activity
20162024
most citedAchieving Forgetting Prevention and Knowledge Transfer in Continual Learning

44 citations · 74 across the 11 of their papers we have counts for

collaborators

11 papers

cond-mat.str-el2024

F NMR and defect spins in vacuum-annealed LaOFBiS

S. Yadav, S. Delgado, O. O. Bernal +9

We report results of magnetization and F NMR measurements in the normal state of as-grown LaOFBiS. The magnetization is dominated by a temperature-indepe…

cs.CL2024

Beyond Sparse Rewards: Enhancing Reinforcement Learning with Language Model Critique in Text Generation

Meng Cao, Lei Shu, Lei Yu +4

Reinforcement learning (RL) can align language models with non-differentiable reward signals, such as human preferences. However, a major challenge arises from the sparsity of thes…

cs.CL20231 cited

SiRA: Sparse Mixture of Low Rank Adaptation

Yun Zhu, Nevan Wichers, Chu-Cheng Lin +8

Parameter Efficient Tuning has been an prominent approach to adapt the Large Language Model to downstream tasks. Most previous works considers adding the dense trainable parameters…

cs.CL2023

Towards an On-device Agent for Text Rewriting

Yun Zhu, Yinxiao Liu, Felix Stahlberg +7

Large Language Models (LLMs) have demonstrated impressive capabilities for text rewriting. Nonetheless, the large sizes of these models make them impractical for on-device inferenc…

cs.CL20231 cited

Adapting a Language Model While Preserving its General Knowledge

Zixuan Ke, Yijia Shao, Haowei Lin +3

Domain-adaptive pre-training (or DA-training for short), also known as post-training, aims to train a pre-trained general-purpose language model (LM) using an unlabeled corpus of a…

cs.CL20219 cited

Continual Learning with Knowledge Transfer for Sentiment Classification

Zixuan Ke, Bing Liu, Hao Wang +1

This paper studies continual learning (CL) for sentiment classification (SC). In this setting, the CL system learns a sequence of SC tasks incrementally in a neural network, where…