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Linqi Song

4 papers hereh-index 223 citations16 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.IT3
  • cs.IR1
same name
  • Linqi Song — 8 papers, h 4
  • Linqi Song — 8 papers, h 5
  • Linqi Song — 7 papers, h 7
  • Linqi Song — 7 papers, h 2
  • Linqi Song — 6 papers, h 11
  • Linqi Song — 6 papers, h 2

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

collaborators

4 papers

cs.IR2025

RALLRec: Improving Retrieval Augmented Large Language Model Recommendation with Representation Learning

Jian Xu, Sichun Luo, Xiangyu Chen +3

Large Language Models (LLMs) have been integrated into recommendation systems to enhance user behavior comprehension. The Retrieval Augmented Generation (RAG) technique is further…

cs.IT2025

Accelerating Data Access for Single Node in Distributed Storage Systems via MDS Codes

Hao Shi, Zhengyi Jiang, Zhongyi Huang +2

Maximum distance separable (MDS) array codes are widely employed in modern distributed storage systems to provide high data reliability with small storage overhead. Compared with t…

cs.IT2024

Error Correction Decoding Algorithms of RS Codes Based on An Earlier Termination Algorithm to Find The Error Locator Polynomial

Zhengyi Jiang, Hao Shi, Zhongyi Huang +4

Reed-Solomon (RS) codes are widely used to correct errors in storage systems. Finding the error locator polynomial is one of the key steps in the error correction procedure of RS c…

cs.IT2024

Reed-Solomon Codes over Cyclic Polynomial Ring with Lower Encoding/Decoding Complexity

Wenhao Liu, Zhengyi Jiang, Zhongyi Huang +2

Reed-Solomon (RS) codes are constructed over a finite field that have been widely employed in storage and communication systems. Many fast encoding/decoding algorithms such as fast…

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