Results 41 to 50 of about 55,072 (308)

Scalable Task Planning via Large Language Models and Structured World Representations

Advanced Robotics Research, EarlyView.
This work efficiently combines graph‐based world representations with the commonsense knowledge in Large Language Models to enhance planning techniques for the large‐scale environments that modern robots will need to face. Planning methods often struggle with computational intractability when solving task‐level problems in large‐scale environments ...
Rodrigo Pérez‐Dattari, Zhaoting Li, Robert Babuška, Jens Kober, Cosimo Della Santina   +4 more
wiley   +1 more source

Comparative analysis between the performance of ChatGPT and medical students outside their examination phase

GMS Medizinische Informatik, Biometrie und Epidemiologie
Introduction: State-run medical licensing examinations in Germany are highly demanding, requiring extensive preparation. While medical expertise remains central to licensure, patients increasingly seek advice from artificial intelligence (AI) models like
Daniel Leufkens, Jörn Pons-Kühnemann, Henning Schneider, Anita C. Windhorst   +3 more
doaj   +1 more source

LLM-Sketch: Enhancing Network Sketches with LLM

CoRR
Network stream mining is fundamental to many network operations. Sketches, as compact data structures that offer low memory overhead with bounded accuracy, have emerged as a promising solution for network stream mining. Recent studies attempt to optimize sketches using machine learning; however, these approaches face the challenges of lacking ...
Yuanpeng Li 0002, Zhen Xu, Zongwei Lv, Yannan Hu, Yong Cui 0001, Tong Yang 0003   +5 more
openaire   +2 more sources

The Future of Research in Cognitive Robotics: Foundation Models or Developmental Cognitive Models?

Advanced Robotics Research, EarlyView.
Research in cognitive robotics founded on principles of developmental psychology and enactive cognitive science would yield what we seek in autonomous robots: the ability to perceive its environment, learn from experience, anticipate the outcome of events, act to pursue goals, and adapt to changing circumstances without resorting to training with ...
David Vernon
wiley   +1 more source

Diffusion LLMs are Natural Adversaries for any LLM

CoRR
We introduce a novel framework that transforms the resource-intensive (adversarial) prompt optimization problem into an \emph{efficient, amortized inference task}. Our core insight is that pretrained, non-autoregressive generative LLMs, such as Diffusion LLMs, which model the joint distribution over prompt-response pairs, can serve as powerful ...
David Lüdke, Tom Wollschläger, Paul Ungermann, Stephan Günnemann, Leo Schwinn   +4 more
openaire   +2 more sources

Grounding Large Language Models for Robot Task Planning Using Closed‐Loop State Feedback

Advanced Robotics Research, EarlyView.
BrainBody‐Large Language Model (LLM) introduces a hierarchical, feedback‐driven planning framework where two LLMs coordinate high‐level reasoning and low‐level control for robotic tasks. By grounding decisions in real‐time state feedback, it reduces hallucinations and improves task reliability.
Vineet Bhat, Ali Umut Kaypak, Prashanth Krishnamurthy, Ramesh Karri, Farshad Khorrami   +4 more
wiley   +1 more source

Who is a Better Player: LLM against LLM

CoRR
Adversarial board games, as a paradigmatic domain of strategic reasoning and intelligence, have long served as both a popular competitive activity and a benchmark for evaluating artificial intelligence (AI) systems. Building on this foundation, we propose an adversarial benchmarking framework to assess the comprehensive performance of Large Language ...
Yingjie Zhou 0003, Jiezhang Cao, Farong Wen, Li Xu 0008, Yanwei Jiang, Jun Jia, Ronghui Li, Xiaohong Liu 0001, Yu Zhou 0016, Xiongkuo Min, Jie Guo, Zicheng Zhang, Guangtao Zhai   +12 more
openaire   +2 more sources

Leveraging LLMs for Non-Security Experts in Threat Hunting: Detecting Living off the Land Techniques

This paper explores the potential use of Large Language Models (LLMs), such as ChatGPT, Google Gemini, and Microsoft Copilot, in threat hunting, specifically focusing on Living off the Land (LotL) techniques.
Politis, Ilias, William J. Buchanan, Buchanan, William J., Konstantinou, Antreas, Ilias Politis, Pitropakis, Nikolaos, Jawad Ahmad, Dimitrios Kasimatis, Kasimatis, Dimitrios, Sana Ullah Jan, Antreas Konstantinou, Nikolaos Pitropakis, Ullah Jan, Sana, Ahmad, Jawad   +13 more
core   +1 more source

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

LLM Chemistry Estimation for Multi-LLM Recommendation

CoRR
Multi-LLM collaboration promises accurate, robust, and context-aware solutions, yet existing approaches rely on implicit selection and output assessment without analyzing whether collaborating models truly complement or conflict. We introduce LLM Chemistry -- a framework that measures when LLM combinations exhibit synergistic or antagonistic behaviors ...
Huascar Sanchez, Briland Hitaj
openaire   +2 more sources