Papers with Code 아카이브

Multi-Task Learning

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하위 태스크: 2
평가표: 8
보존된 평가 기록: 16

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

<span style="color:grey; opacity: 0.6">( Image credit: Cross-stitch Networks for Multi-task Learning )</span>

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/ga1i13o/jist

공식 코드

JIST: Joint Image and Sequence Training for Sequential Visual Place Recognition

https://github.com/gaa-uam/r-mtgb

공식 코드

Robust-Multi-Task Gradient Boosting

https://github.com/gabriel-sgama/semantic-superpoint

공식 코드

Semantic SuperPoint: A Deep Semantic Descriptor

https://github.com/ganchengguang/SLG-framework

공식 코드

Sentence-to-Label Generation Framework for Multi-task Learning of Japanese Sentence Classification and Named Entity Recognition

https://github.com/gao-xiao-bai/UniGDD

공식 코드

UniGDD: A Unified Generative Framework for Goal-Oriented Document-Grounded Dialogue

https://github.com/garynlfd/kfc

공식 코드

KFC: Kinship Verification with Fair Contrastive Loss and Multi-Task Learning

https://github.com/gatorsense/matl

공식 코드

Multi-Task Learning with Multi-Annotation Triplet Loss for Improved Object Detection

https://github.com/geopanag/IMINFECTOR

공식 코드

Multi-task Learning for Influence Estimation and Maximization

https://github.com/gingsmith/fmtl

공식 코드

Federated Multi-Task Learning

https://github.com/girishvn/bigsmall

공식 코드

BigSmall: Efficient Multi-Task Learning for Disparate Spatial and Temporal Physiological Measurements

https://github.com/gloewing/smtl

공식 코드

Multi-Task Learning for Sparsity Pattern Heterogeneity: Statistical and Computational Perspectives

https://github.com/glycanml/glycanml

공식 코드

GlycanML: A Multi-Task and Multi-Structure Benchmark for Glycan Machine Learning

https://github.com/gohyojun15/ANT_diffusion

공식 코드

Addressing Negative Transfer in Diffusion Models

https://github.com/gokulkarthik/deformable-detr

공식 코드

An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers

https://github.com/gokulkarthik/detr

공식 코드

An Empirical Study Of Self-supervised Learning Approaches For Object Detection With Transformers

https://github.com/google-research/ALBERT

공식 코드

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

https://github.com/google-research/big_vision

공식 코드

A Study of Autoregressive Decoders for Multi-Tasking in Computer Vision

https://github.com/google-research/federated

공식 코드

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

https://github.com/google-research/federated/tree/master/personalization_benchmark

공식 코드

Motley: Benchmarking Heterogeneity and Personalization in Federated Learning

https://github.com/google-research/google-research

공식 코드

Efficiently Identifying Task Groupings for Multi-Task Learning

https://github.com/google-research/google-research/tree/master/dselect_k_moe

공식 코드

DSelect-k: Differentiable Selection in the Mixture of Experts with Applications to Multi-Task Learning

https://github.com/google-research/magvit

공식 코드

MAGVIT: Masked Generative Video Transformer

https://github.com/google-research/robopianist

공식 코드

RoboPianist: Dexterous Piano Playing with Deep Reinforcement Learning

https://github.com/google-research/text-to-text-transfer-transformer

공식 코드

ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning

https://github.com/google/gematria

공식 코드

GRANITE: A Graph Neural Network Model for Basic Block Throughput Estimation

https://github.com/google/next-prediction

공식 코드

Peeking into the Future: Predicting Future Person Activities and Locations in Videos

https://github.com/gortizji/tangent_task_arithmetic

공식 코드

Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models

https://github.com/graph-team/apgl4sr

공식 코드

APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

https://github.com/grtzsohalf/SpeechNet-codebase

공식 코드

SpeechNet: A Universal Modularized Model for Speech Processing Tasks

https://github.com/gsarti/interpreting-complexity

공식 코드

UmBERTo-MTSA @ AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised Annotations

https://github.com/gstoica27/JRRELP

공식 코드

Improving Relation Extraction by Leveraging Knowledge Graph Link Prediction

https://github.com/gt4sd/multitask_text_and_chemistry_t5

공식 코드

Unifying Molecular and Textual Representations via Multi-task Language Modelling

https://github.com/gvalvano/multiscale-adversarial-attention-gates

공식 코드

Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates

https://github.com/hahahawu/CSAGN

공식 코드

CSAGN: Conversational Structure Aware Graph Network for Conversational Semantic Role Labeling

https://github.com/haidnguyen0909/mwgrad

공식 코드

Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization

https://github.com/hal-lucination/segfuse

공식 코드

360 Depth Estimation in the Wild -- The Depth360 Dataset and the SegFuse Network

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