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 "multi task learning for coherence modeling"):
  Abstract: We address the task of assessing discourse coherence, an aspect of text quality that is essential for many NLP tasks, such as summarization and language assessment. We propose a hierarchical neural network trained in a multi-task fashion that learns to predict a document-level coherence score (at the network's top layers) along with word-level grammatical roles (at the bottom layers), taking advantage of inductive transfer between the two tasks. We assess the extent to which our framework generalizes to different domains and prediction tasks, and demonstrate its effectiveness not only on standard binary evaluation coherence tasks, but also on real-world tasks involving the prediction of varying degrees of coherence, achieving a new state of the art.

Includes members:
  Member "what do you learn from context probing for sentence structure in contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on contextual embeddings")
  Member "coherence modeling of asynchronous conversations a neural entity grid approach":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a cross domain transferable neural coherence model")
  Member "discourse coherence in the wild a dataset evaluation and methods":
    also connected through other hyperedges:
      (none)
  Member "a hierarchical multi task approach for learning embeddings from semantic tasks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "sbert wk a sentence embedding method by dissecting bert based word models")
  Member "neural automated essay scoring and coherence modeling for adversarially crafted input":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "rc qed evaluating natural language derivations in multi hop reading comprehension")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")
  Member "auxiliary objectives for neural error detection models":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "pretraining methods for dialog context representation learning")
  Member "sentence ordering and coherence modeling using recurrent neural networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "evaluation benchmarks and learning criteria for discourse aware sentence representations")

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)