← Learning Types
Machine Learning › Learning Types ›

Few-Shot Learning

1062 directly classified papers

Papers per year

Papers

Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-training IJCAI 2025
Is Meta-Learning Out? Rethinking Unsupervised Few-Shot Classification with Limited Entropy ICCV 2025
HypDAE: Hyperbolic Diffusion Autoencoders for Hierarchical Few-shot Image Generation ICCV 2025
CountSE: Soft Exemplar Open-set Object Counting ICCV 2025
LLMSR@XLLM25: Less is More: Enhancing Structured Multi-Agent Reasoning via Quality-Guided Distillation ACL 2025
Lark: Low-Rank Updates After Knowledge Localization for Few-shot Class-Incremental Learning ICCV 2025
LIMICS at ArchEHR-QA 2025: Prompting LLMs Beats Fine-Tuned Embeddings ACL 2025
When the Dictionary Strikes Back: A Case Study on Slovak Migration Location Term Extraction and NER via Rule-Based vs. LLM Methods ACL 2025
Read it in Two Steps: Translating Extremely Low-Resource Languages with Code-Augmented Grammar Books ACL 2025
Self-Error-Instruct: Generalizing from Errors for LLMs Mathematical Reasoning ACL 2025
DCG-SQL: Enhancing In-Context Learning for Text-to-SQL with Deep Contextual Schema Link Graph ACL 2025
DS2-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis ACL 2025
Simplified Rewriting Improves Expert Summarization IJCNLP 2025
Using LLMs to Advance Idiom Corpus Construction NAACL 2025
Speaker Identification and Dataset Construction Using LLMs: A Case Study on Japanese Narratives NAACL 2025
In-Context Learning on a Budget: A Case Study in Token Classification NAACL 2025
From Evidence Mining to Meta-Prediction: a Gradient of Methodologies for Task-Specific Challenges in Psychological Assessment NAACL 2025
Exploring Limitations of LLM Capabilities with Multi-Problem Evaluation NAACL 2025
UCSP Submission to the AmericasNLP 2025 Shared Task NAACL 2025
Advancing Uto-Aztecan Language Technologies: A Case Study on the Endangered Comanche Language NAACL 2025
A baseline for self-state identification and classification in mental health data: CLPsych 2025 Task NAACL 2025
Optimizing Cost-Efficiency with LLM-Generated Training Data for Conversational Semantic Frame Analysis NAACL 2025
Enhancing NER Performance in Low-Resource Pakistani Languages using Cross-Lingual Data Augmentation NAACL 2025
XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples NAACL 2025
ImaRA: An Imaginative Frame Augmented Method for Low-Resource Multimodal Metaphor Detection and Explanation NAACL 2025