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researcher

Bin Lu

Shanghai Jiao Tong University

16 papers hereh-index 8432 citations31 works total

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

author position
  • first author5
  • middle author10

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

fields
  • cs.AI6
  • cs.LG6
  • cs.CL2
  • cs.DL1
  • cs.IR1
affiliations
  • Shanghai Jiao Tong University
Homepage
same name
  • Bin Lu — 4 papers, h 3
  • Bin Lu — 2 papers, h 2
  • Bin Lu — 1 paper, h 6
  • Bin Lu — 1 paper, h 1
  • Bin Lu — 1 paper, h 0
  • Bin Lu — 1 paper, h 4

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
20222026
most citedSpatio-Temporal Graph Few-Shot Learning with Cross-City Knowledge Transfer

94 citations · 119 across the 16 of their papers we have counts for

collaborators
Showing 2026 · cs.AIShow all

4 papers · 2 filters

cs.AI2026

Compass: Navigating Global Marine Lead Data Integration through Expert-Guided LLM Agent

Yiming Liu, Bin Lu, Meng Jin +6

Marine lead (Pb) and its isotopes are critical tracers for ocean circulation and anthropogenic pollution, yet in-situ observations remain costly and sparse. While vast historical r…

cs.AI2026

SLASH the Sink: Sharpening Structural Attention Inside LLMs

Yiming Liu, Bin Lu, Xinbing Wang +2

Large Language Models (LLMs) show remarkable semantic understanding but often struggle with structural understanding when processing graph topologies in a serialized format. Existi…

cs.AI2026

Inductive Reasoning for Temporal Knowledge Graphs with Emerging Entities

Ze Zhao, Yuhui He, Lyuwen Wu +6

Reasoning on Temporal Knowledge Graphs (TKGs) is essential for predicting future events and time-aware facts. While existing methods are effective at capturing relational dynamics,…

cs.AI2026

Improving LLM Reasoning with Homophily-aware Structural and Semantic Text-Attributed Graph Compression

Zijun Di, Bin Lu, Huquan Kang +5

Large language models (LLMs) have demonstrated promising capabilities in Text-Attributed Graph (TAG) understanding. Recent studies typically focus on verbalizing the graph structur…

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