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Task Arithmetic

A task vector specifies a direction in the weight space of a pre-trained model, such that movement in that direction improves performance on the task. We build task vectors by subtracting the weights of a pre-trained model from the weights of the same model after fine-tuning on a task. We show that these task vectors can be modified and combined together through arithmetic operations such as negation and addition, and the behavior of the resulting model is steered accordingly.

Papers

Showing 1120 of 61 papers

TitleStatusHype
Concrete Subspace Learning based Interference Elimination for Multi-task Model FusionCode1
Model Merging by Uncertainty-Based Gradient MatchingCode1
Parameter Efficient Multi-task Model Fusion with Partial LinearizationCode1
AdaMerging: Adaptive Model Merging for Multi-Task LearningCode1
Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained ModelsCode1
An Empirical Study of Multimodal Model MergingCode1
Transferring Visual Explainability of Self-Explaining Models through Task Arithmetic0
DuET: Dual Incremental Object Detection via Exemplar-Free Task Arithmetic0
CultureMERT: Continual Pre-Training for Cross-Cultural Music Representation Learning0
Subspace-Boosted Model Merging0
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