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 "a new dataset and model for learning to understand navigational instructions"):
  Abstract: In this paper, we present a state-of-the-art model and introduce a new dataset for grounded language learning. Our goal is to develop a model that can learn to follow new instructions given prior instruction-perception-action examples. We based our work on the SAIL dataset which consists of navigational instructions and actions in a maze-like environment. The new model we propose achieves the best results to date on the SAIL dataset by using an improved perceptual component that can represent relative positions of objects. We also analyze the problems with the SAIL dataset regarding its size and balance. We argue that performance on a small, fixed-size dataset is no longer a good measure to differentiate state-of-the-art models. We introduce SAILx, a synthetic dataset generator, and perform experiments where the size and balance of the dataset are controlled.

Includes members:
  Member "a deep compositional framework for human like language acquisition in virtual environment":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "meta reinforcement learning with autonomous inference of subtask dependencies")
  Member "gated attention architectures for task oriented language grounding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "language as a cognitive tool to imagine goals in curiosity driven exploration")
  Member "shapeworld a new test methodology for multimodal language understanding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a benchmark for systematic generalization in grounded language understanding")
  Member "deep learning evaluation using deep linguistic processing":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a comparative analysis of knowledge intensive and data intensive semantic parsers")
  Member "grounded language learning in a simulated 3d world":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exploiting language instructions for interpretable and compositional reinforcement learning")
  Member "vizdoom a doom based ai research platform for visual reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the sensory commutativity of action sequences for embodied agents")
  Member "analyzing the behavior of visual question answering models":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "grad cam visual explanations from deep networks via gradient based localization")
  Member "virtual embodiment a scalable long term strategy for artificial intelligence research":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "learning to speak and act in a fantasy text adventure game")

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)