190 citations · 238 across the 26 of their papers we have counts for
6 papers · 1 filter
Displacement Geometry Captures Platonic Shared Reality Across Models and Modalities
Chenming Shang, Yujin Tang, Jun Jie Ou Yang +3
The Platonic Representation Hypothesis (PRH) claims that independently trained models converge on a shared statistical model of reality, yet recent work finds only weak pointwise s…
How do World Models and Policies Compose in LLM Agents? A Joint Spectral and Behavioral Account
Ruize Xu, Xiao Yu, Yujin Tang +2
How do LLM agents come to both understand environments they act in and master tasks set within them? Through controlled experiments combining world-model training (next-state predi…
A Neural Network Solves, Explains, and Generates University Math Problems by Program Synthesis and Few-Shot Learning at Human Level
Iddo Drori, Sarah Zhang, Reece Shuttleworth +15
We demonstrate that a neural network pre-trained on text and fine-tuned on code solves mathematics course problems, explains solutions, and generates new questions at a human level…
Solving Probability and Statistics Problems by Program Synthesis
Leonard Tang, Elizabeth Ke, Nikhil Singh +2
We solve university level probability and statistics questions by program synthesis using OpenAI's Codex, a Transformer trained on text and fine-tuned on code. We transform course…
Solving Machine Learning Problems
Sunny Tran, Pranav Krishna, Ishan Pakuwal +4
Can a machine learn Machine Learning? This work trains a machine learning model to solve machine learning problems from a University undergraduate level course. We generate a new t…
Privileged Zero-Shot AutoML
Nikhil Singh, Brandon Kates, Jeff Mentch +3
This work improves the quality of automated machine learning (AutoML) systems by using dataset and function descriptions while significantly decreasing computation time from minute…