human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "fuse multi faceted set expansion by coherent clustering of skip grams"):
  Abstract: Set expansion aims to expand a small set of seed entities into a complete set of relevant entities. Most existing approaches assume the input seed set is unambiguous and completely ignore the multi-faceted semantics of seed entities. As a result, given the seed set {"Canon", "Sony", "Nikon"}, previous methods return one mixed set of entities that are either Camera Brands or Japanese Companies. In this paper, we study the task of multi-faceted set expansion, which aims to capture all semantic facets in the seed set and return multiple sets of entities, one for each semantic facet. We propose an unsupervised framework, FUSE, which consists of three major components: (1) facet discovery module: identifies all semantic facets of each seed entity by extracting and clustering its skip-grams, and (2) facet fusion module: discovers shared semantic facets of the entire seed set by an optimization formulation, and (3) entity expansion module: expands each semantic facet by utilizing an iterative algorithm robust to skip-gram noise. Extensive experiments demonstrate that our algorithm, FUSE, can accurately identify multiple semantic facets of the seed set and generate quality entities for each facet.

Includes members:
  Member "hardware guided symbiotic training for compact accurate yet execution efficient lstm":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "dreaming to distill data free knowledge transfer via deepinversion")
  Member "setexpan corpus based set expansion via context feature selection and rank ensemble":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "taxoexpan self supervised taxonomy expansion with position enhanced graph neural network")
  Member "hiexpan task guided taxonomy construction by hierarchical tree expansion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "keml a knowledge enriched meta learning framework for lexical relation classification")
  Member "term set expansion based nlp architect by intel ai lab":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "guiding corpus based set expansion by auxiliary sets generation and co expansion")
  Member "grow and prune compact fast and accurate lstms":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "recurrent neural networks an embedded computing perspective")
  Member "multilingual models for compositional distributed semantics":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unsupervised sentiment analysis for code mixed data")
  Member "distributed representations of words and phrases and their compositionality":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

Question: Please tell me which class the source paper 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)