human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "ellipsis and coreference resolution as question answering"
  Abstract: Coreference and many forms of ellipsis are similar to reading comprehension questions, in that in order to resolve these, we need to identify an appropriate text span in the previous discourse. This paper exploits this analogy and proposes to use an architecture developed for machine comprehension for ellipsis and coreference resolution. We present both single-task and joint models and evaluate them across standard benchmarks, outperforming the current state of the art for ellipsis by up to 48.5% error reduction -- and for coreference by 37.5% error reduction.

Connected through hyperedge HE-1 (induced by source paper "coreference resolution as query based span prediction"):
  with members:
    - "a unified mrc framework for named entity recognition"
    - "quoref a reading comprehension dataset with questions requiring coreferential reasoning"
    - "spanbert improving pre training by representing and predicting spans"
    - "entity relation extraction as multi turn question answering"
    - "bert for coreference resolution baselines and analysis"
    - "gender bias in contextualized word embeddings"
    - "multiqa an empirical investigation of generalization and transfer in reading comprehension"
    - "mind the gap a balanced corpus of gendered ambiguous pronouns"

Connected through hyperedge HE-2 (induced by source paper "model based annotation of coreference"):
  with members:
    - "solving hard coreference problems"
    - "mind the gap a balanced corpus of gendered ambiguous pronouns"
    - "higher order coreference resolution with coarse to fine inference"
    - "quac question answering in context"

Question: Please tell me which class the center node 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)