research
∙
05/30/2023
Where's the Point? Self-Supervised Multilingual Punctuation-Agnostic Sentence Segmentation
Many NLP pipelines split text into sentences as one of the crucial prepr...
share
research
∙
05/23/2023
mmT5: Modular Multilingual Pre-Training Solves Source Language Hallucinations
Multilingual sequence-to-sequence models perform poorly with increased l...
research
∙
05/23/2023
CompoundPiece: Evaluating and Improving Decompounding Performance of Language Models
While many languages possess processes of joining two or more words to c...
research
∙
04/18/2023
Romanization-based Large-scale Adaptation of Multilingual Language Models
Large multilingual pretrained language models (mPLMs) have become the de...
research
∙
02/22/2023
Modular Deep Learning
Transfer learning has recently become the dominant paradigm of machine l...
research
∙
01/13/2023
Improving Generalization of Adapter-Based Cross-lingual Transfer with Scheduled Unfreezing
Standard fine-tuning of language models typically performs well on in-di...
research
∙
10/12/2022
One does not fit all! On the Complementarity of Vision Encoders for Vision and Language Tasks
Current multimodal models, aimed at solving Vision and Language (V+L) ta...
research
∙
05/12/2022
Lifting the Curse of Multilinguality by Pre-training Modular Transformers
Multilingual pre-trained models are known to suffer from the curse of mu...
research
∙
03/25/2022
UKP-SQUARE: An Online Platform for Question Answering Research
Recent advances in NLP and information retrieval have given rise to a di...
research
∙
02/15/2022
Delving Deeper into Cross-lingual Visual Question Answering
Visual question answering (VQA) is one of the crucial vision-and-languag...
research
∙
09/13/2021
xGQA: Cross-Lingual Visual Question Answering
Recent advances in multimodal vision and language modeling have predomin...
research
∙
09/09/2021
TxT: Crossmodal End-to-End Learning with Transformers
Reasoning over multiple modalities, e.g. in Visual Question Answering (V...
research
∙
09/08/2021
Smelting Gold and Silver for Improved Multilingual AMR-to-Text Generation
Recent work on multilingual AMR-to-text generation has exclusively focus...
research
∙
08/18/2021
AdapterHub Playground: Simple and Flexible Few-Shot Learning with Adapters
The open-access dissemination of pretrained language models through onli...
research
∙
04/16/2021
What to Pre-Train on? Efficient Intermediate Task Selection
Intermediate task fine-tuning has been shown to culminate in large trans...
research
∙
03/22/2021
Retrieve Fast, Rerank Smart: Cooperative and Joint Approaches for Improved Cross-Modal Retrieval
Current state-of-the-art approaches to cross-modal retrieval process tex...
research
∙
12/31/2020
How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models
In this work we provide a systematic empirical comparison of pretrained ...
research
∙
12/31/2020
UNKs Everywhere: Adapting Multilingual Language Models to New Scripts
Massively multilingual language models such as multilingual BERT (mBERT)...
research
∙
10/22/2020
AdapterDrop: On the Efficiency of Adapters in Transformers
Massively pre-trained transformer models are computationally expensive t...
research
∙
10/02/2020
MultiCQA: Zero-Shot Transfer of Self-Supervised Text Matching Models on a Massive Scale
We study the zero-shot transfer capabilities of text matching models on ...
research
∙
07/15/2020
AdapterHub: A Framework for Adapting Transformers
The current modus operandi in NLP involves downloading and fine-tuning p...
research
∙
05/01/2020
Low Resource Multi-Task Sequence Tagging – Revisiting Dynamic Conditional Random Fields
We compare different models for low resource multi-task sequence tagging...
research
∙
05/01/2020
AdapterFusion: Non-Destructive Task Composition for Transfer Learning
Current approaches to solving classification tasks in NLP involve fine-t...
research
∙
04/30/2020
MAD-X: An Adapter-based Framework for Multi-task Cross-lingual Transfer
The main goal behind state-of-the-art pretrained multilingual models suc...
research
∙
10/22/2019
Fine-Tuned Neural Models for Propaganda Detection at the Sentence and Fragment levels
This paper presents the CUNLP submission for the NLP4IF 2019 shared-task...
research
∙
09/10/2019
What do Deep Networks Like to Read?
Recent research towards understanding neural networks probes models in a...
research
∙
08/29/2019
