Tootfinder

The GAPS programme at TNG XYZ. A sub-Neptune suitable for atmospheric characterization in a multiplanet and mutually inclined system orbiting the bright K dwarf TOI-5789 (HIP 99452)
A. S. Bonomo, L. Naponiello, A. Sozzetti, S. Benatti, I. Carleo, K. Biazzo, P. E. Cubillos, M. Damasso, C. Di Maio, C. Dorn, N. Hara, D. Polychroni, M. -L. Steinmeyer, K. A. Collins, S. Desidera, X. Dumusque, A. F. Lanza, B. S. Safonov, C. Stockdale, D. Turrini, C. Ziegler, L. Affer, M. D'Arpa, V. Farde…

The GAPS programme at TNG XYZ. A sub-Neptune suitable for atmospheric characterization in a multiplanet and mutually inclined system orbiting the bright K dwarf TOI-5789 (HIP 99452)
Sub-Neptunes with planetary radii of $R_{p} \simeq 2-4 R_{\oplus}$ are the most common planets around solar-type stars in short-period ($P<100$ d) orbits. It is still unclear, however, what their most likely composition is, that is whether they are predominantly gas dwarfs or water worlds. The sub-Neptunes orbiting bright host stars are very valuable because they are suitable for atmospheric characterization, which can break the well-known degeneracy in planet composition from the planet bulk d…

Efficient Trie-based Biasing using K-step Prediction for Rare Word Recognition
Chin Yuen Kwok, Jia Qi yip
https://arxiv.org/abs/2509.09196 https://arxiv.or…

Efficient Trie-based Biasing using K-step Prediction for Rare Word Recognition
Contextual biasing improves rare word recognition of ASR models by prioritizing the output of rare words during decoding. A common approach is Trie-based biasing, which gives "bonus scores" to partial hypothesis (e.g. "Bon") that may lead to the generation of the rare word (e.g. "Bonham"). If the full word ("Bonham") isn't ultimately recognized, the system revokes those earlier bonuses. This revocation is limited to beam search and is computationally expensive, particularly for models with larg…

ADHDeepNet From Raw EEG to Diagnosis: Improving ADHD Diagnosis through Temporal-Spatial Processing, Adaptive Attention Mechanisms, and Explainability in Raw EEG Signals
Ali Amini, Mohammad Alijanpour, Behnam Latifi, Ali Motie Nasrabadi
https://arxiv.org/abs/2509.08779

ADHDeepNet From Raw EEG to Diagnosis: Improving ADHD Diagnosis through Temporal-Spatial Processing, Adaptive Attention Mechanisms, and Explainability in Raw EEG Signals
Attention Deficit Hyperactivity Disorder (ADHD) is a common brain disorder in children that can persist into adulthood, affecting social, academic, and career life. Early diagnosis is crucial for managing these impacts on patients and the healthcare system but is often labor-intensive and time-consuming. This paper presents a novel method to improve ADHD diagnosis precision and timeliness by leveraging Deep Learning (DL) approaches and electroencephalogram (EEG) signals. We introduce ADHDeepNet…

Investigating the Cognitive Response of Brake Lights in Initiating Braking Action Using EEG
Ramaswamy Palaniappan, Surej Mouli, Howard Bowman, Ian McLoughlin
https://arxiv.org/abs/2508.03274

Investigating the Cognitive Response of Brake Lights in Initiating Braking Action Using EEG
Half of all road accidents result from either lack of driver attention or from maintaining insufficient separation between vehicles. Collision from the rear, in particular, has been identified as the most common class of accident in the UK, and its influencing factors have been widely studied for many years. Rear-mounted stop lamps, illuminated when braking, are the primary mechanism to alert following drivers to the need to reduce speed or brake. This paper develops a novel brain response appr…

Growing Mathlib: maintenance of a large scale mathematical library
Anne Baanen, Matthew Robert Ballard, Johan Commelin, Bryan Gin-ge Chen, Michael Rothgang, Damiano Testa
https://arxiv.org/abs/2508.21593

