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Pei Li

7 papers hereh-index 240 citations9 works total

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

author position
  • middle author7

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.RO3
  • cs.LG2
  • cs.AI1
  • cs.CR1
same name
  • Pei Li — 8 papers, h 2
  • Pei Li — 6 papers, h 7
  • Pei Li — 4 papers, h 7
  • Pei Li — 4 papers, h 3
  • Pei Li — 4 papers, h 2
  • Pei Li — 4 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

activity
20242026
collaborators
Showing 2026Show all

4 papers · 1 filter

cs.LG2026

Forecasting the Emergence and Evolution of Crash Hotspots: A Unified Deep Learning Framework for Proactive Traffic Safety

Jingwen Zhu, Keshu Wu, Pei Li +3

Road crashes remain among the gravest threats to public safety, and preventing them is a defining task of transportation systems worldwide. Much of that harm concentrates at hotspo…

cs.LG2026

Geometry-Aware Infrastructure-Anchored Denoiser for UWB Sensing and Work-Zone Reconstruction

Weizhe Tang, Jiaxi Liu, Junwei you +5

Accurate work-zone geometry perception is critical for intelligent transportation systems, and ultra-wideband sensing offers a low-cost approach for infrastructure-aided reconstruc…

cs.CR2026

An Agentic Workflow for Detecting Personally Identifiable Information in Crash Narratives

Junyi Ma, Pei Li, Rui Gan +3

Crash narratives in crash reports provide crucial contextual information for traffic safety analysis. Yet, their broader use is hindered by the presence of personally identifiable…

cs.RO2026

V2X-QA: A Comprehensive Reasoning Dataset and Benchmark for Multimodal Large Language Models in Autonomous Driving Across Ego, Infrastructure, and Cooperative Views

Junwei You, Pei Li, Zhuoyu Jiang +7

Multimodal large language models (MLLMs) have shown strong potential for autonomous driving, yet existing benchmarks remain largely ego-centric and therefore cannot systematically…

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