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 "transforming complex sentences into a semantic hierarchy"):
  Abstract: We present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that may facilitate a wide variety of artificial intelligence tasks, such as machine translation (MT) or information extraction (IE). Using a set of hand-crafted transformation rules, input sentences are recursively transformed into a two-layered hierarchical representation in the form of core sentences and accompanying contexts that are linked via rhetorical relations. In this way, the semantic relationship of the decomposed constituents is preserved in the output, maintaining its interpretability for downstream applications. Both a thorough manual analysis and automatic evaluation across three datasets from two different domains demonstrate that the proposed syntactic simplification approach outperforms the state of the art in structural text simplification. Moreover, an extrinsic evaluation shows that when applying our framework as a preprocessing step the performance of state-of-the-art Open IE systems can be improved by up to 346% in precision and 52% in recall. To enable reproducible research, all code is provided online.

Includes members:
  Member "semantic structural evaluation for text simplification":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "automatically extracting challenge sets for non local phenomena neural machine translation")
  Member "graphene semantically linked propositions in open information extraction":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "identifying supporting facts for multi hop question answering with document graph networks")
  Member "bleu is not suitable for the evaluation of text simplification":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "emptransfo a multi head transformer architecture for creating empathetic dialog systems")
  Member "simple and effective text simplification using semantic and neural methods":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "made for each other broad coverage semantic structures meet preposition supersenses")
  Member "learning to split and rephrase from wikipedia edit history":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fact aware sentence split and rephrase with permutation invariant training")
  Member "split and rephrase":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fact aware sentence split and rephrase with permutation invariant training")
  Member "sentence simplification with deep reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "generative question refinement with deep reinforcement learning in retrieval based qa system")
  Member "get to the point summarization with pointer generator networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mast a memory augmented self supervised tracker")

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)