human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "using automatically extracted minimum spans to disentangle coreference evaluation from boundary detection"):
  Abstract: The common practice in coreference resolution is to identify and evaluate the maximum span of mentions. The use of maximum spans tangles coreference evaluation with the challenges of mention boundary detection like prepositional phrase attachment. To address this problem, minimum spans are manually annotated in smaller corpora. However, this additional annotation is costly and therefore, this solution does not scale to large corpora. In this paper, we propose the MINA algorithm for automatically extracting minimum spans to benefit from minimum span evaluation in all corpora. We show that the extracted minimum spans by MINA are consistent with those that are manually annotated by experts. Our experiments show that using minimum spans is in particular important in cross-dataset coreference evaluation, in which detected mention boundaries are noisier due to domain shift. We will integrate MINA into this https URL for reporting standard coreference scores based on both maximum and automatically detected minimum spans.

Includes members:
  Member "higher order coreference resolution with coarse to fine inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multiplex word embeddings for selectional preference acquisition")
  Member "end to end neural coreference resolution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "domain independent extraction of scientific concepts from research articles")
  Member "lexical features in coreference resolution to be used with caution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "contextualized embeddings in named entity recognition an empirical study on generalization")
  Member "using linguistic features to improve the generalization capability of neural coreference resolvers":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "contextualized embeddings in named entity recognition an empirical study on generalization")
  Member "improving coreference resolution by learning entity level distributed representations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi task learning based neural bridging reference resolution")
  Member "deep reinforcement learning for mention ranking coreference models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "factor graph attention")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.CL(Computation and Language)