Adaptive Kernel Selection for Kernelized Diffusion Maps
Adaptive kernel selection enhances stability and accuracy of kernelized diffusion maps.
Othmane Aboussaad, Adam Miraoui, Boumediene Hamzi et al.
Adaptive kernel selection enhances stability and accuracy of kernelized diffusion maps.
Othmane Aboussaad, Adam Miraoui, Boumediene Hamzi et al.
ArbGraph enhances long-form RAG reliability through conflict-aware evidence arbitration, reducing hallucinations.
Qingying Niu, Yuhao Wang, Ruiyang Ren et al.
DAG-STL framework achieves zero-shot trajectory planning under Signal Temporal Logic (STL) constraints, significantly enhancing complex task planning capabilities.
Ruijia Liu, Ancheng Hou, Xiao Yu et al.
Enhancing glass surface reconstruction using depth prior improves robot navigation accuracy.
Jiamin Zheng, Jingwen Yu, Guangcheng Chen et al.
Bias-aware simulation-based inference framework addresses selection bias, enhancing estimation accuracy.
Jonas Arruda, Sophie Chervet, Paula Staudt et al.
Relative state estimation using event-based propeller sensing with error under 3%.
Ravi Kumar Thakur, Luis Granados Segura, Jan Klivan et al.
EmbodiedLGR-Agent integrates lightweight graph representation and retrieval for efficient semantic-spatial memory in robots.
Paolo Riva, Leonardo Gargani, Matteo Frosi et al.
COFFAIL dataset includes successful and anomalous robot skill executions in coffee preparation, supporting imitation learning.
Alex Mitrevski, Ayush Salunke
Similarity-based portfolio construction enhances black-box optimization via k-nearest neighbor fine-tuning.
Catalin-Viorel Dinu, Diederick Vermetten, Carola Doerr
MARC method improves recommendation efficiency by modular representation compression, achieving a 2.82% eCPM lift in online tests.
Yunjia Xi, Menghui Zhu, Jianghao Lin et al.
Introduces a framework for understanding the fragility of human-AI collaboration, analyzing grounding conditions and repair burden.
Varad Vishwarupe, Marina Jirotka, Nigel Shadbolt et al.
Analysis of generalization bounds in symbolic regression with genetic programming, revealing complexities in structure selection and constant fitting.
Masahiro Nomura, Ryoki Hamano, Isao Ono
A fully parallel probabilistic Ising machine with inertia achieves significant speedup and improved success rate for real-time applications.
Ruomin Zhu, Abhishek Kumar Singh, Jérémie Laydevant et al.
VS-WNO fails to translate spike sparsity into deployment cost advantage on Jetson Orin Nano.
Jason Yoo, Shailesh Garg, Souvik Chakraborty et al.
LaviGen framework repurposes 3D generative models for autoregressive layout generation, achieving 19% higher physical plausibility on LayoutVLM benchmark.
Haoran Feng, Yifan Niu, Zehuan Huang et al.
A smaller model post-trained with reinforcement learning excels in small-molecule drug design tasks, rivaling state-of-the-art frontier models.
Shriram Chennakesavalu, Kirill Shmilovich, Hayley Weir et al.
Proposed DeepInsightTheorem framework enhances informal theorem proving by identifying core techniques, significantly outperforming baselines.
Yunhe Li, Hao Shi, Bowen Deng et al.
A dual-aspect evaluation framework analyzes LLMs on Vietnamese legal text, revealing readability-accuracy trade-offs.
Van-Truong Le
Proposed SAGR framework coordinates multi-robot language-guided search using semantic area graphs, improving efficiency by 18.8% in large environments.
Ruiyang Wang, Hao-Lun Hsu, Jiwoo Kim et al.
Task-reward optimization enhances Llama-3.2-3B-Instruct's performance on math datasets.
Sarthak Mittal, Leo Gagnon, Guillaume Lajoie