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researcher

Yu Li

4 papers hereh-index 315 citations6 works total

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

author position
  • middle author4

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

fields
  • cs.IR2
  • cs.LG2
same name
  • Yu Li — 15 papers, h 8
  • Yu Li — 14 papers, h 5
  • Yu Li — 14 papers, h 7
  • Yu Li — 9 papers, h 4
  • Yu Li — 9 papers, h 8
  • Yu Li — 8 papers, 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

works on
business ranking 1document identifiers 1e-commerce search 1generative retrieval 1semantic clustering 1

From the 1 of 4 linked papers with an AI index.

collaborators

4 papers

cs.IR2026

Beyond Semantic IDs: Encoding Business-Value Ranking into Document Identifiers for Generative Retrieval

Gui Ling, Zhihong Chen, Yu Li +7

The paper proposes Cluster‑Ranked Identifier (CRID), a document ID design that separates semantic clustering from business‑value ranking to eliminate collisions and better align re…

cs.LG2025

Differentiable Fast Top-K Selection for Large-Scale Recommendation

Yanjie Zhu, Zhen Zhang, Yunli Wang +7

Cascade ranking is a widely adopted paradigm in large-scale information retrieval systems for Top-K item selection. However, the Top-K operator is non-differentiable, hindering end…

cs.IR2025

Learning Cascade Ranking as One Network

Yunli Wang, Zhen Zhang, Zhiqiang Wang +6

Cascade Ranking is a prevalent architecture in large-scale top-k selection systems like recommendation and advertising platforms. Traditional training methods focus on single-stage…

cs.LG2025

Adaptive2: Adaptive Domain Mining for Fine-grained Domain Adaptation Modeling

Wenxuan Sun, Zixuan Yang, Yunli Wang +8

Advertising systems often face the multi-domain challenge, where data distributions vary significantly across scenarios. Existing domain adaptation methods primarily focus on build…

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