Results 111 to 120 of about 16,504,576 (273)

Extending Large Language Models to multimodality for non-English languages

Computer Vision and Image Understanding
The growing popularity of Large Vision-Language Models has highlighted and intensified one of the most well-known challenges in the field of Large Language Models: training is mainly, and most of the time exclusively, conducted on English data.
Elio Musacchio, Lucia Siciliani, Pierpaolo Basile, Giovanni Semeraro   +3 more
openaire   +2 more sources

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

Unified modeling language code generation from diagram images using multimodal large language models

Machine Learning with Applications
The Unified Modeling Language is a standardized visual language widely used for modeling and documenting the design of software systems. Although many tools are available that generate UML diagrams from UML code, generating executable UML code from image-
Averi Bates, Ryan Vavricka, Shane Carleton, Ruosi Shao, Chongle Pan   +4 more
doaj   +1 more source

Flexible Sensors for Robotics Tactile Perception: A Review

Advanced Robotics Research, EarlyView.
Flexible tactile sensing for robotics is reviewed through four interconnected dimensions. Physical mechanisms include piezoresistive, capacitive, piezoelectric, triboelectric, iontronic, and optical sensing. Structural design includes bioinspired, defect‐based, and MEMS‐based tactile systems.
Yu Song, Ying Chen, Yihao Chen, Xue Feng
wiley   +1 more source

Towards Language-Driven Video Inpainting via Multimodal Large Language Models [PDF]

We introduce a new task -- language-driven video inpainting, which uses natural language instructions to guide the inpainting process. This approach overcomes the limitations of traditional video inpainting methods that depend on manually labeled binary ...
Li, Yining, Yang, Jingkang, Si, Chenyang, Zhang, Jiangning, Li, Xiangtai, Wu, Jianzong, Chen, Kai, Zhou, Shangchen, Liu, Ziwei, Loy, Chen Change, Tong, Yunhai   +10 more
core   +1 more source

From text to multimodality: A comprehensive survey of LLMs and MLLMs across diverse domains

ICT Express
The rapid development of Artificial Intelligence has made it possible for advanced language learning systems, including Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs), to be created.
Anbukkarasi S, Hemalatha S, Arunkumar B, Shanmugavalli V, Kokila S, Yashaswini K A   +5 more
doaj   +1 more source

Can We Edit Multimodal Large Language Models? [PDF]

In this paper, we focus on editing Multimodal Large Language Models (MLLMs). Compared to editing single-modal LLMs, multimodal model editing is more challenging, which demands a higher level of scrutiny and careful consideration in the editing process ...
Tian, Bozhong, Chen, Xi, Wang, Yongheng, Cheng, Siyuan, Zhang, Ningyu, Liu, Qingbin, Chen, Huajun   +6 more
core   +1 more source

TacVerse: A Multisensor Dataset and Benchmark for Cross‐Sensor Vision‐Based Tactile Perception

Advanced Robotics Research, EarlyView.
TacVerse provides a controlled benchmark of 106 800 tactile images from seven vision‐based tactile sensors across shape classification, grating classification, and force regression. Direct cross‐sensor transfer reveals substantial sensor‐shift degradation, with grating and force perception more affected than shape recognition.
Lan Wei, Gurmeher Khurana, Sirine Bhouri, Wenhao Hong, Zeyuan Xin, Qingzheng Cong, Wen Fan, Yanzheng Xiang, Dandan Zhang   +8 more
wiley   +1 more source

AASD: Accelerate Inference by Aligning Speculative Decoding in Multimodal Large Language Models

AASD: Accelerate Inference by Aligning Speculative Decoding in Multimodal Large Language ...
W Pang (13543885), R Chen (7680200), M Zhang (5107739), R Xu (7708496), Y Chen (5099375), C Yang (7730849), K Fu (13662238), C Wang (4703686), Longxiang Gao (13081947)   +8 more
core  

Robotic Assistants in the Operating Room: A Systematic Review of Vision‐Based Systems for Nonoperative Tasks

Advanced Robotics Research, EarlyView.
This review brings together 20 publications describing 11 robotic system families developed for instrument handling, sterile‐package opening, supply delivery, and operating room logistics. Perception is becoming more capable through deep learning and language‐guided control, but autonomy remains limited, evidence is largely laboratory‐based, and no ...
Eugenia Mawuenya Akpo, Pietro Falco, Nicholas Raison, Christos Bergeles, Letizia Gionfrida   +4 more
wiley   +1 more source