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 "coupling distributed and symbolic execution for natural language queries"):
  Abstract: Building neural networks to query a knowledge base (a table) with natural language is an emerging research topic in deep learning. An executor for table querying typically requires multiple steps of execution because queries may have complicated structures. In previous studies, researchers have developed either fully distributed executors or symbolic executors for table querying. A distributed executor can be trained in an end-to-end fashion, but is weak in terms of execution efficiency and explicit interpretability. A symbolic executor is efficient in execution, but is very difficult to train especially at initial stages. In this paper, we propose to couple distributed and symbolic execution for natural language queries, where the symbolic executor is pretrained with the distributed executor's intermediate execution results in a step-by-step fashion. Experiments show that our approach significantly outperforms both distributed and symbolic executors, exhibiting high accuracy, high learning efficiency, high execution efficiency, and high interpretability.

Includes members:
  Member "chunk based bi scale decoder for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "syntax enhanced neural machine translation with syntax aware word representations")
  Member "language to logical form with neural attention":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unsupervised question decomposition for question answering")
  Member "harnessing deep neural networks with logic rules":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "natural language qa approaches using reasoning with external knowledge")
  Member "neural symbolic machines learning semantic parsers on freebase with weak supervision":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "a network based end to end trainable task oriented dialogue system":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "coverage embedding models for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "modeling future cost for neural machine translation")
  Member "rationalizing neural predictions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "description based text classification with reinforcement learning")
  Member "neural programmer inducing latent programs with gradient descent":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "automl zero evolving machine learning algorithms from scratch")

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.LG(Machine Learning)