SOTAVerified

Zero-Shot Learning

Zero-shot learning (ZSL) is a model's ability to detect classes never seen during training. The condition is that the classes are not known during supervised learning.

Earlier work in zero-shot learning use attributes in a two-step approach to infer unknown classes. In the computer vision context, more recent advances learn mappings from image feature space to semantic space. Other approaches learn non-linear multimodal embeddings. In the modern NLP context, language models can be evaluated on downstream tasks without fine tuning.

Benchmark datasets for zero-shot learning include aPY, AwA, and CUB, among others.

( Image credit: Prototypical Networks for Few shot Learning in PyTorch )

Further readings:

Papers

Showing 701–750 of 1864 papers

TitleStatusHype
GBE-MLZSL: A Group Bi-Enhancement Framework for Multi-Label Zero-Shot Learning—0
Neural Gradient RegularizerCode0
Using Large Language Models to Automate Category and Trend Analysis of Scientific Articles: An Application in Ophthalmology—0
Cross-Modal Retrieval Meets Inference:Improving Zero-Shot Classification with Cross-Modal Retrieval—0
Privacy-Enhanced Zero-Shot Learning via Data-Free Knowledge TransferCode0
ZeroLeak: Using LLMs for Scalable and Cost Effective Side-Channel Patching—0
Towards Realistic Zero-Shot Classification via Self Structural Semantic AlignmentCode1
Hyperbolic Audio-visual Zero-shot Learning—0
Continual Zero-Shot Learning through Semantically Guided Generative Random WalksCode0
E(3)-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement LearningCode1
Adversarial Illusions in Multi-Modal EmbeddingsCode1
Image-free Classifier Injection for Zero-Shot ClassificationCode1
EGANS: Evolutionary Generative Adversarial Network Search for Zero-Shot Learning—0
BioMedGPT: Open Multimodal Generative Pre-trained Transformer for BioMedicine—0
DiffDis: Empowering Generative Diffusion Model with Cross-Modal Discrimination Capability—0
Leveraging Codebook Knowledge with NLI and ChatGPT for Zero-Shot Political Relation ClassificationCode0
Compositional Learning in Transformer-Based Human-Object Interaction Detection—0
Robustifying Point Cloud Networks by RefocusingCode0
Leverage Weakly Annotation to Pixel-wise Annotation via Zero-shot Segment Anything Model for Molecular-empowered Learning—0
Breaking Language Barriers with MMTweets: Advancing Cross-Lingual Debunked Narrative Retrieval for Fact-Checking—0
Exploring Linguistic Similarity and Zero-Shot Learning for Multilingual Translation of Dravidian Languages—0
"Generate" the Future of Work through AI: Empirical Evidence from Online Labor Markets—0
Hierarchical Visual Primitive Experts for Compositional Zero-Shot LearningCode0
ReCLIP: Refine Contrastive Language Image Pre-Training with Source Free Domain AdaptationCode1
Supply chain emission estimation using large language models—0
Push the Boundary of SAM: A Pseudo-label Correction Framework for Medical Segmentation—0
PerceptionCLIP: Visual Classification by Inferring and Conditioning on ContextsCode1
Zero-Shot Learning by Harnessing Adversarial SamplesCode0
From Generation to Suppression: Towards Effective Irregular Glow Removal for Nighttime Visibility EnhancementCode1
Fuzzy Logic Visual Network (FLVN): A neuro-symbolic approach for visual features matchingCode0
PromptStyler: Prompt-driven Style Generation for Source-free Domain GeneralizationCode1
Developing and Evaluating Tiny to Medium-Sized Turkish BERT Models—0
Zshot: An Open-source Framework for Zero-Shot Named Entity Recognition and Relation ExtractionCode2
PRIOR: Prototype Representation Joint Learning from Medical Images and ReportsCode1
Wisdom of Instruction-Tuned Language Model Crowds. Exploring Model Label Variation—0
Validation of a Zero-Shot Learning Natural Language Processing Tool for Data Abstraction from Unstructured Healthcare DataCode1
Leveraging Knowledge Graphs for Zero-Shot Object-agnostic State Classification—0
MineralImage5k: A benchmark for zero-shot raw mineral visual recognition and descriptionCode1
See More and Know More: Zero-shot Point Cloud Segmentation via Multi-modal Visual Data—0
Distilling Knowledge from Text-to-Image Generative Models Improves Visio-Linguistic Reasoning in CLIP—0
Improving Zero-Shot Generalization for CLIP with Synthesized PromptsCode1
AutoHint: Automatic Prompt Optimization with Hint GenerationCode0
Learning Adversarial Semantic Embeddings for Zero-Shot Recognition in Open WorldsCode1
Distilling Large Vision-Language Model with Out-of-Distribution GeneralizabilityCode1
Knowledge-Aware Audio-Grounded Generative Slot Filling for Limited Annotated Data—0
Stay on topic with Classifier-Free Guidance—0
The Segment Anything Model (SAM) for Remote Sensing Applications: From Zero to One ShotCode4
