Your task is to classify the citation intent within the following provided text from a computational linguistics research paper. The cited work is demarcated by "<cite>" and "</cite>". Determine the purpose of the cited work by selecting from the listed categories:

- Background: The cited paper underpins the subject matter.
- Motivation: The cited paper inspires or provides a rationale for the current research.
- Uses: The current work utilizes concepts or tools from the cited paper.
- Extends: The current work advances ideas or methods from the cited paper.
- Similarities: The current work identifies commonalities with the cited paper.
- Differences: The current work delineates its distinction from the cited paper.
- FutureWork: The cited paper is acknowledged as groundwork for prospective research.

Indicate the intents by listing them in a `json` array, e.g. ["Background", "Uses"]. More than one intent may be applicable. Do not include any extraneous text in your response.

Context with Citation:
In practice, the features automatically induced by NN are combined with the discrete features in the local approach to extend their coverage for EL (Sun et al., 2015;<cite> Francis-Landau et al., 2016)</cite> . However, as the previous NN models for EL are local, they cannot capture the global interdependence among the target entities in the same document (the first limitation of the local approach). Guided by these analyses, in this paper, we propose to use neural networks to model both the local mention-to-entity similarities and the global relatedness among target entities in an unified architecture. This allows us to inherit all the benefits from the previous systems as well as overcome their inherent issues.
["Motivation", "Background"]