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: "hubiness length crossings and their relationships in dependency trees"
  Abstract: Here tree dependency structures are studied from three different perspectives: their degree variance (hubiness), the mean dependency length and the number of dependency crossings. Bounds that reveal pairwise dependencies among these three metrics are derived. Hubiness (the variance of degrees) plays a central role: the mean dependency length is bounded below by hubiness while the number of crossings is bounded above by hubiness. Our findings suggest that the online memory cost of a sentence might be determined not just by the ordering of words but also by the hubiness of the underlying structure. The 2nd moment of degree plays a crucial role that is reminiscent of its role in large complex networks.

Connected through hyperedge HE-1 (induced by source paper "anti dependency distance minimization in short sequences a graph theoretic approach"):
  with members:
    - "the placement of the head that maximizes predictability an information theoretic approach"
    - "towards a theory of word order comment on dependency distance a new perspective on syntactic patterns in natural language by haitao liu et al"
    - "scarcity of crossing dependencies a direct outcome of a specific constraint"
    - "non crossing dependencies least effort not grammar"
    - "liberating language research from dogmas of the 20th century"
    - "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2016"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "random crossings in dependency trees"

Connected through hyperedge HE-2 (induced by source paper "scarcity of crossing dependencies a direct outcome of a specific constraint"):
  with members:
    - "non crossing dependencies least effort not grammar"
    - "crossings as a side effect of dependency lengths"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "a stronger null hypothesis for crossing dependencies"
    - "random crossings in dependency trees"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-3 (induced by source paper "non crossing dependencies least effort not grammar"):
  with members:
    - "the risks of mixing dependency lengths from sequences of different length"
    - "the placement of the head that minimizes online memory a complex systems approach"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-4 (induced by source paper "the placement of the head that minimizes online memory a complex systems approach"):
  with members:
    - "the risks of mixing dependency lengths from sequences of different length"

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)