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 "aser a large scale eventuality knowledge graph"):
  Abstract: Understanding human's language requires complex world knowledge. However, existing large-scale knowledge graphs mainly focus on knowledge about entities while ignoring knowledge about activities, states, or events, which are used to describe how entities or things act in the real world. To fill this gap, we develop ASER (activities, states, events, and their relations), a large-scale eventuality knowledge graph extracted from more than 11-billion-token unstructured textual data. ASER contains 15 relation types belonging to five categories, 194-million unique eventualities, and 64-million unique edges among them. Both human and extrinsic evaluations demonstrate the quality and effectiveness of ASER.

Includes members:
  Member "joint reasoning for temporal and causal relations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "going on a vacation takes longer than going for a walk a study of temporal commonsense understanding")
  Member "a surprisingly robust trick for the winograd schema challenge":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "superglue a stickier benchmark for general purpose language understanding systems")
  Member "sp 10k a large scale evaluation set for selectional preference acquisition":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "multiplex word embeddings for selectional preference acquisition")
  Member "how reasonable are common sense reasoning tasks a case study on the winograd schema challenge and swag":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "align mask and select a simple method for incorporating commonsense knowledge into language representation models")
  Member "a simple method for commonsense reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "minilm deep self attention distillation for task agnostic compression of pre trained transformers")
  Member "on the evaluation of common sense reasoning in natural language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "align mask and select a simple method for incorporating commonsense knowledge into language representation models")
  Member "a knowledge hunting framework for common sense reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "align mask and select a simple method for incorporating commonsense knowledge into language representation models")
  Member "deep contextualized word representations":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "multi simlex a large scale evaluation of multilingual and cross lingual lexical semantic similarity")

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.AI(Artificial Intelligence)