We calculate the agreement of human judgment and our automatic evaluation (i.e., ConvBenchEval()) and find it reaches 81.83% (seeing Table 3 - 6 for detailed agreement of each turn of overall). It demonstrates the effectiveness of ConvBenchEval(), which uses ChatGPT. The agreement between ChatGPT and GPT4 is very high at 87.38%. It demonstrates that using different LLMs as judges slightly influences the evaluation results. ConvBenchEval() armed with ChatGPT can is reliable and low-cost. From the above tables, we also observe that though GPT4V is expensive and can capture images, its judgment performs worse than GPT4's judgment.

Much of the promise of these models relies on learned concepts being high quality .

Environment Climate Change Antarctica has a'gravity hole' The geological oddity has existed since dinosaurs roamed the Earth. Breakthroughs, discoveries, and DIY tips sent six days a week. A "gravity hole" beneath Antarctica sounds like the plot to a bad sci-fi movie, but it's a very real situation deep beneath the Earth's surface stretching back tens of millions of years. The phenomenon thankfully isn't as apocalyptic as it sounds, either. In fact, researchers say these complex interactions between rock densities, gravitational pull, and sea levels are actually helping them understand how the southernmost continent's ice sheets evolved, and what their influences mean for the planet's climate.

In this paper, we explore two fundamental first-order algorithms in convex optimization, namely, gradient descent (GD) and proximal gradient method (ProxGD). Our focus is on making these algorithms entirely adaptive by leveraging local curvature information of smooth functions.