App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 9

Fine-grained image generation via interleaved multimodal chain-of-thought reward

Zheng Kai1a
Zhou Yuanyuan1b
Xu Linli1a
1. a. School of Computer Science and Technology, b. Information Science Center, University of Science and Technology of China, Hefei Anhui 230027, China
DOI: 10.19734/j.issn.1001-3695.2026.02.0023

Abstract

Fine-grained semantic alignment remains a major challenge for current text-to-image generation models, especially in compositional scenarios involving attribute binding, numeracy, and spatial structure. Existing methods often rely on specific model architectures and high-cost training or inference, which limits stable semantic correction and unified optimization across paradigms. To address this issue, this study proposed ICOTR, a unified semantic alignment reward fine-tuning framework based on an interleaved multimodal chain-of-thought reasoning mechanism. ICOTR used the image-text understanding capability of multimodal large language models to build adaptive multi-dimensional semantic reward feedback, and applied consistent semantic guidance to both diffusion and autoregressive models. Experiments on the high-semantic-complexity benchmark T2I-CompBench++ showed that ICOTR improved the overall performance of SDXL from 0.4114 to 0.4965 and that of Show-o from 0.3815 to 0.5202. The results indicate that ICOTR consistently outperforms existing methods in overall performance and several key subtasks, and effectively improves fine-grained image generation across different paradigms.

Foundation Support

国家自然科学基金资助项目(62276245)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.02.0023
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 9

Publish History

[2026-06-02] Accepted Paper

Cite This Article

郑凯, 周远远, 徐林莉. 交错模态思维链奖励机制的细粒度图像生成 [J]. 计算机应用研究, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.02.0023. (Zheng Kai, Zhou Yuanyuan, Xu Linli. Fine-grained image generation via interleaved multimodal chain-of-thought reward [J]. Application Research of Computers, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2026.02.0023. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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