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 "multi sense definition modeling using word sense decompositions"):
  Abstract: Word embeddings capture syntactic and semantic information about words. Definition modeling aims to make the semantic content in each embedding explicit, by outputting a natural language definition based on the embedding. However, existing definition models are limited in their ability to generate accurate definitions for different senses of the same word. In this paper, we introduce a new method that enables definition modeling for multiple senses. We show how a Gumble-Softmax approach outperforms baselines at matching sense-specific embeddings to definitions during training. In experiments, our multi-sense definition model improves recall over a state-of-the-art single-sense definition model by a factor of three, without harming precision.

Includes members:
  Member "incorporating sememes into chinese definition modeling":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "mark my word a sequence to sequence approach to definition modeling")
  Member "conditional generators of words definitions":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "probing for semantic classes diagnosing the meaning content of word embeddings")
  Member "a mixture model for learning multi sense word embeddings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "bertscore evaluating text generation with bert")
  Member "learning to explain non standard english words and phrases":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "learning to decipher hate symbols")
  Member "de conflated semantic representations":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "using multi sense vector embeddings for reverse dictionaries")
  Member "definition modeling learning to define word embeddings in natural language":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "probing for semantic classes diagnosing the meaning content of word embeddings")
  Member "linear algebraic structure of word senses with applications to polysemy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "secnlp a survey of embeddings in clinical natural language processing")
  Member "dynamic memory networks for visual and textual question answering":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "component analysis for visual question answering architectures")

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)