Researchers at Princeton University have published a paper titled 'AI Agents That Matter,' highlighting the need to incorporate cost into AI agent evaluation and optimization. The paper emphasizes the importance of not solely focusing on accuracy but also considering cost in benchmarking AI agents.
AI agents are an exciting new research direction. But today's evaluations encourage agents that are better at benchmarks than the real world. How can we fix this? In our new paper, we recommend five steps to build AI agents that matter. Paper: https://t.co/WWosvf0VpO https://t.co/JlKCXAwci2
cool paper that considers the accuracy-cost tradeoff for AI agents (finally!). so much work to do in benchmarking and cost-aware search techniques. https://t.co/4FOGQFjgGG
[LG] AI Agents That Matter S Kapoor, B Stroebl, Z S. Siegel, N Nadgir, A Narayanan [Princeton University] (2024) https://t.co/rIxJqyiY3e - Current AI agent evaluations focus narrowly on maximizing accuracy, neglecting other important metrics like cost. This leads to… https://t.co/ie61c864qj
📢New paper: AI Agents That Matter Summary: we find pervasive shortcomings in the state of AI agent evaluation. We show how to incorporate cost into agent evaluation and optimization. We also show the importance of being precise about what a benchmark aims to measure and ensuring… https://t.co/fCD8T4u8lL
AI Agents That Matter Kapoor et al.: https://t.co/5pK0vMYzaM #ArtificialIntelligence #DeepLearning #MachineLearning https://t.co/H2m3NeKqrm
AI Agents that Matter: Evaluating & Benchmarking AI Agents - Paper from researchers at Princetin Uni https://t.co/29Y97sB4Pa
AI Agents That Matter abs: https://t.co/ZatxaK3VUW Performs a careful analysis of existing benchmarks, analyzing across additional axes like cost, proposes new baselines 1. AI agent evaluations must be cost-controlled 2. Jointly optimizing accuracy and cost can yield better… https://t.co/pjtIpRKhCF