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: "a stronger null hypothesis for crossing dependencies"
  Abstract: The syntactic structure of a sentence can be modeled as a tree where vertices are words and edges indicate syntactic dependencies between words. It is well-known that those edges normally do not cross when drawn over the sentence. Here a new null hypothesis for the number of edge crossings of a sentence is presented. That null hypothesis takes into account the length of the pair of edges that may cross and predicts the relative number of crossings in random trees with a small error, suggesting that a ban of crossings or a principle of minimization of crossings are not needed in general to explain the origins of non-crossing dependencies. Our work paves the way for more powerful null hypotheses to investigate the origins of non-crossing dependencies in nature.

Connected through hyperedge HE-1 (induced by source paper "edge crossings in random linear arrangements"):
  with members:
    - "on the maximum crossing number"
    - "crossing patterns in nonplanar road networks"
    - "scarcity of crossing dependencies a direct outcome of a specific constraint"
    - "non crossing dependencies least effort not grammar"
    - "crossings as a side effect of dependency lengths"
    - "liberating language research from dogmas of the 20th century"
    - "random crossings in dependency trees"
    - "practical graph isomorphism ii"

Connected through hyperedge HE-2 (induced by source paper "towards a theory of word order comment on dependency distance a new perspective on syntactic patterns in natural language by haitao liu et al"):
  with members:
    - "the placement of the head that maximizes predictability an information theoretic approach"
    - "non crossing dependencies least effort not grammar"
    - "kauffman s adjacent possible in word order evolution"
    - "reply to the commentary be careful when assuming the obvious by p alday"
    - "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-3 (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"
    - "random crossings in dependency trees"
    - "hubiness length crossings and their relationships in dependency trees"
    - "why sov might be initially preferred and then lost or recovered a theoretical framework"

Connected through hyperedge HE-4 (induced by source paper "text authorship identified using the dynamics of word co occurrence networks"):
  with members:
    - "authorship recognition via fluctuation analysis of network topology and word intermittency"
    - "a complex network approach to stylometry"
    - "probing the topological properties of complex networks modeling short written texts"
    - "modeling the average shortest path length in growth of word adjacency networks"
    - "a systematic comparison of supervised classifiers"

Connected through hyperedge HE-5 (induced by source paper "crossings as a side effect of dependency lengths"):
  with members:
    - "can chunking reduce syntactic complexity of natural languages"
    - "transition based dependency parsing with stack long short term memory"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "random crossings in dependency trees"
    - "the placement of the head that minimizes online memory a complex systems approach"

Connected through hyperedge HE-6 (induced by source paper "can chunking reduce syntactic complexity of natural languages"):
  with members:
    - "non crossing dependencies least effort not grammar"
    - "crossings as a side effect of dependency lengths"
    - "complexity measurement of natural and artificial languages"
    - "menzerath altmann law for syntactic structures in ukrainian"

Connected through hyperedge HE-7 (induced by source paper "a commentary on the now or never bottleneck a fundamental constraint on language by christiansen and chater 2015"):
  with members:
    - "compression and the origins of zipf s law for word frequencies"
    - "crossings as a side effect of dependency lengths"
    - "compression and the origins of zipf s law of abbreviation"
    - "reply to the commentary be careful when assuming the obvious by p alday"
    - "the risks of mixing dependency lengths from sequences of different length"
    - "the optimality of attaching unlinked labels to unlinked meanings"
    - "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-8 (induced by source paper "compression and the origins of zipf s law of abbreviation"):
  with members:
    - "rank diversity of languages generic behavior in computational linguistics"
    - "be careful when assuming the obvious commentary on the placement of the head that minimizes online memory a complex systems approach"
    - "the optimality of attaching unlinked labels to unlinked meanings"
    - "the placement of the head that minimizes online memory a complex systems approach"

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)