23 citations · 30 across the 5 of their papers we have counts for
5 papers
Code World Models for General Game Playing
Wolfgang Lehrach, Daniel Hennes, Miguel Lazaro-Gredilla +13
Large Language Models (LLMs) reasoning abilities are increasingly being applied to classical board and card games, but the dominant approach -- involving prompting for direct move…
Model Predictive Simulation Using Structured Graphical Models and Transformers
Xinghua Lou, Meet Dave, Shrinu Kushagra +2
We propose an approach to simulating trajectories of multiple interacting agents (road users) based on transformers and probabilistic graphical models (PGMs), and apply it to the W…
PushWorld: A benchmark for manipulation planning with tools and movable obstacles
Ken Kansky, Skanda Vaidyanath, Scott Swingle +3
While recent advances in artificial intelligence have achieved human-level performance in environments like Starcraft and Go, many physical reasoning tasks remain challenging for m…
Generative Shape Models: Joint Text Recognition and Segmentation with Very Little Training Data
Xinghua Lou, Ken Kansky, Wolfgang Lehrach +4
We demonstrate that a generative model for object shapes can achieve state of the art results on challenging scene text recognition tasks, and with orders of magnitude fewer traini…
Structured Learning from Partial Annotations
Xinghua Lou, Fred Hamprecht
Structured learning is appropriate when predicting structured outputs such as trees, graphs, or sequences. Most prior work requires the training set to consist of complete trees, g…