"multi-task learning" Papers
37 papers found
Efficient Depth Estimation for Unstable Stereo Camera Systems on AR Glasses
Yongfan Liu, Hyoukjun Kwon
Fast Rate Bounds for Multi-Task and Meta-Learning with Different Sample Sizes
Hossein Zakerinia, Christoph Lampert
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
MotionLab: Unified Human Motion Generation and Editing via the Motion-Condition-Motion Paradigm
Ziyan Guo, Zeyu HU, Na Zhao et al.
Resolving Token-Space Gradient Conflicts: Token Space Manipulation for Transformer-Based Multi-Task Learning
Wooseong Jeong, Kuk-Jin Yoon
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning
Yuxiang Lu, Shengcao Cao, Yu-Xiong Wang
Vulnerability-Aware Spatio-Temporal Learning for Generalizable Deepfake Video Detection
Dat NGUYEN, Marcella Astrid, Anis Kacem et al.
Z-Magic: Zero-shot Multiple Attributes Guided Image Creator
Yingying Deng, Xiangyu He, Fan Tang et al.
A Hierarchical Adaptive Multi-Task Reinforcement Learning Framework for Multiplier Circuit Design
Zhihai Wang, Jie Wang, Dongsheng Zuo et al.
A Multimodal, Multi-Task Adapting Framework for Video Action Recognition
Mengmeng Wang, Jiazheng Xing, Boyuan Jiang et al.
Bayesian Uncertainty for Gradient Aggregation in Multi-Task Learning
Idan Achituve, Idit Diamant, Arnon Netzer et al.
Careful with that Scalpel: Improving Gradient Surgery with an EMA
Yu-Guan Hsieh, James Thornton, Eugene Ndiaye et al.
Collaborative Learning with Different Labeling Functions
yuyang deng, Mingda Qiao
Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning
Jannik Deuschel, Caleb Ellington, Yingtao Luo et al.
CUDC: A Curiosity-Driven Unsupervised Data Collection Method with Adaptive Temporal Distances for Offline Reinforcement Learning
Chenyu Sun, Hangwei Qian, Chunyan Miao
DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding
Jincen Jiang, Qianyu Zhou, Yuhang Li et al.
DMTG: One-Shot Differentiable Multi-Task Grouping
Yuan Gao, Shuguo Jiang, Moran Li et al.
Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN, James Kwok
Every Node Is Different: Dynamically Fusing Self-Supervised Tasks for Attributed Graph Clustering
Pengfei Zhu, Qian Wang, Yu Wang et al.
Exploring Correlations of Self-Supervised Tasks for Graphs
Taoran Fang, Wei Chow, Yifei Sun et al.
Exploring Training on Heterogeneous Data with Mixture of Low-rank Adapters
Yuhang Zhou, Zhao Zihua, Siyuan Du et al.
Fair Resource Allocation in Multi-Task Learning
Hao Ban, Kaiyi Ji
Fast and Sample Efficient Multi-Task Representation Learning in Stochastic Contextual Bandits
Jiabin Lin, Shana Moothedath, Namrata Vaswani
Guarantees for Nonlinear Representation Learning: Non-identical Covariates, Dependent Data, Fewer Samples
Thomas T. Zhang, Bruce Lee, Ingvar Ziemann et al.
Learning with Adaptive Resource Allocation
Jing Wang, Miao Yu, Peng Zhao et al.
Localizing Task Information for Improved Model Merging and Compression
Ke Wang, Nikolaos Dimitriadis, Guillermo Ortiz-Jimenez et al.
Merging Multi-Task Models via Weight-Ensembling Mixture of Experts
Anke Tang, Li Shen, Yong Luo et al.
MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts
Jianan Zhou, Zhiguang Cao, Yaoxin Wu et al.
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks
Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi et al.
Quality-Diversity with Limited Resources
Ren-Jian Wang, Ke Xue, Cong Guan et al.
Representation Surgery for Multi-Task Model Merging
Enneng Yang, Li Shen, Zhenyi Wang et al.
Robust Multi-Task Learning with Excess Risks
Yifei He, Shiji Zhou, Guojun Zhang et al.
Sparse-to-dense Multimodal Image Registration via Multi-Task Learning
Kaining Zhang, Jiayi Ma
STEM: Unleashing the Power of Embeddings for Multi-Task Recommendation
Liangcai Su, Junwei Pan, Ximei Wang et al.
Thermometer: Towards Universal Calibration for Large Language Models
Maohao Shen, Subhro Das, Kristjan Greenewald et al.
Towards Modular LLMs by Building and Reusing a Library of LoRAs
Oleksiy Ostapenko, Zhan Su, Edoardo Ponti et al.
VersatileGaussian: Real-time Neural Rendering for Versatile Tasks using Gaussian Splatting
Renjie Li, Zhiwen Fan, Bohua Wang et al.