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 "phrase table as recommendation memory for neural machine translation"):
  Abstract: Neural Machine Translation (NMT) has drawn much attention due to its promising translation performance recently. However, several studies indicate that NMT often generates fluent but unfaithful translations. In this paper, we propose a method to alleviate this problem by using a phrase table as recommendation memory. The main idea is to add bonus to words worthy of recommendation, so that NMT can make correct predictions. Specifically, we first derive a prefix tree to accommodate all the candidate target phrases by searching the phrase translation table according to the source sentence. Then, we construct a recommendation word set by matching between candidate target phrases and previously translated target words by NMT. After that, we determine the specific bonus value for each recommendable word by using the attention vector and phrase translation probability. Finally, we integrate this bonus value into NMT to improve the translation results. The extensive experiments demonstrate that the proposed methods obtain remarkable improvements over the strong attentionbased NMT.

Includes members:
  Member "translating phrases in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi granularity self attention for neural machine translation")
  Member "memory augmented neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "memory attended recurrent network for video captioning")
  Member "neural machine translation advised by statistical machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cued wmt19 ewc lms")
  Member "is neural machine translation ready for deployment a case study on 30 translation directions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cued wmt19 ewc lms")
  Member "implicit distortion and fertility models for attention based encoder decoder nmt model":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "controlling utterance length in nmt based word segmentation with attention")
  Member "bridging neural machine translation and bilingual dictionaries":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "neural machine translation with noisy lexical constraints")
  Member "vocabulary manipulation for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sequence generation from both sides to the middle")
  Member "a coverage embedding model for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "apply chinese radicals into neural machine translation deeper than character level")

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)