Understanding the Capabilities of Large Language Models for Automated Planning

25 May 2023

Papers citing "Understanding the Capabilities of Large Language Models for Automated Planning"

6 / 6 papers shown

Title
Neurosymbolic AI for Enhancing Instructability in Generative AI Amit P. Sheth Vishal Pallagani Kaushik Roy LLMAG 21 2 0 26 Jul 2024
Unlocking Large Language Model's Planning Capabilities with Maximum Diversity Fine-tuning Wenjun Li Changyu Chen Pradeep Varakantham 40 2 0 15 Jun 2024
Open-Endedness is Essential for Artificial Superhuman Intelligence Edward Hughes Michael Dennis Jack Parker-Holder Feryal M. P. Behbahani Aditi Mavalankar Yuge Shi Tom Schaul Tim Rocktaschel LRM 32 18 0 06 Jun 2024
ProgPrompt: Generating Situated Robot Task Plans using Large Language Models Ishika Singh Valts Blukis Arsalan Mousavian Ankit Goyal Danfei Xu Jonathan Tremblay D. Fox Jesse Thomason Animesh Garg LM&Ro LLMAG 112 619 0 22 Sep 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,881 0 04 Mar 2022
CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation Yue Wang Weishi Wang Shafiq R. Joty S. Hoi 210 1,485 0 02 Sep 2021