Results 41 to 50 of about 289,006 (287)
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 +24 more
wiley +1 more source
Metadata formats for learner corpora: case study and discussion [PDF]
, 2022 Metadata provides important information relevant both to finding and understanding corpus data. Meaningful linguistic data requires both reasonable annotations and documentation of these annotations.
Lange, Herbert
core +1 more source
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 +6 more
wiley +1 more source
Corpora for second language assessments
, 2020 This chapter describes how corpora and corpus methods can be used in the analysis of learner language and applied to language testing. The chapter first describes three types of corpora relevant for investigations of learner language: corpora of L1 and ...
Gablasova, Dana
core +3 more sources
Learner corpora: the case of the NOSE corpus [PDF]
Journal of Systemics, Cybernetics and Informatics, 2012 This paper provides a brief overview of the scope of learner corpus research and describes a learner corpus by Spanish university students of English, the NOn-native Spanish corpus of English (NOSE). It presents the corpus data, its annotation and how it
Ana Díaz-Negrillo
doaj
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 +4 more
wiley +1 more source
Written learner corpora to inform teaching
, 2023 This chapter deals with how researchers and practitioners have exploited written learner corpora to inform language teaching. It considers both direct and indirect uses of learner corpora, with a focus on their contribution to dictionaries, grammars and ...
Gilquin, Gaëtanelle
core
The Learner Corpora of Spoken English: What Has Been Done and What Should Be Done? [PDF]
, 2020 The number of spoken learner corpora is smaller than that of written corpora; however, demand for spoken corpora has continuously increased. This study investigates the current state of spoken English-language learner corpora both in the world and in ...
Yoon, Soyeon
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 +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 +3 more
wiley +1 more source