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 "learning to infer program sketches"):
  Abstract: Our goal is to build systems which write code automatically from the kinds of specifications humans can most easily provide, such as examples and natural language instruction. The key idea of this work is that a flexible combination of pattern recognition and explicit reasoning can be used to solve these complex programming problems. We propose a method for dynamically integrating these types of information. Our novel intermediate representation and training algorithm allow a program synthesis system to learn, without direct supervision, when to rely on pattern recognition and when to perform symbolic search. Our model matches the memorization and generalization performance of neural synthesis and symbolic search, respectively, and achieves state-of-the-art performance on a dataset of simple English description-to-code programming problems.

Includes members:
  Member "ain t nobody got time for coding structure aware program synthesis from natural language":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "natural to formal language generation using tensor product representations")
  Member "neural guided deductive search for real time program synthesis from examples":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "comparison of syntactic and semantic representations of programs in neural embeddings")
  Member "automatic program synthesis of long programs with a learned garbage collector":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unsupervised program synthesis for images using tree structured lstm")
  Member "neural program search solving programming tasks from description and examples":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "comparison of syntactic and semantic representations of programs in neural embeddings")
  Member "coarse to fine decoding for neural semantic parsing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "structural language models of code")
  Member "leveraging grammar and reinforcement learning for neural program synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "improving molecular design by stochastic iterative target augmentation")
  Member "neural guided constraint logic programming for program synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "comparison of syntactic and semantic representations of programs in neural embeddings")
  Member "robustfill neural program learning under noisy i o":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "intelligence physics and information the tradeoff between accuracy and simplicity in machine learning")

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.AI(Artificial Intelligence)