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Found 8 papers, 3 papers with code
Improving Abstractive Text Summarization with History Aggregation
Recent neural sequence to sequence models have provided feasible solutions for abstractive summarization.
A Relation-Specific Attention Network for Joint Entity and Relation Extraction
Joint extraction of entities and relations is an important task in natural language processing (NLP), which aims to capture all relational triplets from plain texts.
Ranked #11 on
Relation Extraction
on WebNLG
Designing AI Learning Experiences for K-12: Emerging Works, Future Opportunities and a Design Framework
Artificial intelligence (AI) literacy is a rapidly growing research area and a critical addition to K-12 education.
Image Captioning with Context-Aware Auxiliary Guidance
Image captioning is a challenging computer vision task, which aims to generate a natural language description of an image.
Exploring Explicit and Implicit Visual Relationships for Image Captioning
Image captioning is one of the most challenging tasks in AI, which aims to automatically generate textual sentences for an image.
Unifying Graph Contrastive Learning with Flexible Contextual Scopes
To address aforementioned problems, we present a simple self-supervised learning method termed Unifying Graph Contrastive Learning with Flexible Contextual Scopes (UGCL for short).
Frequency Perception Network for Camouflaged Object Detection
Camouflaged object detection (COD) aims to accurately detect objects hidden in the surrounding environment.
