Deep learning model predicts ECG with R2 of 0.949, reducing structural uncertainty.

Shaheim Ogbomo-Harmitt, Cesare Magnetti, Jakub Grzelak et al.

Proposes VH-CBM, combining VLM embeddings and minimal annotations via Gaussian Processes to enhance concept accuracy and calibration.

Nicola Debole, Andrea Passerini, Stefano Teso et al.

OCH3R uses Transformer for single-image multi-object 3D reconstruction, achieving high speed and accuracy.

Yi Du, Yang You, Xiang Wan et al.

CRAFT uses reward-based fine-tuning with foundation models to improve clinical alignment in medical image synthesis, reducing low-quality hallucinations.

Yunsung Chung, Alex El Darzi, Carlo El Khoury et al.

CUActSpot benchmark enhances GUI complex interaction performance via data synthesis and multimodal evaluation; Phi-Ground-Any-4B excels.

Miaosen Zhang, Xiaohan Zhao, Zhihong Tan et al.

SenseNova-U1 unifies multimodal understanding and generation via NEO-unify architecture, enhancing vision-language model performance.

Haiwen Diao, Penghao Wu, Hanming Deng et al.

CausalCine achieves real-time multi-shot video generation using a causal autoregressive framework, significantly enhancing cross-shot coherence and interactivity.

Yihao Meng, Zichen Liu, Hao Ouyang et al.

AlphaGRPO enhances UMMs' multimodal generation via Decompositional Verifiable Reward, significantly improving benchmarks like GenEval.

Runhui Huang, Jie Wu, Rui Yang et al.

OmniNFT enhances audio-video generation quality and synchronization through a modality-aware online diffusion RL framework.

Guohui Zhang, XiaoXiao Ma, Jie Huang et al.

FuTCR framework improves new-class panoptic quality by up to 28% in continual panoptic segmentation while enhancing base-class performance.

Nicholas Ikechukwu, Keanu Nichols, Deepti Ghadiyaram et al.

Proposes a synchronized multi-view 3D Gaussian Splatting framework for efficient dynamic scene reconstruction without temporal coupling, validated on a new benchmark.

Yunxiao Zhang, Suryansh Kumar

MoCam employs structured denoising dynamics in diffusion models to unify geometry and appearance for robust novel view synthesis.

Haofeng Liu, Yang Zhou, Ziheng Wang et al.

Introducing perceptual entropy to prevent diversity collapse in flow-based RLHF, achieving a score of 0.734 and diversity of 0.989, surpassing baselines.

Xiaofeng Tan, Jun Liu, Bin-Bin Gao et al.

BARISTA employs dense scene graphs in egocentric videos for multi-task understanding, covering 185 real coffee-making videos with over 3.6 million annotations.

Patrick Knab, Orgest Xhelili, Inis Buzi et al.

Chronicles-OCR evaluates VLLMs' cross-temporal visual perception of Chinese character evolution using a Stage-Adaptive Annotation Paradigm with 2,800 images.

Gengluo Li, Shangpin Peng, Xingyu Wan et al.

PointForward uses point-aligned sparse 3D queries for fast, multi-view consistent driving scene reconstruction, outperforming pixel-aligned methods.

Cheng Chi, Xianqi Wang, Hongcheng Luo et al.

A3 mechanism dynamically determines execution horizon via self-speculative prefix verification, improving success rate and inference efficiency across tasks.

Feng Chen, Xianghui Wang, Yuxuan Chen et al.

LaSCD method reduces visual hallucinations using Laplacian energy, improving accuracy.

Fanpu Cao, Xin Zou, Xuming Hu et al.

CADBench evaluates 11 models on 18,000 samples across 6 metrics, revealing performance gaps in multimodal 3D CAD generation.

Anna C. Doris, Jacob Thomas Sony, Ghadi Nehme et al.

Proposed PaMoSplat integrates part-aware modeling and motion priors for dynamic Gaussian splatting, achieving superior rendering and tracking accuracy.

Yinan Deng, Jianyu Dou, Jiahui Wang et al.