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06/02/2023
Resolving Interference When Merging Models
Transfer learning - i.e., further fine-tuning a pre-trained model on a d...
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11/15/2022
Large Language Models Struggle to Learn Long-Tail Knowledge
The internet contains a wealth of knowledge – from the birthdays of hist...
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09/02/2022
Petals: Collaborative Inference and Fine-tuning of Large Models
Many NLP tasks benefit from using large language models (LLMs) that ofte...
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08/31/2022
Efficient Methods for Natural Language Processing: A Survey
Getting the most out of limited resources allows advances in natural lan...
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03/31/2022
Scaling Up Models and Data with and
Recent neural network-based language models have benefited greatly from ...
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02/02/2022
PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts
PromptSource is a system for creating, sharing, and using natural langua...
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11/18/2021
Merging Models with Fisher-Weighted Averaging
Transfer learning provides a way of leveraging knowledge from one task w...
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05/28/2021
ByT5: Towards a token-free future with pre-trained byte-to-byte models
Most widely-used pre-trained language models operate on sequences of tok...
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03/22/2021
Improving and Simplifying Pattern Exploiting Training
Recently, pre-trained language models (LMs) have achieved strong perform...
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02/10/2020
How Much Knowledge Can You Pack Into the Parameters of a Language Model?
It has recently been observed that neural language models trained on uns...
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07/05/2019
Detecting and Diagnosing Adversarial Images with Class-Conditional Capsule Reconstructions
Adversarial examples raise questions about whether neural network models...
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02/21/2019
Lingvo: a Modular and Scalable Framework for Sequence-to-Sequence Modeling
Lingvo is a Tensorflow framework offering a complete solution for collab...
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10/30/2017
