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 "ur funny a multimodal language dataset for understanding humor"):
  Abstract: Humor is a unique and creative communicative behavior displayed during social interactions. It is produced in a multimodal manner, through the usage of words (text), gestures (vision) and prosodic cues (acoustic). Understanding humor from these three modalities falls within boundaries of multimodal language; a recent research trend in natural language processing that models natural language as it happens in face-to-face communication. Although humor detection is an established research area in NLP, in a multimodal context it is an understudied area. This paper presents a diverse multimodal dataset, called UR-FUNNY, to open the door to understanding multimodal language used in expressing humor. The dataset and accompanying studies, present a framework in multimodal humor detection for the natural language processing community. UR-FUNNY is publicly available for research.

Includes members:
  Member "joint robust voicing detection and pitch estimation based on residual harmonics":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "factorized multimodal transformer for multimodal sequential learning")
  Member "detection of glottal closure instants from speech signals a quantitative review":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "factorized multimodal transformer for multimodal sequential learning")
  Member "multimodal language analysis with recurrent multistage fusion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on emergent communication in competitive multi agent teams")
  Member "meld a multimodal multi party dataset for emotion recognition in conversations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "knowledge enriched transformer for emotion detection in textual conversations")
  Member "modality based factorization for multimodal fusion":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "m bert injecting multimodal information in the bert structure")
  Member "found in translation learning robust joint representations by cyclic translations between modalities":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "diverse and admissible trajectory forecasting through multimodal context understanding")
  Member "efficient low rank multimodal fusion with modality specific factors":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "h owan multi distorted image restoration with tensor 1x1 convolution")
  Member "words can shift dynamically adjusting word representations using nonverbal behaviors":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "can we read speech beyond the lips rethinking roi selection for deep visual speech recognition")

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.LG(Machine Learning)