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 "first person activity forecasting with online inverse reinforcement learning"):
  Abstract: We address the problem of incrementally modeling and forecasting long-term goals of a first-person camera wearer: what the user will do, where they will go, and what goal they seek. In contrast to prior work in trajectory forecasting, our algorithm, DARKO, goes further to reason about semantic states (will I pick up an object?), and future goal states that are far in terms of both space and time. DARKO learns and forecasts from first-person visual observations of the user's daily behaviors via an Online Inverse Reinforcement Learning (IRL) approach. Classical IRL discovers only the rewards in a batch setting, whereas DARKO discovers the states, transitions, rewards, and goals of a user from streaming data. Among other results, we show DARKO forecasts goals better than competing methods in both noisy and ideal settings, and our approach is theoretically and empirically no-regret.

Includes members:
  Member "social behavior prediction from first person videos":
    also connected through other hyperedges:
      (none)
  Member "a game theoretic approach to multi pedestrian activity forecasting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "social behavior prediction from first person videos")
  Member "going deeper into first person activity recognition":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "symbiotic attention with privileged information for egocentric action recognition")
  Member "learning action maps of large environments via first person vision":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "ego topo environment affordances from egocentric video")
  Member "learning to filter with predictive state inference machines":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "provably efficient imitation learning from observation alone")
  Member "you only look once unified real time object detection":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "object detection in optical remote sensing images a survey and a new benchmark")
  Member "anticipating visual representations from unlabeled video":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "learning spatiotemporal features via video and text pair discrimination")
  Member "orb slam a versatile and accurate monocular slam system":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "mvp unified motion and visual self supervised learning for large scale robotic navigation")

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.CV(Computer Vision and Pattern Recognition)