GazeVLA: Learning Human Intention for Robotic Manipulation
GazeVLA learns human intention to enhance robotic manipulation, significantly outperforming baseline methods.
Chengyang Li, Kaiyi Xiong, Yuan Xu et al.
GazeVLA learns human intention to enhance robotic manipulation, significantly outperforming baseline methods.
Chengyang Li, Kaiyi Xiong, Yuan Xu et al.
From natural language to verified code using Dafny, Gemma 4-31B achieved a 90.91% verification success rate.
Md Erfan, Md Kamal Hossain Chowdhury, Ahmed Ryan et al.
Proposes an LLM-based evaluation framework to enhance math reasoning assessment accuracy beyond symbolic math limitations.
Erez Yosef, Oron Anschel, Shunit Haviv Hakimi et al.
EV-CLIP efficiently adapts CLIP for few-shot action recognition under visual challenges using visual prompts.
Hyo Jin Jon, Longbin Jin, Eun Yi Kim
RedVLA identifies physical safety risks in VLA models through a two-stage process, achieving an ASR of 95.5%.
Yuhao Zhang, Borong Zhang, Jiaming Fan et al.
FlowAnchor stabilizes video editing signals using spatial attention and adaptive modulation for efficient multi-object scene editing.
Ze Chen, Lan Chen, Yuanhang Li et al.
WassersteinGrad explains dynamic physical field predictions by computing the entropic Wasserstein barycenter, enhancing autoregressive weather forecasting model interpretability.
Younes Essafouri, Laure Raynaud, Luciano Drozda et al.
The study shows that deep networks learn useful nonrobust features in medical images, achieving high accuracy on five MedMNIST tasks.
Coenraad Mouton, Randle Rabe, Niklas C. Koser et al.
Introduced TAWin method using WPAUC to optimize RL-based recommenders, enhancing Top-K performance.
Wentao Shi, Qifan Wang, Chen Chen et al.
Decoding high-dimensional finger motion using Riemannian features and RNNs, TRR achieves 9.79° error on EMG-FK dataset.
Martin Colot, Cédric Simar, Guy Cheron et al.
FedSPDnet outperforms traditional methods on EEG datasets using ProjAvg and RLAvg strategies, enhancing F1 score and robustness.
Thibault Pautrel, Florent Bouchard, Ammar Mian et al.
Point&Grasp enables flexible selection of out-of-reach objects through probabilistic cue integration, improving accuracy and speed.
Xuejing Luo, Hee-Seung Moon, Christian Holz et al.
HubRouter replaces O(n^2) attention with O(nM) routing for efficiency gains.
Abhinaba Basu
AgentSearchBench improves agent search ranking quality using execution signals, bridging the gap between semantics and performance.
Bin Wu, Arastun Mammadli, Xiaoyu Zhang et al.
SQUEAK algorithm achieves low space complexity for kernel ridge regression using unnormalized ridge leverage scores.
Daniele Calandriello, Alessandro Lazaric, Michal Valko
Pliable Rejection Sampling (PRS) learns the proposal distribution using kernel estimation, ensuring high-probability i.i.d. sampling.
Akram Erraqabi, Michal Valko, Alexandra Carpentier et al.
LeHome simulation environment achieves high-fidelity manipulation of deformable objects in household scenarios using PBD and FEM.
Zeyi Li, Yushi Yang, Shawn Xie et al.
Proposes a co-evolutionary theory of human-AI coexistence with a dynamic system model emphasizing mutualism and governance.
Somyajit Chakraborty
Proposes a complementarity fusion method for semantic and collaborative views, avoiding global alignment limitations to enhance recommender systems.
Maolin Wang, Dongze Wu, Jianing Zhou et al.
ResRank enhances retrieval efficiency and effectiveness via residual passage compression and end-to-end joint training.
Xiaojie Ke, Shuai Zhang, Liansheng Sun et al.