Results 91 to 100 of about 19,275 (267)

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

Unleashing the power of pinyin: promoting Chinese named entity recognition with multiple embedding and attention

Complex & Intelligent Systems
Named Entity Recognition (NER) aims to identify entities with specific meanings and their boundaries in natural language texts. Due to the differences between Chinese and English language families, Chinese NER faces challenges such as ambiguous word ...
Jigui Zhao, Yurong Qian, Shuxiang Hou, Jiayin Chen, Kui Wang, Min Liu, Aizimaiti Xiaokaiti   +6 more
doaj   +1 more source

Neural Reranking for Named Entity Recognition

RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning, 2017
We propose a neural reranking system for named entity recognition (NER). The basic idea is to leverage recurrent neural network models to learn sentence-level patterns that involve named entity mentions. In particular, given an output sentence produced by a baseline NER model, we replace all entity mentions, such as \textit{Barack Obama}, into their ...
Jie Yang 0039, Yue Zhang 0004, Fei Dong
openaire   +2 more sources

On–Off Switchable Micromotors for Use in Steerable Microvehicles

Advanced Robotics Research, EarlyView.
Electrically controllable micromotors and microvehicles are developed by tuning the diffusion of the fuel. Self‐propelled micromotors using bubble propulsion show great promise for miniaturized devices with multiuse purposes such as cargo delivery and sensing. However, there is currently no method to electrically switch the micromotors on or off. Here,
Hugo Severinsson, Eswaran Murugasen, Jose G. Martinez, Edwin W. H. Jager   +3 more
wiley   +1 more source

CodeNER: Code Prompting for Named Entity Recognition

IEEE Access
Recent studies have explored various approaches for treating candidate named entity spans as both source and target sequences in named entity recognition (NER) by leveraging large language models (LLMs).
Sungwoo Han, Hyeyeon Kim, Jingun Kwon, Hidetaka Kamigaito, Manabu Okumura   +4 more
doaj   +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

Precursor-induced conditional random fields: connecting separate entities by induction for improved clinical named entity recognition

BMC Medical Informatics and Decision Making, 2019
Background This paper presents a conditional random fields (CRF) method that enables the capture of specific high-order label transition factors to improve clinical named entity recognition performance.
Wangjin Lee, Jinwook Choi
doaj   +1 more source

Query-Based Named Entity Recognition

CoRR, 2019
In this paper, we propose a new strategy for the task of named entity recognition (NER). We cast the task as a query-based machine reading comprehension task: e.g., the task of extracting entities with PER is formalized as answering the question of "which person is mentioned in the text ?".
Yuxian Meng, Xiaoya Li 0001, Zijun Sun, Jiwei Li 0001   +3 more
openaire   +2 more sources

Intelligent Maintenance Review for Robots: Multimodal Information, Deep Diagnosis and Embodied Artificial Intelligence

Advanced Robotics Research, EarlyView.
This review maps the methods to monitor robots’ health by fusing vibration, sound, control signals, vision, force, and oil information with artificial intelligence. It identifies deep learning, transfer learning, digital twins, and physics‐informed models as key methodological pathways enabling earlier diagnosis, safer human–robot collaboration, and ...
Yuting Qiao, Hongbo Wang, Naipeng Li, Shuo Wang, Yaguo Lei, Tonghai Wu, Junyi Cao   +6 more
wiley   +1 more source

Enhancing Maturation of Human Neuromuscular Organoids via Electrical Stimulation

Advanced Science, EarlyView.
A framework for on‐demand and non‐invasive exposure of human neuromuscular organoids (NMOs) to electrical stimuli is established to promote their maturation. The robustness and effectiveness of different stimulation regimes are evaluated via thorough characterization of organoid tissue structure and contraction capacity. Chronic electrical stimulation,
Chrysanthi‐Maria Moysidou, Inês Afonso Martins, Ismail Amr El‐Shimy, Iacopo Bicci, Donatella Cea, Christina Bukas, Isra Mekki, Mara‐Camelia Rusu, Aylin Nebol, Ines Lahmann, Marie Piraud, Enrico Klotzsch, Mina Gouti   +12 more
wiley   +1 more source