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: "pairwise neural machine translation evaluation"
  Abstract: We present a novel framework for machine translation evaluation using neural networks in a pairwise setting, where the goal is to select the better translation from a pair of hypotheses, given the reference translation. In this framework, lexical, syntactic and semantic information from the reference and the two hypotheses is compacted into relatively small distributed vector representations, and fed into a multi-layer neural network that models the interaction between each of the hypotheses and the reference, as well as between the two hypotheses. These compact representations are in turn based on word and sentence embeddings, which are learned using neural networks. The framework is flexible, allows for efficient learning and classification, and yields correlation with humans that rivals the state of the art.

Connected through hyperedge HE-1 (induced by source paper "sentence level human translation quality estimation with attention based neural networks"):
  with members:
    - "unsupervised cross lingual representation learning at scale"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attention is all you need"
    - "machine translation evaluation with neural networks"
    - "xgboost a scalable tree boosting system"
    - "text classification improved by integrating bidirectional lstm with two dimensional max pooling"
    - "effective approaches to attention based neural machine translation"
    - "adam a method for stochastic optimization"

Connected through hyperedge HE-2 (induced by source paper "evaluating pronominal anaphora in machine translation an evaluation measure and a test suite"):
  with members:
    - "findings of the 2016 wmt shared task on cross lingual pronoun prediction"
    - "achieving human parity on automatic chinese to english news translation"
    - "has machine translation achieved human parity a case for document level evaluation"
    - "automatic reference based evaluation of pronoun translation misses the point"
    - "deep contextualized word representations"
    - "context aware neural machine translation learns anaphora resolution"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "a large scale test set for the evaluation of context aware pronoun translation in neural machine translation"

Connected through hyperedge HE-3 (induced by source paper "semeval 2017 task 3 community question answering"):
  with members:
    - "hunting for troll comments in news community forums"
    - "semeval 2015 task 3 answer selection in community question answering"
    - "semeval 2016 task 3 community question answering"
    - "global thread level inference for comment classification in community question answering"
    - "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings"
    - "machine translation evaluation meets community question answering"
    - "a decomposable attention model for natural language inference"
    - "semi supervised question retrieval with gated convolutions"

Connected through hyperedge HE-4 (induced by source paper "semeval 2016 task 3 community question answering"):
  with members:
    - "hunting for troll comments in news community forums"
    - "semeval 2015 task 3 answer selection in community question answering"
    - "global thread level inference for comment classification in community question answering"
    - "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings"
    - "machine translation evaluation meets community question answering"
    - "uh prhlt at semeval 2016 task 3 combining lexical and semantic based features for community question answering"
    - "answer sequence learning with neural networks for answer selection in community question answering"
    - "query chains learning to rank from implicit feedback"

Connected through hyperedge HE-5 (induced by source paper "machine translation evaluation meets community question answering"):
  with members:
    - "semeval 2016 task 3 community question answering"
    - "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings"
    - "semi supervised question retrieval with gated convolutions"
    - "applying deep learning to answer selection a study and an open task"
    - "word embedding based correlation model for question answer matching"
    - "lstm based deep learning models for non factoid answer selection"

Connected through hyperedge HE-6 (induced by source paper "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings"):
  with members:
    - "hunting for troll comments in news community forums"
    - "semeval 2015 task 3 answer selection in community question answering"
    - "global thread level inference for comment classification in community question answering"
    - "machine translation evaluation meets community question answering"
    - "distributed representations of sentences and documents"

Connected through hyperedge HE-7 (induced by source paper "joint multitask learning for community question answering using task specific embeddings"):
  with members:
    - "semeval 2016 task 3 community question answering"
    - "semanticz at semeval 2016 task 3 ranking relevant answers in community question answering using semantic similarity based on fine tuned word embeddings"
    - "adversarial domain adaptation for duplicate question detection"
    - "fact checking in community forums"
    - "large scale goodness polarity lexicons for community question answering"
    - "machine translation evaluation with neural networks"
    - "semi supervised question retrieval with gated convolutions"
    - "bidirectional lstm crf models for sequence tagging"

Connected through hyperedge HE-8 (induced by source paper "otem utem over and under translation evaluation metric for nmt"):
  with members:
    - "sparse and constrained attention for neural machine translation"
    - "lepor an augmented machine translation evaluation metric"
    - "attention is all you need"
    - "a gru gated attention model for neural machine translation"
    - "convolutional sequence to sequence learning"
    - "modeling coverage for neural machine translation"
    - "neural machine translation with recurrent attention modeling"
    - "incorporating structural alignment biases into an attentional neural translation model"

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)