Tootfinder

Lightweight and Accurate Multi-View Stereo with Confidence-Aware Diffusion Model
Fangjinhua Wang, Qingshan Xu, Yew-Soon Ong, Marc Pollefeys
https://arxiv.org/abs/2509.15220 http…

Lightweight and Accurate Multi-View Stereo with Confidence-Aware Diffusion Model
To reconstruct the 3D geometry from calibrated images, learning-based multi-view stereo (MVS) methods typically perform multi-view depth estimation and then fuse depth maps into a mesh or point cloud. To improve the computational efficiency, many methods initialize a coarse depth map and then gradually refine it in higher resolutions. Recently, diffusion models achieve great success in generation tasks. Starting from a random noise, diffusion models gradually recover the sample with an iterativ…

Reconstructing High-fidelity Plasma Turbulence with Data-driven Tuning of Diffusion in Low Resolution Grids
Kunpeng Li, Youngwoo Cho, Xavier Garbet, Chenguang Wan, Robin Varennes, Kyungtak Lim, Virginie Grandgirard, Zhisong Qu, Ong Yew Soon
https://arxiv.org/abs/2509.11576

Reconstructing High-fidelity Plasma Turbulence with Data-driven Tuning of Diffusion in Low Resolution Grids
Developing physically consistent closure models is a longstanding challenge in simulating plasma turbulence, even in minimal systems such as the two-field Hasegawa-Wakatani (HW) model, which captures essential features of drift-wave turbulence with a reduced set of variables. In this work, we leverage theoretical insights from Direct Interaction Approximation (DIA) to construct a six-term closure structure that captures the dominant turbulent transport processes, including both diffusion and hy…

Out of Distribution, Out of Luck: How Well Can LLMs Trained on Vulnerability Datasets Detect Top 25 CWE Weaknesses?
Yikun Li, Ngoc Tan Bui, Ting Zhang, Martin Weyssow, Chengran Yang, Xin Zhou, Jinfeng Jiang, Junkai Chen, Huihui Huang, Huu Hung Nguyen, Chiok Yew Ho, Jie Tan, Ruiyin Li, Yide Yin, Han Wei Ang, Frank Liauw, Eng Lieh Ouh, Lwin Khin Shar, David Lo
ht…

Out of Distribution, Out of Luck: How Well Can LLMs Trained on Vulnerability Datasets Detect Top 25 CWE Weaknesses?
Automated vulnerability detection research has made substantial progress, yet its real-world impact remains limited. Current vulnerability datasets suffer from issues including label inaccuracy rates of 20-71%, extensive duplication, and poor coverage of critical CWE types. These issues create a significant "generalization gap" where models achieve misleading self-testing performance (measured on held-out data from same dataset for training) by exploiting spurious correlations rather than learn…

Quality Diversity Genetic Programming for Learning Scheduling Heuristics
Meng Xu, Frank Neumann, Aneta Neumann, Yew Soon Ong
https://arxiv.org/abs/2507.02235

Quality Diversity Genetic Programming for Learning Scheduling Heuristics
Real-world optimization often demands diverse, high-quality solutions. Quality-Diversity (QD) optimization is a multifaceted approach in evolutionary algorithms that aims to generate a set of solutions that are both high-performing and diverse. QD algorithms have been successfully applied across various domains, providing robust solutions by exploring diverse behavioral niches. However, their application has primarily focused on static problems, with limited exploration in the context of dynami…

A Plug-and-Play Multi-Criteria Guidance for Diverse In-Betweening Human Motion Generation
Hua Yu, Jiao Liu, Xu Gui, Melvin Wong, Yaqing Hou, Yew-Soon Ong
https://arxiv.org/abs/2508.01590

A Plug-and-Play Multi-Criteria Guidance for Diverse In-Betweening Human Motion Generation
In-betweening human motion generation aims to synthesize intermediate motions that transition between user-specified keyframes. In addition to maintaining smooth transitions, a crucial requirement of this task is to generate diverse motion sequences. It is still challenging to maintain diversity, particularly when it is necessary for the motions within a generated batch sampling to differ meaningfully from one another due to complex motion dynamics. In this paper, we propose a novel method, ter…

EMU and the DRAGNs I: A Catalogue of DRAGNs
Ray P. Norris, Miranda Yew, Evan Crawford, Nikhel Gupta, Lawrence Rudnick, H. Andernach, Miroslav D. Filipovi\'c, Yjan A. Gordon, Andrew M. Hopkins, Laurence Park, Michael J. I. Brown, Ana Jimenez-Gallardo, S. S. Shabala
https://arxiv.org/abs/2507.23337…

EMU and the DRAGNs I: A Catalogue of DRAGNs
We present a catalogue of 3557 Double Radio sources associated with Active Galactic Nuclei (DRAGNs) from the First Pilot Survey of the Evolutionary Map of the Universe (EMU), observed at 944 MHz with the Australian Square Kilometre Array Pathfinder (ASKAP) telescope, covering 270 deg^2. We have extracted and identified each source by eye, tagged it with a morphological type and measured its parameters. The resulting catalogue will be used in subsequent papers to explore the properties of these …

Enhanced Superconductivity and Vortex Dynamics in One-Dimensional TaS2 Nanowires
Mathew Pollard, Visakha Ho, Clarissa Wisner, Eric Bohannan, Yew San Hor
https://arxiv.org/abs/2507.15792

Enhanced Superconductivity and Vortex Dynamics in One-Dimensional TaS2 Nanowires
We report the synthesis of high-quality 2H-TaS2 nanowires via a controlled two-step conversion process from TaS3 precursors, achieving robust superconductivity with a transition temperature Tc ~ 3.6 K which is significantly higher than bulk 2H-TaS2 (Tc ~ 0.8 K). Structural and compositional analyses confirm phase purity and preserved 1D morphology, while magnetotransport measurements reveal an enhanced upper critical field μoHc2 (2 K) ~ 5 T, far exceeding the bulk value (μoHc2 (0) ~ 1.17 T), …

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- ($\boldsymbol{\theta}_l, \boldsymbol{\theta}_u$)-Parametric Multi-Task Optimization: Joint Search...
Tingyang Wei, Jiao Liu, Abhishek Gupta, Puay Siew Tan, Yew-Soon Ong

Replaced article(s) found for cs.NE. https://arxiv.org/list/cs.NE/new
[1/1]:
- ($\boldsymbol{\theta}_l, \boldsymbol{\theta}_u$)-Parametric Multi-Task Optimization: Joint Search...
Tingyang Wei, Jiao Liu, Abhishek Gupta, Puay Siew Tan, Yew-Soon Ong