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researcher

Jiawei Jiang

16 papers hereh-index 587 citations37 works total

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

author position
  • middle author8
  • last author7

Across the 15 of 16 papers where every author was matched, so the position is known.

fields
  • cs.LG6
  • cs.AI3
  • cs.CL3
  • cs.IR2
  • cs.DC1
  • cs.SI1
same name
  • Jiawei Jiang — 16 papers, h 25
  • Jiawei Jiang — 5 papers, h 1
  • Jiawei Jiang — 4 papers, h 6
  • Jiawei Jiang — 4 papers, h 4
  • Jiawei Jiang — 4 papers, h 1
  • Jiawei Jiang — 2 papers, h 6

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
20232026
most citedTreeCSS: An Efficient Framework for Vertical Federated Learning

3 citations · 5 across the 16 of their papers we have counts for

collaborators
Showing 2026 · cs.LGShow all

4 papers · 2 filters

cs.LG2026

Text-attributed Graph Condensation via Text Selection and Attribute Matching

Haowei Han, Yuxiang Wang, Guojia Wan +5

Text-Attributed Graph (TAG) is an important type of graph structured data, where each node has a text description. TAG models usually train a Graph Neural Network (GNN) and languag…

cs.LG2026

Scheduling LLM Inference with Uncertainty-Aware Output Length Predictions

Haoyu Zheng, Yongqiang Zhang, Fangcheng Fu +7

To schedule LLM inference, the \textit{shortest job first} (SJF) principle is favorable by prioritizing requests with short output lengths to avoid head-of-line (HOL) blocking. Exi…

cs.LG2026

Efficient Serving for Dynamic Agent Workflows with Prediction-based KV-Cache Management

Haoyu Zheng, Fangcheng Fu, Jia Wu +6

LLM-based workflows compose specialized agents to execute complex tasks, and these agents usually share substantial context, allowing KV-Cache reuse to save computation. Existing a…

cs.LG2026

MTServe: Efficient Serving for Generative Recommendation Models with Hierarchical Caches

Xin Wang, Chi Ma, Shaobin Chen +14

Generative recommendation (GR) offers superior modeling capabilities but suffers from prohibitive inference costs due to the repeated encoding of long user histories. While cross-r…

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