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Jiajun Zhang

8 papers hereh-index 441 citations13 works total

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

author position
  • first author1
  • middle author4
  • last author2

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AI1
  • cs.CL1
  • cs.LG1
  • cs.RO1
same name
  • Jiajun Zhang — 13 papers, h 7
  • Jiajun Zhang — 9 papers, h 6
  • Jiajun Zhang — 8 papers, h 5
  • Jiajun Zhang — 7 papers, h 4
  • Jiajun Zhang — 6 papers, h 6
  • Jiajun Zhang — 5 papers, 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

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

LENS: Multi-level Evaluation of Multimodal Reasoning with Large Language Models

Ruilin Yao, Bo Zhang, Jirui Huang +18

Multimodal Large Language Models (MLLMs) have achieved significant advances in integrating visual and linguistic information, yet their ability to reason about complex and real-wor…

cs.CV2025

MERIT: Multilingual Semantic Retrieval with Interleaved Multi-Condition Query

Wei Chow, Yuan Gao, Linfeng Li +15

Semantic retrieval is crucial for modern applications yet remains underexplored in current research. Existing datasets are limited to single languages, single images, or singular r…

cs.CV2025

CueBench: Advancing Unified Understanding of Context-Aware Video Anomalies in Real-World

Yating Yu, Congqi Cao, Zhaoying Wang +6

How far are deep models from real-world video anomaly understanding (VAU)? Current works typically emphasize on detecting unexpected occurrences deviated from normal patterns or co…

cs.CV2025

MARS2 2025 Challenge on Multimodal Reasoning: Datasets, Methods, Results, Discussion, and Outlook

Peng Xu, Shengwu Xiong, Jiajun Zhang +125

This paper reviews the MARS2 2025 Challenge on Multimodal Reasoning. We aim to bring together different approaches in multimodal machine learning and LLMs via a large benchmark. We…

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