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: "neural program search solving programming tasks from description and examples"
  Abstract: We present a Neural Program Search, an algorithm to generate programs from natural language description and a small number of input/output examples. The algorithm combines methods from Deep Learning and Program Synthesis fields by designing rich domain-specific language (DSL) and defining efficient search algorithm guided by a Seq2Tree model on it. To evaluate the quality of the approach we also present a semi-synthetic dataset of descriptions with test examples and corresponding programs. We show that our algorithm significantly outperforms a sequence-to-sequence model with attention baseline.

Connected through hyperedge HE-1 (induced by source paper "comparison of syntactic and semantic representations of programs in neural embeddings"):
  with members:
    - "a comprehensive survey on graph neural networks"
    - "code2vec learning distributed representations of code"
    - "naps natural program synthesis dataset"
    - "neural guided deductive search for real time program synthesis from examples"
    - "adversarially regularized graph autoencoder for graph embedding"
    - "an empirical evaluation of generic convolutional and recurrent networks for sequence modeling"
    - "neural guided constraint logic programming for program synthesis"
    - "program synthesis using conflict driven learning"

Connected through hyperedge HE-2 (induced by source paper "learning to infer program sketches"):
  with members:
    - "ain t nobody got time for coding structure aware program synthesis from natural language"
    - "neural guided deductive search for real time program synthesis from examples"
    - "automatic program synthesis of long programs with a learned garbage collector"
    - "coarse to fine decoding for neural semantic parsing"
    - "leveraging grammar and reinforcement learning for neural program synthesis"
    - "neural guided constraint logic programming for program synthesis"
    - "robustfill neural program learning under noisy i o"
    - "neural sketch learning for conditional program generation"

Connected through hyperedge HE-3 (induced by source paper "natural to formal language generation using tensor product representations"):
  with members:
    - "core semantic first a top down approach for amr parsing"
    - "ain t nobody got time for coding structure aware program synthesis from natural language"
    - "attentive tensor product learning"
    - "neural approaches to conversational ai"
    - "learning to reason with third order tensor products"
    - "a survey on semantic parsing"
    - "question answering with grammatically interpretable representations"
    - "tensor product generation networks for deep nlp modeling"

Connected through hyperedge HE-4 (induced by source paper "middle out decoding"):
  with members:
    - "fast lexically constrained decoding with dynamic beam allocation for neural machine translation"
    - "texygen a benchmarking platform for text generation models"
    - "quo vadis action recognition a new model and the kinetics dataset"
    - "learning structured text representations"
    - "attention is all you need"
    - "frustratingly short attention spans in neural language modeling"
    - "lexically constrained decoding for sequence generation using grid beam search"
    - "towards diverse and natural image descriptions via a conditional gan"

Connected through hyperedge HE-5 (induced by source paper "naps natural program synthesis dataset"):
  with members:
    - "neural program meta induction"
    - "deep api programmer learning to program with apis"
    - "pointing the unknown words"
    - "deepcoder learning to write programs"
    - "learning a natural language interface with neural programmer"
    - "latent predictor networks for code generation"
    - "neuro symbolic program synthesis"
    - "neural gpus learn algorithms"

Connected through hyperedge HE-6 (induced by source paper "ain t nobody got time for coding structure aware program synthesis from natural language"):
  with members:
    - "tree to tree neural networks for program translation"
    - "abstract syntax networks for code generation and semantic parsing"
    - "a syntactic neural model for general purpose code generation"
    - "deepcoder learning to write programs"
    - "latent predictor networks for code generation"
    - "end to end memory networks"
    - "improved semantic representations from tree structured long short term memory networks"
    - "adam a method for stochastic optimization"

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.AI(Artificial Intelligence)