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.
A Platform and Dataset to Benchmark Large Language Models on Linux Kernel Crash Resolution
Neural Information Processing Systems
Large Language Models (LLMs) are consistently improving at increasingly realistic software engineering (SE) tasks.
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Language-Driven Interactive Traffic Trajectory Generation
Neural Information Processing Systems
In this work, we propose InteractTraj, the first language-driven traffic trajectory generator that can generate interactive traffic trajectories.
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Point Cloud Matters: Rethinking the Impact of Different Observation Spaces on Robot Learning
Neural Information Processing Systems
In this study, we explore the influence of various observation spaces on robot learning, focusing on three predominant modalities: RGB, RGB-D, and point cloud.
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