Multi-Task Learning

1074 papers with code • 6 benchmarks • 54 datasets

Multi-task learning aims to learn multiple different tasks simultaneously while maximizing performance on one or all of the tasks.

( Image credit: Cross-stitch Networks for Multi-task Learning )

Libraries

Use these libraries to find Multi-Task Learning models and implementations

Latest papers with no code

FastCAR: Fast Classification And Regression Multi-Task Learning via Task Consolidation for Modelling a Continuous Property Variable of Object Classes

no code yet • 26 Mar 2024

FastCAR involves a labeling transformation approach that can be used with a single-task regression network architecture.

Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation

no code yet • 26 Mar 2024

In this paper, we study the MTL problem with hybrid targets for the first time and propose the model named Hybrid Targets Learning Network (HTLNet) to explore task dependence and enhance optimization.

Enhanced Facet Generation with LLM Editing

no code yet • 25 Mar 2024

The second strategy is to enhance the facets by combining Large Language Model (LLM) and the small model.

Joint chest X-ray diagnosis and clinical visual attention prediction with multi-stage cooperative learning: enhancing interpretability

no code yet • 25 Mar 2024

As deep learning has become the state-of-the-art for computer-assisted diagnosis, interpretability of the automatic decisions is crucial for clinical deployment.

Multi-Task Learning with Multi-Task Optimization

no code yet • 24 Mar 2024

Multi-task learning solves multiple correlated tasks.

Leveraging Large Language Model-based Room-Object Relationships Knowledge for Enhancing Multimodal-Input Object Goal Navigation

no code yet • 21 Mar 2024

In this study, we propose a data-driven, modular-based approach, trained on a dataset that incorporates common-sense knowledge of object-to-room relationships extracted from a large language model.

Volumetric Environment Representation for Vision-Language Navigation

no code yet • 21 Mar 2024

To achieve a comprehensive 3D representation with fine-grained details, we introduce a Volumetric Environment Representation (VER), which voxelizes the physical world into structured 3D cells.

M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval

no code yet • 21 Mar 2024

In recent research, contrastive learning has proven to be a highly effective method for representation learning and is widely used for dense retrieval.

Open Knowledge Base Canonicalization with Multi-task Learning

no code yet • 21 Mar 2024

MulCanon unifies the learning objectives of these sub-tasks, and adopts a two-stage multi-task learning paradigm for training.

Human Detection in Realistic Through-the-Wall Environments using Raw Radar ADC Data and Parametric Neural Networks

no code yet • 20 Mar 2024

The radar signal processing algorithm is one of the core components in through-wall radar human detection technology.