human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "revisiting challenges in data to text generation with fact grounding"):
  Abstract: Data-to-text generation models face challenges in ensuring data fidelity by referring to the correct input source. To inspire studies in this area, Wiseman et al. (2017) introduced the RotoWire corpus on generating NBA game summaries from the box- and line-score tables. However, limited attempts have been made in this direction and the challenges remain. We observe a prominent bottleneck in the corpus where only about 60% of the summary contents can be grounded to the boxscore records. Such information deficiency tends to misguide a conditioned language model to produce unconditioned random facts and thus leads to factual hallucinations. In this work, we restore the information balance and revamp this task to focus on fact-grounded data-to-text generation. We introduce a purified and larger-scale dataset, RotoWire-FG (Fact-Grounding), with 50% more data from the year 2017-19 and enriched input tables, hoping to attract more research focuses in this direction. Moreover, we achieve improved data fidelity over the state-of-the-art models by integrating a new form of table reconstruction as an auxiliary task to boost the generation quality.

Includes members:
  Member "learning to select track and generate for data to text":
    also connected through other hyperedges:
      (none)
  Member "data to text generation with entity modeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "sticking to the facts confident decoding for faithful data to text generation")
  Member "step by step separating planning from realization in neural data to text generation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "paraphrase generation with latent bag of words")
  Member "end to end content and plan selection for data to text generation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "paraphrase generation with latent bag of words")
  Member "describing a knowledge base":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "variational template machine for data to text generation")
  Member "multi reference training with pseudo references for neural translation and text generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "robust machine translation with domain sensitive pseudo sources baidu osu wmt19 mt robustness shared task system report")
  Member "data to text generation with content selection and planning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "paraphrase generation with latent bag of words")
  Member "learning to generate one sentence biographies from wikidata":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "variational template machine for data to text generation")

Question: Please tell me which class the source paper 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)