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researcher

Jun Zhou

11 papers here

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

author position
  • middle author8
  • last author2

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.CL3
  • cs.LG3
  • cs.CV1
same name
  • Jun Zhou — 28 papers, h 26
  • Jun Zhou — 17 papers, h 20
  • Jun Zhou — 16 papers
  • Jun Zhou — 16 papers, h 22
  • Jun Zhou — 16 papers
  • Jun Zhou — 11 papers, h 20

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

most citedOn Path to Multimodal Historical Reasoning: HistBench and HistAgent

1 citations · 2 across the 8 of their papers we have counts for

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Ostrakon-VL: Towards Domain-Expert MLLM for Food-Service and Retail Stores

Zhiyong Shen, Gongpeng Zhao, Jun Zhou +10

Multimodal Large Language Models (MLLMs) have recently achieved substantial progress in general-purpose perception and reasoning. Nevertheless, their deployment in Food-Service and…

cs.AI2025

M2-Reasoning: Empowering MLLMs with Unified General and Spatial Reasoning

Inclusion AI, :, Fudong Wang +12

Recent advancements in Multimodal Large Language Models (MLLMs), particularly through Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced their reaso…

cs.AI2025★ 1 cited

On Path to Multimodal Historical Reasoning: HistBench and HistAgent

Jiahao Qiu, Fulian Xiao, Yimin Wang +96

Recent advances in large language models (LLMs) have led to remarkable progress across domains, yet their capabilities in the humanities, particularly history, remain underexplored…

cs.AI2025★ 1 cited

Ming-Omni: A Unified Multimodal Model for Perception and Generation

Inclusion AI, Biao Gong, Cheng Zou +55

We propose Ming-Omni, a unified multimodal model capable of processing images, text, audio, and video, while demonstrating strong proficiency in both speech and image generation. M…

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