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: "compositional operators in distributional semantics"
  Abstract: This survey presents in some detail the main advances that have been recently taking place in Computational Linguistics towards the unification of the two prominent semantic paradigms: the compositional formal semantics view and the distributional models of meaning based on vector spaces. After an introduction to these two approaches, I review the most important models that aim to provide compositionality in distributional semantics. Then I proceed and present in more detail a particular framework [7] based on the abstract mathematical setting of category theory, as a more complete example capable to demonstrate the diversity of techniques and scientific disciplines that this kind of research can draw from. This paper concludes with a discussion about important open issues that need to be addressed by the researchers in the future.

Connected through hyperedge HE-1 (induced by source paper "the compositionality of neural networks integrating symbolism and connectionism"):
  with members:
    - "unsupervised recurrent neural network grammars"
    - "cnns found to jump around more skillfully than rnns compositional generalization in seq2seq convolutional networks"
    - "assessing bert s syntactic abilities"
    - "bert rediscovers the classical nlp pipeline"
    - "measuring compositionality in representation learning"
    - "analyzing the structure of attention in a transformer language model"
    - "what do you learn from context probing for sentence structure in contextualized word representations"
    - "the emergence of number and syntax units in lstm language models"

Connected through hyperedge HE-2 (induced by source paper "compositional distributional semantics with compact closed categories and frobenius algebras"):
  with members:
    - "the frobenius anatomy of word meanings ii possessive relative pronouns"
    - "a frobenius model of information structure in categorical compositional distributional semantics"
    - "efficient non parametric estimation of multiple embeddings per word in vector space"
    - "open system categorical quantum semantics in natural language processing"
    - "resolving lexical ambiguity in tensor regression models of meaning"
    - "a study of entanglement in a categorical framework of natural language"
    - "investigating the role of prior disambiguation in deep learning compositional models of meaning"
    - "evaluating neural word representations in tensor based compositional settings"

Connected through hyperedge HE-3 (induced by source paper "resolving lexical ambiguity in tensor regression models of meaning"):
  with members:
    - "recurrent convolutional neural networks for discourse compositionality"
    - "multi step regression learning for compositional distributional semantics"

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)