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05/24/2023
Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts
The explosive growth of language models and their applications have led ...
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01/31/2023
The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
We study the design decisions of publicly available instruction tuning m...
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12/26/2022
Large Language Models Encode Clinical Knowledge
Large language models (LLMs) have demonstrated impressive capabilities i...
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11/03/2022
Inverse scaling can become U-shaped
Although scaling language models improves performance on a range of task...
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10/06/2022
Language Models are Multilingual Chain-of-Thought Reasoners
We evaluate the reasoning abilities of large language models in multilin...
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05/21/2022
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
We propose a novel prompting strategy, least-to-most prompting, that ena...
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03/21/2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models
We explore a simple ensemble strategy, self-consistency, that significan...
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01/28/2022
Chain of Thought Prompting Elicits Reasoning in Large Language Models
Although scaling up language model size has reliably improved performanc...
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09/08/2021
A Recipe For Arbitrary Text Style Transfer with Large Language Models
In this paper, we leverage large language models (LMs) to perform zero-s...
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09/03/2021
Finetuned Language Models Are Zero-Shot Learners
This paper explores a simple method for improving the zero-shot learning...
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11/20/2018
