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 "automated chess commentator powered by neural chess engine"):
  Abstract: In this paper, we explore a new approach for automated chess commentary generation, which aims to generate chess commentary texts in different categories (e.g., description, comparison, planning, etc.). We introduce a neural chess engine into text generation models to help with encoding boards, predicting moves, and analyzing situations. By jointly training the neural chess engine and the generation models for different categories, the models become more effective. We conduct experiments on 5 categories in a benchmark Chess Commentary dataset and achieve inspiring results in both automatic and human evaluations.

Includes members:
  Member "press space to fire automatic video game tutorial generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mech elites illuminating the mechanic space of gvgai")
  Member "a hierarchical multi task approach for learning embeddings from semantic tasks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sbert wk a sentence embedding method by dissecting bert based word models")
  Member "generating levels that teach mechanics":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "mario level generation from mechanics using scene stitching")
  Member "order planning neural text generation from structured data":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "paraphrase generation with latent bag of words")
  Member "challenges in data to document generation":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "variational template machine for data to text generation")
  Member "story generation from sequence of independent short descriptions":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a knowledge enhanced pretraining model for commonsense story generation")
  Member "deepchess end to end deep neural network for automatic learning in chess":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "deepmimic mentor student unlabeled data based training")
  Member "effective approaches to attention based neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "attention over parameters for dialogue systems")

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)