Solving Wordle with uv's dependency resolver (mildbyte.xyz)
74 points by mildbyte 1d ago 11 comments
A non-anthropomorphized view of LLMs (addxorrol.blogspot.com)
357 points by zdw 19h ago 313 comments
Pure-vision browser agent scores 94% on WebVoyager (SOTA)
1 anerli 1 7/7/2025, 6:07:39 PM github.com ↗
You can view the entire run here: https://magnitude-webvoyager.vercel.app/
The original WebVoyager benchmark was meant to demonstrate a new technique for interacting with the browser by annotating the DOM. Since then, vision models have come a long way in terms of accuracy and visual understanding. Our pure-vision approach with our framework and today's models surpasses the hybrid DOM strategies used by the original WebVoyager paper and other agents like browser-use.
So why does pure-vision beat hybrid DOM approaches?
- Generalizes far better - handles canvas elements, iframes, drag-and-drop, precise text selection, and many other scenarios elegantly where hybrid DOM would struggle and need to implement hacks for those cases to work
- Easier for the LLM - we think LLM performance is roughly proportional to prompt clarity. If the prompt contains a crowded screenshot with loads of colored boxes + a long list of element labels and is asked to pick one, vs given a clean screenshot + where do you want to click - the latter seems far easier
We believe another reason for our success is that we can still hook into the browser as needed. We can use browser-native actions like tab switching, can look at network traffic to know when a page is ready, or use the DOM for other purposes like data extraction. Computer use agents like Operator or Claude Computer Use on the other hand are limited to generic mouse and keyboard controls.
It's worth mentioning that WebVoyager is a strange and flawed benchmark. It contains many tasks that depend on the current date (and need their dates updated), tasks that depend on the time of day, and some tasks that are impossible or too ambiguous to properly evaluate. In the repo we detailed exactly the patches we made to the original WebVoyager benchmark such that each task is at least theoretically possible.
Why does this all matter? People are trying to adopt agents for real use cases, but they often fail to make it to production. We want to enable developers to build with production-ready browser agents - which is why it's important to get the fundamental interaction paradigm right. We think this benchmark is a step in the right direction, showing that pure-vision has best-in-class performance in the browser domain. Curious to hear what others think about this, would love to get your feedback!