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: "loss in translation learning bilingual word mapping with a retrieval criterion"
  Abstract: Continuous word representations learned separately on distinct languages can be aligned so that their words become comparable in a common space. Existing works typically solve a least-square regression problem to learn a rotation aligning a small bilingual lexicon, and use a retrieval criterion for inference. In this paper, we propose an unified formulation that directly optimizes a retrieval criterion in an end-to-end fashion. Our experiments on standard benchmarks show that our approach outperforms the state of the art on word translation, with the biggest improvements observed for distant language pairs such as English-Chinese.

Connected through hyperedge HE-1 (induced by source paper "effective cross lingual transfer of neural machine translation models without shared vocabularies"):
  with members:
    - "two new evaluation datasets for low resource machine translation nepali english and sinhala english"
    - "improving unsupervised word by word translation with language model and denoising autoencoder"
    - "cross lingual language model pretraining"
    - "multilingual neural machine translation with soft decoupled encoding"
    - "unsupervised statistical machine translation"
    - "trivial transfer learning for low resource neural machine translation"
    - "universal neural machine translation for extremely low resource languages"
    - "parameter sharing methods for multilingual self attentional translation models"

Connected through hyperedge HE-2 (induced by source paper "cross lingual alignment of contextual word embeddings with applications to zero shot dependency parsing"):
  with members:
    - "context aware cross lingual mapping"
    - "linguistic knowledge and transferability of contextual representations"
    - "gromov wasserstein alignment of word embedding spaces"
    - "towards better ud parsing deep contextualized word embeddings ensemble and treebank concatenation"
    - "parameter sharing between dependency parsers for related languages"
    - "allennlp a deep semantic natural language processing platform"
    - "deep contextualized word representations"
    - "when and why are pre trained word embeddings useful for neural machine translation"

Connected through hyperedge HE-3 (induced by source paper "robust cross lingual embeddings from parallel sentences"):
  with members:
    - "crosslingual document embedding as reduced rank ridge regression"
    - "a survey of cross lingual word embedding models"
    - "analyzing the limitations of cross lingual word embedding mappings"
    - "better word embeddings by disentangling contextual n gram information"
    - "a corpus for multilingual document classification in eight languages"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "unsupervised multilingual word embeddings"
    - "non adversarial unsupervised word translation"

Connected through hyperedge HE-4 (induced by source paper "density matching for bilingual word embedding"):
  with members:
    - "unsupervised statistical machine translation"
    - "universal neural machine translation for extremely low resource languages"
    - "near or far wide range zero shot cross lingual dependency parsing"
    - "learning multilingual word embeddings in latent metric space a geometric approach"
    - "non adversarial unsupervised word translation"
    - "unsupervised alignment of embeddings with wasserstein procrustes"
    - "on the limitations of unsupervised bilingual dictionary induction"
    - "a robust self learning method for fully unsupervised cross lingual mappings of word embeddings"

Connected through hyperedge HE-5 (induced by source paper "aligning multilingual word embeddings for cross modal retrieval task"):
  with members:
    - "neural baby talk"
    - "learning two branch neural networks for image text matching tasks"
    - "multilingual multi modal embeddings for natural language processing"
    - "image pivoting for learning multilingual multimodal representations"
    - "stair captions constructing a large scale japanese image caption dataset"
    - "word translation without parallel data"
    - "instance aware image and sentence matching with selective multimodal lstm"
    - "multimodal pivots for image caption translation"

Connected through hyperedge HE-6 (induced by source paper "attention informed mixed language training for zero shot cross lingual task oriented dialogue systems"):
  with members:
    - "zero shot cross lingual dialogue systems with transferable latent variables"
    - "universal transformers"
    - "cross lingual language model pretraining"
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "xl nbt a cross lingual neural belief tracking framework"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "cross lingual transfer learning for multilingual task oriented dialog"
    - "weakly supervised cross lingual named entity recognition via effective annotation and representation projection"

Connected through hyperedge HE-7 (induced by source paper "zero shot cross lingual dialogue systems with transferable latent variables"):
  with members:
    - "incorporating word and subword units in unsupervised machine translation using language model rescoring"
    - "universal neural machine translation for extremely low resource languages"
    - "unsupervised discrete sentence representation learning for interpretable neural dialog generation"
    - "xl nbt a cross lingual neural belief tracking framework"
    - "emo2vec learning generalized emotion representation by multi task training"
    - "cross lingual transfer learning for multilingual task oriented dialog"
    - "latent intention dialogue models"
    - "learned in translation contextualized word vectors"

Connected through hyperedge HE-8 (induced by source paper "pidginunmt unsupervised neural machine translation from west african pidgin to english"):
  with members:
    - "a survey of cross lingual word embedding models"
    - "phrase based neural unsupervised machine translation"
    - "unsupervised machine translation using monolingual corpora only"
    - "attention is all you need"
    - "unsupervised neural machine translation"
    - "offline bilingual word vectors orthogonal transformations and the inverted softmax"
    - "word translation without parallel data"
    - "enriching word vectors with subword information"

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)