  The CL-SciSumm 2016 shared task introduced an interesting problem: given a
document D and a piece of text that cites D, how do we identify the text spans
of D being referenced by the piece of text? The shared task provided the first
annotated dataset for studying this problem. We present an analysis of our
continued work in improving our system's performance on this task. We
demonstrate how topic models and word embeddings can be used to surpass the
previously best performing system.
