AdaMTL: Adaptive Input-dependent Inference for Efficient Multi-Task Learning

17 April 2023

Papers citing "AdaMTL: Adaptive Input-dependent Inference for Efficient Multi-Task Learning"

5 / 5 papers shown

Title
$$\texttt{DINO-Foresight}$: Looking into the Future with DINO$ $\texttt{DINO-Foresight}$ : Looking into the Future with DINO Efstathios Karypidis Ioannis Kakogeorgiou Spyros Gidaris N. Komodakis AI4CE 87 2 0 16 Dec 2024
Swiss Army Knife: Synergizing Biases in Knowledge from Vision Foundation Models for Multi-Task Learning Yuxiang Lu Shengcao Cao Yu-xiong Wang 55 1 0 18 Oct 2024
MTLoRA: A Low-Rank Adaptation Approach for Efficient Multi-Task Learning Ahmed A. Agiza Marina Neseem Sherief Reda MoE 48 12 0 29 Mar 2024
MulT: An End-to-End Multitask Learning Transformer Deblina Bhattacharjee Tong Zhang Sabine Süsstrunk Mathieu Salzmann ViT 42 63 0 17 May 2022
Multi-task Learning with Attention for End-to-end Autonomous Driving Keishi Ishihara Anssi Kanervisto J. Miura Ville Hautamaki 42 60 0 21 Apr 2021