Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Graph Refinement for Coreference Resolution   The state-of-the-art models for coreference resolution are based on
independent mention pair-wise decisions. We propose a modelling approach that
learns coreference at the document-level and takes global decisions. For this
purpose, we model coreference links in a graph structure where the nodes are
tokens in the text, and the edges represent the relationship between them. Our
model predicts the graph in a non-autoregressive manner, then iteratively
refines it based on previous predictions, allowing global dependencies between
decisions. The experimental results show improvements over various baselines,
reinforcing the hypothesis that document-level information improves conference
resolution.

24
The categories of this paper are: dg-ga
36
The categories of this paper are: cmp-lg
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
5
The categories of this paper are: gr-qc
15
The categories of this paper are: nucl-ex
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int