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This section discusses overfitting in prompt optimization, noting that while training accuracies may exceed test accuracies, they can still yield effective results if solutions overfit similarly. We compare our OPRO approach with EvoPrompt's Genetic Algorithm and Differential Evolution methods, revealing that OPRO's use of optimization trajectories and exemplars leads to more stable and effective prompt performance across benchmarks like GSM8K and BBH sports understanding.

This article presents findings from our ablation studies using text-bison and PaLM 2-L to optimize prompt performance. Key insights include the impact of instruction order, the importance of exemplars, and the effects of initial instructions on optimization stability and accuracy in math and sports understanding tasks. Our results indicate that carefully crafted meta-prompts significantly enhance model performance.

This section discusses prompt optimization results on GSM8K and BBH tasks, showing significant improvements in training accuracy through various instructions. It emphasizes the importance of nuanced instruction variations and the transferability of optimized prompts across different math reasoning benchmarks.

OPRO enhances LLM performance in tasks like GSM8K and BBH by optimizing instructions using models like PaLM 2-L and GPT-4. Experiments reveal improved transferability of optimized instructions across mathematical reasoning datasets.

Meta-prompt design for LLM optimization involves using training examples, tracking optimization trajectory with past instructions, and adding meta-instructions to guide the model in generating effective, task-specific prompts.

OPRO is applied to prompt optimization for natural language tasks, where the goal is to maximize task accuracy. The process uses small training samples and involves two LLMs: the optimizer (which generates the prompt) and the scorer (which evaluates the output). Different positions for inserting instructions into prompts are explored to enhance performance.

The Traveling Salesman Problem (TSP) was tackled using LLMs, starting with five random solutions and generating up to eight new solutions at each step. While LLMs achieved optimal solutions for small instances (n = 10), their performance declined with larger problem sizes compared to heuristics. OPRO's limitations include context window constraints and challenges in navigating complex optimization landscapes.

We first demonstrate the potential of LLMs in serving as optimizers for mathematical optimization. In particular, we present a case study on linear regression as an example of continuous optimization, and on the Traveling Salesman Problem (TSP) as an example of discrete optimization. On both tasks, we see LLMs properly capture the optimization directions on small-scale problems merely based on the past optimization trajectory...

Meta-prompt design involves describing optimization problems and leveraging past solutions to guide LLMs. By managing stability and the exploration-exploitation trade-off, LLMs generate improved solutions.

The OPRO framework uses LLMs as optimizers, generating new solutions in iterative steps. By leveraging natural language descriptions and balancing exploration with exploitation, it maximizes performance across optimization tasks.

This paper introduces Optimization by PROmpting (OPRO), a method using large language models (LLMs) to solve optimization problems. OPRO enhances prompt-based tasks by iteratively generating solutions, achieving up to 50% accuracy improvement in benchmarks compared to human-designed prompts.

Docker is an open platform for developing, shipping, and running applications. Docker allows you to package and run your application as a single entity in a loosely isolated environment called a CONTAINER. Containers are lightweight and contain everything needed to run the application, so you don't need to rely on what's installed on the host.

Everything starts with art, and it goes with us further; it is woven into everything we do since through it, we show everything that is within us.

By default, CloudWatch does not provide any memory metrics, but by a simple YAML configuration provided in the article, it's possible to add them to CloudWatch monitoring dashboard.

Alex Wick is the founder and CEO of Cascadia Carbon, a public benefit corporation which is dedicated to building a verifiable offset database of individual, geotagged trees.

Mikhail Tsyrulnikov is a seasoned gametech entrepreneur with over 16 years of experience in the gaming and e-commerce industries, and the founder and CEO of Gameray. Before Gameray, Tsyrulnikov was responsible for spearheading the development and successful launch of an updated e-commerce platform for one of the largest electronic retailers in Eastern Europe. This initiative resulted in a notable 10% surge in conversion rates....

How are you, hacker? 🪐Want to know what's trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. From Clicks to Value: TapSwap's Sustainable Approach to Tap-to-Earn By @tapswapai [ 4 Min read ] The "Play-Generate Value-E...

Learning in public has to do with sharing your learning journey, openly documenting your experiences, and engaging with the community.

Webcrumbs Frontend AI is an open-source tool for front-end coding. It uses artificial intelligence to generate code components directly from images or text descriptions. You can describe any UI element, or even upload a visual reference, and Webcrumbs instantly transforms that into React, Vue, Svelte or even HTML.

When you're just starting out in the SaaS space, it's hard to know who to trust or what advice to follow. Here are some tips that can help you cut through all that noise. Follow people with real skin in the game: Don't waste your time on people who haven't built something real.

Discover why software architecture matters, key concepts like cohesion and coupling, and how to build scalable, maintainable projects in React, Vue, Svelte.

The article "The Double-Edged Sword of AI in Education" delves into the ethical and psychological challenges of integrating AI into children's education. It highlights the risks posed by conversational agents designed for adults, which can expose children to inappropriate content and disrupt their cognitive development. Through role-playing games and linguistic interactions, these AI tools may allow children to bypass parental and educational boundaries, hindering...

The #OptOut Writing Contest is closing soon! Submit your entries on decentralization for a chance to win from a $6,000 prize pool before the October 9, 2024 deadline. Compete in themes like "Create Your Own Standard" and "Break Ties with the Status Quo" to make your voice heard!

My tool called Basefront - basefront.app is within the Airtable space (it's a tool to create directories, galleries and job boards with airtable data that you can integrate on any site) and I had already built up an audience in this space.