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 "broad coverage semantic parsing as transduction"):
  Abstract: We unify different broad-coverage semantic parsing tasks under a transduction paradigm, and propose an attention-based neural framework that incrementally builds a meaning representation via a sequence of semantic relations. By leveraging multiple attention mechanisms, the transducer can be effectively trained without relying on a pre-trained aligner. Experiments conducted on three separate broad-coverage semantic parsing tasks -- AMR, SDP and UCCA -- demonstrate that our attention-based neural transducer improves the state of the art on both AMR and UCCA, and is competitive with the state of the art on SDP.

Includes members:
  Member "core semantic first a top down approach for amr parsing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "amr similarity metrics from principles")
  Member "compositional semantic parsing across graphbanks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "core semantic first a top down approach for amr parsing")
  Member "semeval 2019 task 1 cross lingual semantic parsing with ucca":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "made for each other broad coverage semantic structures meet preposition supersenses")
  Member "rewarding smatch transition based amr parsing with reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "amr parsing as sequence to graph transduction")
  Member "hlt suda at semeval 2019 task 1 ucca graph parsing as constituent tree parsing":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "made for each other broad coverage semantic structures meet preposition supersenses")
  Member "learning joint semantic parsers from disjoint data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "text generation with exemplar based adaptive decoding")
  Member "multitask parsing across semantic representations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sequence labeling parsing by learning across representations")
  Member "bert pre training of deep bidirectional transformers for language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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)