Tootfinder

Da sind sie wieder. Hab schon gewartet, wann die #Raupen auftauchen. Den #Kohlweißling hatte ich bereits vor Wochen beobachten können. Eigentlich soll der ja an die #Kapuzinerkresse geh…

"I just want my life back!"
New from Chuck Tingle. This Summer don't stray too far from the standards track, lest you be…
Pounded in the Ass By the RFC Process
https://mailarchive.ietf.org/arch/msg/dane/JPY1_4_KFznrh_sAPUvQc2ig9Cs/

Near optimal quantum algorithm for estimating Shannon entropy
Myeongjin Shin, Kabgyun Jeong
https://arxiv.org/abs/2509.07452 https://arxiv.org/pdf/2509.074…

Near optimal quantum algorithm for estimating Shannon entropy
We present a near-optimal quantum algorithm, up to logarithmic factors, for estimating the Shannon entropy in the quantum probability oracle model. Our approach combines the singular value separation algorithm with quantum amplitude amplification, followed by the application of quantum singular value transformation. On the lower bound side, we construct probability distributions encoded via Hamming weights in the oracle, establishing a tight query lower bound up to logarithmic factors. Conseque…

Replaced article(s) found for physics.chem-ph. https://arxiv.org/list/physics.chem-ph/new
[1/1]:
- Core-Excited States of Linear and Bent Uranyl Complexes: Insights from High-Energy Resolution X-r...
Misael, Amidani, M\"arz, Bazarkina, Kvashnina, Vallet, Gomes
…

KVCompose: Efficient Structured KV Cache Compression with Composite Tokens
Dmitry Akulov, Mohamed Sana, Antonio De Domenico, Tareq Si Salem, Nicola Piovesan, Fadhel Ayed
https://arxiv.org/abs/2509.05165

KVCompose: Efficient Structured KV Cache Compression with Composite Tokens
Large language models (LLMs) rely on key-value (KV) caches for efficient autoregressive decoding; however, cache size grows linearly with context length and model depth, becoming a major bottleneck in long-context inference. Prior KV cache compression methods either enforce rigid heuristics, disrupt tensor layouts with per-attention-head variability, or require specialized compute kernels. We propose a simple, yet effective, KV cache compression framework based on attention-guided, layer-adap…

Cross-Dataset Semantic Segmentation Performance Analysis: Unifying NIST Point Cloud City Datasets for 3D Deep Learning
Alexander Nikitas Dimopoulos, Joseph Grasso
https://arxiv.org/abs/2508.00822

Cross-Dataset Semantic Segmentation Performance Analysis: Unifying NIST Point Cloud City Datasets for 3D Deep Learning
This study analyzes semantic segmentation performance across heterogeneously labeled point-cloud datasets relevant to public safety applications, including pre-incident planning systems derived from lidar scans. Using NIST's Point Cloud City dataset (Enfield and Memphis collections), we investigate challenges in unifying differently labeled 3D data. Our methodology employs a graded schema with the KPConv architecture, evaluating performance through IoU metrics on safety-relevant features. Resul…

Replaced article(s) found for physics.geo-ph. https://arxiv.org/list/physics.geo-ph/new
[1/1]:
- Lie Group Theory of Multipole Moments and Shape of Stationary Rotating Fluid Bodies
Sergei M. Kopeikin (University of Missouri-Columbia, USA)

Tenyidie Syllabification corpus creation and deep learning applications
Teisovi Angami, Kevisino Khate
https://arxiv.org/abs/2510.00629 https://arxiv.org/p…

Tenyidie Syllabification corpus creation and deep learning applications
The Tenyidie language is a low-resource language of the Tibeto-Burman family spoken by the Tenyimia Community of Nagaland in the north-eastern part of India and is considered a major language in Nagaland. It is tonal, Subject-Object-Verb, and highly agglutinative in nature. Being a low-resource language, very limited research on Natural Language Processing (NLP) has been conducted. To the best of our knowledge, no work on syllabification has been reported for this language. Among the many NLP t…

Laser-Synthesized Amorphous PdSe$_{\mathrm{2-x}}$ Nanoparticles: A Defect-Rich Platform for High-Efficiency SERS, Photocatalysis, and Photothermal Conversion
Andrei Ushkov, Nadezhda Belozerova, Dmitriy Dyubo, Ilya Martynov, Alexander Syuy, Daniil Tselikov, Georgy Ermolaev, Sergey V. Bazhenov, Roman I. Romanov, Ivan Kruglov, Anton A. Popov, Alexander Chernov, Alexey D. Bolshakov, Sergey Novikov, Andrey A. Vyshnevyy, Aleksey Arsenin, Andrei V. Kabashin, Gleb I. Tselikov, Valentyn Volkov

Laser-Synthesized Amorphous PdSe$_{\mathrm{2-x}}$ Nanoparticles: A Defect-Rich Platform for High-Efficiency SERS, Photocatalysis, and Photothermal Conversion
The control of material properties at the atomic scale remains a central challenge in materials science. Transition metal dichalcogenides (TMDCs) offer remarkable electronic and optical properties, but their functionality is largely dictated by their stable crystalline phases. Here we demonstrate a single-step, ligand-free strategy using femtosecond laser ablation in liquid to transform crystalline, stoichiometric palladium diselenide (PdSe$_{\mathrm{2}}$) into highly stable, amorphous, and non…

Optimization of Base-n Radix Sort for Skewed Datasets
Atharv Pandey, Lakshmanan Kuppusamy
https://arxiv.org/abs/2509.19021 https://arxiv.org/pdf/2509.19021…