Tootfinder

Multiset Metric Dimension of Binomial Random Graphs
Austin Eide, Pawel Pralat
https://arxiv.org/abs/2507.11686 https://arxiv.org/pdf/…

Multiset Metric Dimension of Binomial Random Graphs
For a graph $G = (V,E)$ and a subset $R \subseteq V$, we say that $R$ is \textit{multiset resolving} for $G$ if for every pair of vertices $v,w$, the \textit{multisets} $\{d(v,r): r \in R\}$ and $\{d(w,r):r \in R\}$ are distinct, where $d(x,y)$ is the graph distance between vertices $x$ and $y$. The \textit{multiset metric dimension} of $G$ is the size of a smallest set $R \subseteq V$ that is multiset resolving (or $\infty$ if no such set exists). This graph parameter was introduced by Simanju…

'There's Nothing I Can Say!' Trump Melts Down Over Negative Reports On Putin Meeting | Crooks and Liars
https://crooksandliars.com/2025/08/theres-nothing-i-can-say-trump-melts-down

Data Augmentation for Maltese NLP using Transliterated and Machine Translated Arabic Data
Kurt Micallef, Nizar Habash, Claudia Borg
https://arxiv.org/abs/2509.12853 https://

Data Augmentation for Maltese NLP using Transliterated and Machine Translated Arabic Data
Maltese is a unique Semitic language that has evolved under extensive influence from Romance and Germanic languages, particularly Italian and English. Despite its Semitic roots, its orthography is based on the Latin script, creating a gap between it and its closest linguistic relatives in Arabic. In this paper, we explore whether Arabic-language resources can support Maltese natural language processing (NLP) through cross-lingual augmentation techniques. We investigate multiple strategies for a…

🇺🇦 #NowPlaying on KEXP's #Early
New Age Healers:
🎵 Melts Away
#NewAgeHealers
https://newagehealers.bandcamp.com/track/melts-away
https://open.spotify.com/track/4QdKnewMA7ONzbji2oKaJH

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Dahang Wan, Rongsheng Lu, Yang Fang, Xianli Lang, Shuangbao Shu, Jingjing Chen, Siyuan Shen, Ting Xu, Zecong Ye
https://arxiv.org/abs/2506.14696

YOLOv11-RGBT: Towards a Comprehensive Single-Stage Multispectral Object Detection Framework
Multispectral object detection, which integrates information from multiple bands, can enhance detection accuracy and environmental adaptability, holding great application potential across various fields. Although existing methods have made progress in cross-modal interaction, low-light conditions, and model lightweight, there are still challenges like the lack of a unified single-stage framework, difficulty in balancing performance and fusion strategy, and unreasonable modality weight allocatio…

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
Carolina Higuera, Akash Sharma, Taosha Fan, Chaithanya Krishna Bodduluri, Byron Boots, Michael Kaess, Mike Lambeta, Tingfan Wu, Zixi Liu, Francois Robert Hogan, Mustafa Mukadam
https://arxiv.org/abs/2506.14754…

Tactile Beyond Pixels: Multisensory Touch Representations for Robot Manipulation
We present Sparsh-X, the first multisensory touch representations across four tactile modalities: image, audio, motion, and pressure. Trained on ~1M contact-rich interactions collected with the Digit 360 sensor, Sparsh-X captures complementary touch signals at diverse temporal and spatial scales. By leveraging self-supervised learning, Sparsh-X fuses these modalities into a unified representation that captures physical properties useful for robot manipulation tasks. We study how to effectively …

A Chinese restaurant process for multiset permutations
Dudley Stark
https://arxiv.org/abs/2509.13979 https://arxiv.org/pdf/2509.13979

A Chinese restaurant process for multiset permutations
Multisets are like sets, except that they can contain multiple copies of their elements. If there are $n_i$ copies of $i$, $1\leq i\leq t$, in multiset $M_t$, then there are $\binom{n_1+\cdots+n_t}{n_1,\ldots, n_t}$ possible permutations of $M_t$. Knuth showed how to factor any multiset permutation into cycles. For fixed $n_i$, $i\geq 1$, we show how to adapt the Chinese restaurant process, which generates random permutations on $n$ elements with weighting $θ^{\# \, {\rm cycles}}$, $θ>0$, seq…

Ground and excited-state properties of the extended Hubbard dimer from the multichannel Dyson equation
Stefano Paggi, J. Arjan Berger, Pina Romaniello
https://arxiv.org/abs/2507.12437

Ground and excited-state properties of the extended Hubbard dimer from the multichannel Dyson equation
We have recently presented the multichannel Dyson equation as an alternative to the standard single-channel Dyson equation. While the latter involves a single many-body Green's function, the former uses a multichannel Green's function in which two or more many-body Green's functions are coupled. Quasiparticles and satellites are thus naturally treated on equal footing in the multichannel Dyson equation. To assess the accuracy of our approach we apply it here to the ground- and excited-state pro…

Reconfigurable Intelligent Surface-Assisted Multiuser Tracking and Signal Detection in ISAC
Weifeng Zhu, Junyuan Gao, Shuowen Zhang, Liang Liu
https://arxiv.org/abs/2509.13940 h…

Reconfigurable Intelligent Surface-Assisted Multiuser Tracking and Signal Detection in ISAC
This paper investigates the multiuser tracking and signal detection problem in integrated sensing and communication (ISAC) systems with the assistance of reconfigurable intelligent surfaces (RISs). Due to the diverse and high user mobility, the tracking and signal detection performance can be significantly deteriorated without choreographed user state (position and velocity) updating principle. To tackle this challenge, we manage to establish a comprehensive probabilistic signal model to charac…

AnyAccomp: Generalizable Accompaniment Generation via Quantized Melodic Bottleneck
Junan Zhang, Yunjia Zhang, Xueyao Zhang, Zhizheng Wu
https://arxiv.org/abs/2509.14052 https://…

AnyAccomp: Generalizable Accompaniment Generation via Quantized Melodic Bottleneck
Singing Accompaniment Generation (SAG) is the process of generating instrumental music for a given clean vocal input. However, existing SAG techniques use source-separated vocals as input and overfit to separation artifacts. This creates a critical train-test mismatch, leading to failure on clean, real-world vocal inputs. We introduce AnyAccomp, a framework that resolves this by decoupling accompaniment generation from source-dependent artifacts. AnyAccomp first employs a quantized melodic bott…