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 "probabilistic top down parsing and language modeling"):
  Abstract: This paper describes the functioning of a broad-coverage probabilistic top-down parser, and its application to the problem of language modeling for speech recognition. The paper first introduces key notions in language modeling and probabilistic parsing, and briefly reviews some previous approaches to using syntactic structure for language modeling. A lexicalized probabilistic top-down parser is then presented, which performs very well, in terms of both the accuracy of returned parses and the efficiency with which they are found, relative to the best broad-coverage statistical parsers. A new language model which utilizes probabilistic top-down parsing is then outlined, and empirical results show that it improves upon previous work in test corpus perplexity. Interpolation with a trigram model yields an exceptional improvement relative to the improvement observed by other models, demonstrating the degree to which the information captured by our parsing model is orthogonal to that captured by a trigram model. A small recognition experiment also demonstrates the utility of the model.

Includes members:
  Member "exploiting syntactic structure for natural language modeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "robust probabilistic predictive syntactic processing")
  Member "exploiting diversity in natural language processing combining parsers":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improving semantic parsing for task oriented dialog")
  Member "recognition performance of a structured language model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "robust probabilistic predictive syntactic processing")
  Member "estimators for stochastic unification based grammars":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "worst case polynomial time exact map inference on discrete models with global dependencies")
  Member "efficient probabilistic top down and left corner parsing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "in order transition based constituent parsing")
  Member "measuring efficiency in high accuracy broad coverage statistical parsing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "framework and resources for natural language parser evaluation")
  Member "refinement of a structured language model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust probabilistic predictive syntactic processing")
  Member "expoiting syntactic structure for language modeling":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "palm a hybrid parser and language model")

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)