4 citations · 6 across the 9 of their papers we have counts for
3 papers · 1 filter
Frontier Large Language Models Rival State-of-the-Art Planners
Augusto B. Corrêa, André G. Pereira, Jendrik Seipp
A series of influential studies established that large language models cannot reliably solve even simple planning tasks. We show that the latest generation of frontier models overt…
Symmetry-Aware Transformer Training for Automated Planning
Markus Fritzsche, Elliot Gestrin, Jendrik Seipp
While transformers excel in many settings, their application in the field of automated planning is limited. Prior work like PlanGPT, a state-of-the-art decoder-only transformer, st…
Classical Planning with LLM-Generated Heuristics: Challenging the State of the Art with Python Code
Augusto B. Corrêa, André G. Pereira, Jendrik Seipp
In recent years, large language models (LLMs) have shown remarkable capabilities in various artificial intelligence problems. However, they fail to plan reliably, even when prompte…