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: "universal dependency parsing from scratch"
  Abstract: This paper describes Stanford's system at the CoNLL 2018 UD Shared Task. We introduce a complete neural pipeline system that takes raw text as input, and performs all tasks required by the shared task, ranging from tokenization and sentence segmentation, to POS tagging and dependency parsing. Our single system submission achieved very competitive performance on big treebanks. Moreover, after fixing an unfortunate bug, our corrected system would have placed the 2nd, 1st, and 3rd on the official evaluation metrics LAS,MLAS, and BLEX, and would have outperformed all submission systems on low-resource treebank categories on all metrics by a large margin. We further show the effectiveness of different model components through extensive ablation studies.

Connected through hyperedge HE-1 (induced by source paper "learning spatiotemporal features via video and text pair discrimination"):
  with members:
    - "self supervised spatio temporal representation learning for videos by predicting motion and appearance statistics"
    - "distilbert a distilled version of bert smaller faster cheaper and lighter"
    - "contrastive multiview coding"
    - "dynamonet dynamic action and motion network"
    - "learning correspondence from the cycle consistency of time"
    - "videobert a joint model for video and language representation learning"
    - "howto100m learning a text video embedding by watching hundred million narrated video clips"
    - "video representation learning by dense predictive coding"

Connected through hyperedge HE-2 (induced by source paper "grounded and controllable image completion by incorporating lexical semantics"):
  with members:
    - "learning pyramid context encoder network for high quality image inpainting"
    - "foreground aware image inpainting"
    - "pluralistic image completion"
    - "unconstrained foreground object search"
    - "inferring semantic layout for hierarchical text to image synthesis"
    - "text adaptive generative adversarial networks manipulating images with natural language"
    - "mc gan multi conditional generative adversarial network for image synthesis"
    - "hole filling with multiple reference views in dibr view synthesis"

Connected through hyperedge HE-3 (induced by source paper "lscp enhanced large scale colloquial persian language understanding"):
  with members:
    - "deep multimodal image text embeddings for automatic cross media retrieval"
    - "lsicc a large scale informal chinese corpus"
    - "xnli evaluating cross lingual sentence representations"
    - "attention is all you need"
    - "opennmt open source toolkit for neural machine translation"
    - "extracting an english persian parallel corpus from comparable corpora"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-4 (induced by source paper "stanza a python natural language processing toolkit for many human languages"):
  with members:
    - "deep biaffine attention for neural dependency parsing"
    - "enriching word vectors with subword information"
    - "one billion word benchmark for measuring progress in statistical language modeling"
    - "introduction to the conll 2003 shared task language independent named entity recognition"
    - "introduction to the conll 2002 shared task language independent named entity recognition"

Connected through hyperedge HE-5 (induced by source paper "a corpus of adpositional supersenses for mandarin chinese"):
  with members:
    - "comprehensive supersense disambiguation of english prepositions and possessives"
    - "adpositional supersenses for mandarin chinese"
    - "adposition supersenses v2"

Connected through hyperedge HE-6 (induced by source paper "deep unified multimodal embeddings for understanding both content and users in social media networks"):
  with members:
    - "integrating text and image determining multimodal document intent in instagram posts"
    - "align2ground weakly supervised phrase grounding guided by image caption alignment"
    - "deep learning based recommender system a survey and new perspectives"
    - "exploring the limits of weakly supervised pretraining"
    - "a comprehensive survey of deep learning for image captioning"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attributed social network embedding"
    - "characterizing and detecting hateful users on twitter"

Connected through hyperedge HE-7 (induced by source paper "compositional generalization in image captioning"):
  with members:
    - "the curious case of neural text degeneration"
    - "nocaps novel object captioning at scale"
    - "neural baby talk"
    - "assessing composition in sentence vector representations"
    - "hierarchical neural story generation"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "rnns implicitly implement tensor product representations"
    - "evaluating compositionality in sentence embeddings"

Connected through hyperedge HE-8 (induced by source paper "deep contextualized word embeddings in transition based and graph based dependency parsing a tale of two parsers revisited"):
  with members:
    - "assessing bert s syntactic abilities"
    - "what do you learn from context probing for sentence structure in contextualized word representations"
    - "the non utility of structural features in bilstm based dependency parsers"
    - "75 languages 1 model parsing universal dependencies universally"
    - "linguistic knowledge and transferability of contextual representations"
    - "cross lingual alignment of contextual word embeddings with applications to zero shot dependency parsing"
    - "towards better ud parsing deep contextualized word embeddings ensemble and treebank concatenation"
    - "glue a multi task benchmark and analysis platform for natural language understanding"

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)