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:
Word representations and more recently, word embeddings, learned from large amounts of text have been quite successful as features in various NLP tasks (Koo et al., 2008; Turian et al., 2010; Collobert et al., 2011; Dhillon et al., 2012; Al-Rfou' et al., 2013; <cite>Bansal et al., 2014</cite>; Guo et al., 2014; Pennington et al., 2014; Yu and Dredze, 2014; Faruqui et al., 2014; Wang et al., 2015) . While these word representations do capture useful, dense relationships among known and unknown words, one still has to work with sparse conjunctions of features on the multiple words involved in the substructure that a task factors on, e.g., head-argument links in dependency parsing. Therefore, most statistical dependency parsers still suffer from millions of such conjoined, template-based, n-ary features on word clusters or embeddings (Koo et al., 2008; <cite>Bansal et al., 2014</cite>) .
["Background"]