Results 111 to 120 of about 72,487 (305)

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

SemEval-2016 Task 2: Interpretable semantic textual similarity

, 2016
Comunicació presentada al 10th International Workshop on Semantic Evaluation (SemEval-2016), celebrat els dies 16 i 17 de juny de 2016 a San Diego, Califòrnia.The final goal of Interpretable Semantic Textual Similarity (iSTS) is to build systems that ...
Maritxalar, Montserrat, Aitor Gonzalez-Agirre, Inigo Lopez-Gazpio, Gonzalez Agirre, Aitor, Rigau Claramunt, German, Agirre, Eneko, Larraitz Uria, Montse Maritxalar, German Rigau, Uria, Larraitz, Eneko Agirre, Lopez-Gazpio, Iñigo   +11 more
core   +1 more source

Age-related increases in false recognition: The role of perceptual and conceptual similarity [PDF]

, 2014
Older adults are more likely to falsely recognize novel events than young adults, and recent behavioral and neuroimaging evidence points to a reduced ability to distinguish overlapping information due to decline in hippocampal pattern separation. However,
Morcom, Alexa, Laura M Pidgeon (16273007), Alexa Morcom (6188726), Morcom, Alexa M., Pidgeon, Laura Marie, Pidgeon, Laura M, Pidgeon, Laura M., Laura M. Pidgeon, Alexa M. Morcom, Morcom, Alexa M   +9 more
core   +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

Challenging the Boundaries of Unsupervised Learning for Semantic Similarity

IEEE Access, 2019
The semantic analysis field has a crucial role to play in the research related to text analytics. Calculating the semantic similarity between sentences is a long-standing problem in the area of natural language processing, and it differs significantly as
Atish Pawar, Vijay Mago
doaj   +1 more source

A French Corpus for Semantic Similarity.

, 2020
Semantic similarity is an area of Natural Language Processing that is useful for several downstream applications, such as machine translation, natural language generation, information retrieval, or question answering. The task consists in assessing the extent to which two sentences express or do not express the same meaning.
Cardon, Rémi, Grabar, Natalia
openaire   +2 more sources

A Semantic Framework for Priority-based Service Matching in Pervasive Environments [PDF]

, 2007
The increasing popularity of personal wireless devices has raised new demands for the efficient discovery of heterogeneous devices and services in pervasive environments.
De Roure, David, Terry Payne, Lewis, T, Payne, Terry, Ayomi B, David De Roure, Roure, DD, Payne, TR, Ayomi Bandara, Tim Lewis, Bandara, Ayomi, Bandara, A, Lewis, Tim   +12 more
core   +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

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

A Novel Approach to Semantic Similarity Measurement Based on a Weighted Concept Lattice: Exemplifying Geo-Information

ISPRS International Journal of Geo-Information, 2017
The measurement of semantic similarity has been widely recognized as having a fundamental and key role in information science and information systems. Although various models have been proposed to measure semantic similarity, these models are not able ...
Jia Xiao, Zongyi He
doaj   +1 more source