DiT4SR integrates bidirectional attention and local info injection, significantly improving real-world image super-resolution performance.

Zheng-Peng Duan, Jiawei Zhang, Xin Jin et al.

Proposes a taxonomy for GUI agent trust, addressing perception, reasoning, and interaction trust.

Yucheng Shi, Wenhao Yu, Jingyuan Huang et al.

Proposed Magiv3 unifies detection, OCR, and grounding tasks, enabling automated manga-to-text conversion with 85% detection accuracy and 92% OCR rate.

Ragav Sachdeva, Andrew Zisserman

Agentic LLMs enhance decision-making via reasoning, acting, and interacting, significantly improving medical diagnosis and logistics analysis.

Aske Plaat, Max van Duijn, Niki van Stein et al.

Hi3DGen generates high-fidelity 3D geometry from images using normal bridging, achieving superior detail fidelity.

Chongjie Ye, Yushuang Wu, Ziteng Lu et al.

Proposes Enhanced Instance Replay (EIR) combining dynamic class merging and background fusion to mitigate catastrophic forgetting in continual semantic segmentation.

Hongmei Yin, Tingliang Feng, Fan Lyu et al.

CORAL employs contrastive preference expansion and learning, achieving up to 99.72% Recall@10, significantly improving retrieval-based conversational recommendation.

Heejin Kook, Junyoung Kim, Seongmin Park et al.

OntoAligner: a modular Python toolkit integrating traditional and AI methods for large-scale ontology alignment, achieving high accuracy with efficiency.

Hamed Babaei Giglou, Jennifer D'Souza, Oliver Karras et al.

Introduces Video-R1 with T-GRPO algorithm and hybrid datasets, achieving 37.1% accuracy on VSI-Bench, surpassing GPT-4o.

Kaituo Feng, Kaixiong Gong, Bohao Li et al.

This study surveys the evolution of physics cognition in video generation, proposing a three-tier taxonomy.

Minghui Lin, Xiang Wang, Yishan Wang et al.

LeX-Art enhances text rendering in T2I models via high-quality data synthesis, achieving 79.81% PNED improvement and superior attribute accuracy.

Shitian Zhao, Qilong Wu, Xinyue Li et al.

UI-R1 enhances GUI action prediction via rule-based RL, achieving 22.1% accuracy improvement.

Zhengxi Lu, Yuxiang Chai, Yaxuan Guo et al.

Proposes a methodology-centered taxonomy for LLM agents, covering construction, collaboration, and evolution, advancing towards artificial general intelligence.

Junyu Luo, Weizhi Zhang, Ye Yuan et al.

Proposes R-PRM, leveraging stronger models for seed data, preference optimization, and multi-trajectory inference, boosting step evaluation F1 by 11.9 points.

Shuaijie She, Junxiao Liu, Yifeng Liu et al.

Survey on vision-to-music generation, analyzing technical challenges and providing datasets and evaluation metrics.

Zhaokai Wang, Chenxi Bao, Le Zhuo et al.

Using Llama-3.1-8B, 73% of responses were highly relevant with 100% recall.

Julia Ive, Felix Jozsa, Nick Jackson et al.

Proposes holistic mathematical modeling using multilayer networks and simulation to overcome reductionist limits in biological systems.

Ramón Nartallo-Kaluarachchi, Renaud Lambiotte, Alain Goriely

Proposed RIM manifold optimization reduces complexity from O(n^3) to O(n), excelling in tasks like image denoising.

Jinghui Yuan, Fangyuan Xie, Feiping Nie et al.

Wan employs a diffusion transformer with 14B parameters, achieving state-of-the-art video generation performance.

Team Wan, Ang Wang, Baole Ai et al.

Introduced 3MDBench, a multimodal multi-agent framework for realistic telemedicine evaluation, improving diagnostic F1 by up to 20%.

Ivan Sviridov, Amina Miftakhova, Artemiy Tereshchenko et al.