5 citations · 12 across the 7 of their papers we have counts for
10 papers
Reducing Hallucinations in Neural Machine Translation with Feature Attribution
Joël Tang, Marina Fomicheva, Lucia Specia
Neural conditional language generation models achieve the state-of-the-art in Neural Machine Translation (NMT) but are highly dependent on the quality of parallel training dataset.…
Contrastive Video-Language Learning with Fine-grained Frame Sampling
Zixu Wang, Yujie Zhong, Yishu Miao +2
Despite recent progress in video and language representation learning, the weak or sparse correspondence between the two modalities remains a bottleneck in the area. Most video-lan…
Burst2Vec: An Adversarial Multi-Task Approach for Predicting Emotion, Age, and Origin from Vocal Bursts
Atijit Anuchitanukul, Lucia Specia
We present Burst2Vec, our multi-task learning approach to predict emotion, age, and origin (i.e., native country/language) from vocal bursts. Burst2Vec utilises pre-trained speech…
Logically Consistent Adversarial Attacks for Soft Theorem Provers
Alexander Gaskell, Yishu Miao, Lucia Specia +1
Recent efforts within the AI community have yielded impressive results towards "soft theorem proving" over natural language sentences using language models. We propose a novel, gen…
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation
Diptesh Kanojia, Marina Fomicheva, Tharindu Ranasinghe +3
Current Machine Translation (MT) systems achieve very good results on a growing variety of language pairs and datasets. However, they are known to produce fluent translation output…
Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications
Shuo Sun, Ahmed El-Kishky, Vishrav Chaudhary +3
Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson co…
Translation Error Detection as Rationale Extraction
Marina Fomicheva, Lucia Specia, Nikolaos Aletras
Recent Quality Estimation (QE) models based on multilingual pre-trained representations have achieved very competitive results when predicting the overall quality of translated sen…
Knowledge Distillation for Quality Estimation
Amit Gajbhiye, Marina Fomicheva, Fernando Alva-Manchego +4
Quality Estimation (QE) is the task of automatically predicting Machine Translation quality in the absence of reference translations, making it applicable in real-time settings, su…
What Makes a Scientific Paper be Accepted for Publication?
Panagiotis Fytas, Georgios Rizos, Lucia Specia
Despite peer-reviewing being an essential component of academia since the 1600s, it has repeatedly received criticisms for lack of transparency and consistency. We posit that recen…
Backtranslation Feedback Improves User Confidence in MT, Not Quality
Vilém Zouhar, Michal Novák, Matúš Žilinec +7
Translating text into a language unknown to the text's author, dubbed outbound translation, is a modern need for which the user experience has significant room for improvement, bey…