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: "nematus a toolkit for neural machine translation"
  Abstract: We present Nematus, a toolkit for Neural Machine Translation. The toolkit prioritizes high translation accuracy, usability, and extensibility. Nematus has been used to build top-performing submissions to shared translation tasks at WMT and IWSLT, and has been used to train systems for production environments.

Connected through hyperedge HE-1 (induced by source paper "multilingual neural machine translation for zero resource languages"):
  with members:
    - "self attention with relative position representations"
    - "deep neural machine translation with weakly recurrent units"
    - "improving zero shot translation of low resource languages"
    - "the university of edinburgh s neural mt systems for wmt17"
    - "attention is all you need"
    - "opennmt open source toolkit for neural machine translation"
    - "six challenges for neural machine translation"
    - "zero resource translation with multi lingual neural machine translation"

Connected through hyperedge HE-2 (induced by source paper "english bhojpuri smt system insights from the karaka model"):
  with members:
    - "the rgnlp machine translation systems for wat 2018"
    - "automatic identification of closely related indian languages resources and experiments"
    - "demo of sanskrit hindi smt system"
    - "joining hands exploiting monolingual treebanks for parsing of code mixing data"
    - "opennmt open source toolkit for neural machine translation"
    - "modeling source syntax for neural machine translation"
    - "six challenges for neural machine translation"
    - "reordering rules for english hindi smt"

Connected through hyperedge HE-3 (induced by source paper "generating commit messages from git diffs"):
  with members:
    - "code2vec learning distributed representations of code"
    - "code2seq generating sequences from structured representations of code"
    - "automatically generating commit messages from diffs using neural machine translation"
    - "a survey of machine learning for big code and naturalness"
    - "towards automatic generation of short summaries of commits"
    - "a neural architecture for generating natural language descriptions from source code changes"
    - "effective approaches to attention based neural machine translation"
    - "neural machine translation by jointly learning to align and translate"

Connected through hyperedge HE-4 (induced by source paper "texar a modularized versatile and extensible toolkit for text generation"):
  with members:
    - "toward unsupervised text content manipulation"
    - "target guided open domain conversation"
    - "deepmind control suite"
    - "unsupervised text style transfer using language models as discriminators"
    - "tensor2tensor for neural machine translation"
    - "deep generative models with learnable knowledge constraints"
    - "xnmt the extensible neural machine translation toolkit"
    - "marian fast neural machine translation in c"

Connected through hyperedge HE-5 (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"
    - "translating phrases in neural machine translation"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "doubly attentive transformer machine translation"):
  with members:
    - "image transformer"
    - "subword regularization improving neural network translation models with multiple subword candidates"
    - "attention is all you need"
    - "doubly attentive decoder for multi modal neural machine translation"
    - "cuni system for wmt16 automatic post editing and multimodal translation tasks"
    - "multimodal pivots for image caption translation"
    - "multi30k multilingual english german image descriptions"
    - "multi way multilingual neural machine translation with a shared attention mechanism"

Connected through hyperedge HE-7 (induced by source paper "returnn as a generic flexible neural toolkit with application to translation and speech recognition"):
  with members:
    - "tensor2tensor for neural machine translation"
    - "a comprehensive study of deep bidirectional lstm rnns for acoustic modeling in speech recognition"
    - "machine translation at booking com journey and lessons learned"
    - "english conversational telephone speech recognition by humans and machines"
    - "sockeye a toolkit for neural machine translation"
    - "focal loss for dense object detection"
    - "attention is all you need"
    - "minimum word error rate training for attention based sequence to sequence models"

Connected through hyperedge HE-8 (induced by source paper "adversarial example generation with syntactically controlled paraphrase networks"):
  with members:
    - "deep text classification can be fooled"
    - "generating sentences by editing prototypes"
    - "learning to paraphrase for question answering"
    - "paranmt 50m pushing the limits of paraphrastic sentence embeddings with millions of machine translations"
    - "controlling linguistic style aspects in neural language generation"
    - "learning paraphrastic sentence embeddings from back translated bitext"
    - "steering output style and topic in neural response generation"
    - "a deep generative framework for paraphrase generation"

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)