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/kjytay/fwelnet

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Feature-weighted elastic net: using "features of features" for better prediction

https://github.com/knowledgetechnologyuhh/grid-3d

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What is Right for Me is Not Yet Right for You: A Dataset for Grounding Relative Directions via Multi-Task Learning

https://github.com/kosciukiewicz/similarity_based_memory_re

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https://github.com/kris927b/JobStack

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De-identification of Privacy-related Entities in Job Postings

https://github.com/kris927b/skillspan

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SkillSpan: Hard and Soft Skill Extraction from English Job Postings

https://github.com/krystalan/awesomeseg

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Incorporating Commonsense Knowledge into Story Ending Generation via Heterogeneous Graph Networks

https://github.com/kushalchawla/CaSiNo

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CaSiNo: A Corpus of Campsite Negotiation Dialogues for Automatic Negotiation Systems

https://github.com/kw2934/armul

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Adaptive and Robust Multi-Task Learning

https://github.com/kyrie-23/linear_task_arithmetic

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Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic

https://github.com/kyrie-23/task_arithmetic_tangent

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Fine-Tuning Attention Modules Only: Enhancing Weight Disentanglement in Task Arithmetic

https://github.com/labull/engineeringpatternrecognition

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Hierarchical Bayesian Modelling for Knowledge Transfer Across Engineering Fleets via Multitask Learning

https://github.com/lalithjets/domain-adaptation-in-mtl

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Task-Aware Asynchronous Multi-Task Model with Class Incremental Contrastive Learning for Surgical Scene Understanding

https://github.com/lalithjets/global-reasoned-multi-task-model

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Global-Reasoned Multi-Task Learning Model for Surgical Scene Understanding

https://github.com/lalonderodney/X-Caps

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Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses

https://github.com/lbechberger/LearningPsychologicalSpaces

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Grounding Psychological Shape Space in Convolutional Neural Networks

https://github.com/lcmhoang/hmg-dynamics

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Deep Homography Estimation for Dynamic Scenes

https://github.com/lct-rug-2022/edos-2023

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LCT-1 at SemEval-2023 Task 10: Pre-training and Multi-task Learning for Sexism Detection and Classification

https://github.com/leaf-ai/muir

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Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains

https://github.com/learnables/learn2learn

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When MAML Can Adapt Fast and How to Assist When It Cannot

https://github.com/leedaeuni/Temporal-Symptom-Aware-Multitask-Learning-KDD23

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Towards Suicide Prevention from Bipolar Disorder with Temporal Symptom-Aware Multitask Learning

https://github.com/leeroo-ai/leeroo_orchestrator

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Routoo: Learning to Route to Large Language Models Effectively

https://github.com/lely475/ctplab_semicol2023

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Multi-task learning for tissue segmentation and tumor detection in colorectal cancer histology slides

https://github.com/lhmtriet/deepcva

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DeepCVA: Automated Commit-level Vulnerability Assessment with Deep Multi-task Learning

https://github.com/lhoangan/multas

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Data exploitation: multi-task learning of object detection and semantic segmentation on partially annotated data

https://github.com/lhoyer/improving_segmentation_with_selfsupervised_depth

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Improving Semi-Supervised and Domain-Adaptive Semantic Segmentation with Self-Supervised Depth Estimation

https://github.com/liangcaisu/stem

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STEM: Unleashing the Power of Embeddings for Multi-task Recommendation

https://github.com/liangzid/MERGE

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MERGE: Fast Private Text Generation

https://github.com/lifu-tu/Study-NLP-Robustness

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An Empirical Study on Robustness to Spurious Correlations using Pre-trained Language Models

https://github.com/lin-tianwei/teamlora

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TeamLoRA: Boosting Low-Rank Adaptation with Expert Collaboration and Competition

https://github.com/linzwcs/see

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SEE: Continual Fine-tuning with Sequential Ensemble of Experts

https://github.com/lishuhuai527/coco-unihuman

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You Only Learn One Query: Learning Unified Human Query for Single-Stage Multi-Person Multi-Task Human-Centric Perception

https://github.com/litian96/ditto

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Ditto: Fair and Robust Federated Learning Through Personalization

https://github.com/liuqidong07/moelora-peft

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When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications

https://github.com/liuruijin17/clgo

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Learning to Predict 3D Lane Shape and Camera Pose from a Single Image via Geometry Constraints

https://github.com/lixin4ever/E2E-TBSA

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An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis

https://github.com/lly00412/sednet

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Learning the Distribution of Errors in Stereo Matching for Joint Disparity and Uncertainty Estimation

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