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 "dynamic past and future for neural machine translation"):
  Abstract: Previous studies have shown that neural machine translation (NMT) models can benefit from explicitly modeling translated (Past) and untranslated (Future) to groups of translated and untranslated contents through parts-to-wholes assignment. The assignment is learned through a novel variant of routing-by-agreement mechanism (Sabour et al., 2017), namely {\em Guided Dynamic Routing}, where the translating status at each decoding step {\em guides} the routing process to assign each source word to its associated group (i.e., translated or untranslated content) represented by a capsule, enabling translation to be made from holistic context. Experiments show that our approach achieves substantial improvements over both RNMT and Transformer by producing more adequate translations. Extensive analysis demonstrates that our method is highly interpretable, which is able to recognize the translated and untranslated contents as expected.

Includes members:
  Member "synchronous bidirectional neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "blank language models")
  Member "dynamic layer aggregation for neural machine translation with routing by agreement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "atloc attention guided camera localization")
  Member "information aggregation for multi head attention with routing by agreement":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "assessing the ability of self attention networks to learn word order")
  Member "neural machine translation with adequacy oriented learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "context aware self attention networks")
  Member "deconvolution based global decoding for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "gret global representation enhanced transformer")
  Member "asynchronous bidirectional decoding for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "pseudo bidirectional decoding for local sequence transduction")
  Member "investigating capsule networks with dynamic routing for text classification":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gret global representation enhanced transformer")
  Member "information aggregation via dynamic routing for sequence encoding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "detecting fake news with capsule neural networks")

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)