2 citations · 4 across the 7 of their papers we have counts for
7 papers
Planning in the Dark: LLM-Symbolic Planning Pipeline without Experts
Sukai Huang, Nir Lipovetzky, Trevor Cohn
Large Language Models (LLMs) have shown promise in solving natural language-described planning tasks, but their direct use often leads to inconsistent reasoning and hallucination.…
Human Goal Recognition as Bayesian Inference: Investigating the Impact of Actions, Timing, and Goal Solvability
Chenyuan Zhang, Charles Kemp, Nir Lipovetzky
Goal recognition is a fundamental cognitive process that enables individuals to infer intentions based on available cues. Current goal recognition algorithms often take only observ…
Generalized Planning for the Abstraction and Reasoning Corpus
Chao Lei, Nir Lipovetzky, Krista A. Ehinger
The Abstraction and Reasoning Corpus (ARC) is a general artificial intelligence benchmark that poses difficulties for pure machine learning methods due to its requirement for fluid…
Data-Driven Goal Recognition in Transhumeral Prostheses Using Process Mining Techniques
Zihang Su, Tianshi Yu, Nir Lipovetzky +6
A transhumeral prosthesis restores missing anatomical segments below the shoulder, including the hand. Active prostheses utilize real-valued, continuous sensor data to recognize pa…
Diverse, Top-k, and Top-Quality Planning Over Simulators
Lyndon Benke, Tim Miller, Michael Papasimeon +1
Diverse, top-k, and top-quality planning are concerned with the generation of sets of solutions to sequential decision problems. Previously this area has been the domain of classic…
Lifted Sequential Planning with Lazy Constraint Generation Solvers
Anubhav Singh, Miquel Ramirez, Nir Lipovetzky +1
This paper studies the possibilities made open by the use of Lazy Clause Generation (LCG) based approaches to Constraint Programming (CP) for tackling sequential classical planning…