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
MARS: Unleashing the Power of Variance Reduction for Training Large Models
Huizhuo Yuan, Yifeng Liu, Shuang Wu, Xun Zhou, Quanquan Gu
OnlyFlow: Optical Flow based Motion Conditioning for Video Diffusion Models
Mathis Koroglu, Hugo Caselles-Dupré, Guillaume Jeanneret Sanmiguel, Matthieu Cord
Explanation for Trajectory Planning using Multi-modal Large Language Model for Autonomous Driving
Shota Yamazaki, Chenyu Zhang, Takuya Nanri, Akio Shigekane, Siyuan Wang, Jo Nishiyama, Tao Chu, Kohei Yokosawa
DT-JRD: Deep Transformer based Just Recognizable Difference Prediction Model for Video Coding for Machines
Junqi Liu, Yun Zhang, Xiaoqi Wang, Xu Long, Sam Kwong
Enhancing Financial Domain Adaptation of Language Models via Model Augmentation
Kota Tanabe, Masanori Hirano, Kazuki Matoya, Kentaro Imajo, Hiroki Sakaji, Itsuki Noda
Model agnostic local variable importance for locally dependent relationships
Kelvyn K. Bladen, Adele Cutler, D. Richard Cutler, Kevin R. Moon
Towards Optimizing a Retrieval Augmented Generation using Large Language Model on Academic Data
Anum Afzal, Juraj Vladika, Gentrit Fazlija, Andrei Staradubets, Florian Matthes
Deceiving Question-Answering Models: A Hybrid Word-Level Adversarial Approach
Jiyao Li, Mingze Ni, Yongshun Gong, Wei Liu
PERFT: Parameter-Efficient Routed Fine-Tuning for Mixture-of-Expert Model
Yilun Liu, Yunpu Ma, Shuo Chen, Zifeng Ding, Bailan He, Zhen Han, Volker Tresp
LLMPhy: Complex Physical Reasoning Using Large Language Models and World Models
Anoop Cherian, Radu Corcodel, Siddarth Jain, Diego Romeres
Controlled Evaluation of Syntactic Knowledge in Multilingual Language Models
Daria Kryvosheieva, Roger Levy
DecoPrompt : Decoding Prompts Reduces Hallucinations when Large Language Models Meet False Premises
Nan Xu, Xuezhe Ma
Chinese SimpleQA: A Chinese Factuality Evaluation for Large Language Models
Yancheng He, Shilong Li, Jiaheng Liu, Yingshui Tan, Hui Huang, Weixun Wang, Xingyuan Bu, Hangyu Guo, Chengwei Hu, Boren Zheng, Xuepeng Liu, Dekai Sun, Wenbo Su, Bo Zheng
Cancer-Answer: Empowering Cancer Care with Advanced Large Language Models
Aniket Deroy, Subhankar Maity
UMFC: Unsupervised Multi-Domain Feature Calibration for Vision-Language Models
Jiachen Liang, Ruibing Hou, Minyang Hu, Hong Chang, Shiguang Shan, Xilin Chen
LLM-Neo: Parameter Efficient Knowledge Distillation for Large Language Models
Runming Yang, Taiqiang Wu, Jiahao Wang, Pengfei Hu, Ngai Wong, Yujiu Yang
Autonomous Droplet Microfluidic Design Framework with Large Language Models
Dinh-Nguyen Nguyen, Raymond Kai-Yu Tong, Ngoc-Duy Dinh