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 "situated mapping of sequential instructions to actions with single step reward observation"):
  Abstract: We propose a learning approach for mapping context-dependent sequential instructions to actions. We address the problem of discourse and state dependencies with an attention-based model that considers both the history of the interaction and the state of the world. To train from start and goal states without access to demonstrations, we propose SESTRA, a learning algorithm that takes advantage of single-step reward observations and immediate expected reward maximization. We evaluate on the SCONE domains, and show absolute accuracy improvements of 9.8%-25.3% across the domains over approaches that use high-level logical representations.

Includes members:
  Member "learning to map context dependent sentences to executable formal queries":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "how far are we from effective context modeling an exploratory study on semantic parsing in context")
  Member "from language to programs bridging reinforcement learning and maximum marginal likelihood":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "why build an assistant in minecraft")
  Member "source target inference models for spatial instruction understanding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "improving natural language interaction with robots using advice")
  Member "mapping instructions and visual observations to actions with reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards learning a generic agent for vision and language navigation via pre training")
  Member "learning interpretable spatial operations in a rich 3d blocks world":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "why build an assistant in minecraft")
  Member "neural symbolic machines learning semantic parsers on freebase with weak supervision":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "recent advances and challenges in task oriented dialog system")
  Member "simpler context dependent logical forms via model projections":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "how far are we from effective context modeling an exploratory study on semantic parsing in context")
  Member "listen attend and walk neural mapping of navigational instructions to action sequences":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "linguistic generalization and compositionality in modern artificial neural networks")

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)