Results 121 to 130 of about 89,825 (246)
Safe-Child-LLM: A Developmental Benchmark for Evaluating LLM Safety in Child-LLM Interactions
CoRRAs Large Language Models (LLMs) increasingly power applications used by children and adolescents, ensuring safe and age-appropriate interactions has become an urgent ethical imperative. Despite progress in AI safety, current evaluations predominantly focus on adults, neglecting the unique vulnerabilities of minors engaging with generative AI.
Junfeng Jiao +5 more
openaire +3 more sources
From Artificial to Embodied and Physical Intelligence in Smart Manufacturing
Advanced Science, EarlyView.Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang +9 more
wiley +1 more source
InformationThe development of large language models (LLMs) has promoted a transformation of human–computer interaction (HCI) models and has attracted the attention of scholars to the evaluation of personality traits of LLMs.
Qianli Lin, Zhipeng Hu, Jun Ma
doaj +1 more source
GUARD-D-LLM: An LLM-Based Risk Assessment Engine for the Downstream uses of LLMs
CoRRAmidst escalating concerns about the detriments inflicted by AI systems, risk management assumes paramount importance, notably for high-risk applications as demanded by the European Union AI Act. Guidelines provided by ISO and NIST aim to govern AI risk management; however, practical implementations remain scarce in scholarly works.
Sundaraparipurnan Narayanan +1 more
openaire +2 more sources
An AI‐Driven Framework for Directed Self‐Assembly Toward Design‐Technology Co‐Optimization
Advanced Science, EarlyView.An artificial intelligence (AI)‐driven closed‐loop framework integrates experiment, three‐dimensional physics‐based simulation, and template design for directed self‐assembly (DSA). Guided by experimental data, AI‐assisted calibration accelerates model optimization, supports morphology prediction, and identifies template windows.
Caiwei Shang +9 more
wiley +1 more source
mBLIP: Efficient Bootstrapping of Multilingual Vision-LLMs [PDF]
Modular vision-language models (Vision-LLMs) align pretrained image encoders with (frozen) large language models (LLMs) and post-hoc condition LLMs to `understand\u27 the image input.
Geigle, Gregor +3 more
core +1 more source
Epistemology in the Age of Large Language Models
KnowledgeEpistemology and technology have been working in synergy throughout history. This relationship has culminated in large language models (LLMs). LLMs are rapidly becoming integral parts of our daily lives through smartphones and personal computers, and we ...
Jennifer Mugleston +4 more
doaj +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
BIO IntegrationThis comprehensive review explores the intersection between large language models (LLMs) and cognitive science, by examining similarities and differences between LLMs and human cognitive processes.
Qian Niu +18 more
doaj +1 more source
Securing educational LLMs: A generalised taxonomy of attacks on LLMs and DREAD risk assessment
Securing educational LLMs: A generalised taxonomy of attacks on LLMs and DREAD risk ...
Roopak Sinha (17900219) +4 more
core