activity
20162022
most citedSemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation

596 citations · 652 across the 18 of their papers we have counts for

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32 papers · 1 filter

cs.CL2021

A Survey of Online Hate Speech through the Causal Lens

Antigoni-Maria Founta, Lucia Specia

The societal issue of digital hostility has previously attracted a lot of attention. The topic counts an ample body of literature, yet remains prominent and challenging as ever due…

cs.CL2021

BERTGEN: Multi-task Generation through BERT

Faidon Mitzalis, Ozan Caglayan, Pranava Madhyastha +1

We present BERTGEN, a novel generative, decoder-only model which extends BERT by fusing multimodal and multilingual pretrained models VL-BERT and M-BERT, respectively. BERTGEN is a…

cs.CL2021

Exploring Supervised and Unsupervised Rewards in Machine Translation

Julia Ive, Zixu Wang, Marina Fomicheva +1

Reinforcement Learning (RL) is a powerful framework to address the discrepancy between loss functions used during training and the final evaluation metrics to be used at test time.…

cs.CL2021

Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation

Julia Ive, Andy Mingren Li, Yishu Miao +3

This paper addresses the problem of simultaneous machine translation (SiMT) by exploring two main concepts: (a) adaptive policies to learn a good trade-off between high translation…

cs.CL20212 cited

Quality Estimation without Human-labeled Data

Yi-Lin Tuan, Ahmed El-Kishky, Adithya Renduchintala +3

Quality estimation aims to measure the quality of translated content without access to a reference translation. This is crucial for machine translation systems in real-world scenar…

cs.CL2021

Cross-lingual Visual Pre-training for Multimodal Machine Translation

Ozan Caglayan, Menekse Kuyu, Mustafa Sercan Amac +4

Pre-trained language models have been shown to improve performance in many natural language tasks substantially. Although the early focus of such models was single language pre-tra…