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/ncbi/biorex

공식 코드

BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets

https://github.com/nethermanpro/comsl

공식 코드

ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation

https://github.com/neu-statsml-research/task-modeling

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Identification of Negative Transfers in Multitask Learning Using Surrogate Models

https://github.com/neukg/MultiIE

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An Effective System for Multi-format Information Extraction

https://github.com/neukg/robustmrc

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An Understanding-Oriented Robust Machine Reading Comprehension Model

https://github.com/neulab/cmu-multinlp

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Generalizing Natural Language Analysis through Span-relation Representations

https://github.com/neurai-lab/mtsl

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Multi-Task Structural Learning using Local Task Similarity induced Neuron Creation and Removal

https://github.com/neurai-lab/progressivedecoderfusion

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Curbing Task Interference using Representation Similarity-Guided Multi-Task Feature Sharing

https://github.com/news-vt/makassar-ml

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A Transformer Framework for Data Fusion and Multi-Task Learning in Smart Cities

https://github.com/nghuyong/MTL-SLAM

공식 코드

Multi-task Learning for Low-resource Second Language Acquisition Modeling

https://github.com/nguyentthong/CrossSummOptimalTransport

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Improving Neural Cross-Lingual Summarization via Employing Optimal Transport Distance for Knowledge Distillation

https://github.com/niiceMing/CMTA

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Contrastive Modules with Temporal Attention for Multi-Task Reinforcement Learning

https://github.com/nik-dim/pamal

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Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models

https://github.com/nik-dim/tall_masks

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Localizing Task Information for Improved Model Merging and Compression

https://github.com/nilakshdas/skelevision

공식 코드

SkeleVision: Towards Adversarial Resiliency of Person Tracking with Multi-Task Learning

https://github.com/niloofaryousefi/ECML2015

공식 코드

Multi-Task Learning with Group-Specific Feature Space Sharing

https://github.com/ningyu1991/DefectDetection

공식 코드

Learning to Detect Multiple Photographic Defects

https://github.com/niuchuangnn/m3fm

공식 코드

Specialty-Oriented Generalist Medical AI for Chest CT Screening

https://github.com/nlp-waseda/expr-exper-emo

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Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions

https://github.com/nlp2ct/unite

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UniTE: Unified Translation Evaluation

https://github.com/nlpfreshman0/more

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MoRE: A Mixture of Low-Rank Experts for Adaptive Multi-Task Learning

https://github.com/nms05/audio-visual-deception-detection-dolos-dataset-and-parameter-efficient-crossmodal-learning

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Audio-Visual Deception Detection: DOLOS Dataset and Parameter-Efficient Crossmodal Learning

https://github.com/northsummer/proximityqa

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Proximity QA: Unleashing the Power of Multi-Modal Large Language Models for Spatial Proximity Analysis

https://github.com/nphamdinh/transfer-learning-vsr-mouthing-sign-language

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Transfer Learning from Visual Speech Recognition to Mouthing Recognition in German Sign Language

https://github.com/numenta/htmpapers

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Avoiding Catastrophe: Active Dendrites Enable Multi-Task Learning in Dynamic Environments

https://github.com/octopusli/neurips2022-traffic4cast

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Multi-task Learning for Sparse Traffic Forecasting

https://github.com/ofa-sys/ofa

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MMSpeech: Multi-modal Multi-task Encoder-Decoder Pre-training for Speech Recognition

https://github.com/ofa-sys/ofasys

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OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models

https://github.com/omarfoq/fedem

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Federated Multi-Task Learning under a Mixture of Distributions

https://github.com/openai/evals

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GPT-4 Technical Report

https://github.com/openai/gpt-3

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Language Models are Few-Shot Learners

https://github.com/openai/human-eval

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Evaluating Large Language Models Trained on Code

https://github.com/opendilab/LightZero

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UniZero: Generalized and Efficient Planning with Scalable Latent World Models

https://github.com/optmn-lab/-bilb4mtl

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LDC-MTL: Balancing Multi-Task Learning through Scalable Loss Discrepancy Control

https://github.com/optmn-lab/fairgrad

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Fair Resource Allocation in Multi-Task Learning

https://github.com/optmn-lab/ldc-mtl

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LDC-MTL: Balancing Multi-Task Learning through Scalable Loss Discrepancy Control

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