Results 41 to 50 of about 67,162,078 (293)

The MuLeCo project: A learner corpus of L1 German learners of Romance languages

Ampersand
The importance of learner corpora for foreign language acquisition research as well as their role in data-driven learning and other learning contexts is now widely recognised.
Stephan Lücke, Patricia de Crignis, Johanna Wolf, Florian Zacherl   +3 more
doaj   +1 more source

The Cambridge Handbook of Learner Corpus Research

, 2015
The origins of learner corpus research go back to the late 1980s when large electronic collections of written or spoken data started to be collected from foreign/second language learners, with a view to advancing our understanding of the mechanisms of second language acquisition and developing tailor-made pedagogical tools.
Granger, Sylviane, Gilquin, Gaëtanelle, Meunier, Fanny   +2 more
openaire   +1 more source

Breaking Bottlenecks in Solid Electrolyte Discovery With Large Artificial Intelligence Models

Advanced Materials, EarlyView.
Large AI models are presented as a route to break key bottlenecks in solid electrolyte discovery by linking materials databases, machine‐learning interatomic potentials, large language models, and autonomous experiments. This perspective highlights how AI can accelerate the identification of solid electrolytes with fast ion transport, stable interfaces,
Eric Jianfeng Cheng, Min Hong, Zhiquan Zeng, Chuanyu Liu, Qian Wang, Melissa Jane Meadowcroft, Vlad Badilita, Carlos Miguel Costa, Senentxu Lanceros‐Méndez, Ying Li, Chenyao Ma, Weibo Gong, Surendra Kumar Martha, Aloysius Soon, Piao Ma, Di Zhang, Teguh Ariyanto, Sudaryanto, Hiroshi Kakinuma, Jie Zhao, Jiayu Peng, Pengfei Ou, Jun Lu, Shin‐ichi Orimo, Hao Li   +24 more
wiley   +1 more source

Using Learner Corpora to Inform Material Development and Classroom Practices

Babylonia
This article examines how a university in Japan uses a longitudinal learner corpus to bridge the gap between research and classroom practice in a two-year English for Academic Purposes (EAP) program.
Gavin Brooks
doaj   +1 more source

LO SVILUPPO LONGITUDINALE DELLA FRASEOLOGIA IN APPRENDENTI CINESI DI ITALIANO L2: UNO STUDIO PRELIMINARE SU ALCUNE CATEGORIE DI ERRORI

RiCognizioni, 2018
This study is a preliminary investigation of the development of phraseology in Chinese learners of Italian. Based on an error-annotated longitudinal learner corpus, it aims at analysing three different categories of lexical combinations, in order to ...
Stefania Spina
doaj   +1 more source

Toward Perception‐Native Electronic Skin: Bio‐Inspired In‐/Near‐Sensor and Neuromorphic Computing for Humanoid Robots

Advanced Materials Technologies, EarlyView.
Dense tactile streams from across the humanoid body converge on collide in a central wiring and data bottleneck. By relocating computation closer to and then into the skin itself, near‐ and in‐sensor architectures, together with neuromorphic computing, chart a path toward perception‐native electronic skin, in which the conversion of stimulus into ...
Mijin Kim, Chang‐Jae Beak, Jiyoung Park, Youngdo Jung, Sunjong Oh, Sin‐Hyung Lee, Bo‐Yeon Lee   +6 more
wiley   +1 more source

Slovene Subcorpus of the International Corpus of Learner English and Its Potential for Contrastive Interlanguage Analysis

ELOPE
This paper introduces the Slovene subcorpus of the International Corpus of Learner English (ICLE), the first representative dataset of English produced by Slovene L1 speakers.
Monika Kavalir
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

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

Learning‐Based Soft Robotic Grasping: Recent Progress and Remaining Challenges

Advanced Robotics Research, EarlyView.
This review analyzes learning‐based soft robotic grasping from a pipeline‐oriented perspective, encompassing soft gripper design, multimodal sensing, and learning‐based planning and control. It surveys key neural network architectures and benchmark datasets and identifies critical challenges such as sim‐to‐real transfer, generalization, and continual ...
Arnab Majumder, Jelizaveta Konstantinova, Graham Deacon, Kaspar Althoefer   +3 more
wiley   +1 more source