1 code implementation • 24 Oct 2022 • Chen Qiu, Dan Oneata, Emanuele Bugliarello, Stella Frank, Desmond Elliott
We call this framework TD-MML: Translated Data for Multilingual Multimodal Learning, and it can be applied to any multimodal dataset and model.
Zero-Shot Cross-Lingual Image-to-Text Retrieval
Zero-Shot Cross-Lingual Text-to-Image Retrieval
+3
1 code implementation • 14 Jul 2022 • Phillip Rust, Jonas F. Lotz, Emanuele Bugliarello, Elizabeth Salesky, Miryam de Lhoneux, Desmond Elliott
Language models are defined over a finite set of inputs, which creates a vocabulary bottleneck when we attempt to scale the number of supported languages.
Ranked #1 on
Named Entity Recognition (NER)
on MasakhaNER
no code implementations • insights (ACL) 2022 • Heather Lent, Emanuele Bugliarello, Anders Søgaard
We aim to learn language models for Creole languages for which large volumes of data are not readily available, and therefore explore the potential transfer from ancestor languages (the 'Ancestry Transfer Hypothesis').
no code implementations • 24 May 2022 • Aishwarya Agrawal, Ivana Kajić, Emanuele Bugliarello, Elnaz Davoodi, Anita Gergely, Phil Blunsom, Aida Nematzadeh
Vision-and-language (V&L) models pretrained on large-scale multimodal data have demonstrated strong performance on various tasks such as image captioning and visual question answering (VQA).
no code implementations • 22 Apr 2022 • Emanuele Bugliarello, Rishabh Mehrotra, James Kirk, Mounia Lalmas
We consider the task of sequencing tracks on music streaming platforms where the goal is to maximise not only user satisfaction, but also artist- and platform-centric objectives, needed to ensure long-term health and sustainability of the platform.
no code implementations • ACL 2022 • Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, Anders Søgaard
Various efforts in the Natural Language Processing (NLP) community have been made to accommodate linguistic diversity and serve speakers of many different languages.
2 code implementations • 27 Jan 2022 • Emanuele Bugliarello, Fangyu Liu, Jonas Pfeiffer, Siva Reddy, Desmond Elliott, Edoardo Maria Ponti, Ivan Vulić
Our benchmark enables the evaluation of multilingual multimodal models for transfer learning, not only in a zero-shot setting, but also in newly defined few-shot learning setups.
2 code implementations • EMNLP 2021 • Fangyu Liu, Emanuele Bugliarello, Edoardo Maria Ponti, Siva Reddy, Nigel Collier, Desmond Elliott
The design of widespread vision-and-language datasets and pre-trained encoders directly adopts, or draws inspiration from, the concepts and images of ImageNet.
Ranked #1 on
Zero-Shot Cross-Lingual Transfer
on MaRVL
1 code implementation • CoNLL (EMNLP) 2021 • Heather Lent, Emanuele Bugliarello, Miryam de Lhoneux, Chen Qiu, Anders Søgaard
Creole languages such as Nigerian Pidgin English and Haitian Creole are under-resourced and largely ignored in the NLP literature.
2 code implementations • EMNLP 2021 • Stella Frank, Emanuele Bugliarello, Desmond Elliott
Models that have learned to construct cross-modal representations using both modalities are expected to perform worse when inputs are missing from a modality.
1 code implementation • EACL 2021 • Emanuele Bugliarello, Desmond Elliott
Image captioning has focused on generalizing to images drawn from the same distribution as the training set, and not to the more challenging problem of generalizing to different distributions of images.
2 code implementations • 30 Nov 2020 • Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, Desmond Elliott
Large-scale pretraining and task-specific fine-tuning is now the standard methodology for many tasks in computer vision and natural language processing.
1 code implementation • ACL 2020 • Emanuele Bugliarello, Sabrina J. Mielke, Antonios Anastasopoulos, Ryan Cotterell, Naoaki Okazaki
The performance of neural machine translation systems is commonly evaluated in terms of BLEU.
1 code implementation • ACL 2020 • Emanuele Bugliarello, Naoaki Okazaki
Most neural machine translation models only rely on pairs of parallel sentences, assuming syntactic information is automatically learned by an attention mechanism.
1 code implementation • 30 May 2019 • Emanuele Bugliarello, Swayambhoo Jain, Vineeth Rakesh
We tackle this challenge by using a two-fold approach: first, we transform this task into a constrained matrix completion problem with entries bounded in the unit interval [0, 1]; second, we propose two novel matrix factorization models that leverage our knowledge of the VFX environment.