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Guoliang Xing

20 papers hereh-index 10336 citations25 works total

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

author position
  • middle author9
  • last author7

Across the 16 of 20 papers where every author was matched, so the position is known.

fields
  • cs.AI5
  • cs.LG4
  • cs.CV3
  • cs.HC2
  • cs.CL1
  • cs.CR1
same name
  • Guoliang Xing — 7 papers, h 3
  • Guoliang Xing — 6 papers, h 15
  • Guoliang Xing — 2 papers, h 2
  • Guoliang Xing — 2 papers, h 5
  • Guoliang Xing — 1 paper, h 49
  • Guoliang Xing — 1 paper, 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
20232026
most citedSoar: Design and Deployment of A Smart Roadside Infrastructure System for Autonomous Driving

3 citations · 14 across the 15 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

EdgeCraft: Automated Model Crafting for Edge IoT

Genglin Wang, Kaiwei Liu, Liekang Zeng +4

Machine learning (ML) increasingly powers Internet of Things (IoT) applications at the edge. Yet producing a deployable edge ML artifact for a specific scenario requires navigating…

cs.LG2026

CacheRepair: Learning to Repair Cross-Chunk Context in RAG for KV Cache Fusion

Genglin Wang, Wangsong Yin, Yeerzhati Abudunuer +3

Multi-document retrieval-augmented generation (RAG) requires a language model to process multiple retrieved text chunks before answering a question. Precomputing each chunk's KV ca…

cs.LG2025

SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients

Heming Fu, Hongkai Chen, Shan Lin +1

Alzheimer's Disease (AD) has become an increasingly critical global health concern, which necessitates effective monitoring solutions in smart health applications. However, the dev…

cs.LG2023★ 3 cited

EdgeFM: Leveraging Foundation Model for Open-set Learning on the Edge

Bufang Yang, Lixing He, Neiwen Ling +5

Deep Learning (DL) models have been widely deployed on IoT devices with the help of advancements in DL algorithms and chips. However, the limited resources of edge devices make the…

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