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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/hankook/SLA

공식 코드

Self-supervised Label Augmentation via Input Transformations

https://github.com/haomengz/hyperpc

공식 코드

Hyperspherical Embedding for Point Cloud Completion

https://github.com/harmonbhasin/curriculum_learning_icl

공식 코드

How does Multi-Task Training Affect Transformer In-Context Capabilities? Investigations with Function Classes

https://github.com/harshs27/neural-graphical-models

공식 코드

Neural Graphical Models

https://github.com/harshs27/uglad

공식 코드

uGLAD: Sparse graph recovery by optimizing deep unrolled networks

https://github.com/hassanmojab/metanli

공식 코드

Persian Natural Language Inference: A Meta-learning approach

https://github.com/hassyGo/charNgram2vec

공식 코드

A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks

https://github.com/hendrycks/test

공식 코드

Measuring Massive Multitask Language Understanding

https://github.com/hengxyz/Dynamic_multi-task-learning

공식 코드

Dynamic Multi-Task Learning for Face Recognition with Facial Expression

https://github.com/hengxyz/cari-visual-recognition-via-multitask-learning

공식 코드

Dynamic Deep Multi-task Learning for Caricature-Visual Face Recognition

https://github.com/hguimaraes/robustdistiller

공식 코드

An Efficient End-to-End Approach to Noise Invariant Speech Features via Multi-Task Learning

https://github.com/hiyouga/llama-factory

공식 코드

Language Models are Homer Simpson! Safety Re-Alignment of Fine-tuned Language Models through Task Arithmetic

https://github.com/hku-medai/mult-ehr

공식 코드

Multi-task Heterogeneous Graph Learning on Electronic Health Records

https://github.com/hku-tasr/anywheredoor

공식 코드

AnywhereDoor: Multi-Target Backdoor Attacks on Object Detection

https://github.com/hkuedl/Latent-Variable-based-Optimization

공식 코드

Dimension-reduced Optimization of Multi-zone Thermostatically Controlled Loads

https://github.com/hltchkust/framing-bias-metric

공식 코드

NeuS: Neutral Multi-News Summarization for Mitigating Framing Bias

https://github.com/hmarkc/FW-Merging

공식 코드

FW-Merging: Scaling Model Merging with Frank-Wolfe Optimization

https://github.com/holistic-video-understanding/HVU-Dataset

공식 코드

Large Scale Holistic Video Understanding

https://github.com/hoon9405/genhpf

공식 코드

GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

https://github.com/hoon9405/unihpf

공식 코드

GenHPF: General Healthcare Predictive Framework with Multi-task Multi-source Learning

https://github.com/houpingy/ea-gcl

공식 코드

Unbiased and Robust: External Attention-enhanced Graph Contrastive Learning for Cross-domain Sequential Recommendation

https://github.com/htang113/multi-task-electronic

공식 코드

Multi-task learning for molecular electronic structure approaching coupled-cluster accuracy

https://github.com/hu64/SpotNet

공식 코드

SpotNet: Self-Attention Multi-Task Network for Object Detection

https://github.com/huanghanchi/camrl

공식 코드

Curriculum-based Asymmetric Multi-task Reinforcement Learning

https://github.com/huangkun101230/360mtlgeometricestimation

공식 코드

Multi-task Geometric Estimation of Depth and Surface Normal from Monocular 360° Images

https://github.com/huangyjhust/3D-RU-Net

공식 코드

3D RoI-aware U-Net for Accurate and Efficient Colorectal Tumor Segmentation

https://github.com/huaqinghe/joined

공식 코드

JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection

https://github.com/hushell/sib_meta_learn

공식 코드

Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

https://github.com/hustvl/yolop

공식 코드

YOLOP: You Only Look Once for Panoptic Driving Perception

https://github.com/hw-du/emkd

공식 코드

Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation

https://github.com/hwwang55/MKR

공식 코드

Multi-Task Feature Learning for Knowledge Graph Enhanced Recommendation

https://github.com/hz-zhu/mt-unet

공식 코드

Multi-task UNet: Jointly Boosting Saliency Prediction and Disease Classification on Chest X-ray Images

https://github.com/hzakerinia/mtl

공식 코드

From Low Intrinsic Dimensionality to Non-Vacuous Generalization Bounds in Deep Multi-Task Learning

https://github.com/iacercalixto/variational_mmt

공식 코드

Latent Variable Model for Multi-modal Translation

https://github.com/iamjanvijay/meet

공식 코드

Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding

https://github.com/iamjanvijay/set

공식 코드

Entity Tracking via Effective Use of Multi-Task Learning Model and Mention-guided Decoding

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