{"total":35,"rows":[{"id":"2205.05638","title":"Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning","created":"2022-05-11","cited_by_count":896,"area":null},{"id":"2206.08155","title":"Zero-Shot Video Question Answering via Frozen Bidirectional Language Models","created":"2022-06-16","cited_by_count":229,"area":null},{"id":"2307.00184","title":"Personality Traits in Large Language Models","created":"2023-07-01","cited_by_count":169,"area":null},{"id":"2209.11055","title":"Efficient Few-Shot Learning Without Prompts","created":"2022-09-22","cited_by_count":137,"area":null},{"id":"2209.00099","title":"Efficient Methods for Natural Language Processing: A Survey","created":"2022-08-31","cited_by_count":78,"area":null},{"id":"2301.12971","title":"Quantifying Context Mixing in Transformers","created":"2023-01-30","cited_by_count":43,"area":null},{"id":"2210.03821","title":"Large Language Models can Implement Policy Iteration","created":"2022-10-07","cited_by_count":31,"area":null},{"id":"2212.02216","title":"Improving Few-Shot Performance of Language Models via Nearest Neighbor Calibration","created":"2022-12-05","cited_by_count":24,"area":null},{"id":"2211.03154","title":"On the Domain Adaptation and Generalization of Pretrained Language Models: A Survey","created":"2022-11-06","cited_by_count":23,"area":null},{"id":"2212.10563","title":"BLIND: Bias Removal With No Demographics","created":"2022-12-20","cited_by_count":22,"area":null},{"id":"2402.12819","title":"Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance","created":"2024-02-20","cited_by_count":18,"area":null},{"id":"2405.10808","title":"ActiveLLM: Large Language Model-based Active Learning for Textual Few-Shot Scenarios","created":"2024-05-17","cited_by_count":18,"area":null},{"id":"2210.02952","title":"Improving the Sample Efficiency of Prompt Tuning with Domain Adaptation","created":"2022-10-06","cited_by_count":15,"area":null},{"id":"2303.12314","title":"Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization","created":"2023-03-22","cited_by_count":15,"area":null},{"id":"2211.08099","title":"A Universal Discriminator for Zero-Shot Generalization","created":"2022-11-15","cited_by_count":11,"area":null},{"id":"2302.09236","title":"Scalable Prompt Generation for Semi-supervised Learning with Language Models","created":"2023-02-18","cited_by_count":11,"area":null},{"id":"2205.13722","title":"Can Foundation Models Help Us Achieve Perfect Secrecy?","created":"2022-05-27","cited_by_count":9,"area":null},{"id":"2305.12576","title":"Automated Few-shot Classification with Instruction-Finetuned Language Models","created":"2023-05-21","cited_by_count":9,"area":null},{"id":"2502.18782","title":"Active Few-Shot Learning for Text Classification","created":"2025-02-26","cited_by_count":6,"area":null},{"id":"2207.04993","title":"Embedding Recycling for Language Models","created":"2022-07-11","cited_by_count":5,"area":null},{"id":"2306.15430","title":"KnowPrefix-Tuning: A Two-Stage Prefix-Tuning Framework for Knowledge-Grounded Dialogue Generation","created":"2023-06-27","cited_by_count":5,"area":null},{"id":"2207.11076","title":"Multi-Level Fine-Tuning, Data Augmentation, and Few-Shot Learning for Specialized Cyber Threat Intelligence","created":"2022-07-22","cited_by_count":4,"area":null},{"id":"2310.13998","title":"Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models","created":"2023-10-21","cited_by_count":4,"area":null},{"id":"2411.09539","title":"Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide","created":"2024-11-14","cited_by_count":4,"area":null},{"id":"2311.00408","title":"AdaSent: Efficient Domain-Adapted Sentence Embeddings for Few-Shot Classification","created":"2023-11-01","cited_by_count":3,"area":null},{"id":"2410.05770","title":"Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes","created":"2024-10-08","cited_by_count":3,"area":null},{"id":"2210.12619","title":"Conformal Predictor for Improving Zero-shot Text Classification Efficiency","created":"2022-10-23","cited_by_count":2,"area":null},{"id":"2404.17832","title":"Evaluation of Few-Shot Learning for Classification Tasks in the Polish Language","created":"2024-04-27","cited_by_count":1,"area":null},{"id":"2410.03447","title":"How Language Models Prioritize Contextual Grammatical Cues?","created":"2024-10-04","cited_by_count":1,"area":null},{"id":"2209.09401","title":"Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models","created":"2022-09-20","cited_by_count":0,"area":null},{"id":"2410.13313","title":"Mitigating Biases to Embrace Diversity: A Comprehensive Annotation Benchmark for Toxic Language","created":"2024-10-17","cited_by_count":0,"area":null},{"id":"2411.07917","title":"CryptoLLM: Unleashing the Power of Prompted LLMs for SmartQnA and Classification of Crypto Posts","created":"2024-11-12","cited_by_count":0,"area":null},{"id":"2412.04975","title":"PETapter: Leveraging PET-style classification heads for modular few-shot parameter-efficient fine-tuning","created":"2024-12-06","cited_by_count":0,"area":null},{"id":"2508.05690","title":"Leveraging large language models for SQL behavior-based database intrusion detection","created":"2025-08-06","cited_by_count":0,"area":null},{"id":"2510.06249","title":"TRepLiNa: Layer-wise CKA+REPINA Alignment Improves Low-Resource Machine Translation in Aya-23 8B","created":"2025-10-03","cited_by_count":0,"area":null}],"next_cursor":null}