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researcher

Jing Zhang

27 papers hereh-index 212.4k citations69 works total

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

author position
  • first author1
  • middle author21
  • last author4

Across the 26 of 27 papers where every author was matched, so the position is known.

fields
  • cs.CL14
  • cs.AI4
  • cs.DB4
  • cs.IR2
  • cs.LG2
  • cs.SI1
same name
  • Jing Zhang — 57 papers, h 41
  • Jing Zhang — 39 papers, h 23
  • Jing Zhang — 35 papers, h 32
  • Jing Zhang — 23 papers, h 19
  • Jing Zhang — 21 papers, h 11
  • Jing Zhang — 20 papers, h 9

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
20192026
most citedSubgraph Retrieval Enhanced Model for Multi-hop Knowledge Base Question Answering

107 citations · 183 across the 26 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.LG2025

QUAD: Quantization and Parameter-Efficient Tuning of LLM with Activation Decomposition

Yuxuan Hu, Xiaodong Chen, Cuiping Li +2

Large Language Models (LLMs) excel in diverse applications but suffer inefficiency due to massive scale. While quantization reduces computational costs, existing methods degrade ac…

cs.DB2025★ 1 cited

A Query Optimization Method Utilizing Large Language Models

Zhiming Yao, Haoyang Li, Jing Zhang +2

Query optimization is a critical task in database systems, focused on determining the most efficient way to execute a query from an enormous set of possible strategies. Traditional…

cs.DB2025

LLMIA: An Out-of-the-Box Index Advisor via In-Context Learning with LLMs

Xinxin Zhao, Xinmei Huang, Haoyang Li +7

Index recommendation is crucial for optimizing database performance. However, existing heuristic- and learning-based methods often rely on inefficient exhaustive search and estimat…

cs.CL2025

LoRS: Efficient Low-Rank Adaptation for Sparse Large Language Model

Yuxuan Hu, Jing Zhang, Xiaodong Chen +3

Existing low-rank adaptation (LoRA) methods face challenges on sparse large language models (LLMs) due to the inability to maintain sparsity. Recent works introduced methods that m…

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