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Yue Feng

4 papers hereh-index 14 citations6 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CL4
same name
  • Yue Feng — 23 papers, h 8
  • Yue Feng — 19 papers, h 13
  • Yue Feng — 13 papers, h 14
  • Yue Feng — 6 papers, h 3
  • Yue Feng — 4 papers, h 2
  • Yue Feng — 2 papers, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedSocial Bias in Multilingual Language Models: A Survey

1 citations · 1 across the 4 of their papers we have counts for

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

Cross-Lingual Bias in Large Language Models: A Comparative Analysis of English and Swahili

Ruolei Zhang, Teddy Njuguna, Yue Feng

Large language models are increasingly deployed in multilingual contexts, yet safety alignment and bias evaluation remain overwhelmingly English-centric. We investigate whether soc…

cs.CL2026

CACHE-UK: A Stability-Aware Memory Editor for Sequentially Updated Quantized LLMs in Finance

Anubhav Lakra, Yue Feng

Large Language Models (LLMs) deployed in dynamic financial environments face a critical challenge: maintaining factual accuracy as market conditions, regulations, and corporate fac…

cs.CL2025★ 1 cited

Social Bias in Multilingual Language Models: A Survey

Lance Calvin Lim Gamboa, Yue Feng, Mark Lee

Pretrained multilingual models exhibit the same social bias as models processing English texts. This systematic review analyzes emerging research that extends bias evaluation and m…

cs.CL2025

Bias Attribution in Filipino Language Models: Extending a Bias Interpretability Metric for Application on Agglutinative Languages

Lance Calvin Lim Gamboa, Yue Feng, Mark Lee

Emerging research on bias attribution and interpretability have revealed how tokens contribute to biased behavior in language models processing English texts. We build on this line…

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