Tootfinder

Zelensky discusses Russian airspace provocations with Macron, Rutte at UN: https://benborges.xyz/2025/09/25/zelensky-discusses-russian-airspace-provocations.html

from my link log —
AeroSpace: an i3-like tiling window manager for macOS.
https://nikitabobko.github.io/AeroSpace/guide
saved 2025-09-15 https://…

ExpFace: Exponential Angular Margin Loss for Deep Face Recognition
Jinhui Zheng, Xueyuan Gong
https://arxiv.org/abs/2509.19753 https://arxiv.org/pdf/2509.1…

ExpFace: Exponential Angular Margin Loss for Deep Face Recognition
Face recognition is an open-set problem requiring high discriminative power to ensure that intra-class distances remain smaller than inter-class distances. Margin-based softmax losses, such as SphereFace, CosFace, and ArcFace, have been widely adopted to enhance intra-class compactness and inter-class separability, yet they overlook the impact of noisy samples. By examining the distribution of samples in the angular space, we observe that clean samples predominantly cluster in the center region…

On graphs with equal and different Kromatic symmetric functions
Laura Pierson, Soham Samanta
https://arxiv.org/abs/2508.17682 https://arxiv.org/pdf/2508.17…

On graphs with equal and different Kromatic symmetric functions
The Kromatic symmetric function (KSF) $\overline{X}_G$ of a graph $G$ is a $K$-analogue introduced by Crew, Pechenik, and Spirkl in arXiv:2301.02177 of Stanley's chromatic symmetric function (CSF) $X_G$. The KSF is known to distinguish some pairs of graphs with the same CSF. The first author showed in arXiv:2403.15929 and arXiv:2502.21285 that the number of copies in $G$ of certain induced subgraphs can be determined given $\overline{X}_G$, and conjectured that $\overline{X}_G$ distinguishes al…

ARSP: Automated Repair of Verilog Designs via Semantic Partitioning
Bingkun Yao, Ning Wang, Xiangfeng Liu, Yuxin Du, Yuchen Hu, Hong Gao, Zhe Jiang, Nan Guan
https://arxiv.org/abs/2508.16517

ARSP: Automated Repair of Verilog Designs via Semantic Partitioning
Debugging functional Verilog bugs consumes a significant portion of front-end design time. While Large Language Models (LLMs) have demonstrated great potential in mitigating this effort, existing LLM-based automated debugging methods underperform on industrial-scale modules. A major reason for this is bug signal dilution in long contexts, where a few bug-relevant tokens are overwhelmed by hundreds of unrelated lines, diffusing the model's attention. To address this issue, we introduce ARSP, a t…

Not Just for Archiving: Provable Benefits of Reusing the Archive in Evolutionary Multi-objective Optimization
Shengjie Ren, Zimin Liang, Miqing Li, Chao Qian
https://arxiv.org/abs/2508.16993

Not Just for Archiving: Provable Benefits of Reusing the Archive in Evolutionary Multi-objective Optimization
Evolutionary Algorithms (EAs) have become the most popular tool for solving widely-existed multi-objective optimization problems. In Multi-Objective EAs (MOEAs), there is increasing interest in using an archive to store non-dominated solutions generated during the search. This approach can 1) mitigate the effects of population oscillation, a common issue in many MOEAs, and 2) allow for the use of smaller, more practical population sizes. In this paper, we analytically show that the archive can …

arxiv_collab: Scientific collaborations in physics (1995-2005)
Collaboration graphs for scientists, extracted from the Los Alamos e-Print arXiv (physics), for 1995-1999 for three categories, and additionally for 1995-2003 and 1995-2005 for one category. For copyright reasons, the MEDLINE (biomedical research) and NCSTRL (computer science) collaboration graphs from this paper are not publicly available.
This network has 8361 nodes and 15751 edges.
Tags: Social, Collaboration…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/6]:
- Efficiently learning depth-3 circuits via quantum agnostic boosting
Srinivasan Arunachalam, Arkopal Dutt, Alexandru Gheorghiu, Michael de Oliveira

Hungarian drones breach Ukraine's airspace, Zelensky says: https://benborges.xyz/2025/09/26/hungarian-drones-breach-ukraines-airspace.html

On Zero-Shot Reinforcement Learning
Scott Jeen
https://arxiv.org/abs/2508.16496 https://arxiv.org/pdf/2508.16496 …

On Zero-Shot Reinforcement Learning
Modern reinforcement learning (RL) systems capture deep truths about general, human problem-solving. In domains where new data can be simulated cheaply, these systems uncover sequential decision-making policies that far exceed the ability of any human. Society faces many problems whose solutions require this skill, but they are often in domains where new data cannot be cheaply simulated. In such scenarios, we can learn simulators from existing data, but these will only ever be approximately cor…