Generative Knowledge Graph Construction (KGC) refers to those methods that leverage the
sequence-to-sequence framework for building knowledge graphs, which is flexible and can …

Camouflaged object detection (COD) aims to address the tough issue of identifying
camouflaged objects visually blended into the surrounding backgrounds. COD is a …

Reasoning, as an essential ability for complex problem-solving, can provide back-end
support for various real-world applications, such as medical diagnosis, negotiation, etc. This …

Grammatical error correction (GEC) can be divided into sequence-to-edit (Seq2Edit) and
sequence-to-sequence (Seq2Seq) frameworks, both of which have their pros and cons. To …

Grammatical error correction (GEC) is a promising task aimed at correcting errors in a text.
Many methods have been proposed to facilitate this task with remarkable results. However …

Neural ordinary differential equations (ODEs) represent an emergent class of deep learning
models exhibiting continuous depth. While they have shown promising results across …

In this article, we present a novel approach for forecasting significant wave heights in
oceanic waters. We propose an algorithm based on the WaveWatch III, differencing, and a …

Infrared small target detection (ISTD) is aimed at segmenting small targets from infrared
images and has wide applications in military areas. With the specially designed spatial …

Transformers are widely used for solving tasks in natural language processing, computer
vision, speech, and music domains. In this paper, we talk about the efficiency of transformers …

Diffusion Models (DMs) have recently set state-of-the-art on many generation benchmarks.
However, there are myriad ways to describe them mathematically, which makes it difficult to …