Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series
We develop a family of stable continuous-time neural state space-models.
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Large Language Models as Zero-Shot Human Models for Human-Robot Interaction
We explore the potential of LLMs to act as zero-shot human models for HRI. We contribute an empirical study and case studies on a simulated table-clearing task and a new robot utensil-passing experiment.
Generative Modeling with Flow-Guided Density Ratio Learning
We extend gradient flow methods to a variety of high-quality image synthesis tasks using a novel density ratio learning method.
Introducing Dr. Xie Yaqi.
Xie Yaqi successfully defended her thesis and is now Dr. Xie. Congratulations Yaqi! You can find out more about Yaqi’s work on embedding symbolic knowledg...
Translating Natural Language to Planning Goals with Large-Language Models
We contribute an empirical study into the effectiveness of LLMs, specifically GPT-3.5 variants, for the task of natural language goal translation to PDDL.
Safety-Constrained Policy Transfer with Successor Features
Transfer source policies to a target reinforcement learning task with safety constraints using Successor Features.
Heterogeneous Beliefs and Multi-Population Learning in Network Games
We introduce a model of multi-population learning with heterogenous beliefs.