Growing Mathlib: maintenance of a large scale mathematical library
The Lean mathematical library Mathlib is one of the fastest-growing libraries of formalised mathematics. We describe various strategies to manage this growth, while allowing for change and avoiding maintainer overload. This includes dealing with breaking changes via a deprecation system, using code quality analysis tools (linters) to provide direct user feedback about common pitfalls, speeding up compilation times through conscious library (re-)design, dealing with technical debt as well as wri…

A Dynamic Allocation Scheme for Adaptive Shared-Memory Mapping on Kilo-core RV Clusters for Attention-Based Model Deployment
Bowen Wang, Marco Bertuletti, Yichao Zhang, Victor J. B. Jung, Luca Benini
https://arxiv.org/abs/2508.01180

A Dynamic Allocation Scheme for Adaptive Shared-Memory Mapping on Kilo-core RV Clusters for Attention-Based Model Deployment
Attention-based models demand flexible hardware to manage diverse kernels with varying arithmetic intensities and memory access patterns. Large clusters with shared L1 memory, a common architectural pattern, struggle to fully utilize their processing elements (PEs) when scaled up due to reduced throughput in the hierarchical PE-to-L1 intra-cluster interconnect. This paper presents Dynamic Allocation Scheme (DAS), a runtime programmable address remapping hardware unit coupled with a unified memo…

Instability of the Sherman-Morrison formula and stabilization by iterative refinement
Behnam Hashemi, Yuji Nakatsukasa
https://arxiv.org/abs/2510.01696 https://

Instability of the Sherman-Morrison formula and stabilization by iterative refinement
Owing to its simplicity and efficiency, the Sherman-Morrison (SM) formula has seen widespread use across various scientific and engineering applications for solving rank-one perturbed linear systems of the form $(A+uv^T)x = b$. Although the formula dates back at least to 1944, its numerical stability properties have remained an open question and continue to be a topic of current research. We analyze the backward stability of the SM, demonstrate its instability in a scenario increasingly common …

Covariate-adjusted win statistics in randomized clinical trials with ordinal outcomes
Zhiqiang Cao, Scott Zuo, Mary Ryan Baumann, Kendra Plourde, Patrick Heagerty, Guangyu Tong, Fan Li
https://arxiv.org/abs/2508.20349

Covariate-adjusted win statistics in randomized clinical trials with ordinal outcomes
Ordinal outcomes are common in clinical settings where they often represent increasing levels of disease progression or different levels of functional impairment. Such outcomes can characterize differences in meaningful patient health states that are directly relevant to clinical researchers and frequently represent composite outcomes that include absorbing states such as death. To compare different intervention strategies in clinical trials, the direct use of ordinal logistic regression models…

Assessing Pedestrian Behavior Around Autonomous Cleaning Robots in Public Spaces: Findings from a Field Observation
Maren Raab, Linda Miller, Zhe Zeng, Pascal Jansen, Martin Baumann, Johannes Kraus
https://arxiv.org/abs/2508.13699

Assessing Pedestrian Behavior Around Autonomous Cleaning Robots in Public Spaces: Findings from a Field Observation
As autonomous robots become more common in public spaces, spontaneous encounters with laypersons are more frequent. For this, robots need to be equipped with communication strategies that enhance momentary transparency and reduce the probability of critical situations. Adapting these robotic strategies requires consideration of robot movements, environmental conditions, and user characteristics and states. While numerous studies have investigated the impact of distraction on pedestrians' moveme…

Extended Abstract: Towards a Performance Comparison of Syntax and Type-Directed NbE
Chester J. F. Gould, William J. Bowman
https://arxiv.org/abs/2509.13489 https://

Extended Abstract: Towards a Performance Comparison of Syntax and Type-Directed NbE
A key part of any dependent type-checker is the method for checking whether two types are equal. A common claim is that syntax-directed equality is more performant, although type-directed equality is more expressive. However, this claim is difficult to make precise, since implementations choose only one or the other approach, making a direct comparison impossible. We present some work-in-progress developing a realistic platform for direct, apples-to-apples, comparison of the two approaches, qua…