activity
20172026
most citedCoarse-to-Fine Vision-Language Pre-training with Fusion in the Backbone

67 citations · 118 across the 25 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.CL2020

CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems

Yiran Chen, Pengfei Liu, Ming Zhong +4

Neural network-based models augmented with unsupervised pre-trained knowledge have achieved impressive performance on text summarization. However, most existing evaluation methods…

cs.CL2020

GSum: A General Framework for Guided Neural Abstractive Summarization

Zi-Yi Dou, Pengfei Liu, Hiroaki Hayashi +2

Neural abstractive summarization models are flexible and can produce coherent summaries, but they are sometimes unfaithful and can be difficult to control. While previous studies a…

cs.CL2020

TICO-19: the Translation Initiative for Covid-19

Antonios Anastasopoulos, Alessandro Cattelan, Zi-Yi Dou +15

The COVID-19 pandemic is the worst pandemic to strike the world in over a century. Crucial to stemming the tide of the SARS-CoV-2 virus is communicating to vulnerable populations t…

cs.CL2020★ 1 cited

A Deep Reinforced Model for Zero-Shot Cross-Lingual Summarization with Bilingual Semantic Similarity Rewards

Zi-Yi Dou, Sachin Kumar, Yulia Tsvetkov

Cross-lingual text summarization aims at generating a document summary in one language given input in another language. It is a practically important but under-explored task, prima…

cs.CL2020

Dynamic Data Selection and Weighting for Iterative Back-Translation

Zi-Yi Dou, Antonios Anastasopoulos, Graham Neubig

Back-translation has proven to be an effective method to utilize monolingual data in neural machine translation (NMT), and iteratively conducting back-translation can further impro…