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 "on the evaluation of semantic phenomena in neural machine translation using natural language inference"):
  Abstract: We propose a process for investigating the extent to which sentence representations arising from neural machine translation (NMT) systems encode distinct semantic phenomena. We use these representations as features to train a natural language inference (NLI) classifier based on datasets recast from existing semantic annotations. In applying this process to a representative NMT system, we find its encoder appears most suited to supporting inferences at the syntax-semantics interface, as compared to anaphora resolution requiring world-knowledge. We conclude with a discussion on the merits and potential deficiencies of the existing process, and how it may be improved and extended as a broader framework for evaluating semantic coverage.

Includes members:
  Member "hypothesis only baselines in natural language inference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "adversarial filters of dataset biases")
  Member "evaluating layers of representation in neural machine translation on part of speech and semantic tagging tasks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "linguistic knowledge and transferability of contextual representations")
  Member "analogs of linguistic structure in deep representations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "measuring compositionality in representation learning")
  Member "attention is all you need":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "using a thousand optimization tasks to learn hyperparameter search strategies")
  Member "the repeval 2017 shared task multi genre natural language inference with sentence representations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stress test evaluation of transformer based models in natural language understanding tasks")
  Member "neural machine translation and sequence to sequence models a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a brief survey of multilingual neural machine translation")
  Member "evaluating discourse phenomena 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 "paranmt 50m pushing the limits of paraphrastic sentence embeddings with millions of machine translations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "modelling latent skills for multitask language generation")

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)