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: "translating phrases in neural machine translation"
  Abstract: Phrases play an important role in natural language understanding and machine translation (Sag et al., 2002; Villavicencio et al., 2005). However, it is difficult to integrate them into current neural machine translation (NMT) which reads and generates sentences word by word. In this work, we propose a method to translate phrases in NMT by integrating a phrase memory storing target phrases from a phrase-based statistical machine translation (SMT) system into the encoder-decoder architecture of NMT. At each decoding step, the phrase memory is first re-written by the SMT model, which dynamically generates relevant target phrases with contextual information provided by the NMT model. Then the proposed model reads the phrase memory to make probability estimations for all phrases in the phrase memory. If phrase generation is carried on, the NMT decoder selects an appropriate phrase from the memory to perform phrase translation and updates its decoding state by consuming the words in the selected phrase. Otherwise, the NMT decoder generates a word from the vocabulary as the general NMT decoder does. Experiment results on the Chinese to English translation show that the proposed model achieves significant improvements over the baseline on various test sets.

Connected through hyperedge HE-1 (induced by source paper "multi granularity self attention for neural machine translation"):
  with members:
    - "analyzing multi head self attention specialized heads do the heavy lifting the rest can be pruned"
    - "area attention"
    - "information aggregation for multi head attention with routing by agreement"
    - "strategies for structuring story generation"
    - "towards better modeling hierarchical structure for self attention with ordered neurons"
    - "syntax enhanced neural machine translation with syntax aware word representations"
    - "modeling recurrence for transformer"
    - "phrase based attentions"

Connected through hyperedge HE-2 (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"
    - "lexically constrained decoding for sequence generation using grid beam search"
    - "unsupervised neural machine translation"
    - "neural machine translation leveraging phrase based models in a hybrid search"

Connected through hyperedge HE-3 (induced by source paper "learning to discriminate noises for incorporating external information in neural machine translation"):
  with members:
    - "fast lexically constrained decoding with dynamic beam allocation for neural machine translation"
    - "context aware neural machine translation learns anaphora resolution"
    - "neural machine translation decoding with terminology constraints"
    - "the university of edinburgh s neural mt systems for wmt17"
    - "neural system combination for machine translation"
    - "learning to remember translation history with a continuous cache"
    - "attention is all you need"
    - "lexically constrained decoding for sequence generation using grid beam search"

Connected through hyperedge HE-4 (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"
    - "attention is all you need"
    - "convolutional sequence to sequence learning"
    - "multitask learning with ctc and segmental crf for speech recognition"

Connected through hyperedge HE-5 (induced by source paper "translating pro drop languages with reconstruction models"):
  with members:
    - "learning to remember translation history with a continuous cache"
    - "chunk based bi scale decoder for neural machine translation"
    - "exploiting cross sentence context for neural machine translation"
    - "modeling source syntax for neural machine translation"
    - "search engine guided non parametric neural machine translation"
    - "neural machine translation advised by statistical machine translation"
    - "context gates for neural machine translation"
    - "neural machine translation with reconstruction"

Connected through hyperedge HE-6 (induced by source paper "sequential copying networks"):
  with members:
    - "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"
    - "machine comprehension using match lstm and answer pointer"

Connected through hyperedge HE-7 (induced by source paper "quantum statistics inspired neural attention"):
  with members:
    - "analyzing uncertainty in neural machine translation"
    - "eigendecomposition free training of deep networks with zero eigenvalue based losses"
    - "enhancing sentence embedding with generalized pooling"
    - "online and linear time attention by enforcing monotonic alignments"
    - "structured attention networks"
    - "breaking the softmax bottleneck a high rank rnn language model"
    - "sentence ordering and coherence modeling using recurrent neural networks"
    - "end to end memory networks"

Connected through hyperedge HE-8 (induced by source paper "phrase table as recommendation memory for neural machine translation"):
  with members:
    - "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"
    - "the amu uedin submission to the wmt16 news translation task attention based nmt models as feature functions in phrase based smt"

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)