PIGLeT: Language Grounding Through Neuro-Symbolic Interaction in a 3D World
Rowan Zellers♠ Ari Holtzman♠ Matthew Peters♡ Roozbeh Mottaghi♡ Aniruddha Kembhavi♡ Ali Farhadi♠ Yejin Choi♠♡ ♠Paul G. Allen School of Computer Science、Engineering, University of Washington ♡Allen Institute for Artificial Intelligence https://rowanzellers.com/piglet
Abstract
We propose PIGLeT: a model that learns physical commonsense knowledge through interaction, and then uses this knowledge to ground language. We factorize PIGLeT into a physical dynamics model, and a separate language model. Our dynamics model learns not just what objects are but also what they do: glass cups break when thrown, plastic ones don’t. We then use it as the interface to our language model, giving us a unified model of linguistic form and grounded meaning. PIGLeT can read a sentence, simulate neurally what might happen next, and then communicate that result through a literal symbolic representation, or natural language.
原文 arXiv:2106.00188;中英对照 + 大白话阅读 https://aha.fim.ai/paper/2106.00188v2