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Jun Luo

16 papers hereh-index 6301 citations17 works total

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

author position
  • middle author10
  • last author4

Across the 14 of 16 papers where every author was matched, so the position is known.

fields
  • cs.CV6
  • cs.CL4
  • cs.AI2
  • cs.LG2
  • cs.NE1
  • cs.SD1
same name
  • Jun Luo — 23 papers, h 21
  • Jun Luo — 16 papers, h 6
  • Jun Luo — 15 papers, h 30
  • Jun Luo — 14 papers, h 52
  • Jun Luo — 11 papers, h 15
  • Jun Luo — 10 papers, h 31

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 citedKimi K2.5: Visual Agentic Intelligence

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

collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026★ 2 cited

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +333

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.CL2025

A Survey of Automatic Evaluation Methods on Text, Visual and Speech Generations

Tian Lan, Yang-Hao Zhou, Zi-Ao Ma +8

Recent advances in deep learning have significantly enhanced generative AI capabilities across text, images, and audio. However, automatically evaluating the quality of these gener…

cs.CL2025

Can Large Language Models Understand Internet Buzzwords Through User-Generated Content

Chen Huang, Junkai Luo, Xinzuo Wang +2

The massive user-generated content (UGC) available in Chinese social media is giving rise to the possibility of studying internet buzzwords. In this paper, we study if large langua…

cs.CL2023

Ask Language Model to Clean Your Noisy Translation Data

Quinten Bolding, Baohao Liao, Brandon James Denis +2

Transformer models have demonstrated remarkable performance in neural machine translation (NMT). However, their vulnerability to noisy input poses a significant challenge in practi…

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