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: "tracing metaphors in time through self distance in vector spaces"
  Abstract: From a diachronic corpus of Italian, we build consecutive vector spaces in time and use them to compare a term's cosine similarity to itself in different time spans. We assume that a drop in similarity might be related to the emergence of a metaphorical sense at a given time. Similarity-based observations are matched to the actual year when a figurative meaning was documented in a reference dictionary and through manual inspection of corpus occurrences.

Connected through hyperedge HE-1 (induced by source paper "training temporal word embeddings with a compass"):
  with members:
    - "tracking the evolution of words with time reflective text representations"
    - "dynamic word embeddings for evolving semantic discovery"
    - "learning distributed representations of texts and entities from knowledge base"
    - "offline bilingual word vectors orthogonal transformations and the inverted softmax"
    - "semantics derived automatically from language corpora contain human like biases"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "document classification by inversion of distributed language representations"
    - "statistically significant detection of linguistic change"

Connected through hyperedge HE-2 (induced by source paper "a wind of change detecting and evaluating lexical semantic change across times and domains"):
  with members:
    - "survey of computational approaches to diachronic conceptual change"
    - "distribution based prediction of the degree of grammaticalization for german prepositions"
    - "a robust self learning method for fully unsupervised cross lingual mappings of word embeddings"
    - "on the linearity of semantic change investigating meaning variation via dynamic graph models"
    - "dialectometric analysis of language variation in twitter"
    - "competition and selection among conventions"
    - "cultural shift or linguistic drift comparing two computational measures of semantic change"
    - "diachronic word embeddings reveal statistical laws of semantic change"

Connected through hyperedge HE-3 (induced by source paper "short term meaning shift a distributional exploration"):
  with members:
    - "a state of the art of semantic change computation"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "diachronic word embeddings and semantic shifts a survey"
    - "competition and selection among conventions"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "statistically significant detection of linguistic change"
    - "temporal analysis of language through neural language models"
    - "distributed representations of words and phrases and their compositionality"

Connected through hyperedge HE-4 (induced by source paper "short term meaning shift an exploratory distributional analysis"):
  with members:
    - "a state of the art of semantic change computation"
    - "the road to success assessing the fate of linguistic innovations in online communities"
    - "diachronic word embeddings and semantic shifts a survey"
    - "competition and selection among conventions"
    - "words are malleable computing semantic shifts in political and media discourse"
    - "diachronic word embeddings reveal statistical laws of semantic change"
    - "temporal analysis of language through neural language models"
    - "distributed representations of words and phrases and their compositionality"

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)