BioMol-MQA constructs a multi-modal drug interaction QA dataset integrating knowledge graphs, text, and SMILES, enhancing LLM reasoning in biomedical tasks.

Saptarshi Sengupta, Shuhua Yang, Paul Kwong Yu et al.

Proposes a real-time large-scale scene reconstruction method combining fast initial pose estimation and direct Gaussian primitive sampling, completing scene modeling within 30 minutes with PSNR 21.7dB.

Andreas Meuleman, Ishaan Shah, Alexandre Lanvin et al.

TimeMCL employs WTA loss in multi-head neural networks for diverse probabilistic time series forecasting, achieving high-quality multi-modal predictions with theoretical guarantees.

Adrien Cortés, Rémi Rehm, Victor Letzelter

A delayed-exploration MTS algorithm matches the best predictor within O(OPT^{2/3}), with a nearly matching lower bound.

Matei Gabriel Coşa, Marek Eliáš

Proposes 3D-aware pseudo-label learning for semantic correspondence, achieving over 4% improvement on SPair-71k.

Olaf Dünkel, Thomas Wimmer, Christian Theobalt et al.

PAM combines SAM 2 and LLMs for efficient, multi-task regional understanding in images and videos, achieving 1.2-2.4× faster performance.

Weifeng Lin, Xinyu Wei, Ruichuan An et al.

Introduces MMSU, a comprehensive benchmark with 47 tasks, integrating audio, semantics, prosody, and reasoning, evaluating 22 SpeechLLMs.

Dingdong Wang, Junan Li, Jincenzi Wu et al.

UNO algorithm uses orthogonalization for fast unlearning in generative models while maintaining generation quality.

Pinak Mandal, Georg A. Gottwald

GUI-Critic-R1 model with S-GRPO optimizes pre-operation error diagnosis in GUI automation, achieving 85% critic accuracy and improving success rate from 22.4% to 27.6%.

Yuyang Wanyan, Xi Zhang, Haiyang Xu et al.

Follow-Your-Creation employs a video inpainting framework to generate and edit 4D content from monocular videos, achieving multi-view consistency and flexible editing.

Yue Ma, Kunyu Feng, Xinhua Zhang et al.

Struct2D enables 3D spatial reasoning using perception-guided structured 2D inputs, achieving high performance without explicit 3D data.

Fangrui Zhu, Hanhui Wang, Yiming Xie et al.

Proposes pseudo-simulation combining real data and synthetic observations via 3D Gaussian Splatting, achieving R²=0.8 correlation with closed-loop evaluation, outperforming open-loop methods.

Wei Cao, Marcel Hallgarten, Tianyu Li et al.

Extended Cutoff: near-optimal multi-agent control by thinking beyond visible range

Alex DeWeese, Guannan Qu

Ether0, a 24B-parameter scientific reasoning model trained via reinforcement learning, outperforms existing chemistry models on molecular design tasks with high data efficiency.

Siddharth M. Narayanan, James D. Braza, Ryan-Rhys Griffiths et al.

R-Search enhances LLM reasoning with search via multi-reward reinforcement learning, achieving a 32.2% improvement.

Qingfei Zhao, Ruobing Wang, Dingling Xu et al.

Systematic data recipes improve reasoning models, achieving 53% on AIME 2025, 51% on LiveCodeBench, and 54% on GPQA, surpassing previous models.

Etash Guha, Ryan Marten, Sedrick Keh et al.

Proposes Contour Errors (CE), an ego-centric matching metric based on Hausdorff distance, improving 3D MOT evaluation over IoU and CPD.

Sharang Kaul, Simon Bultmann, Mario Berk et al.

Rex-Thinker uses Chain-of-Thought reasoning for object referring, enhancing precision and interpretability.

Qing Jiang, Xingyu Chen, Zhaoyang Zeng et al.

Pre³ transforms LR(1) grammar into DPDA, reducing decoding time by 40% and increasing throughput by 36%.

Junyi Chen, Shihao Bai, Zaijun Wang et al.

A prompt-based multi-agent framework raises GPT-4o-mini PrivacyQA performance from 0.394 to 0.587 while narrowing dialect gaps.

Đorđe Klisura, Astrid R Bernaga Torres, Anna Karen Gárate-Escamilla et al.