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 "compare mt a tool for holistic comparison of language generation systems"):
  Abstract: In this paper, we describe compare-mt, a tool for holistic analysis and comparison of the results of systems for language generation tasks such as machine translation. The main goal of the tool is to give the user a high-level and coherent view of the salient differences between systems that can then be used to guide further analysis or system improvement. It implements a number of tools to do so, such as analysis of accuracy of generation of particular types of words, bucketed histograms of sentence accuracies or counts based on salient characteristics, and extraction of characteristic $n$-grams for each system. It also has a number of advanced features such as use of linguistic labels, source side data, or comparison of log likelihoods for probabilistic models, and also aims to be easily extensible by users to new types of analysis. The code is available at this https URL

Includes members:
  Member "von mises fisher loss for training sequence to sequence models with continuous outputs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "directional deep embedding and appearance learning for fast video object segmentation")
  Member "a tree based decoder for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unsupervised program synthesis for images using tree structured lstm")
  Member "parameter sharing methods for multilingual self attentional translation models":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "when and why are pre trained word embeddings useful for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "distill adapt distill training small in domain models for neural machine translation")
  Member "rapid adaptation of neural machine translation to new languages":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "mtnt a testbed for machine translation of noisy text":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "findings of the first shared task on machine translation robustness")
  Member "a large scale test set for the evaluation of context aware pronoun translation in neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "toward making the most of context in neural machine translation")
  Member "a challenge set approach to evaluating machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "stance detection benchmark how robust is your stance detection")

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)