Results 131 to 140 of about 459,286 (299)

Task-Agnostic Adaptive Activation Scaling Network for LLMs

IEEE Access
The advent of Large Language Models (LLMs) has revolutionized Natural Language Processing (NLP), offering unprecedented capabilities for understanding and generating human-like texts.
Ni Jia, Tong Liu, Jiadi Chen, Ying Zhang, Song Han   +4 more
doaj   +1 more source

Cytoplasmic p21 promotes stemness of colon cancer cells via activation of the NFκB pathway

Molecular Oncology, EarlyView.
Cytoplasmic p21 promotes colorectal cancer stem cell (CSC) features by destabilizing the NFκB–IκB complex, activating NFκB signaling, and upregulating BCL‐xL and COX2. In contrast to nuclear p21, cytoplasmic p21 enhances spheroid formation and stemness transcription factor CD133.
Arnatchai Maiuthed, Kerstin Huebner, Katharina Erlenbach‐Wuensch, Chuanpit Hampel, Daniela Thalheim, Adriana Vial‐Roehe, Bodee Nutho, Susanne Merkel, Arndt Hartmann, Pithi Chanvorachote, Regine Schneider‐Stock   +10 more
wiley   +1 more source

LLM4WM: Adapting LLM for Wireless Multi-Tasking

IEEE Transactions on Machine Learning in Communications and Networking
The wireless channel is fundamental to communication, encompassing numerous tasks collectively referred to as channel-associated tasks. These tasks can leverage joint learning based on channel characteristics to share representations and enhance system ...
Xuanyu Liu, Shijian Gao, Boxun Liu, Xiang Cheng, Liuqing Yang   +4 more
doaj   +1 more source

zFLoRA: Zero-Latency Fused Low-Rank Adapters

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Large language models (LLMs) are increasingly deployed with task-specific adapters catering to multiple downstream applications. In such a scenario, the additional compute associated with these apparently insignificant number of adapter parameters (typically less than 1% of the base model) turns out to be disproportionately significant during inference
Gowda, Dhananjaya, Song, Seoha, Goka, Harshith, Lee, Junhyun   +3 more
openaire   +2 more sources

Effective Fine-Tuning of Vision Transformers with Low-Rank Adaptation for Privacy-Preserving Image Classification [PDF]

Han Yu Lin, Shoko Imaizumi, Hitoshi Kiya
openalex   +1 more source

LoRA: Low-Rank Adaptation of Large Language Models [PDF]

, 2021
J. Edward Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Weizhu Chen, Chen, Weizhu   +7 more
openalex   +1 more source

Class IIa HDACs forced degradation allows resensitization of oxaliplatin‐resistant FBXW7‐mutated colorectal cancer

Molecular Oncology, EarlyView.
HDAC4 is degraded by the E3 ligase FBXW7. In colorectal cancer, FBXW7 mutations prevent HDAC4 degradation, leading to oxaliplatin resistance. Forced degradation of HDAC4 using a PROTAC compound restores drug sensitivity by resetting the super‐enhancer landscape, reprogramming the epigenetic state of FBXW7‐mutated cells to resemble oxaliplatin ...
Vanessa Tolotto, Nicolò Gualandi, Ylenia Cortolezzis, Raffaella Picco, Monica Colitti, Francesca D'Este, Mariachiara Gani, Wayne W. Hancock, Giovanni Terrosu, Cristina Degrassi, Francesca Agostini, Claudio Brancolini, Luigi E. Xodo, Eros Di Giorgio   +13 more
wiley   +1 more source

Dual large language model core-driven adaptive framework for ship navigation agents

Zhongguo Jianchuan Yanjiu
Objective Current ship navigation decision-making systems struggle to demonstrate superior performance in undefined sailing scenarios. Given the broad applicability of large language models （LLMs） in unknown scenarios, this study proposes a dual-LLM-core-
Feng MA, Xiumin WANG, Chen CHEN, Xiaobin XU, Xinping YAN   +4 more
doaj   +1 more source

ST-LoRA: Low-rank Adaptation for Spatio-Temporal Forecasting [PDF]

Weilin Ruan, Wei Chen, Xilin Dang, Jianxiang Zhou, W. G. Li, Xu Liu, Yuxuan Liang   +6 more
openalex   +1 more source

Bayesian Low-rank Adaptation for Large Language Models [PDF]

, 2023
Adam X. Yang, Maxime Robeyns, Xi Wang, Laurence Aitchison   +3 more
openalex   +1 more source