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 "translationese as a language in multilingual nmt"):
  Abstract: Machine translation has an undesirable propensity to produce "translationese" artifacts, which can lead to higher BLEU scores while being liked less by human raters. Motivated by this, we model translationese and original (i.e. natural) text as separate languages in a multilingual model, and pose the question: can we perform zero-shot translation between original source text and original target text? There is no data with original source and original target, so we train sentence-level classifiers to distinguish translationese from original target text, and use this classifier to tag the training data for an NMT model. Using this technique we bias the model to produce more natural outputs at test time, yielding gains in human evaluation scores on both accuracy and fluency. Additionally, we demonstrate that it is possible to bias the model to produce translationese and game the BLEU score, increasing it while decreasing human-rated quality. We analyze these models using metrics to measure the degree of translationese in the output, and present an analysis of the capriciousness of heuristically-based train-data tagging.

Includes members:
  Member "post editese an exacerbated translationese":
    also connected through other hyperedges:
      (none)
  Member "tagged back translation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "tag less back translation")
  Member "the effect of translationese in machine translation test sets":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the evaluation of machine translation systems trained with back translation")
  Member "ape at scale and its implications on mt evaluation biases":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "domain translationese and noise in synthetic data for neural machine translation")
  Member "controlling text complexity in neural machine translation":
    also connected through other hyperedges:
      (none)
  Member "on the evaluation of machine translation systems trained with back translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "question answering is a format when is it useful")
  Member "translationese in machine translation evaluation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a survey on document level machine translation methods and evaluation")
  Member "attaining the unattainable reassessing claims of human parity in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on document level machine translation methods and evaluation")

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)