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 "align and copy uzh at sigmorphon 2017 shared task for morphological reinflection"):
  Abstract: This paper presents the submissions by the University of Zurich to the SIGMORPHON 2017 shared task on morphological reinflection. The task is to predict the inflected form given a lemma and a set of morpho-syntactic features. We focus on neural network approaches that can tackle the task in a limited-resource setting. As the transduction of the lemma into the inflected form is dominated by copying over lemma characters, we propose two recurrent neural network architectures with hard monotonic attention that are strong at copying and, yet, substantially different in how they achieve this. The first approach is an encoder-decoder model with a copy mechanism. The second approach is a neural state-transition system over a set of explicit edit actions, including a designated COPY action. We experiment with character alignment and find that naive, greedy alignment consistently produces strong results for some languages. Our best system combination is the overall winner of the SIGMORPHON 2017 Shared Task 1 without external resources. At a setting with 100 training samples, both our approaches, as ensembles of models, outperform the next best competitor.

Includes members:
  Member "get to the point summarization with pointer generator networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mast a memory augmented self supervised tracker")
  Member "incorporating copying mechanism in sequence to sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "single model encoder decoder with explicit morphological representation for reinflection":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the conll sigmorphon 2018 shared task universal morphological reinflection")
  Member "neural architectures for named entity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowledge graphs")
  Member "transition based dependency parsing with stack long short term memory":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "improving entity linking by modeling latent entity type information")
  Member "learning to transduce with unbounded memory":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "encoding based memory modules for recurrent neural networks")
  Member "neural machine translation by jointly learning to align and translate":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "chameleon a deep learning meta architecture for news recommender systems phd thesis")

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)