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: "generating fine grained open vocabulary entity type descriptions"
  Abstract: While large-scale knowledge graphs provide vast amounts of structured facts about entities, a short textual description can often be useful to succinctly characterize an entity and its type. Unfortunately, many knowledge graph entities lack such textual descriptions. In this paper, we introduce a dynamic memory-based network that generates a short open vocabulary description of an entity by jointly leveraging induced fact embeddings as well as the dynamic context of the generated sequence of words. We demonstrate the ability of our architecture to discern relevant information for more accurate generation of type description by pitting the system against several strong baselines.

Connected through hyperedge HE-1 (induced by source paper "ensuring readability and data fidelity using head modifier templates in deep type description generation"):
  with members:
    - "attention is all you need"
    - "opennmt open source toolkit for neural machine translation"
    - "get to the point summarization with pointer generator networks"
    - "fine grained entity type classification by jointly learning representations and label embeddings"
    - "challenges in data to document generation"
    - "table to text generation by structure aware seq2seq learning"
    - "pointing the unknown words"
    - "context gates for neural machine translation"

Connected through hyperedge HE-2 (induced by source paper "be concise and precise synthesizing open domain entity descriptions from facts"):
  with members:
    - "generating wikipedia by summarizing long sequences"
    - "neuralreg an end to end approach to referring expression generation"
    - "get to the point summarization with pointer generator networks"
    - "a neural knowledge language model"
    - "pointing the unknown words"
    - "incorporating copying mechanism in sequence to sequence learning"
    - "video captioning with multi faceted attention"
    - "generating text from structured data with application to the biography domain"

Connected through hyperedge HE-3 (induced by source paper "unsupervised text generation from structured data"):
  with members:
    - "text generation from knowledge graphs with graph transformers"
    - "phrase based neural unsupervised machine translation"
    - "a survey on open information extraction"
    - "data to text generation with content selection and planning"
    - "massive exploration of neural machine translation architectures"
    - "challenges in data to document generation"
    - "incorporating copying mechanism in sequence to sequence learning"
    - "visual relationship detection with language priors"

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)