Rethinking the Evaluation of Neural Machine Translation

This paper proposes a novel evaluation protocol, which not only avoids the effect of search errors but provides a system-level evaluation in the perspective ...

(PDF) Rethinking the Evaluation of Neural Machine Translation

PDF | The evaluation of neural machine translation systems is usually built upon generated translation of a certain decoding method (e.g., beam search).

Rethinking the Evaluation of Neural Machine Translation | DeepAI

The evaluation of neural machine translation systems is usually built upon generated translation of a certain decoding method (e.g., ...

Rethinking Document-level Neural Machine Translation

Experiments show that document-level Transformer models outperforms sentence-level ones and many previous methods in a comprehensive set of metrics, including ...

Digging Errors in NMT: Evaluating and Understanding Model ... - arXiv

Abstract:Solid evaluation of neural machine translation (NMT) is key to its understanding and improvement. Current evaluation of an NMT ...

sunzewei2715/Doc2Doc_NMT: The repository for the paper - GitHub

Cititaion. If you use our data or evaluation scripts, please cite: @inproceedings{sun2020rethinking, title={Rethinking Document-level Neural Machine Translation} ...

Rethinking Round-Trip Translation for Machine Translation Evaluation

In this paper, we revisit this technique with modern neural translation (NMT) and show that round-trip translation does allow for accurate automatic evaluation ...

Salute the Classic: Revisiting Challenges of Machine Translation in ...

Abstract:The evolution of Neural Machine Translation (NMT) has been significantly influenced by six core challenges (Koehn and Knowles, ...

Rethinking Targeted Adversarial Attacks for Neural Machine ...

Abstract: Targeted adversarial attacks are widely used to evaluate the robustness of neural machine translation systems. Unfortunately, this paper first ...

Rethinking Round-Trip Translation for Machine Translation Evaluation

In this paper, we revisit this technique with modern neural translation (NMT) and show that round-trip translation does allow for accurate automatic evaluation ...

Rethinking Zero-shot Neural Machine Translation - Papers With Code

On two benchmark machine translation datasets, we demonstrate that the proposed method is able to effectively eliminate the spurious correlations and ...

Rethinking the Exploitation of Monolingual Data for Low-Resource ...

The Neural Machine Translation (NMT) model has shown significant improvement in translation tasks when trained on large-scale parallel data. However, low- ...

Rethinking Document-level Neural Machine Translation

We evaluate this model and several recent approaches on nine document- level datasets and two sentence-level datasets across six languages. Experiments show ...

Rethinking round-trip translation for machine translation evaluation ...

... translation quality judgments. In this paper, we revisit this technique with modern neural translation (NMT) and show that round-trip translation does allow ...

[PDF] Rethinking Document-level Neural Machine Translation

... evaluation. This paper does not aim at introducing a novel model for document-level neural machine translation. Instead, we head back to the original ...

(PDF) Rethinking Translation Memory Augmented Neural Machine ...

This paper rethinks translation memory augmented neural machine translation (TM-augmented NMT) from two perspectives, i.e., a probabilistic ...

An Analysis of the Evaluation of the Translation Quality of Neural ...

Neural network technologies help machine translation to increasingly mature. NMT application systems are widely used and have yielded huge ...

Rethinking Round-trip Translation for Machine Translation Evaluation

translation systems, System 1 and System 2 are based on Statistical Machine Translation (SMT) and Neural Machine. Translation (NMT), respectively. The ...

A survey of context in neural machine translation and its evaluation

Furthermore, we also discuss recent experiments in the field as they relate to the use of large language models in translation and evaluation.

Rethinking Targeted Adversarial Attacks for Neural Machine ...

Targeted adversarial attacks are widely used to evaluate the robust- ness of neural machine translation systems. Unfortunately, this paper first identifies a ...