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Found 15 papers, 11 papers with code
Multilingual Multimodal Learning with Machine Translated Text
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
Language Modelling with Pixels
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
Ancestor-to-Creole Transfer is Not a Walk in the Park
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').
Rethinking Evaluation Practices in Visual Question Answering: A Case Study on Out-of-Distribution Generalization
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).
Mostra: A Flexible Balancing Framework to Trade-off User, Artist and Platform Objectives for Music Sequencing
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.
Challenges and Strategies in Cross-Cultural NLP
Various efforts in the Natural Language Processing (NLP) community have been made to accommodate linguistic diversity and serve speakers of many different languages.
IGLUE: A Benchmark for Transfer Learning across Modalities, Tasks, and Languages
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.
Visually Grounded Reasoning across Languages and Cultures
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
On Language Models for Creoles
Creole languages such as Nigerian Pidgin English and Haitian Creole are under-resourced and largely ignored in the NLP literature.
Vision-and-Language or Vision-for-Language? On Cross-Modal Influence in Multimodal Transformers
Models that have learned to construct cross-modal representations using both modalities are expected to perform worse when inputs are missing from a modality.
The Role of Syntactic Planning in Compositional Image Captioning
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.
Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs
Large-scale pretraining and task-specific fine-tuning is now the standard methodology for many tasks in computer vision and natural language processing.
It's Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information
The performance of neural machine translation systems is commonly evaluated in terms of BLEU.
Enhancing Machine Translation with Dependency-Aware Self-Attention
Most neural machine translation models only rely on pairs of parallel sentences, assuming syntactic information is automatically learned by an attention mechanism.
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization
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.
