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 order to establish the long dependencies easily and overcome the disadvantage of the approximate inference,<cite> Krishnan and Manning (2006)</cite> propose a two-stage approach using Conditional Random Fields (CRFs) with extract inference. They represent the non-locality with non-local features, and extract the nonlocal features from the output of the first stage CRF using local context alone; then they incorporate the non-local features into the second CRF. But the features in this approach are only used to improve label consistency. To our best knowledge, up to now, non-local information has not been explored to improve NER recall in previous researches; on the other hand, NER is always impaired by its lower recall due to the imbalanced distribution where the NONE class dominates the entity classes.
["Motivation", "Background"]