In this work, we will investigate the SetCon model from 'Learning Object-Centric Video Models by Contrasting Sets' by Löwe et al. The SetCon model has been published in November 2020 by the Google ...

This is the source code for the paper "Influence beyond similarity: a Contrastive Learning approach to Object Influence Retrieval", published as a EKAW conference paper. We introduce an approach to ...

To enhance communication between humans and robots, it is essential to improve the ability of robots to comprehend the meaning of ambiguous natural language (ANL) used by humans. Artificial ...

Image-level contrastive representation learning has proven to be highly effective as a generic model for transfer learning. Such generality for transfer learning, however, sacrifices specificity if we ...

Conducting text retrieval in a dense learned representation space has many intriguing advantages over sparse retrieval. Yet the effectiveness of dense retrieval (DR) often requires combination with ...

Text retrieval in machine learning faces significant challenges in developing effective methods for indexing and retrieving documents. Traditional approaches relied on sparse lexical matching methods ...

Contrastive learning based multimodal object recognition using ambiguous natural language Abstract: ... In the multimodal object retrieval experiment, the top-1 and top-2 retrieval accuracies were 0.7 ...