Prompting/In-context learning AND Arxiv Doc
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13 Documents
[2404.11018] Many-Shot In-Context Learning
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2024-04-21 About
[2401.12178] In-Context Learning for Extreme Multi-Label Classification
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2024-03-17 About
[2310.03025] Retrieval meets Long Context Large Language Models
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2023-10-07 About
[2309.12307] LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
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2023-09-26 About
[2305.14128] Dr.ICL: Demonstration-Retrieved In-context Learning
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2023-07-14 About
[2307.02486] LongNet: Scaling Transformers to 1,000,000,000 Tokens
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2023-07-06 About
[2212.14024] Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP
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2023-06-23 About
[2306.07536] TART: A plug-and-play Transformer module for task-agnostic reasoning
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2023-06-15 About
[2205.05638] Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning
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2022-12-15 About
[2208.01066] What Can Transformers Learn In-Context? A Case Study of Simple Function Classes
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2022-09-17 About
[2201.04337] PromptBERT: Improving BERT Sentence Embeddings with Prompts
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2022-09-16 About
[2209.01975] Selective Annotation Makes Language Models Better Few-Shot Learners
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2022-09-07 About
[2203.08913] Memorizing Transformers
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2022-05-07 About