Christopher Wang retweeted
Can “chicken” make a base model reason? 🐔
Yes!
Why? With the right first tokens, base models can match RL in reasoning. We trace this to learned training data associations and use a simple data edit to make “chicken” elicit reasoning too.
blog: sophielwang.com/cues
Christopher Wang retweeted
There is a new kind of robotics called "Vibe Robotics"
It's when you ask agents for fully functioning embodied agents (both hardware and software) that must solve a given task in physically grounded environments.
We build an evaluation to test how good agents (frontier models) are at "Vibe Robotics".
Website: artifactarena.ai/
Want to scale models on brain datasets recorded with variable sensor layouts?
Population Transformer at #ICLR2025 may be your answer!
🗺️ Fri, Apr 25 | 10am - 12:30pm (poster @ Hall 3 + Hall 2B #58)
🗣️ Fri, Apr 25 | 4:06 pm - 4:18 pm (oral @ Garnet 216-218)
More ⬇️
The Population Transformer is a pretrained approach for aggregating electrode data that scales across experiments, subjects, and datasets.
📍 Poster: iclr.cc/virtual/2025/poster/…
🔗 Project: glchau.github.io/population-…
💻 Code: github.com/czlwang/Populatio…
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