activity
20192021
most citedOn the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

4 citations · 7 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL20212 cited

DebIE: A Platform for Implicit and Explicit Debiasing of Word Embedding Spaces

Niklas Friedrich, Anne Lauscher, Simone Paolo Ponzetto +1

Recent research efforts in NLP have demonstrated that distributional word vector spaces often encode stereotypical human biases, such as racism and sexism. With word representation…

cs.CL2021

Evaluating Multilingual Text Encoders for Unsupervised Cross-Lingual Retrieval

Robert Litschko, Ivan Vulić, Simone Paolo Ponzetto +1

Pretrained multilingual text encoders based on neural Transformer architectures, such as multilingual BERT (mBERT) and XLM, have achieved strong performance on a myriad of language…

cs.IR20211 cited

Self-Supervised Learning for Visual Summary Identification in Scientific Publications

Shintaro Yamamoto, Anne Lauscher, Simone Paolo Ponzetto +2

Providing visual summaries of scientific publications can increase information access for readers and thereby help deal with the exponential growth in the number of scientific publ…

cs.CL20204 cited

On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

Wei Zhao, Goran Glavaš, Maxime Peyrard +3

Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual simil…

cs.CL2020

Common Sense or World Knowledge? Investigating Adapter-Based Knowledge Injection into Pretrained Transformers

Anne Lauscher, Olga Majewska, Leonardo F. R. Ribeiro +3

Following the major success of neural language models (LMs) such as BERT or GPT-2 on a variety of language understanding tasks, recent work focused on injecting (structured) knowle…

cs.CL2020

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning

Edoardo Maria Ponti, Goran Glavaš, Olga Majewska +3

In order to simulate human language capacity, natural language processing systems must be able to reason about the dynamics of everyday situations, including their possible causes…