The mapKurator System: A Complete Pipeline for Extracting and Linking Text from Historical MapsCode1
Is ChatGPT a Biomedical Expert? -- Exploring the Zero-Shot Performance of Current GPT Models in Biomedical TasksCode0
Towards Open Vocabulary Learning: A SurveyCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ZeroDiffaverage top-1 classification accuracy87.5—Unverified
2DUETaverage top-1 classification accuracy72.3—Unverified
3Composeraverage top-1 classification accuracy69.4—Unverified
4HDC-ZSC-MLPaverage top-1 classification accuracy65.6—Unverified
5ZSL_TF-VAEGANaverage top-1 classification accuracy64.9—Unverified
6ZLaPAccuracy64.3—Unverified
7ZLaP*Accuracy64.2—Unverified
8HDC-ZSCaverage top-1 classification accuracy63.8—Unverified
9SPOTaverage top-1 classification accuracy62.9—Unverified
10f-VAEGAN-D2average top-1 classification accuracy61—Unverified
#ModelMetricClaimedVerifiedStatus
1dmis-lab/biobert-v1.1Accuracy26.15—Unverified
2meta-llama/Meta-Llama-3-8B-InstructAccuracy25.84—Unverified
3epfl-llm/meditron-7bAccuracy25.75—Unverified
4dmis-lab/meerkat-7b-v1.0Accuracy25.68—Unverified
5meta-llama/Meta-Llama-3-8B-InstructAccuracy25.65—Unverified
6HuggingFaceH4/zephyr-7b-betaAccuracy25.54—Unverified
7dmis-lab/biobert-v1.1Accuracy25.46—Unverified
8epfl-llm/meditron-70bAccuracy25.36—Unverified
9epfl-llm/meditron-70bAccuracy25.26—Unverified
10HuggingFaceH4/zephyr-7b-betaAccuracy25.06—Unverified
#ModelMetricClaimedVerifiedStatus
1ZeroDiffaverage top-1 classification accuracy77.3—Unverified
2SPOT (VAEGAN)average top-1 classification accuracy66.04—Unverified
3ZSL_TF-VAEGANaverage top-1 classification accuracy66—Unverified
4f-VAEGANaverage top-1 classification accuracy64.7—Unverified
5DUET (Ours)average top-1 classification accuracy64.4—Unverified
6LisGANaverage top-1 classification accuracy61.7—Unverified
7TCNaverage top-1 classification accuracy61.5—Unverified
8f-CLSWGANaverage top-1 classification accuracy60.8—Unverified
9Cycle-WGANaverage top-1 classification accuracy59.9—Unverified
#ModelMetricClaimedVerifiedStatus
1ZeroDiffaverage top-1 classification accuracy86.4—Unverified
2ZSL-KGaverage top-1 classification accuracy78.08—Unverified
3ZSL_TF-VAEGANaverage top-1 classification accuracy72.2—Unverified
4DUET (Ours)average top-1 classification accuracy69.9—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPAccuracy84—Unverified
2ZLaP*Accuracy83.1—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy93.6—Unverified
2ZLaPAccuracy93.4—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy74.2—Unverified
2ZLaPAccuracy74—Unverified
#ModelMetricClaimedVerifiedStatus
1ViT-B/16Average mAP60.17—Unverified
2ResNet-50Average mAP56.19—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPAccuracy51.2—Unverified
2ZLaP*Accuracy51—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPAccuracy29.1—Unverified
2ZLaP*Accuracy29—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPAccuracy75.9—Unverified
2ZLaP*Accuracy75.5—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy87.9—Unverified
2ZLaPAccuracy87.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPTop 1 Accuracy72.1—Unverified
2ZLaP*Top 1 Accuracy72.1—Unverified
#ModelMetricClaimedVerifiedStatus
1HiTeAAccuracy21.7—Unverified
2HiTeAAccuracy0.46—Unverified
#ModelMetricClaimedVerifiedStatus
1HiTeAAccuracy37.4—Unverified
2HiTeAAccuracy0.56—Unverified
#ModelMetricClaimedVerifiedStatus
1SPOTaverage top-1 classification accuracy71.9—Unverified
2ZSL_TF-VAEGANaverage top-1 classification accuracy70.8—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaPAccuracy90—Unverified
2ZLaP*Accuracy89—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy71.8—Unverified
2ZLaPAccuracy71.2—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy71.4—Unverified
2ZLaPAccuracy71—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy76.3—Unverified
2ZLaPAccuracy76.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CLIP(ViT-B/16)Average mAP85.77—Unverified
2CLIP(ResNet-50)Average mAP84.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ZSL-KGTop-160.54—Unverified
#ModelMetricClaimedVerifiedStatus
1zsl_ADAAverage Per-Class Accuracy70.9—Unverified
#ModelMetricClaimedVerifiedStatus
1ZLaP*Accuracy63.2—Unverified
#ModelMetricClaimedVerifiedStatus
1MSDAPearson correlation coefficient (PCC)0.52—Unverified
#ModelMetricClaimedVerifiedStatus
1SeViLAAccuracy72.3—Unverified
#ModelMetricClaimedVerifiedStatus
1M^2-EncoderAccuracy80.7—Unverified
#ModelMetricClaimedVerifiedStatus
1FrozenBiLMAccuracy51.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CZSLA-acc36—Unverified
#ModelMetricClaimedVerifiedStatus
1ZS3Netk=10 mIOU26.3—Unverified
#ModelMetricClaimedVerifiedStatus
1ZSL-KGAccuracy88.98—Unverified
#ModelMetricClaimedVerifiedStatus
1VideoChat2Accuracy40.6—Unverified