human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "first principle study on honeycomb fluorated inte monolayer with large rashba spin splitting and direct bandgap"
  Abstract: Abstract   Rashba effect is much related to next-generation spintronic devices. It is highly desirable to search for Rashba materials with large Rashba spin splitting, which is considered as the key factor for the application of spin field-effect transistor. Here, we design a two-dimensional monolayer of fluorated-InTe (InTeF) with large Rashba spin splitting and direct bandgap on the basis of first-principles calculations. InTeF monolayer is energetically and dynamically stable based on the calculations of cohesive energy and phonon dispersion. Remarkably, the Rashba parameter αR is about 1.08 eV·A, comparable to that of the BiTeI monolayer (1.86 eV·A). The direct bandgap is estimated to be 2.48 eV by HSE06 hybrid functional, which shows good prospects in light-emitting devices and photodetectors. To further explore the effect of substrates on the electronic structure of InTeF monolayer, we build two heterostructures, and the results show that the strength of Rashba effect and the direct bandgap nature in InTeF monolayer can be well preserved under the influence of substrates. Based on the above findings in our work, InTeF monolayer is considered to be one of the promising 2D materials for the application of spintronics as well as optoelectronics.

Connected through hyperedge HE-1 (induced by source paper "refnet a reference aware network for background based conversation"):
  with members:
    - "incremental transformer with deliberation decoder for document grounded conversations"
    - "improving neural response diversity with frequency aware cross entropy loss"
    - "conversing by reading contentful neural conversation with on demand machine reading"
    - "challenges in building intelligent open domain dialog systems"
    - "knowledge aware conversation generation with explainable reasoning on augmented graphs"
    - "improving background based conversation with context aware knowledge pre selection"
    - "learning to select knowledge for response generation in dialog systems"
    - "knowledge aware conversation generation with reasoning on augmented graph"

Question: Please tell me which class the center node 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)