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Allen Institute for AI (AI2) - Arxiv Doc - Catastrophic forgetting - Fine-tuning - Knowledge Extraction - Knowledge Graph Completion - LLM - LMs: context length - Long documents - NLP@IBM - NLP@Meta - NLP@Microsoft - NLP@Stanford - OpenAI GPT - Prompting/In-context learning - Sentence Embeddings - Transfer learning - Transformers - Zero-Shot Learning -

Arxiv Doc ; Transformers AND LLM

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12 Documents

[2306.04640] ModuleFormer: Modularity Emerges from Mixture-of-Experts

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2023-09-16 About

[2307.08621] Retentive Network: A Successor to Transformer for Large Language Models

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2023-07-20 About

[2307.02486] LongNet: Scaling Transformers to 1,000,000,000 Tokens

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2023-07-06 About

[2305.07185] MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers

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2023-07-01 About

[2306.07536] TART: A plug-and-play Transformer module for task-agnostic reasoning

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2023-06-15 About

[2202.08904] SGPT: GPT Sentence Embeddings for Semantic Search

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2023-04-25 About

[2304.02711] Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learning

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2023-04-07 About

[2303.17651] Self-Refine: Iterative Refinement with Self-Feedback

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2023-04-03 About

[2302.10724] ChatGPT: Jack of all trades, master of none

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2023-02-22 About

[2302.04870] Offsite-Tuning: Transfer Learning without Full Model

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2023-02-11 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