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
Unified Triplet-Level Hallucination Evaluation for Large Vision-Language Models
Junjie Wu, Tsz Ting Chung, Kai Chen, Dit-Yan Yeung
A Study of Secure Algorithms for Vertical Federated Learning: Take Secure Logistic Regression as an Example
Huan-Chih Wang, Ja-Ling Wu
EnsIR: An Ensemble Algorithm for Image Restoration via Gaussian Mixture Models
Shangquan Sun, Wenqi Ren, Zikun Liu, Hyunhee Park, Rui Wang, Xiaochun Cao
HijackRAG: Hijacking Attacks against Retrieval-Augmented Large Language Models
Yucheng Zhang, Qinfeng Li, Tianyu Du, Xuhong Zhang, Xinkui Zhao, Zhengwen Feng, Jianwei Yin
st-DTPM: Spatial-Temporal Guided Diffusion Transformer Probabilistic Model for Delayed Scan PET Image Prediction
Ran Hong, Yuxia Huang, Lei Liu, Zhonghui Wu, Bingxuan Li, Xuemei Wang, Qiegen Liu
One Prompt to Verify Your Models: Black-Box Text-to-Image Models Verification via Non-Transferable Adversarial Attacks
Ji Guo, Wenbo Jiang, Rui Zhang, Guoming Lu, Hongwei Li, Weiren Wu
A Comprehensive Study on Quantization Techniques for Large Language Models
Jiedong Lang, Zhehao Guo, Shuyu Huang
Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models
Rishabh Adiga, Besmira Nushi, Varun Chandrasekaran
Image2Struct: Benchmarking Structure Extraction for Vision-Language Models
Josselin Somerville Roberts, Tony Lee, Chi Heem Wong, Michihiro Yasunaga, Yifan Mai, Percy Liang
Natural Language Inference Improves Compositionality in Vision-Language Models
Paola Cascante-Bonilla, Yu Hou, Yang Trista Cao, Hal Daumé III, Rachel Rudinger
A Systematic Literature Review of Spatio-Temporal Graph Neural Network Models for Time Series Forecasting and Classification
Flavio Corradini, Marco Gori, Carlo Lucheroni, Marco Piangerelli, Martina Zannotti
Gnothi Seauton: Empowering Faithful Self-Interpretability in Black-Box Models
Shaobo Wang, Hongxuan Tang, Mingyang Wang, Hongrui Zhang, Xuyang Liu, Weiya Li, Xuming Hu, Linfeng Zhang
Model Equality Testing: Which Model Is This API Serving?
Irena Gao, Percy Liang, Carlos Guestrin
Detection-Guided Deep Learning-Based Model with Spatial Regularization for Lung Nodule Segmentation
Jiasen Zhang, Mingrui Yang, Weihong Guo, Brian A. Xavier, Michael Bolen, Xiaojuan Li
On-Site Precise Screening of SARS-CoV-2 Systems Using a Channel-Wise Attention-Based PLS-1D-CNN Model with Limited Infrared Signatures
Wenwen Zhang, Zhouzhuo Tang, Yingmei Feng, Xia Yu, Qi Jie Wang, Zhiping Lin
Super-resolved virtual staining of label-free tissue using diffusion models
Yijie Zhang, Luzhe Huang, Nir Pillar, Yuzhu Li, Hanlong Chen, Aydogan Ozcan
OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery
Philipe Dias, Aristeidis Tsaris, Jordan Bowman, Abhishek Potnis, Jacob Arndt, H. Lexie Yang, Dalton Lunga
Model merging with SVD to tie the Knots
George Stoica, Pratik Ramesh, Boglarka Ecsedi, Leshem Choshen, Judy Hoffman