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 "speculative beam search for simultaneous translation"):
  Abstract: Beam search is universally used in full-sentence translation but its application to simultaneous translation remains non-trivial, where output words are committed on the fly. In particular, the recently proposed wait-k policy (Ma et al., 2019a) is a simple and effective method that (after an initial wait) commits one output word on receiving each input word, making beam search seemingly impossible. To address this challenge, we propose a speculative beam search algorithm that hallucinates several steps into the future in order to reach a more accurate decision, implicitly benefiting from a target language model. This makes beam search applicable for the first time to the generation of a single word in each step. Experiments over diverse language pairs show large improvements over previous work.

Includes members:
  Member "simultaneous translation with flexible policy via restricted imitation learning":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "learning coupled policies for simultaneous machine translation")
  Member "monotonic infinite lookback attention for simultaneous machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (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-3 (induced by source paper "learning coupled policies for simultaneous machine translation")
  Member "learning to stop in structured prediction for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "simultaneous translation with flexible policy via restricted imitation learning")
  Member "incremental decoding and training methods for simultaneous translation in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning coupled policies for simultaneous machine translation")
  Member "correcting length bias in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "consistency of a recurrent language model with respect to incomplete decoding")
  Member "when to finish optimal beam search for neural text generation modulo beam size":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "robust machine translation with domain sensitive pseudo sources baidu osu wmt19 mt robustness shared task system report")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")

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)