SOTAVerified

Transfer Learning

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.

( Image credit: Subodh Malgonde )

Papers

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Showing 8901–8950 of 10307 papers

TitleStatusHype
Cross-Lingual Transfer Learning for Statistical Type Inference—0
Cross-lingual and Cross-domain Transfer Learning for Automatic Term Extraction from Low Resource Data—0
Cross-lingual, Character-Level Neural Morphological Tagging—0
Cross-lingual Character-Level Neural Morphological Tagging—0
Cross-lingual Constituency Parsing with Linguistic Typology Knowledge—0
Cross-lingual Universal Dependency Parsing Only from One Monolingual Treebank—0
Cross-lingual dependency parsing for closely related languages - Helsinki's submission to VarDial 2017—0
Cross-lingual Fine-tuning for Abstractive Arabic Text Summarization—0
Cross-lingual German Biomedical Information Extraction: from Zero-shot to Human-in-the-Loop—0
Cross-lingual hate speech detection based on multilingual domain-specific word embeddings—0
Cross-Lingual Image Caption Generation—0
Cross-lingual Knowledge Transfer and Iterative Pseudo-labeling for Low-Resource Speech Recognition with Transducers—0
Cross-lingual Knowledge Transfer via Distillation for Multilingual Information Retrieval—0
Cross-lingual Lifelong Learning—0
Cross-lingual Opinion Analysis via Negative Transfer Detection—0
Cross-Lingual Parser Selection for Low-Resource Languages—0
Cross-lingual Pre-training Based Transfer for Zero-shot Neural Machine Translation—0
Cross-lingual Semantic Role Labelling with the ValPaL Database Knowledge—0
Cross-lingual Structure Transfer for Zero-resource Event Extraction—0
Cross-Lingual Syntactically Informed Distributed Word Representations—0
Cross-lingual Transfer Can Worsen Bias in Sentiment Analysis—0
Cross-lingual Transfer Learning and Multitask Learning for Capturing Multiword Expressions—0
Cross-Lingual Transfer Learning for Multilingual Task Oriented Dialog—0
Cross-lingual Transfer Learning for Grammatical Error Correction—0
Cross-Lingual Transfer Learning for Alzheimer's Detection From Spontaneous Speech—0
Cross-lingual Transfer Learning for Check-worthy Claim Identification over Twitter—0
Cross-Lingual Transfer Learning for Complex Word Identification—0
Cross-lingual Transfer Learning for COVID-19 Outbreak Alignment—0
Cross-lingual Approaches for Task-specific Dialogue Act Recognition—0
Cross-Lingual Transfer Learning for Hate Speech Detection—0
Cross-lingual Transfer Learning for Japanese Named Entity Recognition—0
Cross-lingual Transfer Learning for Javanese Dependency Parsing—0
Cross-Lingual Transfer Learning for Phrase Break Prediction with Multilingual Language Model—0
Cross-Lingual Transfer Learning for POS Tagging without Cross-Lingual Resources—0
Cross-lingual Transfer Learning for Pre-trained Contextualized Language Models—0
Cross-Lingual Transfer Learning for Question Answering—0
Crosslingual Transfer Learning for Relation and Event Extraction via Word Category and Class Alignments—0
Cross-lingual Transfer Learning for Semantic Role Labeling in Russian—0
Cross-Lingual Transfer Learning for Speech Translation—0
Cross-lingual transfer learning for spoken language understanding—0
Cross lingual transfer learning for zero-resource domain adaptation—0
Cross-lingual Transfer Learning with Data Selection for Large-Scale Spoken Language Understanding—0
Cross-lingual Transfer of Named Entity Recognizers without Parallel Corpora—0
Cross-Lingual Unsupervised Sentiment Classification with Multi-View Transfer Learning—0
Cross-Linguistic Examination of Machine Translation Transfer Learning—0
Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models—0
Cross-modal Alignment with Optimal Transport for CTC-based ASR—0
Cross-Modal Analysis of Human Detection for Robotics: An Industrial Case Study—0
Cross-modal and Cross-domain Knowledge Transfer for Label-free 3D Segmentation—0
Cross-Modal Few-Shot Learning: a Generative Transfer Learning Framework—0
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All datasetsOffice-Home100 sleep nights of 8 caregiversBanglaLekha Isolated DatasetCOCO70KITTI Object Tracking Evaluation 2012Retinal Fundus MultiDisease Image Dataset (RFMiD)

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1APCLIPAccuracy84.2—Unverified
2DFA-ENTAccuracy69.2—Unverified
3DFA-SAFNAccuracy69.1—Unverified
4EasyTLAccuracy63.3—Unverified
5MEDAAccuracy60.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CNN10-20% Mask PSNR3.23—Unverified
#ModelMetricClaimedVerifiedStatus
1Chatterjee, Dutta et al.[1]Accuracy96.12—Unverified
#ModelMetricClaimedVerifiedStatus
1Co-TuningAccuracy85.65—Unverified
#ModelMetricClaimedVerifiedStatus
1Physical AccessEER5.74—Unverified
#ModelMetricClaimedVerifiedStatus
1riadd.aucmediAUROC0.95—Unverified