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researcher

Wenqi Shi

Georgia Institute of Technology

20 papers hereh-index 10388 citations29 works total

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

author position
  • first author2
  • middle author15
  • last author1

Across the 18 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CL10
  • cs.AI4
  • cs.LG3
  • cs.CV2
  • cs.IR1
affiliations
  • Georgia Institute of Technology
Homepage
same name
  • Wenqi Shi — 9 papers, h 13
  • Wenqi Shi — 5 papers, h 5
  • Wenqi Shi — 5 papers, h 4
  • Wenqi Shi — 4 papers, h 2
  • Wenqi Shi — 3 papers, h 4
  • Wenqi Shi — 2 papers, h 1

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 citedBMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers

2 citations · 9 across the 18 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Agents' Last Exam

Yiyou Sun, Xinyang Han, Weichen Zhang +378

Recent AI systems have achieved strong results on a wide range of benchmarks, yet these gains have not translated into economically meaningful deployment across many professional d…

cs.AI2026

ClinEnv: An Interactive Multi-Stage Long Horizon EHR Environment for Agents

Yuxing Lu, Yushuhong Lin, Wenqi Shi +4

Clinical practice is not the selection of an answer from enumerated options: a physician gathers heterogeneous information incrementally and commits to sequential, irreversible dec…

cs.AI2026

Deep reflective reasoning in interdependence constrained structured data extraction from clinical notes for digital health

Jingwei Huang, Kuroush Nezafati, Zhikai Chi +9

Extracting structured information from clinical notes requires navigating a dense web of interdependent variables where the value of one attribute logically constrains others. Exis…

cs.AI2025

Scaling Agentic Reinforcement Learning for Tool-Integrated Reasoning in VLMs

Meng Lu, Ran Xu, Yi Fang +14

While recent vision-language models (VLMs) demonstrate strong image understanding, their ability to "think with images", i.e., to reason through multi-step visual interactions, rem…

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