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20212023
most citedAn Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

57 citations · 58 across the 3 of their papers we have counts for

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5 papers

cs.CL2023★ 57 cited

An Empirical Study of Catastrophic Forgetting in Large Language Models During Continual Fine-tuning

Yun Luo, Zhen Yang, Fandong Meng +3

Catastrophic forgetting (CF) is a phenomenon that occurs in machine learning when a model forgets previously learned information while acquiring new knowledge for achieving a satis…

cs.CL2023★ 1 cited

Investigating Forgetting in Pre-Trained Representations Through Continual Learning

Yun Luo, Zhen Yang, Xuefeng Bai +3

Representation forgetting refers to the drift of contextualized representations during continual training. Intuitively, the representation forgetting can influence the general know…

cs.CL2022

EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation

Yulin Xu, Zhen Yang, Fandong Meng +1

Complete Multi-lingual Neural Machine Translation (C-MNMT) achieves superior performance against the conventional MNMT by constructing multi-way aligned corpus, i.e., aligning bili…

cs.CL2021

WeTS: A Benchmark for Translation Suggestion

Zhen Yang, Fandong Meng, Yingxue Zhang +2

Translation Suggestion (TS), which provides alternatives for specific words or phrases given the entire documents translated by machine translation (MT) \cite{lee2021intellicat}, h…

cs.CL2021

Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information

Fengji Zhang, Xiao Yu, Jacky Keung +5

Context: Stack Overflow is very helpful for software developers who are seeking answers to programming problems. Previous studies have shown that a growing number of questions are…