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Found 8 papers, 6 papers with code
The IICT-Yverdon System for the WMT 2021 Unsupervised MT and Very Low Resource Supervised MT Task
We then present the application of this system to the 2021 task for low-resource supervised Upper Sorbian (HSB) to German translation, in both directions.
Don't Rank, Combine! Combining Machine Translation Hypotheses Using Quality Estimation
We demonstrate that our approach generates novel translations in over half of the cases and consistently outperforms other methods across varying numbers of candidates (5-200).
Assessing the Importance of Frequency versus Compositionality for Subword-based Tokenization in NMT
Subword tokenization is the de facto standard for tokenization in neural language models and machine translation systems.
Small Language Models Improve Giants by Rewriting Their Outputs
Despite the impressive performance of large language models (LLMs), they often lag behind specialized models in various tasks.
Embarrassingly Easy Document-Level MT Metrics: How to Convert Any Pretrained Metric Into a Document-Level Metric
Our experimental results support our initial hypothesis and show that a simple extension of the metrics permits them to take advantage of context to resolve ambiguities in the reference.
Subword Mapping and Anchoring across Languages
State-of-the-art multilingual systems rely on shared vocabularies that sufficiently cover all considered languages.
Cross-Lingual Natural Language Inference
Machine Translation
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Active Learning by Acquiring Contrastive Examples
Common acquisition functions for active learning use either uncertainty or diversity sampling, aiming to select difficult and diverse data points from the pool of unlabeled data, respectively.
Domain Adversarial Fine-Tuning as an Effective Regularizer
To address this issue, we introduce a new regularization technique, AFTER; domain Adversarial Fine-Tuning as an Effective Regularizer.
