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Zhan Shi

4 papers hereh-index 329 citations10 works total

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

author position
  • first author2
  • middle author2

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

fields
  • cs.CL2
  • cs.CV1
  • cs.IR1
same name
  • Zhan Shi — 23 papers, h 26
  • Zhan Shi — 4 papers
  • Zhan Shi — 4 papers, h 6
  • Zhan Shi — 3 papers, h 6
  • Zhan Shi — 2 papers
  • Zhan Shi — 2 papers

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 citedIntegrating Domain Knowledge into Large Language Models for Enhanced Fashion Recommendations

1 citations · 1 across the 3 of their papers we have counts for

collaborators

4 papers

cs.CL2025

Compass-Embedding v4: Robust Contrastive Learning for Multilingual E-commerce Embeddings

Pakorn Ueareeworakul, Shuman Liu, Jinghao Feng +7

As global e-commerce rapidly expands into emerging markets, the lack of high-quality semantic representations for low-resource languages has become a decisive bottleneck for retrie…

cs.IR2025

Selective LLM-Guided Regularization for Enhancing Recommendation Models

Shanglin Yang, Zhan Shi

Large language models provide rich semantic priors and strong reasoning capabilities, making them promising auxiliary signals for recommendation. However, prevailing approaches eit…

cs.CV2025

Efficient Whole Slide Pathology VQA via Token Compression

Weimin Lyu, Qingqiao Hu, Kehan Qi +4

Whole-slide images (WSIs) in pathology can reach up to 10,000 x 10,000 pixels, posing significant challenges for multimodal large language model (MLLM) due to long context length a…

cs.CL2025★ 1 cited

Integrating Domain Knowledge into Large Language Models for Enhanced Fashion Recommendations

Zhan Shi, Shanglin Yang

Fashion, deeply rooted in sociocultural dynamics, evolves as individuals emulate styles popularized by influencers and iconic figures. In the quest to replicate such refined tastes…

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