Abstractive text summarization: State of the art, challenges, and improvements

H Shakil, A Farooq, J Kalita - Neurocomputing, 2024 - Elsevier
Specifically focusing on the landscape of abstractive text summarization, as opposed to
extractive techniques, this survey presents a comprehensive overview, delving into state-of …

Zero-shot cross-lingual knowledge transfer in vqa via multimodal distillation

Y Weng, J Dong, W He, X Liu, Z Liu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As multilingual artificial intelligence systems proliferate, achieving robust cross-lingual
understanding remains an open challenge. Recent works have made progress on visual …

Large Multimodal Models for Low-Resource Languages: A Survey

M Lupascu, AC Rogoz, MS Stupariu… - arxiv preprint arxiv …, 2025 - arxiv.org
In this survey, we systematically analyze techniques used to adapt large multimodal models
(LMMs) for low-resource (LR) languages, examining approaches ranging from visual …

LCV2: A Universal Pretraining-Free Framework for Grounded Visual Question Answering

Y Chen, L Su, L Chen, Z Lin - Electronics, 2024 - mdpi.com
Grounded Visual Question Answering systems place heavy reliance on substantial
computational power and data resources in pretraining. In response to this challenge, this …

Meta-learning For Vision-and-language Cross-lingual Transfer

H Hu, F Keller - arxiv preprint arxiv:2305.14843, 2023 - arxiv.org
Current pre-trained vison-language models (PVLMs) achieve excellent performance on a
range of multi-modal datasets. Recent work has aimed at building multilingual models, and …