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: "the cl scisumm shared task 2018 results and key insights"
  Abstract: This overview describes the official results of the CL-SciSumm Shared Task 2018 -- the first medium-scale shared task on scientific document summarization in the computational linguistics (CL) domain. This year, the dataset comprised 60 annotated sets of citing and reference papers from the open access research papers in the CL domain. The Shared Task was organized as a part of the 41st Annual Conference of the Special Interest Group in Information Retrieval (SIGIR), held in Ann Arbor, USA in July 2018. We compare the participating systems in terms of two evaluation metrics. The annotated dataset and evaluation scripts can be accessed and used by the community from: \url{this https URL}.

Connected through hyperedge HE-1 (induced by source paper "scisummnet a large annotated corpus and content impact models for scientific paper summarization with citation networks"):
  with members:
    - "scientific document summarization via citation contextualization and scientific discourse"
    - "ranking sentences for extractive summarization with reinforcement learning"
    - "a discourse aware attention model for abstractive summarization of long documents"
    - "a supervised approach to extractive summarisation of scientific papers"
    - "contextualizing citations for scientific summarization using word embeddings and domain knowledge"
    - "get to the point summarization with pointer generator networks"
    - "encoding sentences with graph convolutional networks for semantic role labeling"
    - "scientific article summarization using citation context and article s discourse structure"

Connected through hyperedge HE-2 (induced by source paper "talksumm a dataset and scalable annotation method for scientific paper summarization based on conference talks"):
  with members:
    - "scisummnet a large annotated corpus and content impact models for scientific paper summarization with citation networks"
    - "data driven summarization of scientific articles"
    - "scientific document summarization via citation contextualization and scientific discourse"
    - "fast abstractive summarization with reinforce selected sentence rewriting"
    - "a supervised approach to extractive summarisation of scientific papers"
    - "get to the point summarization with pointer generator networks"
    - "neural summarization by extracting sentences and words"
    - "what s cookin interpreting cooking videos using text speech and vision"

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)