Daliang Li | DeepAI

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∙ 11/09/2022

Large Language Models with Controllable Working Memory

Large language models (LLMs) have led to a series of breakthroughs in na...

6 Daliang Li, et al. ∙

∙ 11/01/2022

Preserving In-Context Learning ability in Large Language Model Fine-tuning

Pretrained large language models (LLMs) are strong in-context learners t...

5 Yihan Wang, et al. ∙

∙ 10/12/2022

Large Models are Parsimonious Learners: Activation Sparsity in Trained Transformers

This paper studies the curious phenomenon for machine learning models wi...

19 Zonglin Li, et al. ∙

∙ 03/26/2021

Understanding Robustness of Transformers for Image Classification

Deep Convolutional Neural Networks (CNNs) have long been the architectur...

0 Srinadh Bhojanapalli, et al. ∙

∙ 12/01/2020

Modifying Memories in Transformer Models

Large Transformer models have achieved impressive performance in many na...

0 Chen Zhu, et al. ∙

∙ 10/08/2019

FedMD: Heterogenous Federated Learning via Model Distillation

Federated learning enables the creation of a powerful centralized model ...

0 Daliang Li, et al. ∙

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