Results 71 to 80 of about 49,461 (233)

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

Learning Highly Dynamic Skills Transition for Quadruped Jumping Through Constrained Space

Advanced Robotics Research, EarlyView.
A quadruped robot masters dynamic jumps through constrained spaces with animal‐inspired moves and intelligent vision control. This hierarchical learning approach combines imitation of biological agility with real‐time trajectory planning. Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating ...
Zeren Luo, Jiahui Zhang, Yimin Han, Ji Ma, Minghao Lu, Ioannis Havoutis, Peng Lu   +6 more
wiley   +1 more source

Linking Datasets Using Semantic Textual Similarity

Cybernetics and Information Technologies, 2018
Linked data has been widely recognized as an important paradigm for representing data and one of the most important aspects of supporting its use is discovery of links between datasets.
McCrae John P., Buitelaar Paul
doaj   +1 more source

Metrics for GO based protein semantic similarity: a systematic evaluation

BMC Bioinformatics, 2008
Background Several semantic similarity measures have been applied to gene products annotated with Gene Ontology terms, providing a basis for their functional comparison.
Falcão André O, Ferreira António EN, Bastos Hugo, Faria Daniel, Pesquita Catia, Couto Francisco M   +5 more
doaj   +1 more source

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

Leveraging large language models and embedding representations for enhanced word similarity computation

Scientific Reports
Current mainstream methods for computing word similarity often struggle to precisely capture the fine-grained semantics of words across different contexts.
XiaoHong Peng, Hongbin Jiang, Jing Chen, MingXin Liu, Xiao Chen   +4 more
doaj   +1 more source

Arabic Word Semantic Similarity

, 2012
This paper is concerned with the production of an Arabic word semantic similarity benchmark dataset. It is the first of its kind for Arabic which was particularly developed to assess the accuracy of word semantic similarity measurements. Semantic similarity is an essential component to numerous applications in fields such as natural language processing,
Faaza A, Almarsoomi, D, James, O'Shea, A, Zuhair, Bandar, A, Keeley, Crockett   +7 more
openaire   +1 more source

Improving the Robustness of Visual Teach‐and‐Repeat Navigation Using Drift Error Correction and Event‐Based Vision for Low‐Light Environments

Advanced Robotics Research, EarlyView.
Visual teach‐and‐repeat (VTR) navigation allows robots to learn and follow routes without building a full metric map. We show that navigation accuracy for VTR can be improved by integrating a topological map with error‐drift correction based on stereo vision.
Fuhai Ling, Ze Huang, Tony J. Prescott
wiley   +1 more source

Continual Learning for Multimodal Data Fusion of a Soft Gripper

Advanced Robotics Research, EarlyView.
Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
wiley   +1 more source

Revealing the Influence of Semantic Similarity on Survey Responses: A Synthetic Data Generation Approach

IEEE Access
Questionnaires are essential for measuring self-reported attitudes, beliefs, and behaviour in many research fields. Semantic similarity of the questions is recognized as a source of covariance in the human data, implying that response patterns partly ...
Esko Lehtonen, Tommi Buder-Grondahl, Sina Nordhoff   +2 more
doaj   +1 more source