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 "how to do simultaneous translation better with consecutive neural machine translation"):
  Abstract: Despite the success of neural machine translation (NMT), simultaneous neural machine translation (SNMT), the task of translating in real time before a full sentence has been observed, remains challenging due to the syntactic structure difference and simultaneity requirements. In this paper, we propose a general framework to improve simultaneous translation with a pretrained consecutive neural machine translation (CNMT) model. Our framework contains two parts: prefix translation that utilizes a pretrained CNMT model to better translate source prefixes and a stopping criterion that determines when to stop the prefix translation. Experiments on three translation corpora and two language pairs show the efficacy of the proposed framework on balancing the quality and latency in simultaneous translation.

Includes members:
  Member "monotonic infinite lookback attention for simultaneous machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "controlling computation versus quality for neural sequence models")
  Member "simpler and faster learning of adaptive policies for simultaneous translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "learning coupled policies for simultaneous machine translation")
  Member "incremental decoding and training methods for simultaneous translation in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning coupled policies for simultaneous machine translation")
  Member "stacl simultaneous translation with integrated anticipation and controllable latency":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "dutongchuan context aware translation model for simultaneous interpreting")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "convolutional sequence to sequence learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "learning to translate in real time with neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "plug and play language models a simple approach to controlled text generation")
  Member "can neural machine translation do simultaneous translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "dutongchuan context aware translation model for simultaneous interpreting")

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)