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Cong Fu

11 papers hereh-index 448 citations13 works total

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

author position
  • first author1
  • middle author10

Across the 11 of 11 papers where every author was matched, so the position is known.

fields
  • cs.IR8
  • cs.DB2
  • cs.LG1
same name
  • Cong Fu — 13 papers, h 11
  • Cong Fu — 5 papers, h 22
  • Cong Fu — 4 papers, h 4
  • Cong Fu — 3 papers, h 2
  • Cong Fu — 2 papers, h 2
  • Cong Fu — 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

activity
20242026
collaborators
Showing 2026Show all

4 papers · 1 filter

cs.IR2026

Knowledge-Geometry Decoupling: Refreshable Pretrained Transfer for Streaming Recommendation

Zixuan Wang, Yuhong Chen, Yuxuan Zhu +10

Industrial recommenders increasingly adopt the pretrain-then-transfer paradigm, yet behavioral distribution drift raises two questions: what to learn from behavior sequences, and h…

cs.IR2026

OneRank: Unified Transformer-Native Ranking Architecture for Multi-Task Recommendation

Jiakai Tang, Sunhao Dai, Kun Wang +8

Multi-task learning (MTL) is essential in recommender systems to enable complementary learning among diverse user feedback. While modern industrial practices have shifted from DNNs…

cs.IR2026

ManCAR: Manifold-Constrained Latent Reasoning with Adaptive Test-Time Computation for Sequential Recommendation

Kun Yang, Yuxuan Zhu, Yazhe Chen +7

Sequential recommendation increasingly employs latent multi-step reasoning to enhance test-time computation. Despite empirical gains, existing approaches largely drive intermediate…

cs.IR2026

Rethinking Generative Recommender Tokenizer: Recsys-Native Encoding and Semantic Quantization Beyond LLMs

Yu Liang, Zhongjin Zhang, Yuxuan Zhu +10

Semantic ID (SID)-based recommendation is a promising paradigm for scaling sequential recommender systems, but existing methods largely follow a semantic-centric pipeline: item emb…

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