Full Model
"Full Model" research encompasses the development and improvement of large-scale machine learning models across diverse applications, aiming to enhance performance, efficiency, and robustness. Current research focuses on addressing model vulnerabilities (e.g., adversarial attacks, hallucinations), improving efficiency for resource-constrained devices, and developing specialized models for specific domains (e.g., finance, astronomy, medical imaging). This work is significant for advancing AI capabilities in various fields and for mitigating potential risks associated with deploying complex models in real-world settings.
Papers
Rethinking Strategic Mechanism Design In The Age Of Large Language Models: New Directions For Communication Systems
Ismail Lotfi, Nouf Alabbasi, Omar Alhussein
Two Models for Surface Segmentation using the Total Variation of the Normal Vector
Lukas Baumgärtner, Ronny Bergmann, Roland Herzog, Stephan Schmidt, Manuel Weiß
One Model for One Graph: A New Perspective for Pretraining with Cross-domain Graphs
Jingzhe Liu, Haitao Mao, Zhikai Chen, Wenqi Fan, Mingxuan Ju, Tong Zhao, Neil Shah, Jiliang Tang
Skeleton Detection Using Dual Radars with Integration of Dual-View CNN Models and mmPose
Masaharu Kodama (Department of Computer and Information Sciences, Hosei University), Runhe Huang (Hosei University)
Improving sub-seasonal wind-speed forecasts in Europe with a non-linear model
Ganglin Tian (1), Camille Le Coz (1), Anastase Alexandre Charantonis (1, 2), Alexis Tantet (1), Naveen Goutham (1, 3), Riwal Plougonven (1) ((1) LMD/IPSL, École Polytechnique, Palaiseau, France, (2) INRIA, Paris, France, (3) EDF R&D, Palaiseau, France)
Perception of Visual Content: Differences Between Humans and Foundation Models
Nardiena A. Pratama, Shaoyang Fan, Gianluca Demartini
Rephrasing Electronic Health Records for Pretraining Clinical Language Models
Jinghui Liu, Anthony Nguyen
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
Letian Chen, Matthew Gombolay
The Performance of the LSTM-based Code Generated by Large Language Models (LLMs) in Forecasting Time Series Data
Saroj Gopali, Sima Siami-Namini, Faranak Abri, Akbar Siami Namin
Embracing AI in Education: Understanding the Surge in Large Language Model Use by Secondary Students
Tiffany Zhu, Kexun Zhang, William Yang Wang
SimCMF: A Simple Cross-modal Fine-tuning Strategy from Vision Foundation Models to Any Imaging Modality
Chenyang Lei, Liyi Chen, Jun Cen, Xiao Chen, Zhen Lei, Felix Heide, Qifeng Chen, Zhaoxiang Zhang
Learning the Evolution of Physical Structure of Galaxies via Diffusion Models
Andrew Lizarraga, Eric Hanchen Jiang, Jacob Nowack, Yun Qi Li, Ying Nian Wu, Bernie Boscoe, Tuan Do
Aligning Pre-trained Models for Spoken Language Translation
Šimon Sedláček, Santosh Kesiraju, Alexander Polok, Jan Černocký
Neutralizing Backdoors through Information Conflicts for Large Language Models
Chen Chen, Yuchen Sun, Xueluan Gong, Jiaxin Gao, Kwok-Yan Lam
A gentle push funziona benissimo: making instructed models in Italian via contrastive activation steering
Daniel Scalena, Elisabetta Fersini, Malvina Nissim
MSA-ASR: Efficient Multilingual Speaker Attribution with frozen ASR Models
Thai-Binh Nguyen, Alexander Waibel
JPPO: Joint Power and Prompt Optimization for Accelerated Large Language Model Services
Feiran You, Hongyang Du, Kaibin Huang, Abbas Jamalipour
RS-vHeat: Heat Conduction Guided Efficient Remote Sensing Foundation Model
Huiyang Hu, Peijin Wang, Hanbo Bi, Boyuan Tong, Zhaozhi Wang, Wenhui Diao, Hao Chang, Yingchao Feng, Ziqi Zhang, Qixiang Ye, Kun Fu, Xian Sun