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Yi-Fei Wang

4 papers hereh-index 226 citations6 works total

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

author position
  • middle author3
  • last author1

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

fields
  • cs.CL2
  • cs.LG2
same name
  • Yi-Fei Wang — 21 papers, h 12
  • Yi-Fei Wang — 19 papers, h 8
  • Yi-Fei Wang — 3 papers, h 3
  • Yi-Fei Wang — 2 papers, h 1
  • Yi-Fei Wang — 1 paper, h 2
  • Yi-fei Wang — 1 paper, h 1

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 citedLaplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding

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

collaborators

4 papers

cs.CL2025

Hierarchical Indexing with Knowledge Enrichment for Multilingual Video Corpus Retrieval

Yu Wang, Tianhao Tan, Yifei Wang

Retrieving relevant instructional videos from multilingual medical archives is crucial for answering complex, multi-hop questions across language boundaries. However, existing syst…

cs.CL2025

Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning

Ang Li, Yichuan Mo, Mingjie Li +2

Large Language Models (LLMs) have demonstrated remarkable success across various NLP benchmarks. However, excelling in complex tasks that require nuanced reasoning and precise deci…

cs.LG2023★ 1 cited

Adversarial Examples Are Not Real Features

Ang Li, Yifei Wang, Yiwen Guo +1

The existence of adversarial examples has been a mystery for years and attracted much interest. A well-known theory by \citet{ilyas2019adversarial} explains adversarial vulnerabili…

cs.LG2023★ 3 cited

Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding

Jiangyan Ma, Yifei Wang, Yisen Wang

Spectral embedding is a powerful graph embedding technique that has received a lot of attention recently due to its effectiveness on Graph Transformers. However, from a theoretical…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.