arXiv Machine Learning

Element-Aware Group Learning for E-Commerce Image Generation

arXiv:2608. 00584v1 Announce Type: cross Abstract: Recent advances in image generation and editing have made prompt quality a key bottleneck for e-commerce creatives.

arXiv Machine Learning

Jun 29

Qwen-Image-2.0-RL Technical Report

arXiv:2606. 27608v1 Announce Type: cross Abstract: We present Qwen-Image-2.

By Yixian Xu, Kaiyuan Gao, Yuxiang Chen, Yilei Chen, Zecheng Tang, Zihao Liu, Zikai Zhou, Deqing Li, Hao Meng, Kuan Cao, Jiahao Li, Jie Zhang, Liang Peng, Lihan Jiang, Ningyuan Tang, Shengming Yin, Tianhe Wu, Xiaoyue Chen, Yan Shu, Yanran Zhang, Yi Wang, Yu Wu, Yujia Wu, Zekai Zhang, Zhendong Wang, Xiao Xu, Kun Yan, Chenfei Wu

llms diffusion reinforcement-learning fine-tuning efficiency multimodal safety

arXiv AI

Jun 18

ProductConsistency: Improving Product Identity Preservation in Instruction-Based Image Editing via SFT and RL

arXiv:2606. 19103v1 Announce Type: cross Abstract: Recent advances in instruction-based image editing have enabled models to perform complex visual edits from natural language instructions.

By Mukund Khanna, Raj Singh Yadav, Kunal Singh

computer-vision reinforcement-learning fine-tuning benchmarks

Hugging Face Trending Papers

Jun 1

MT-EditFlow: Reinforcement Learning for Multi-Turn Image Editing with Flow Matching

Recent breakthroughs in instruction-based image editing have captured significant attention, as models are now capable of handling real-world editing demands with the practicality required by everyday users. However, editing models trained primarily for single-turn edits often break down in multi-turn editing--the natural interactive setting where a user iteratively refines an image based on the model's own previous outputs.

diffusion reinforcement-learning multimodal benchmarks safety

Hugging Face Trending Papers

3d ago

TransAnyText: Translating Arbitrary Text in E-commerce Images via Structured Visual Generation

Cross-border e-commerce image translation is essential for global retail, where product images, banners, and detail pages need to be produced in different languages. Existing methods struggle to achieve accurate translation, faithful visual identity preservation, and easy-to-edit outputs, simultaneously.

llms diffusion reinforcement-learning fine-tuning efficiency multimodal benchmarks

arXiv AI

Jun 16

Efficient Reinforcement for Visual-Textual Thinking with Discrete Diffusion Model

arXiv:2606. 14792v1 Announce Type: cross Abstract: RL-based post-training has been widely adopted to enable interleaved visual and textual reasoning in unified multimodal models capable of both text and image generation.

By Yoonjeon Kim, Yuhta Takida, Chieh-Hsin Lai, Eunho Yang, Yuki Mitsufuji

diffusion reinforcement-learning multimodal

Hugging Face Trending Papers

Jun 4

ShotCrop$^3$: Cropping Human-Centric Images into Cinematic Triple-Shot Compositions

Prior work on aesthetic composition typically produces a single aesthetically pleasing crop, overlooking the narrative value of composing multiple shots from one scene. In practice, multi-shot composition is critical for downstream creative workflows: commercial posters often require multiple crops with different emphases (e.

llms fine-tuning benchmarks

arXiv AI

Aug 11

COMEX: A Composition-Grounded Benchmark and Learning Framework for Explainable Aesthetic Image Cropping

arXiv:2608. 07570v1 Announce Type: cross Abstract: Explainable aesthetic image cropping requires not only localizing a visually pleasing crop but also explaining why it is preferred.

By Rui Yang, Wei Zhou, Dingyong Gou, Xiaohui Cui, Cong Li, Yinyin Gong, Yipo Huang, Jiliang Zhao

llms fine-tuning multimodal benchmarks

arXiv AI

Jul 28

VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing

arXiv:2607. 22632v1 Announce Type: new Abstract: The rapid rise of vlogs as a personalized storytelling medium has created a demand for automated systems to evaluate and refine vlog editing plans.

By Yexiang Liu, Wen Zhong, Sijie Zhu, Xin Gu, Fan Chen, Junxian Duan, Jie Cao, Longyin Wen, Zhenfang Chen

llms reinforcement-learning multimodal benchmarks

arXiv Machine Learning

Aug 5

Crayotter: Learning Long-Horizon Video Editing Agents via Group-Relative Preference Backpropagation

arXiv:2608. 02694v1 Announce Type: cross Abstract: Long-horizon video editing agents receive final-product feedback only after many interdependent decisions.

By Lecheng Yan, Jianze Lin, Yichong Zhang, Ben Pan, Wenxi Li, Chenyang Lyu, Liting Zhou, Cathal Gurrin

agents benchmarks

Hugging Face Trending Papers

Aug 3

MIEScore: Human-Aligned Evaluation for Multi-Source Image Editing

Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-Pro and GPT-Image-2 demonstrate emerging capabilities in multi-source image editing (MIE), including tasks such as object synthesis, person-background composition, and cross-image style fusion.

llms fine-tuning multimodal benchmarks

arXiv AI

Aug 11

What to Edit Next: Visually Aligned Image-Editing Follow-Up Suggestions in Conversational Systems

arXiv:2608. 07565v1 Announce Type: cross Abstract: Conversational assistants increasingly recommend follow-up edits to help users continue a task.

By Zhijing Zhang, Jinpeng Yu, Xin Song, Bingnan Li, Chuyue Li, Changhui Du, Xiaolin Fang, Jiaming Liu, Ruihua Huang

reinforcement-learning fine-tuning multimodal

arXiv AI

Jul 1

TRIAGE: Role-Typed Credit Assignment for Agentic Reinforcement Learning

arXiv:2606. 32017v1 Announce Type: cross Abstract: Agentic reinforcement learning requires assigning credit to environment-facing actions such as searches, clicks, edits, navigation commands, and object interactions.

By Yuanda Xu, Zhengze Zhou, Hejian Sang, Xiaomin Li, Jiaxin Zhang, Xinchen Du, Zhipeng Wang, Alborz Geramifard

agents reinforcement-learning

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