributes while preserving the original attribute-independent content. One main challenge in learning a style transfer system is a lack of parallel data where the source sentence is …