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: "emo2vec learning generalized emotion representation by multi task training"
  Abstract: In this paper, we propose Emo2Vec which encodes emotional semantics into vectors. We train Emo2Vec by multi-task learning six different emotion-related tasks, including emotion/sentiment analysis, sarcasm classification, stress detection, abusive language classification, insult detection, and personality recognition. Our evaluation of Emo2Vec shows that it outperforms existing affect-related representations, such as Sentiment-Specific Word Embedding and DeepMoji embeddings with much smaller training corpora. When concatenated with GloVe, Emo2Vec achieves competitive performances to state-of-the-art results on several tasks using a simple logistic regression classifier.

Connected through hyperedge HE-1 (induced by source paper "learning to memorize in neural task oriented dialogue systems"):
  with members:
    - "transferable multi domain state generator for task oriented dialogue systems"
    - "zero shot dialog generation with cross domain latent actions"
    - "skeleton to response dialogue generation guided by retrieval memory"
    - "the natural language decathlon multitask learning as question answering"
    - "an end to end approach for handling unknown slot values in dialogue state tracking"
    - "mem2seq effectively incorporating knowledge bases into end to end task oriented dialog systems"
    - "global locally self attentive dialogue state tracker"
    - "neural approaches to conversational ai"

Connected through hyperedge HE-2 (induced by source paper "moel mixture of empathetic listeners"):
  with members:
    - "the second conversational intelligence challenge convai2"
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "global to local memory pointer networks for task oriented dialogue"
    - "happybot generating empathetic dialogue responses by improving user experience look ahead"
    - "deepcopy grounded response generation with hierarchical pointer networks"
    - "importance of search and evaluation strategies in neural dialogue modeling"
    - "aiming to know you better perhaps makes me a more engaging dialogue partner"
    - "skeleton to response dialogue generation guided by retrieval memory"

Connected through hyperedge HE-3 (induced by source paper "clickbait sensational headline generation with auto tuned reinforcement learning"):
  with members:
    - "caire an end to end empathetic chatbot"
    - "a novel repetition normalized adversarial reward for headline generation"
    - "deep communicating agents for abstractive summarization"
    - "improving abstraction in text summarization"
    - "the clickbait challenge 2017 towards a regression model for clickbait strength"
    - "plusemo2vec at semeval 2018 task 1 exploiting emotion knowledge from emoji and hashtags"
    - "the design and implementation of xiaoice an empathetic social chatbot"
    - "a reinforced topic aware convolutional sequence to sequence model for abstractive text summarization"

Connected through hyperedge HE-4 (induced by source paper "happybot generating empathetic dialogue responses by improving user experience look ahead"):
  with members:
    - "towards empathetic open domain conversation models a new benchmark and dataset"
    - "personalizing dialogue agents i have a dog do you have pets too"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "toward controlled generation of text"
    - "emotional chatting machine emotional conversation generation with internal and external memory"
    - "mojitalk generating emotional responses at scale"
    - "attention is all you need"
    - "dailydialog a manually labelled multi turn dialogue dataset"

Connected through hyperedge HE-5 (induced by source paper "caire an end to end empathetic chatbot"):
  with members:
    - "transfertransfo a transfer learning approach for neural network based conversational agents"
    - "moel mixture of empathetic listeners"
    - "negative training for neural dialogue response generation"
    - "xlnet generalized autoregressive pretraining for language understanding"
    - "the design and implementation of xiaoice an empathetic social chatbot"
    - "towards empathetic open domain conversation models a new benchmark and dataset"
    - "deep contextualized word representations"
    - "personalizing dialogue agents i have a dog do you have pets too"

Connected through hyperedge HE-6 (induced by source paper "hierarchical meta embeddings for code switching named entity recognition"):
  with members:
    - "named entity recognition on code switched data overview of the calcs 2018 shared task"
    - "incorporating word and subword units in unsupervised machine translation using language model rescoring"
    - "frustratingly easy meta embedding computing meta embeddings by averaging source word embeddings"
    - "code switching language modeling using syntax aware multi task learning"
    - "dynamic meta embeddings for improved sentence representations"
    - "learning word vectors for 157 languages"
    - "think globally embed locally locally linear meta embedding of words"
    - "attention is all you need"

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"
    - "loss in translation learning bilingual word mapping with a retrieval criterion"
    - "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"
    - "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 "caire_hkust at semeval 2019 task 3 hierarchical attention for dialogue emotion classification"):
  with members:
    - "universal transformers"
    - "plusemo2vec at semeval 2018 task 1 exploiting emotion knowledge from emoji and hashtags"
    - "attnconvnet at semeval 2018 task 1 attention based convolutional neural networks for multi label emotion classification"
    - "deep contextualized word representations"
    - "attention based lstm for psychological stress detection from spoken language using distant supervision"
    - "bert pre training of deep bidirectional transformers for language understanding"
    - "attention is all you need"
    - "learned in translation contextualized word vectors"

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)