https://github.com/Chen-Wang-CUHK/KG-KE-KR-M
공식 코드An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction
Papers with Code 아카이브
Multi-Task Learning
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 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/Chenzhaowei13/Light-Condition-Style-Transfer
공식 코드https://github.com/ChongjianGE/MetaBEV
공식 코드MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation
https://github.com/ChuchuHan/DMRNet
공식 코드https://github.com/Code-Triad/Large-Language-Models-for-Ingredient-Substitution
공식 코드https://github.com/CogComp/MultiOpEd
공식 코드https://github.com/ConvLab/ConvLab-3/tree/emo_loop/convlab/dst/emodst/modeling
공식 코드https://github.com/CyberAgentAILab/flex-dm
공식 코드https://github.com/DaoD/KPN
공식 코드Proactive Retrieval-based Chatbots based on Relevant Knowledge and Goals
https://github.com/DaphneAntotsiou/MAPS
공식 코드Modular Adaptive Policy Selection for Multi-Task Imitation Learning through Task Division
https://github.com/Dilruk/CnGAN
공식 코드https://github.com/EPFL-VILAB/XTConsistency
공식 코드https://github.com/EdisonNi-hku/when-does-mtl-work
공식 코드When Does Aggregating Multiple Skills with Multi-Task Learning Work? A Case Study in Financial NLP
https://github.com/EducationalTestingService/CATS
공식 코드Two-Level Transformer and Auxiliary Coherence Modeling for Improved Text Segmentation
https://github.com/EiraZhang/LACO
공식 코드Enhancing Label Correlation Feedback in Multi-Label Text Classification via Multi-Task Learning
https://github.com/Engler93/Self-Supervised-Autogenous-Learning
공식 코드Contextual Classification Using Self-Supervised Auxiliary Models for Deep Neural Networks
https://github.com/EnnengYang/AdaMerging
공식 코드https://github.com/EriCongMa/E2E_TIT_With_MT
공식 코드Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task
https://github.com/EricFH/salient_object_ranking_with_PPA
공식 코드https://github.com/Exploration-Lab/FineGrained-Emotion-Prediciton-Using-Definitions
공식 코드Fine-Grained Emotion Prediction by Modeling Emotion Definitions
https://github.com/F2-Song/PromptSLU
공식 코드A Unified Framework for Multi-intent Spoken Language Understanding with prompting
https://github.com/FedML-AI/SpreadGNN
공식 코드SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks
https://github.com/Francois-Aubet/EQuANt
공식 코드https://github.com/FraunhoferMEVIS/MedicalMultitaskModeling
공식 코드Overcoming Data Scarcity in Biomedical Imaging with a Foundational Multi-Task Model
https://github.com/GMago-LeWay/GECFramework
공식 코드Detection-Correction Structure via General Language Model for Grammatical Error Correction
https://github.com/GeneZC/OTE-MTL
공식 코드A Multi-task Learning Framework for Opinion Triplet Extraction
https://github.com/Georgetown-IR-Lab/ExtendedSumm
공식 코드https://github.com/GiorgosPanagopoulos/IMINFECTOR
공식 코드Multi-task Learning for Influence Estimation and Maximization
https://github.com/Gitsamshi/WeakVRD-Captioning
공식 코드https://github.com/GuanRunwei/Achelous
공식 코드https://github.com/GuanyaShi/Online-Meta-Adaptive-Control
공식 코드https://github.com/HSE-asavchenko/face-emotion-recognition
공식 코드https://github.com/HassanHayat08/Recognizing-Emotions-evoked-by-Movies-usingMultitask-Learning
공식 코드Recognizing Emotions evoked by Movies using Multitask Learning
https://github.com/Hazel1994/Visually_Grounded_Word_Embeddings
공식 코드Learning Zero-Shot Multifaceted Visually Grounded Word Embeddings via Multi-Task Training
https://github.com/HenrryBryant/Scene-Recognition-in-3D
공식 코드https://github.com/HongyuGong/Abusive-Language-Detection-Categorization
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.