Results 121 to 130 of about 6,586,139 (300)

MVACLNet: A Multimodal Virtual Augmentation Contrastive Learning Network for Rumor Detection

Algorithms
In today’s digital era, rumors spreading on social media threaten societal stability and individuals’ daily lives, especially multimodal rumors. Hence, there is an urgent need for effective multimodal rumor detection methods. However, existing approaches
Xin Liu, Mingjiang Pang, Qiang Li, Jiehan Zhou, Haiwen Wang, Dawei Yang   +5 more
doaj   +1 more source

Multimodal Representation Learning and Fusion

CoRR
Multi-modal learning is a fast growing area in artificial intelligence. It tries to help machines understand complex things by combining information from different sources, like images, text, and audio. By using the strengths of each modality, multi-modal learning allows AI systems to build stronger and richer internal representations.
Jin, Qihang, Ge, Enze, Xie, Yuhang, Luo, Hongying, Song, Junhao, Bi, Ziqian, Liang, Chia Xin, Guan, Jibin, Yeong, Joe, Song, Xinyuan, Hao, Junfeng   +10 more
openaire   +3 more sources

Azobenzene's Cross‐Scale Optics and Photonics: Molecular Photoswitching, Mesoscopic Material Motions, and Adaptive Devices

Advanced Materials, EarlyView.
Azobenzene photoswitches translate molecular‐scale E/Z photoisomerization into macroscopic material responses and device‐level photonic functions. This Review highlights how azobenzene research has evolved from molecular photochemistry to photoalignment, mass migration, photomechanics, and heat release, ultimately enabling holography, reconfigurable ...
Heeju Son, Soyul Kwak, Heerin Noh, Minsang Kim, Doyeon Noh, Subhayan Chakraborty, Jaewon Lee, YongDeok Cho, Kyeongsoo Kim, Taewoong Eom, Moonyoung Kim, Jangwon Kim, Hoyoung Lee, Soyoung Lee, Jaehun Kim, Grace G. D. Han, Shin‐Tson Wu, Stefano Oscurato, Arri Priimagi, Marina Saphiannikova, Seungwoo Lee   +20 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Multimodal Challenge: Analytics Beyond User-computer Interaction Data [PDF]

, 2018
This contribution describes one the challenges explored in the Fourth LAK Hackathon. This challenge aims at shifting the focus from learning situations which can be easily traced through user-computer interactions data and concentrate more on user-world ...
Di Mitri, Daniele, Schneider, Jan, Buckingham Shum, Simon, Pardo, Abelardo, Merceron, Agathe, Drachsler, Hendrik, Ochoa, Xavier, Specht, Marcus, Ferguson, Rebecca, Bartimote, Kathryn, Lynch, Grace   +10 more
core  

Bioinspired Adaptive Surfaces for Intelligent Liquid Manipulation: Progressing From Passive and Active to Hybrid Strategies

Advanced Materials, EarlyView.
This review examines passive, active, and hybrid liquid manipulation strategies, highlighting hybrid approaches as an emerging route to reconcile energy efficiency with adaptive control. By actively reconstructing passive surfaces to store programmable interfacial energy, hybrid systems enable flexible yet low‐power liquid transport, with perspectives ...
Jiaqi Miao, Yiyuan Zhang, Liqiu Wang, Alan C. H. Tsang   +3 more
wiley   +1 more source

Multimodal Contrastive In-Context Learning

CoRR
The rapid growth of Large Language Models (LLMs) usage has highlighted the importance of gradient-free in-context learning (ICL). However, interpreting their inner workings remains challenging. This paper introduces a novel multimodal contrastive in-context learning framework to enhance our understanding of ICL in LLMs.
Yosuke Miyanishi, Le-Minh Nguyen 0001
openaire   +2 more sources

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

A Review of Multimodal Interaction in Remote Education: Technologies, Applications, and Challenges

Applied Sciences
Multimodal interaction technology has become a key aspect of remote education by enriching student engagement and learning results as it utilizes the speech, gesture, and visual feedback as various sensory channels.
Yangmei Xie, Liuyi Yang, Miao Zhang, Sinan Chen, Jialong Li   +4 more
doaj   +1 more source

Closed‐Loop Solid‐State Synthesis Planning for Materials Discovery With Large Language Models

Advanced Materials, EarlyView.
Leveraging literature data, we build a large‐language‐model‐driven workflow that extracts synthesis steps from 4407 papers, retrieves similar precedents, and generates candidate solid‐state synthesis recipes. The system benchmarks against ground‐truth and then operates in a closed loop with experiments to synthesize oxy‐selenide electrolyte materials ...
Dong Won Jeon, Dong Hwi Kim, Taeyang Jeon, Joo Yeong Na, Heegyu Kim, Hyunsouk Cho, Dae Soo Jung, Ju Li, Jin‐Sung Park, Sung Beom Cho   +9 more
wiley   +1 more source