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: "learning joint multilingual sentence representations with neural machine translation"
  Abstract: In this paper, we use the framework of neural machine translation to learn joint sentence representations across six very different languages. Our aim is that a representation which is independent of the language, is likely to capture the underlying semantics. We define a new cross-lingual similarity measure, compare up to 1.4M sentence representations and study the characteristics of close sentences. We provide experimental evidence that sentences that are close in embedding space are indeed semantically highly related, but often have quite different structure and syntax. These relations also hold when comparing sentences in different languages.

Connected through hyperedge HE-1 (induced by source paper "absent cross lingual sentence representation mapping with bidirectional gans"):
  with members:
    - "reinforcement knowledge graph reasoning for explainable recommendation"
    - "improving multilingual sentence embedding using bi directional dual encoder with additive margin softmax"
    - "multilingual neural machine translation with soft decoupled encoding"
    - "oogan disentangling gan with one hot sampling and orthogonal regularization"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "characterizing departures from linearity in word translation"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "triangle generative adversarial networks"

Connected through hyperedge HE-2 (induced by source paper "semantic drift in multilingual representations"):
  with members:
    - "a survey of cross lingual word embedding models"
    - "what do language representations really represent"
    - "blackbox meets blackbox representational similarity and stability analysis of neural language models and brains"
    - "filtering and mining parallel data in a joint multilingual space"
    - "xnli evaluating cross lingual sentence representations"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "multimodal grounding for language processing"
    - "glue a multi task benchmark and analysis platform for natural language understanding"

Connected through hyperedge HE-3 (induced by source paper "a bilingual generative transformer for semantic sentence embedding"):
  with members:
    - "a multi task approach for disentangling syntax and semantics in sentence representations"
    - "lagging inference networks and posterior collapse in variational autoencoders"
    - "sentence bert sentence embeddings using siamese bert networks"
    - "simple and effective paraphrastic similarity from parallel translations"
    - "beyond bleu training neural machine translation with semantic similarity"
    - "sentencepiece a simple and language independent subword tokenizer and detokenizer for neural text processing"
    - "filtering and mining parallel data in a joint multilingual space"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"

Connected through hyperedge HE-4 (induced by source paper "probing multilingual sentence representations with x probe"):
  with members:
    - "scalable cross lingual transfer of neural sentence embeddings"
    - "cross lingual language model pretraining"
    - "linguistic knowledge and transferability of contextual representations"
    - "xnli evaluating cross lingual sentence representations"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "deep contextualized word representations"
    - "universal sentence encoder"
    - "understanding learning dynamics of language models with svcca"

Connected through hyperedge HE-5 (induced by source paper "emu enhancing multilingual sentence embeddings with semantic specialization"):
  with members:
    - "sentence bert sentence embeddings using siamese bert networks"
    - "how to properly evaluate cross lingual word embeddings on strong baselines comparative analyses and some misconceptions"
    - "improving multilingual sentence embedding using bi directional dual encoder with additive margin softmax"
    - "multi lingual common semantic space construction via cluster consistent word embedding"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "unsupervised multilingual word embeddings"
    - "deep contextualized word representations"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-6 (induced by source paper "simple and effective paraphrastic similarity from parallel translations"):
  with members:
    - "parabank monolingual bitext generation and sentential paraphrasing via lexically constrained neural machine translation"
    - "sentencepiece a simple and language independent subword tokenizer and detokenizer for neural text processing"
    - "effective parallel corpus mining using bilingual sentence embeddings"
    - "filtering and mining parallel data in a joint multilingual space"
    - "massively multilingual sentence embeddings for zero shot cross lingual transfer and beyond"
    - "deep contextualized word representations"
    - "extracting parallel sentences with bidirectional recurrent neural networks to improve machine translation"
    - "bert pre training of deep bidirectional transformers for language understanding"

Connected through hyperedge HE-7 (induced by source paper "scalable cross lingual transfer of neural sentence embeddings"):
  with members:
    - "context aware cross lingual mapping"
    - "effective parallel corpus mining using bilingual sentence embeddings"
    - "a corpus for multilingual document classification in eight languages"
    - "evaluation of unsupervised compositional representations"
    - "evaluating compositionality in sentence embeddings"
    - "senteval an evaluation toolkit for universal sentence representations"
    - "supervised learning of universal sentence representations from natural language inference data"
    - "unsupervised word mapping using structural similarities in monolingual embeddings"

Connected through hyperedge HE-8 (induced by source paper "pivot based transfer learning for neural machine translation between non english languages"):
  with members:
    - "effective cross lingual transfer of neural machine translation models without shared vocabularies"
    - "massively multilingual neural machine translation"
    - "filtering and mining parallel data in a joint multilingual space"
    - "trivial transfer learning for low resource neural machine translation"
    - "triangular architecture for rare language translation"
    - "improving zero shot translation of low resource languages"
    - "a neural interlingua for multilingual machine translation"
    - "zero shot dual 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)