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few-shot learning

3390 papers

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Also known as

ICL FSL FSAS FSED FSOD FSSL FSR FSC FFG FSAC FEW-SHOT FSCD FSIG FLAD FSCIL FSS FSRE FSIL CDFSL FS-XLT

Co-occurring keywords

large language model (12755) zero-shot learning (3637) transfer learning (5442) in-context learning (1369) text classification (6776) domain adaptation (4578) prompt engineering (1128) language model (4573) representation learning (6174) contrastive learning (3979)

Papers

Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP NIPS 2024
One-to-Normal: Anomaly Personalization for Few-shot Anomaly Detection NIPS 2024
Continuous Attentive Multimodal Prompt Tuning for Few-Shot Multimodal Sarcasm Detection CONLL 2024
Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models NIPS 2024
Language Models Don’t Learn the Physical Manifestation of Language ACL 2024
A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detection NAACL 2024
DeMuX: Data-efficient Multilingual Learning NAACL 2024
Exploring In-Context Learning of Textless Speech Language Model for Speech Classification Tasks INTERSPEECH 2024
MDR: Model-Specific Demonstration Retrieval at Inference Time for In-Context Learning NAACL 2024
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NIPS 2024
OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning CVPR 2024
Generative Multimodal Models are In-Context Learners CVPR 2024
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset NIPS 2024
DAVE - A Detect-and-Verify Paradigm for Low-Shot Counting CVPR 2024
Understanding Inverse Scaling and Emergence in Multitask Representation Learning AISTATS 2024
A Novel Unified Architecture for Low-Shot Counting by Detection and Segmentation NIPS 2024
In-context Learning and Gradient Descent Revisited NAACL 2024
REPLUG: Retrieval-Augmented Black-Box Language Models NAACL 2024
ARC: A Generalist Graph Anomaly Detector with In-Context Learning NIPS 2024
LP++: A Surprisingly Strong Linear Probe for Few-Shot CLIP CVPR 2024
Toward Generalist Anomaly Detection via In-context Residual Learning with Few-shot Sample Prompts CVPR 2024
Few-Shot Adversarial Prompt Learning on Vision-Language Models NIPS 2024
Make-An-Agent: A Generalizable Policy Network Generator with Behavior-Prompted Diffusion NIPS 2024
Large Language Models are Good Prompt Learners for Low-Shot Image Classification CVPR 2024
On Scaling Up a Multilingual Vision and Language Model CVPR 2024