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few-shot learning

3398 papers

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Also known as

FSL FEW-SHOT

Co-occurring keywords

large language model (13587) zero-shot learning (3650) transfer learning (5449) in-context learning (1405) text classification (6793) domain adaptation (4595) prompt engineering (1135) representation learning (6206) language model (4599) contrastive learning (4032)

Papers

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models NIPS 2024
In-Context Example Retrieval from Multi-Perspectives for Few-Shot Aspect-Based Sentiment Analysis COLING 2024
HANS, are you clever? Clever Hans Effect Analysis of Neural Systems NAACL 2024
ISDS-NLP at SemEval-2024 Task 10: Transformer based neural networks for emotion recognition in conversations NAACL 2024
Exploring Factual Entailment with NLI: A News Media Study NAACL 2024
A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detection NAACL 2024
Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling AAAI 2024
Any-Way Meta Learning AAAI 2024
Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classification NAACL 2024
Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting NIPS 2024
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
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
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