A comprehensive overview of large language models

H Naveed, AU Khan, S Qiu, M Saqib, S Anwar… - arXiv preprint arXiv …, 2023 - arxiv.org
Large Language Models (LLMs) have recently demonstrated remarkable capabilities in
natural language processing tasks and beyond. This success of LLMs has led to a large …

On the prospects of incorporating large language models (llms) in automated planning and scheduling (aps)

V Pallagani, BC Muppasani, K Roy, F Fabiano… - Proceedings of the …, 2024 - ojs.aaai.org
Abstract Automated Planning and Scheduling is among the growing areas in Artificial
Intelligence (AI) where mention of LLMs has gained popularity. Based on a comprehensive …

Large language models as generalizable policies for embodied tasks

A Szot, M Schwarzer, H Agrawal… - The Twelfth …, 2023 - openreview.net
We show that large language models (LLMs) can be adapted to be generalizable policies
for embodied visual tasks. Our approach, called Large LAnguage model Reinforcement …

Scene-llm: Extending language model for 3d visual understanding and reasoning

R Fu, J Liu, X Chen, Y Nie, W Xiong - arXiv preprint arXiv:2403.11401, 2024 - arxiv.org
This paper introduces Scene-LLM, a 3D-visual-language model that enhances embodied
agents' abilities in interactive 3D indoor environments by integrating the reasoning strengths …

Language-grounded dynamic scene graphs for interactive object search with mobile manipulation

D Honerkamp, M Büchner, F Despinoy… - IEEE Robotics and …, 2024 - ieeexplore.ieee.org
To fully leverage the capabilities of mobile manipulation robots, it is imperative that they are
able to autonomously execute long-horizon tasks in large unexplored environments. While …

Language-conditioned learning for robotic manipulation: A survey

H Zhou, X Yao, Y Meng, S Sun, Z BIng, K Huang… - arXiv preprint arXiv …, 2023 - arxiv.org
Language-conditioned robotic manipulation represents a cutting-edge area of research,
enabling seamless communication and cooperation between humans and robotic agents …

Graph machine learning in the era of large language models (llms)

W Fan, S Wang, J Huang, Z Chen, Y Song… - arXiv preprint arXiv …, 2024 - arxiv.org
Graphs play an important role in representing complex relationships in various domains like
social networks, knowledge graphs, and molecular discovery. With the advent of deep …

Grid: Scene-graph-based instruction-driven robotic task planning

Z Ni, X Deng, C Tai, X Zhu, Q Xie, W Huang… - arXiv preprint arXiv …, 2023 - arxiv.org
Recent works have shown that Large Language Models (LLMs) can facilitate the grounding
of instructions for robotic task planning. Despite this progress, most existing works have …

Delta: Decomposed efficient long-term robot task planning using large language models

Y Liu, L Palmieri, S Koch, I Georgievski… - arXiv preprint arXiv …, 2024 - arxiv.org
Recent advancements in Large Language Models (LLMs) have sparked a revolution across
various research fields. In particular, the integration of common-sense knowledge from LLMs …

Llm-based human-robot collaboration framework for manipulation tasks

H Liu, Y Zhu, K Kato, I Kondo, T Aoyama… - arXiv preprint arXiv …, 2023 - arxiv.org
This paper presents a novel approach to enhance autonomous robotic manipulation using
the Large Language Model (LLM) for logical inference, converting high-level language …