Results 1 to 10 of about 43,205 (112)

Parameter-efficient fine-tuning of large language models using semantic knowledge tuning [PDF]

Scientific Reports
Large Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning and
Nusrat Jahan Prottasha, Asif Mahmud, Md. Shohanur Islam Sobuj, Prakash Bhat, Md Kowsher, Niloofar Yousefi, Ozlem Ozmen Garibay   +6 more
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Structure-Aware Low-Rank Adaptation for Parameter-Efficient Fine-Tuning

Mathematics, 2023
With the growing scale of pre-trained language models (PLMs), full parameter fine-tuning becomes prohibitively expensive and practically infeasible.
Yahao Hu, Yifei Xie, Tianfeng Wang, Man Chen, Zhisong Pan   +4 more
doaj   +3 more sources

U-SplitDoRA: an improved privacy-preserved U-shaped split parameter-efficient fine-tuning framework through weight decomposition for large language models [PDF]

Frontiers in Artificial Intelligence
As large language models (LLMs) are getting bigger with respect to the parameter count, ranging from a few million to billions, methods like parameter-efficient fine-tuning (PEFT) have emerged as a crucial approach for adapting these LLMs, such as GPT ...
Samar Singh, Brindha Subburaj, R. Alagewaran, Sherly Alphonse   +3 more
doaj   +2 more sources

InfoMSD: an information-maximization self-distillation framework for parameter-efficient fine-tuning on artwork images [PDF]

Frontiers in Artificial Intelligence
In recent years, despite the remarkable performance of large-scale vision language models across various visual classification tasks, their substantial parameter counts and high fine-tuning costs have hindered deployment in resource-constrained cultural ...
Feng Guan, Feng Guan, Hao Hong, Yong Wang   +3 more
doaj   +2 more sources

The BSRA framework for dual sparse parameter efficient fine tuning with block structured gating and rank adaptation [PDF]

Scientific Reports
Current large-scale language models face severe resource constraints when applied to downstream tasks. While full-fledged fine-tuning enhances model performance, it incurs substantial computational costs. Parameter-efficient fine-tuning (PEFT) techniques
Wang Jian, Guorong Chen, Hu Hong, Yixuan Zhang, Chongling Du, Zhang Bao   +5 more
doaj   +2 more sources

CPMI-ChatGLM: parameter-efficient fine-tuning ChatGLM with Chinese patent medicine instructions [PDF]

Scientific Reports
Chinese patent medicine (CPM) is a typical type of traditional Chinese medicine (TCM) preparation that uses Chinese herbs as raw materials and is an important means of treating diseases in TCM. Chinese patent medicine instructions (CPMI) serve as a guide
Can Liu, Kaijie Sun, Qingqing Zhou, Yuchen Duan, Jianhua Shu, Hongxing Kan, Zongyun Gu, Jili Hu   +7 more
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Efficient fine-tuning of vision-language adapters in chemical VLMs for molecular image-text tasks [PDF]

Journal of Cheminformatics
Vision–language models (VLMs) have recently shown strong potential for multimodal scientific applications, yet their direct application to molecular structure images remains challenging due to the need for precise visual–textual alignment. In this study,
Hyukjun Choi, Donghyeon Lee, Juyoung Kang   +2 more
doaj   +2 more sources

Multiscale feature fusion for few-shot medical image learning with fisher information-driven layer selection [PDF]

Visual Computing for Industry, Biomedicine, and Art
Few-shot medical image classification is a highly challenging problem in computer-aided diagnosis, with the central difficulty being enabling deep models to learn discriminative features conducive to classification from limited labeled samples.
Kai Zhang, Yanjun Peng, Bo Pang, Xue Chen   +3 more
doaj   +2 more sources

Multimodal Assessment of Schizophrenia Symptom Severity From Linguistic, Acoustic and Visual Cues

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023
Assessing the condition of every schizophrenia patient correctly normally requires lengthy and frequent interviews with professionally trained doctors.
Chih-Yuan Chuang, Yi-Ting Lin, Chen-Chung Liu, Lue-En Lee, Hsin-Yang Chang, An-Sheng Liu, Shu-Hui Hung, Li-Chen Fu   +7 more
doaj   +1 more source

Parameter-Efficient Fine-Tuning Method for Task-Oriented Dialogue Systems

Mathematics, 2023
The use of Transformer-based pre-trained language models has become prevalent in enhancing the performance of task-oriented dialogue systems. These models, which are pre-trained on large text data to grasp the language syntax and semantics, fine-tune the
Yunho Mo, Joon Yoo, Sangwoo Kang
doaj   +1 more source