2025 "multi-task learning" Papers
17 papers found
Decouple-Then-Merge: Finetune Diffusion Models as Multi-Task Learning
Qianli Ma, Xuefei Ning, Dongrui Liu et al.
CVPR 2025posterarXiv:2410.06664
1
citations
Efficient Depth Estimation for Unstable Stereo Camera Systems on AR Glasses
Yongfan Liu, Hyoukjun Kwon
CVPR 2025posterarXiv:2411.10013
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
Hossein Zakerinia, Christoph Lampert
NeurIPS 2025posterarXiv:2505.15496
1
citations
FedRAM: Federated Reweighting and Aggregation for Multi-Task Learning
Fan Wu, Xinyu Yan, Jiabei Liu et al.
NeurIPS 2025poster
FREE-Merging: Fourier Transform for Efficient Model Merging
Shenghe Zheng, Hongzhi Wang
ICCV 2025posterarXiv:2411.16815
3
citations
GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning
Minghao Xu, Yunteng Geng, Yihang Zhang et al.
ICLR 2025posterarXiv:2405.16206
6
citations
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
ICLR 2025posterarXiv:2509.08058
4
citations
LiFT: Learning to Fine-Tune via Bayesian Parameter Efficient Meta Fine-Tuning
Minyoung Kim, Timothy Hospedales
ICLR 2025poster
1
citations
MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm
Ziyan Guo, Zeyu HU, Na Zhao et al.
ICCV 2025posterarXiv:2502.02358
12
citations
Progressive Homeostatic and Plastic Prompt Tuning for Audio-Visual Multi-Task Incremental Learning
Jiong Yin, Liang Li, Jiehua Zhang et al.
ICCV 2025posterarXiv:2507.21588
1
citations
Provable Meta-Learning with Low-Rank Adaptations
Jacob Block, Sundararajan Srinivasan, Liam Collins et al.
NeurIPS 2025posterarXiv:2410.22264
Resolving Token-Space Gradient Conflicts: Token Space Manipulation for Transformer-Based Multi-Task Learning
Wooseong Jeong, Kuk-Jin Yoon
ICCV 2025posterarXiv:2507.07485
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Yuxiang Lu, Shengcao Cao, Yu-Xiong Wang
ICLR 2025posterarXiv:2410.14633
6
citations
Task Vector Quantization for Memory-Efficient Model Merging
Youngeun Kim, Seunghwan Lee, Aecheon Jung et al.
ICCV 2025posterarXiv:2503.06921
3
citations
Towards Minimizing Feature Drift in Model Merging: Layer-wise Task Vector Fusion for Adaptive Knowledge Integration
Wenju Sun, Qingyong Li, Wen Wang et al.
NeurIPS 2025posterarXiv:2505.23859
2
citations
Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detection
Dat NGUYEN, Marcella Astrid, Anis Kacem et al.
ICCV 2025posterarXiv:2501.01184
Z-Magic: Zero-shot Multiple Attributes Guided Image Creator
Yingying Deng, Xiangyu He, Fan Tang et al.
CVPR 2025posterarXiv:2503.12124