Does the coordinated pass@k policy optimization proposed in Cast a Wider Net improve diversity of generated co

Abstract

Abstract: Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate network architecture, gradient-based learning algorithms can be used to synthesize a complex decision surface that can classify high-dimensional patterns, such as handwritten characters, with minimal preprocessing. This paper reviews various methods applied to handwritten character recognition and compares them on a standard handwritten digit recognition task. Convolutional neural networks, which are specifically designed to

Research Question

Does the coordinated pass@k policy optimization proposed in Cast a Wider Net improve diversity of generated code reasoning paths for multimodal LLMs on visual programming tasks, as measured by distinct solution count and functional correctness?

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