FGOS-Net achieves 91.3% mIoU and 97.1% clDice via frequency-geometric disentanglement.

Jin Bai, Huiyao Zhang, Qi Wen et al.

Study shows risk-controlling recommender systems are vulnerable to 1% user coordination, causing 20% nDCG drop.

Giovanni De Toni, Cristian Consonni, Erasmo Purificato et al.

HISA employs a hierarchical index to accelerate sparse attention, reducing complexity from O(L^2) to near O(L) without retraining, achieving up to 3.75× speedup at 64K context.

Yufei Xu, Fanxu Meng, Fan Jiang et al.

Using Qwen3:30b and others to annotate PersuasionForGood, guilt induction reduces donation rates by 23 percentage points.

Tatiana Petrova, Stanislav Sokol, Radu State

GEMS framework enhances multimodal generation with memory and skills, enabling Z-Image-Turbo to surpass Nano Banana 2 on GenEval2.

Zefeng He, Siyuan Huang, Xiaoye Qu et al.

Proposed a Cross-Scale Decoder for off-road semantic segmentation, achieving 89.97 mIoU.

Seongkyu Choi Jhonghyun An

RINO achieves rotation-invariant non-rigid matching via RINONet, significantly improving 3D shape correspondence accuracy.

Maolin Gao, Shao Jie Hu-Chen, Congyue Deng et al.

DBR-AF framework achieves multivariate time series anomaly detection via dual-branch reconstruction and autoregressive flow, outperforming existing methods.

Jun Liu, Ying Chen, Ziqian Lu et al.

MAR3 framework achieves 69.2% J&F on Ref-AVSBench, surpassing SOTA by 3.4%.

Yuan Zhao, Zhenqi Jia, Yongqiang Zhang

Proposes a nonparametric optimal transport projection method integrating limited coupled data with abundant marginals for joint distribution reconstruction.

Jakwang Kim, Young-Heon Kim, Chan Park

GIFT uses geometric feedback for self-bootstrapping, boosting IoU by 12% and reducing inference costs by 80% in image-to-CAD synthesis.

Giorgio Giannone, Anna Clare Doris, Amin Heyrani Nobari et al.

Syn4Seg framework enhances GFSS performance by generating diverse synthetic images and pseudo-labels, achieving significant improvements on PASCAL-5i and COCO-20i.

Guohuan Xie, Xin He, Dingying Fan et al.

SJD-VP enhances autoregressive image generation by predicting verification to improve acceleration and quality.

Bingqi Shan, Baoquan Zhang, Xiaochen Qi et al.

PAR supervision combines local contrastive learning with causal forward error propagation across five tunable ODE systems.

Menachem Stern, Adam G. Frim, Raúl Candás et al.

Proposes ASPECT, a psychometrically-guided pipeline for AI personal profile inference, achieving moderate alignment without per-user training.

Ruoxi Shang, Dan Marshall, Edward Cutrell et al.

VLA-OPD combines SFT and RL via Reverse-KL distillation, improving sample efficiency and robustness for Vision-Language-Action models.

Zhide Zhong, Haodong Yan, Junfeng Li et al.

Proposes a curvature-aware Expected Free Energy acquisition function for Bayesian optimization, outperforming state-of-the-art methods in joint learning and optimization tasks.

Ajith Anil Meera, Wouter Kouw

DFM-VLA refines robot action sequences iteratively via discrete flow matching, achieving top performance on CALVIN benchmarks.

Jiayi Chen, Wenxuan Song, Jiaxin Fang et al.

VAN-AD combines visual MAE with normalizing flow for enhanced time series anomaly detection.

PengYu Chen, Shang Wan, Xiaohou Shi et al.

DataFlex unifies data selection, mixing, and reweighting, boosting large model training efficiency and accuracy.

Hao Liang, Zhengyang Zhao, Meiyi Qiang et al.