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 "what gets echoed understanding the pointers in explanations of persuasive arguments"):
  Abstract: Explanations are central to everyday life, and are a topic of growing interest in the AI community. To investigate the process of providing natural language explanations, we leverage the dynamics of the /r/ChangeMyView subreddit to build a dataset with 36K naturally occurring explanations of why an argument is persuasive. We propose a novel word-level prediction task to investigate how explanations selectively reuse, or echo, information from what is being explained (henceforth, explanandum). We develop features to capture the properties of a word in the explanandum, and show that our proposed features not only have relatively strong predictive power on the echoing of a word in an explanation, but also enhance neural methods of generating explanations. In particular, while the non-contextual properties of a word itself are more valuable for stopwords, the interaction between the constituent parts of an explanandum is crucial in predicting the echoing of content words. We also find intriguing patterns of a word being echoed. For example, although nouns are generally less likely to be echoed, subjects and objects can, depending on their source, be more likely to be echoed in the explanations.

Includes members:
  Member "on human predictions with explanations and predictions of machine learning models a case study on deception detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "questioning the ai informing design practices for explainable ai user experiences")
  Member "rating reliability and bias in news articles does ai assistance help everyone":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "why is chicago deceptive towards building model driven tutorials for humans")
  Member "explain yourself leveraging language models for commonsense reasoning":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "learning from explanations with neural execution tree")
  Member "exploring the role of prior beliefs for argument persuasion":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "determining relative argument specificity and stance for complex argumentative structures")
  Member "e snli natural language inference with natural language explanations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "learning from explanations with neural execution tree")
  Member "you are no jack kennedy on media selection of highlights from presidential debates":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "no permanent friends or enemies tracking relationships between nations from news")
  Member "explanation in artificial intelligence insights from the social sciences":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "causal interpretability for machine learning problems methods and evaluation")
  Member "opennmt open source toolkit for neural machine translation":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "prophetnet predicting future n gram for sequence to sequence pre training")

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)