Deep Learning
New computational algorithms make it possible to build neural networks with many input nodes and many layers, and distinguish "deep learning" of these networks from previous work on artificial neural nets.
SSA-Seg: Semantic and Spatial Adaptive Pixel-level Classifier for Semantic Segmentation Xiaowen Ma
Neural Information Processing Systems
Visual comparison of the baseline and SSA-Seg can be found in Figure 1.
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When Y our AIs Deceive You: Challenges of Partial Observability in Reinforcement Learning from Human Feedback Leon Lang University of Amsterdam Davis Foote
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Modeling the human as Boltzmann-rational w.r.t. a belief over trajectories, we prove conditions under which RLHF is
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CausalChaos for Comprehensive Causal Action Question Answering Over Longer Causal Chains Grounded in Dynamic Visual Scenes
Neural Information Processing Systems
Understanding the intricate motivations behind human actions is paramount in developing sophisticated systems capable of nuanced behavior analysis.
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