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 machine translation with external phrase memory"
  Abstract: In this paper, we propose phraseNet, a neural machine translator with a phrase memory which stores phrase pairs in symbolic form, mined from corpus or specified by human experts. For any given source sentence, phraseNet scans the phrase memory to determine the candidate phrase pairs and integrates tagging information in the representation of source sentence accordingly. The decoder utilizes a mixture of word-generating component and phrase-generating component, with a specifically designed strategy to generate a sequence of multiple words all at once. The phraseNet not only approaches one step towards incorporating external knowledge into neural machine translation, but also makes an effort to extend the word-by-word generation mechanism of recurrent neural network. Our empirical study on Chinese-to-English translation shows that, with carefully-chosen phrase table in memory, phraseNet yields 3.45 BLEU improvement over the generic neural machine translator.

Connected through hyperedge HE-1 (induced by source paper "latent relation language models"):
  with members:
    - "barack s wife hillary using knowledge graphs for fact aware language modeling"
    - "transformer xl attentive language models beyond a fixed length context"
    - "bootstrapping generators from noisy data"
    - "neural lattice language models"
    - "describing a knowledge base"
    - "deep contextualized word representations"
    - "building language models for text with named entities"
    - "structvae tree structured latent variable models for semi supervised semantic parsing"

Connected through hyperedge HE-2 (induced by source paper "code switching for enhancing nmt with pre specified translation"):
  with members:
    - "on the alignment problem in multi head attention based neural machine translation"
    - "fast lexically constrained decoding with dynamic beam allocation for neural machine translation"
    - "neural machine translation decoding with terminology constraints"
    - "attention is all you need"
    - "lexically constrained decoding for sequence generation using grid beam search"
    - "get to the point summarization with pointer generator networks"
    - "searching for activation functions"
    - "pointing the unknown words"

Connected through hyperedge HE-3 (induced by source paper "unsupervised neural machine translation with smt as posterior regularization"):
  with members:
    - "on the impact of various types of noise on neural machine translation"
    - "achieving human parity on automatic chinese to english news translation"
    - "regularizing neural machine translation by target bidirectional agreement"
    - "prior knowledge integration for neural machine translation using posterior regularization"
    - "joint training for neural machine translation models with monolingual data"
    - "phrase based neural unsupervised machine translation"
    - "unsupervised neural machine translation with weight sharing"
    - "unsupervised machine translation using monolingual corpora only"

Connected through hyperedge HE-4 (induced by source paper "merging external bilingual pairs into neural machine translation"):
  with members:
    - "code switching for enhancing nmt with pre specified translation"
    - "scaling neural machine translation"
    - "prior knowledge integration for neural machine translation using posterior regularization"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "phrase based neural unsupervised machine translation"
    - "translating phrases in neural machine translation"
    - "lexically constrained decoding for sequence generation using grid beam search"
    - "unsupervised neural machine translation"

Connected through hyperedge HE-5 (induced by source paper "neural phrase to phrase machine translation"):
  with members:
    - "phrase based attentions"
    - "modeling localness for self attention networks"
    - "neural machine translation decoding with terminology constraints"
    - "phrase table as recommendation memory for neural machine translation"
    - "the best of both worlds combining recent advances in neural machine translation"
    - "translating phrases in neural machine translation"
    - "attention is all you need"
    - "convolutional sequence to sequence learning"

Connected through hyperedge HE-6 (induced by source paper "sequential copying networks"):
  with members:
    - "translating phrases in neural machine translation"
    - "selective encoding for abstractive sentence summarization"
    - "neural question generation from text a preliminary study"
    - "neural machine translation leveraging phrase based models in a hybrid search"
    - "pointing the unknown words"
    - "abstractive text summarization using sequence to sequence rnns and beyond"
    - "incorporating copying mechanism in sequence to sequence learning"
    - "squad 100 000 questions for machine comprehension of text"

Connected through hyperedge HE-7 (induced by source paper "neural entity reasoner for global consistency in ner"):
  with members:
    - "chinese ner using lattice lstm"
    - "fast and accurate entity recognition with iterated dilated convolutions"
    - "semi supervised multitask learning for sequence labeling"
    - "semi supervised sequence tagging with bidirectional language models"
    - "memory enhanced decoder for neural machine translation"
    - "end to end sequence labeling via bi directional lstm cnns crf"
    - "toward mention detection robustness with recurrent neural networks"
    - "neural architectures for named entity recognition"

Connected through hyperedge HE-8 (induced by source paper "phrase table as recommendation memory for neural machine translation"):
  with members:
    - "translating phrases in neural machine translation"
    - "memory augmented neural machine translation"
    - "neural machine translation advised by statistical machine translation"
    - "is neural machine translation ready for deployment a case study on 30 translation directions"
    - "implicit distortion and fertility models for attention based encoder decoder nmt model"
    - "bridging neural machine translation and bilingual dictionaries"
    - "vocabulary manipulation for neural machine translation"
    - "a coverage embedding model for neural machine translation"

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.CL(Computation and Language)