most citedGenetic Improvement in the Shackleton Framework for Optimizing LLVM Pass Sequences

5 citations · 10 across the 10 of their papers we have counts for

collaborators

10 papers

cs.CL2023★ 1 cited

A Quantitative Approach to Understand Self-Supervised Models as Cross-lingual Feature Extractors

Shuyue Stella Li, Beining Xu, Xiangyu Zhang +3

In this work, we study the features extracted by English self-supervised learning (SSL) models in cross-lingual contexts and propose a new metric to predict the quality of feature…

cs.CL2023

Narrowing the Gap between Zero- and Few-shot Machine Translation by Matching Styles

Weiting Tan, Haoran Xu, Lingfeng Shen +5

Large language models trained primarily in a monolingual setting have demonstrated their ability to generalize to machine translation using zero- and few-shot examples with in-cont…

cs.CL2023★ 2 cited

Simple yet Effective Code-Switching Language Identification with Multitask Pre-Training and Transfer Learning

Shuyue Stella Li, Cihan Xiao, Tianjian Li +1

Code-switching, also called code-mixing, is the linguistics phenomenon where in casual settings, multilingual speakers mix words from different languages in one utterance. Due to i…

cs.CL2023

Condensing Multilingual Knowledge with Lightweight Language-Specific Modules

Haoran Xu, Weiting Tan, Shuyue Stella Li +4

Incorporating language-specific (LS) modules is a proven method to boost performance in multilingual machine translation. This approach bears similarity to Mixture-of-Experts (MoE)…

cs.CL2022★ 1 cited

Language Agnostic Code-Mixing Data Augmentation by Predicting Linguistic Patterns

Shuyue Stella Li, Kenton Murray

In this work, we focus on intrasentential code-mixing and propose several different Synthetic Code-Mixing (SCM) data augmentation methods that outperform the baseline on downstream…

eess.AS2022

End-to-End Lyrics Recognition with Self-supervised Learning

Xiangyu Zhang, Shuyue Stella Li, Zhanhong He +2

Lyrics recognition is an important task in music processing. Despite traditional algorithms such as the hybrid HMM- TDNN model achieving good performance, studies on applying end-t…

eess.SP2022★ 1 cited

A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters

Yu Xuan, Xiangyu Zhang, Shuyue Stella Li +4

The detection of abnormal fetal heartbeats during pregnancy is important for monitoring the health conditions of the fetus. While adult ECG has made several advances in modern medi…

cs.LG2022

PQLM -- Multilingual Decentralized Portable Quantum Language Model for Privacy Protection

Shuyue Stella Li, Xiangyu Zhang, Shu Zhou +4

With careful manipulation, malicious agents can reverse engineer private information encoded in pre-trained language models. Security concerns motivate the development of quantum p…

cs.NE2022★ 5 cited

Genetic Improvement in the Shackleton Framework for Optimizing LLVM Pass Sequences

Shuyue Stella Li, Hannah Peeler, Andrew N. Sloss +2

Genetic improvement is a search technique that aims to improve a given acceptable solution to a problem. In this paper, we present the novel use of genetic improvement to find prob…

cs.NE2022

Optimizing LLVM Pass Sequences with Shackleton: A Linear Genetic Programming Framework

Hannah Peeler, Shuyue Stella Li, Andrew N. Sloss +3

In this paper we introduce Shackleton as a generalized framework enabling the application of linear genetic programming -- a technique under the umbrella of evolutionary algorithms…