Many NLP pipelines split text into sentences as one of the crucial
prepr...
Multilingual sequence-to-sequence models perform poorly with increased
l...
While many languages possess processes of joining two or more words to c...
Large multilingual pretrained language models (mPLMs) have become the de...
Transfer learning has recently become the dominant paradigm of machine
l...
Standard fine-tuning of language models typically performs well on
in-di...
Current multimodal models, aimed at solving Vision and Language (V+L) ta...
Multilingual pre-trained models are known to suffer from the curse of
mu...
Recent advances in NLP and information retrieval have given rise to a di...
Visual question answering (VQA) is one of the crucial vision-and-languag...
Recent advances in multimodal vision and language modeling have predomin...
Reasoning over multiple modalities, e.g. in Visual Question Answering (V...
Recent work on multilingual AMR-to-text generation has exclusively focus...
The open-access dissemination of pretrained language models through onli...
Intermediate task fine-tuning has been shown to culminate in large trans...
Current state-of-the-art approaches to cross-modal retrieval process tex...
In this work we provide a systematic empirical comparison of
pretrained ...
Massively multilingual language models such as multilingual BERT (mBERT)...
Massively pre-trained transformer models are computationally expensive t...
We study the zero-shot transfer capabilities of text matching models on ...
The current modus operandi in NLP involves downloading and fine-tuning
p...
We compare different models for low resource multi-task sequence tagging...
Current approaches to solving classification tasks in NLP involve fine-t...
The main goal behind state-of-the-art pretrained multilingual models suc...
This paper presents the CUNLP submission for the NLP4IF 2019 shared-task...
Recent research towards understanding neural networks probes models in a...
Our proposed system FAMULUS helps students learn to diagnose based on
au...