https://github.com/GauravVanmane/Detection-of-Insincere-Questions/blob/main/Detection%20Of%20Insincere%20Questions.ipynb
공식 코드Detecting Insincere Questions from Text: A Transfer Learning Approach
Papers with Code 아카이브
Transfer Learning
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Transfer Learning is a machine learning technique where a model trained on one task is re-purposed and fine-tuned for a related, but different task. The idea behind transfer learning is to leverage the knowledge learned from a pre-trained model to solve a new, but related problem. This can be useful in situations where there is limited data available to train a new model from scratch, or when the new task is similar enough to the original task that the pre-trained model can be adapted to the new problem with only minor modifications.
<span style="color:grey; opacity: 0.6">( Image credit: Subodh Malgonde )</span>
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/GeneZC/OTE-MTL
공식 코드A Multi-task Learning Framework for Opinion Triplet Extraction
https://github.com/GentleZhu/EGI
공식 코드Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
https://github.com/Georgetown-IR-Lab/ExtendedSumm
공식 코드https://github.com/GhadaSokar/Invariant-Representation-for-Continual-Learning
공식 코드https://github.com/Giguelingueling/MyoArmbandDataset
공식 코드Deep Learning for Electromyographic Hand Gesture Signal Classification Using Transfer Learning
https://github.com/GiorgosPanagopoulos/IMINFECTOR
공식 코드Multi-task Learning for Influence Estimation and Maximization
https://github.com/GiorgosPanagopoulos/pandemic_tgnn
공식 코드https://github.com/Gitsamshi/WeakVRD-Captioning
공식 코드https://github.com/GongShuai8210/PLAN
공식 코드Federated Domain Generalization via Prompt Learning and Aggregation
https://github.com/GregoireMialon/screening_samples
공식 코드On Inductive Biases for Machine Learning in Data Constrained Settings
https://github.com/GuanRunwei/Achelous
공식 코드https://github.com/GuanyaShi/Online-Meta-Adaptive-Control
공식 코드https://github.com/Gumpest/AvatarKD
공식 코드Avatar Knowledge Distillation: Self-ensemble Teacher Paradigm with Uncertainty
https://github.com/GuyHacohen/curriculum_learning
공식 코드On The Power of Curriculum Learning in Training Deep Networks
https://github.com/H-shw/futurepedia
공식 코드Not All Languages are Equal: Insights into Multilingual Retrieval-Augmented Generation
https://github.com/HCPLab-SYSU/SKT
공식 코드https://github.com/HIK-LAB/Unsupervised-Image-Classification
공식 코드Unsupervised Image Classification for Deep Representation Learning
https://github.com/HIT-ICES/AL-NER
공식 코드LTP: A New Active Learning Strategy for CRF-Based Named Entity Recognition
https://github.com/HIT-SMC/DRL_solver
공식 코드https://github.com/HJYao00/Side4Video
공식 코드Side4Video: Spatial-Temporal Side Network for Memory-Efficient Image-to-Video Transfer Learning
https://github.com/HKUST-KnowComp/AttackTransferLearning
공식 코드Two Sides of the Same Coin: White-box and Black-box Attacks for Transfer Learning
https://github.com/HKUST-KnowComp/NeuralSubgraphCounting
공식 코드https://github.com/HKUST-KnowComp/cfet
공식 코드https://github.com/HLTCHKUST/BiToD
공식 코드BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling
https://github.com/HSE-asavchenko/face-emotion-recognition
공식 코드https://github.com/HamidBostani2021/robust-Android-malware-detector
공식 코드https://github.com/HaokunChen245/FedDAT
공식 코드FedDAT: An Approach for Foundation Model Finetuning in Multi-Modal Heterogeneous Federated Learning
https://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/Helsinki-NLP/HBMP
공식 코드Sentence Embeddings in NLI with Iterative Refinement Encoders
https://github.com/HenrryBryant/Scene-Recognition-in-3D
공식 코드https://github.com/HobbitLong/RepDistiller
공식 코드https://github.com/Holliemin9090/Mammographic-mass-CAD-via-pseudo-color-mammogram-and-Mask-R-CNN
공식 코드https://github.com/HongyuGong/Abusive-Language-Detection-Categorization
공식 코드https://github.com/Howardqlz/Meta-MTL
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.