"pre-trained models" Papers
29 papers found
Conference
AnaCP: Toward Upper-Bound Continual Learning via Analytic Contrastive Projection
Saleh Momeni, Changnan Xiao, Bing Liu
BiLoRA: Almost-Orthogonal Parameter Spaces for Continual Learning
Hao Zhu, Yifei Zhang, Junhao Dong et al.
CAMH: Advancing Model Hijacking Attack in Machine Learning
Xing He, Jiahao Chen, Yuwen Pu et al.
CAPrompt: Cyclic Prompt Aggregation for Pre-Trained Model Based Class Incremental Learning
Qiwei Li, Jiahuan Zhou
CLDyB: Towards Dynamic Benchmarking for Continual Learning with Pre-trained Models
Shengzhuang Chen, Yikai Liao, Xiaoxiao Sun et al.
Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
Dipam Goswami, Simone Magistri, Kai Wang et al.
Dataset Ownership Verification for Pre-trained Masked Models
Yuechen Xie, Jie Song, Yicheng Shan et al.
Endowing Visual Reprogramming with Adversarial Robustness
Shengjie Zhou, Xin Cheng, Haiyang Xu et al.
LOMIA: Label-Only Membership Inference Attacks against Pre-trained Large Vision-Language Models
Yihao LIU, Xinqi Lyu, Dong Wang et al.
Mind Control through Causal Inference: Predicting Clean Images from Poisoned Data
Mengxuan Hu, Zihan Guan, Yi Zeng et al.
MOS: Model Surgery for Pre-Trained Model-Based Class-Incremental Learning
Hai-Long Sun, Da-Wei Zhou, Hanbin Zhao et al.
Mysteries of the Deep: Role of Intermediate Representations in Out of Distribution Detection
Ignacio Meza De la Jara, Cristian Rodriguez-Opazo, Damien Teney et al.
PEARL: Input-Agnostic Prompt Enhancement with Negative Feedback Regulation for Class-Incremental Learning
Yongchun Qin, Pengfei Fang, Hui Xue
Progressive Parameter Efficient Transfer Learning for Semantic Segmentation
Nan Zhou, Huiqun Wang, Yaoyan Zheng et al.
Unified Transferability Metrics for Time Series Foundation Models
Weiyang Zhang, Xinyang Chen, Xiucheng Li et al.
BDIQA: A New Dataset for Video Question Answering to Explore Cognitive Reasoning through Theory of Mind
Yuanyuan Mao, Xin Lin, Qin Ni et al.
Constructing Concept-based Models to Mitigate Spurious Correlations with Minimal Human Effort
Jeeyung Kim, Ze Wang, Qiang Qiu
Epistemic Uncertainty Quantification For Pre-Trained Neural Networks
Hanjing Wang, Qiang Ji
Erasing the Bias: Fine-Tuning Foundation Models for Semi-Supervised Learning
Kai Gan, Tong Wei
Event-Adapted Video Super-Resolution
Zeyu Xiao, Dachun Kai, Yueyi Zhang et al.
LEAD: Exploring Logit Space Evolution for Model Selection
Zixuan Hu, Xiaotong Li, SHIXIANG TANG et al.
LEVI: Generalizable Fine-tuning via Layer-wise Ensemble of Different Views
Yuji Roh, Qingyun Liu, Huan Gui et al.
Make Me a BNN: A Simple Strategy for Estimating Bayesian Uncertainty from Pre-trained Models
Gianni Franchi, Olivier Laurent, Maxence Leguéry et al.
Model Stock: All we need is just a few fine-tuned models
Dong-Hwan Jang, Sangdoo Yun, Dongyoon Han
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning
Chendi Wang, Yuqing Zhu, Weijie Su et al.
ProS: Prompting-to-simulate Generalized knowledge for Universal Cross-Domain Retrieval
Fang Kaipeng, Jingkuan Song, Lianli Gao et al.
SeA: Semantic Adversarial Augmentation for Last Layer Features from Unsupervised Representation Learning
Qi Qian, Yuanhong Xu, JUHUA HU
Text-Conditioned Resampler For Long Form Video Understanding
Bruno Korbar, Yongqin Xian, Alessio Tonioni et al.
Text Grouping Adapter: Adapting Pre-trained Text Detector for Layout Analysis
Tianci Bi, Xiaoyi Zhang, Zhizheng Zhang et al.