Excited to share our work on disentangled/abstract representations, to appear at
#ICLR2025 (
@iclr_conf)!
We mathematically prove and experimentally demonstrate that multi-task learning leads to disentangled representations, and propose a unifying mechanism for generalization in brains and machines: parallel processing (π§΅ paper below)
Our work connects to the Platonic representation hypothesis, suggests why alignment across models/organisms can occur, and shows why transformers excel at constructing world models π€π