π¨ New paper!
π MENLO: From Preferences to Proficiency
We introduce a framework + dataset for evaluating and modeling native-like LLM response quality across 47 languages, inspired by audience design principles.
π Paper: https://t.co/n8Z2cDJm5a
π€ Data: https://t.co/fzM6Um32nD
π§΅Details π
Reading public ICLR reviews, it's obvious that ChatGPT was used by a good number of reviewers :)
I think it's time to start prompt injecting papers. Add some white colored text to tell LLMs to give it a perfect score. Better prompt engineering means better chances of acceptance.
@zuhayeer So a whole stream of prompt injection attacks are now coming into play to recover the original prompt / RAG in deployed systems... this is gonna be interesting!
After a year of heavy R&D, Beam AI V1 has achieved 2x better accuracy while running 6x faster on iPhone devices. Stay tuned for our V2 - that one is gonna be even bigger!
The review process at every conference/journal is also meant to provide constructive feedback to the authors on how to improve their submissions. Simply saying "not convinced enough" is quite poor. I expected more from fellow reviewers!
Well well well! Beam AI Lite is out on App Store. Our app enables users to monitor their stress, HRV, and pulse just through the selfie camera! Check it out: https://t.co/al2wsnWhF4
Working on a startup means you will do what your customers, and in turn your product, demand!
I have spent the past 2 weeks doing Metal programming and parallelizing our core algorithms to achieve higher FPS on the iPhone. And I went to grad school for ML to avoid systems...
Fashionably late ;) My thesis presentation on "On Label-Efficient Computer Vision: Building Fast and Effective Few-Shot Image Classifiers" is now on YouTube! Check it out at https://t.co/v4zaoZSAS5!
For a PDF copy of my graduate thesis, "On Label-Efficient Computer Vision: Building Fast and Effective Few-Shot Image Classifiers", please visit https://t.co/SN83XOdwK4.
Fashionably late ;) My thesis presentation on "On Label-Efficient Computer Vision: Building Fast and Effective Few-Shot Image Classifiers" is now on YouTube! Check it out at https://t.co/v4zaoZSAS5!