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: "memory augmented neural machine translation"
  Abstract: Neural machine translation (NMT) has achieved notable success in recent times, however it is also widely recognized that this approach has limitations with handling infrequent words and word pairs. This paper presents a novel memory-augmented NMT (M-NMT) architecture, which stores knowledge about how words (usually infrequently encountered ones) should be translated in a memory and then utilizes them to assist the neural model. We use this memory mechanism to combine the knowledge learned from a conventional statistical machine translation system and the rules learned by an NMT system, and also propose a solution for out-of-vocabulary (OOV) words based on this framework. Our experiments on two Chinese-English translation tasks demonstrated that the M-NMT architecture outperformed the NMT baseline by $9.0$ and $2.7$ BLEU points on the two tasks, respectively. Additionally, we found this architecture resulted in a much more effective OOV treatment compared to competitive methods.

Connected through hyperedge HE-1 (induced by source paper "memory attended recurrent network for video captioning"):
  with members:
    - "less is more picking informative frames for video captioning"
    - "bidirectional attentive fusion with context gating for dense video captioning"
    - "automatic stance detection using end to end memory networks"
    - "reconstruction network for video captioning"
    - "recurrent fusion network for image captioning"
    - "end to end video captioning with multitask reinforcement learning"
    - "a closer look at spatiotemporal convolutions for action recognition"
    - "can spatiotemporal 3d cnns retrace the history of 2d cnns and imagenet"

Connected through hyperedge HE-2 (induced by source paper "shared private bilingual word embeddings for neural machine translation"):
  with members:
    - "achieving human parity on automatic chinese to english news translation"
    - "universal neural machine translation for extremely low resource languages"
    - "compositional representation of morphologically rich input for neural machine translation"
    - "the best of both worlds combining recent advances in neural machine translation"
    - "thumt an open source toolkit for neural machine translation"
    - "the university of edinburgh s neural mt systems for wmt17"
    - "attention is all you need"
    - "slim embedding layers for recurrent neural language models"

Connected through hyperedge HE-3 (induced by source paper "cpgan full spectrum content parsing generative adversarial networks for text to image synthesis"):
  with members:
    - "object driven text to image synthesis via adversarial training"
    - "memory attended recurrent network for video captioning"
    - "mirrorgan learning text to image generation by redescription"
    - "dm gan dynamic memory generative adversarial networks for text to image synthesis"
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "automatic stance detection using end to end memory networks"
    - "yolov3 an incremental improvement"
    - "spectral normalization for generative adversarial networks"

Connected through hyperedge HE-4 (induced by source paper "cm net a novel collaborative memory network for spoken language understanding"):
  with members:
    - "bert for joint intent classification and slot filling"
    - "simple fast accurate intent classification and slot labeling"
    - "joint slot filling and intent detection via capsule neural networks"
    - "deep contextualized word representations"
    - "a bi model based rnn semantic frame parsing model for intent detection and slot filling"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "unsupervised transfer learning for spoken language understanding in intelligent agents"
    - "sentence state lstm for text representation"

Connected through hyperedge HE-5 (induced by source paper "neural machine translation with noisy lexical constraints"):
  with members:
    - "non parametric adaptation for neural machine translation"
    - "training neural machine translation to apply terminology constraints"
    - "fast lexically constrained decoding with dynamic beam allocation for neural machine translation"
    - "neural machine translation decoding with terminology constraints"
    - "quickedit editing text translations by crossing words out"
    - "learning to remember translation history with a continuous cache"
    - "attention is all you need"
    - "opennmt open source toolkit for neural machine translation"

Connected through hyperedge HE-6 (induced by source paper "learning efficient lexically constrained neural machine translation with external memory"):
  with members:
    - "towards one shot learning for rare word translation with external experts"
    - "fast lexically constrained decoding with dynamic beam allocation for neural machine translation"
    - "a call for clarity in reporting bleu scores"
    - "neural machine translation with key value memory augmented attention"
    - "phrase table as recommendation memory for neural machine translation"
    - "phrase based neural unsupervised machine translation"
    - "unsupervised machine translation using monolingual corpora only"
    - "attention is all you need"

Connected through hyperedge HE-7 (induced by source paper "phrase table as recommendation memory for neural machine translation"):
  with members:
    - "translating phrases in 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"

Connected through hyperedge HE-8 (induced by source paper "neural machine translation with key value memory augmented attention"):
  with members:
    - "attention is all you need"
    - "frustratingly short attention spans in neural language modeling"
    - "search engine guided non parametric neural machine translation"
    - "neural machine translation advised by statistical machine translation"
    - "memory enhanced decoder for neural machine translation"
    - "implicit distortion and fertility models for attention based encoder decoder nmt model"
    - "coverage embedding models for neural machine translation"
    - "interactive attention 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)