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: "the amu uedin submission to the wmt16 news translation task attention based nmt models as feature functions in phrase based smt"
  Abstract: This paper describes the AMU-UEDIN submissions to the WMT 2016 shared task on news translation. We explore methods of decode-time integration of attention-based neural translation models with phrase-based statistical machine translation. Efficient batch-algorithms for GPU-querying are proposed and implemented. For English-Russian, our system stays behind the state-of-the-art pure neural models in terms of BLEU. Among restricted systems, manual evaluation places it in the first cluster tied with the pure neural model. For the Russian-English task, our submission achieves the top BLEU result, outperforming the best pure neural system by 1.1 BLEU points and our own phrase-based baseline by 1.6 BLEU. After manual evaluation, this system is the best restricted system in its own cluster. In follow-up experiments we improve results by additional 0.8 BLEU.

Connected through hyperedge HE-1 (induced by source paper "cued wmt19 ewc lms"):
  with members:
    - "selective attention for context aware neural machine translation"
    - "domain adaptive inference for neural machine translation"
    - "investigating backtranslation in neural machine translation"
    - "modeling coherence for discourse neural machine translation"
    - "has machine translation achieved human parity a case for document level evaluation"
    - "near human level performance in grammatical error correction with hybrid machine translation"
    - "improving the transformer translation model with document level context"
    - "simple fusion return of the language model"

Connected through hyperedge HE-2 (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"
    - "nematus a toolkit for neural machine translation"
    - "six challenges for neural machine translation"

Connected through hyperedge HE-3 (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-4 (induced by source paper "ucam biomedical translation at wmt19 transfer learning multi domain ensembles"):
  with members:
    - "domain adaptive inference for neural machine translation"
    - "cued wmt19 ewc lms"
    - "a call for clarity in reporting bleu scores"
    - "multi representation ensembles and delayed sgd updates improve syntax based nmt"
    - "an empirical comparison of simple domain adaptation methods for neural machine translation"
    - "sgnmt a flexible nmt decoding platform for quick prototyping of new models and search strategies"
    - "domain control for neural machine translation"
    - "fast domain adaptation for neural machine translation"

Connected through hyperedge HE-5 (induced by source paper "the university of cambridge s machine translation systems for wmt18"):
  with members:
    - "achieving human parity on automatic chinese to english news translation"
    - "weighted transformer network for machine translation"
    - "near human level performance in grammatical error correction with hybrid machine translation"
    - "self attention with relative position representations"
    - "training tips for the transformer model"
    - "why not be versatile applications of the sgnmt decoder for machine translation"
    - "fine grained evaluation of german english machine translation based on a test suite"
    - "accelerating nmt batched beam decoding with lmbr posteriors for deployment"

Connected through hyperedge HE-6 (induced by source paper "zero shot cross lingual classification using multilingual neural machine translation"):
  with members:
    - "deep contextualized word representations"
    - "supervised learning of universal sentence representations from natural language inference data"
    - "learned in translation contextualized word vectors"
    - "stochastic answer networks for machine reading comprehension"
    - "semi supervised sequence tagging with bidirectional language models"
    - "baselines and test data for cross lingual inference"
    - "what makes imagenet good for transfer learning"
    - "enriching word vectors with subword information"

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"
    - "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"

Connected through hyperedge HE-8 (induced by source paper "bi directional neural machine translation with synthetic parallel data"):
  with members:
    - "joint training for neural machine translation models with monolingual data"
    - "sockeye a toolkit for neural machine translation"
    - "an empirical comparison of simple domain adaptation methods for neural machine translation"
    - "improving lexical choice in neural machine translation"
    - "six challenges for neural machine translation"
    - "unsupervised pretraining for sequence to sequence learning"
    - "using the output embedding to improve language models"
    - "multi way multilingual neural machine translation with a shared attention mechanism"

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)