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

Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning NIPS 2024

The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models NIPS 2024

AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation NIPS 2024

More Samples or More Prompts? Exploring Effective Few-Shot In-Context Learning for LLMs with In-Context Sampling NAACL 2024

Identifying Self-Disclosures of Use, Misuse and Addiction in Community-based Social Media Posts NAACL 2024

Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition ACL 2024

Concept-aware Data Construction Improves In-context Learning of Language Models ACL 2024

REPLUG: Retrieval-Augmented Black-Box Language Models NAACL 2024

Empowering Large Language Models for Textual Data Augmentation ACL 2024

MDR: Model-Specific Demonstration Retrieval at Inference Time for In-Context Learning NAACL 2024

LegalDiscourse: Interpreting When Laws Apply and To Whom NAACL 2024

Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning ACL 2024

Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models NIPS 2024

AustroTox: A Dataset for Target-Based Austrian German Offensive Language Detection ACL 2024

In-context Learning and Gradient Descent Revisited NAACL 2024

Concept Over Time Analysis: Unveiling Temporal Patterns for Qualitative Data Analysis NAACL 2024

Decoupling Representation and Knowledge for Few-Shot Intent Classification and Slot Filling AAAI 2024

Any-Way Meta Learning AAAI 2024

Many-Shot In-Context Learning NIPS 2024

Automating Dataset Updates Towards Reliable and Timely Evaluation of Large Language Models NIPS 2024

Demonstration Augmentation for Zero-shot In-context Learning ACL 2024

Few-Shot Event Argument Extraction Based on a Meta-Learning Approach NAACL 2024

Learning to Learn Better Visual Prompts AAAI 2024

Argument Mining in Data Scarce Settings: Cross-lingual Transfer and Few-shot Techniques ACL 2024

Mashee at SemEval-2024 Task 8: The Impact of Samples Quality on the Performance of In-Context Learning for Machine Text Classification NAACL 2024