Information and knowledge management

Integrating structured knowledge into language model representations increases recall of domain-specific information useful for downstream tasks. Matching between knowledge graph entities and text entity mentions can be easily performed when entity names are unique or there exists entity linking data. When extending this setting to new domains, newly mined knowledge contains ambiguous and incorrect information

Querying incomplete knowledge graphs (KGs) using deep learning approaches can naturally leverage the reasoning and generalization ability to learn to infer better answers. Traditional neural complex query answering (CQA) approaches mostly work on entity-centric KGs. However, in the real world, we also need to make logical inferences about events, states, and activities (i.e., eventualities or situations

Attribute Value Extraction (AVE) aims to retrieve the values of attributes from the product profiles. The state-of-the-art methods tackle the AVE task through a question-answering (QA) paradigm, where the value is predicted from the context (i.e. product profile) given a query (i.e. attributes). Despite of the substantial advancements that have been made, the performance of existing methods on rare attributes

E-commerce platforms enable brands to connect with relevant online shoppers. While major brands are easily identifiable by shoppers, smaller and emerging brands often lean on advertising campaigns in e-commerce platforms to reach a wide audience. For such advertising campaigns, brands need to come up with a leading ad creative which may be shown together with their listed products. Designing such creatives

Traditional image-to-image and text-to-image search struggle with comprehending complex user intentions, particularly in fashion e-commerce, where users search for similar products with text modifications to a reference image. This paper introduces Progressive Vision-Language Alignment and Multimodal Fusion (ProVLA), a novel approach which utilizes a transformer-based vision and language model to generate