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Junming Lin

7 papers hereh-index 3646 citations6 works total

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

author position
  • sole author1
  • first author1
  • middle author4

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.AI1
  • cs.CL1
  • cs.LG1
same name
  • Junming Lin — 2 papers, h 2
  • Junming Lin — 1 paper
  • Junming Lin — 1 paper

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
20242026
most citedVLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

3 citations · 3 across the 6 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.AI2026

MMPostTrainBench: Benchmarking Autonomous Research for Multimodal Post-Training

Yuxin Liu, Yuxuan Wang, Zhenxin Lei +9

Autonomous research seeks sustained model improvements through iterative experimentation and feedback. LLM agents show promise in automating machine learning and language-model pos…

cs.CL2026

Qwen3.8-Omni: Towards Native Omni-Modal Agents

Qwen Team

We introduce Qwen3.8-Omni-Flash, a natively multimodal agentic model for real-world multimodal productivity. Compared with previous omni models, which primarily emphasized percepti…

cs.LG2026

Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale

Yicheng Zou, Dongsheng Zhu, Lin Zhu +174

We introduce Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model. Scaling to this unprecedented size, the model delivers a comprehensive enhancem…

cs.CV2026

Trust Your Critic: Robust Reward Modeling and Reinforcement Learning for Faithful Image Editing and Generation

Xiangyu Zhao, Peiyuan Zhang, Junming Lin +7

Reinforcement learning (RL) has emerged as a promising paradigm for enhancing image editing and text-to-image (T2I) generation. However, current reward models, which act as critics…

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