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Found 19 papers, 5 papers with code
A Small but Informed and Diverse Model: The Case of the Multimodal GuessWhat!? Guessing Game
Pre-trained Vision and Language Transformers achieve high performance on downstream tasks due to their ability to transfer representational knowledge accumulated during pretraining on substantial amounts of data.
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
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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.
Can Language Models Encode Perceptual Structure Without Grounding? A Case Study in Color
Pretrained language models have been shown to encode relational information, such as the relations between entities or concepts in knowledge-bases -- (Paris, Capital, France).
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.
CompGuessWhat?!: A Multi-task Evaluation Framework for Grounded Language Learning
To remedy this, we present GROLLA, an evaluation framework for Grounded Language Learning with Attributes with three sub-tasks: 1) Goal-oriented evaluation; 2) Object attribute prediction evaluation; and 3) Zero-shot evaluation.
The Emergence of Compositional Languages for Numeric Concepts Through Iterated Learning in Neural Agents
Since first introduced, computer simulation has been an increasingly important tool in evolutionary linguistics.
Findings of the Third Shared Task on Multimodal Machine Translation
In this task a source sentence in English is supplemented by an image and participating systems are required to generate a translation for such a sentence into German, French or Czech.
Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description
The multilingual image description task was changed such that at test time, only the image is given.
Multi30K: Multilingual English-German Image Descriptions
We introduce the Multi30K dataset to stimulate multilingual multimodal research.
Multilingual Image Description with Neural Sequence Models
In this paper we present an approach to multi-language image description bringing together insights from neural machine translation and neural image description.
Splitting Compounds by Semantic Analogy
Compounding is a highly productive word-formation process in some languages that is often problematic for natural language processing applications.
