Tootfinder

Mind the Gap: A Readability-Aware Metric for Test Code Complexity
Wendk\^uuni C. Ou\'edraogo, Yinghua Li, Xueqi Dang, Xin Zhou, Anil Koyuncu, Jacques Klein, David Lo, Tegawend\'e F. Bissyand\'e
https://arxiv.org/abs/2506.06764

Mind the Gap: A Readability-Aware Metric for Test Code Complexity
Automatically generated unit tests-from search-based tools like EvoSuite or LLMs-vary significantly in structure and readability. Yet most evaluations rely on metrics like Cyclomatic Complexity and Cognitive Complexity, designed for functional code rather than test code. Recent studies have shown that SonarSource's Cognitive Complexity metric assigns near-zero scores to LLM-generated tests, yet its behavior on EvoSuite-generated tests and its applicability to test-specific code structures remai…

The Epoch of Giant Planet Migration Planet Search Program. III. The Occurrence Rate of Young Giant Planets Inside the Water Ice Line
Quang H. Tran, Brendan P. Bowler, William D. Cochran, Chad F. Bender, Samuel Halverson, Suvrath Mahadevan, Joe P. Ninan, Paul Robertson, Arpita Roy, Gu{\dh}mundur Stef\'ansson, Ryan C. Terrien
https://

The Epoch of Giant Planet Migration Planet Search Program. III. The Occurrence Rate of Young Giant Planets Inside the Water Ice Line
We present statistical results from the Epoch of Giant Planet Migration RV planet search program. This survey was designed to measure the occurrence rate of giant planets interior to the water ice line of young Sun-like stars, compare this to the prevalence of giant planets at older ages, and provide constraints on the timescale and dominant inward migration mechanism of giant planets. Our final sample amounts to 85 single young (20-200 Myr) G and K dwarfs which we target across a 4-year time b…

Series D, Episode 07 - Assassin
AVON: [V.O.] Scorpio, come in Scorpio.
TARRANT: Avon, what's happening?
AVON: [V.O.] Never mind what's happening. Just get me up as quickly as you can. [Cut to Domo]
NEBROX: You promised! You promised! [Back to Scorpio]
https://blake.torpidity.net/m/407/181

Blakes7Bot | Search
Companion site to the Blakes7Bot Twitter, Mastodon, and Bluesky accounts. Automated lines of Blakes 7 dialog. Includes a script search facility.

This https://arxiv.org/abs/2502.17701 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

From Perceptions to Decisions: Wildfire Evacuation Decision Prediction with Behavioral Theory-informed LLMs
Evacuation decision prediction is critical for efficient and effective wildfire response by helping emergency management anticipate traffic congestion and bottlenecks, allocate resources, and minimize negative impacts. Traditional statistical methods for evacuation decision prediction fail to capture the complex and diverse behavioral logic of different individuals. In this work, for the first time, we introduce FLARE, short for facilitating LLM for advanced reasoning on wildfire evacuation dec…

A global urban road network self-adaptive simplification workflow from traffic to spatial representation
https://www.nature.com/articles/s41597-025-05164-9
Data for 35 cities. Looks similar to the neatnet method

A global urban road network self-adaptive simplification workflow from traffic to spatial representation - Scientific Data
Urban road network is crucial for understanding and revealing the spatial logic of urban organization and evolution. However, existing urban road network datasets like OpenStreetMap are designed for traffic studies, treating each lane as a distinct spatial unit of mobility, which may not align with urban studies considering each road as an integration space for social and cultural dynamics. This study established a novel workflow to self-adaptively transform the global urban road network from t…

A Statistics-Driven Differentiable Approach for Sound Texture Synthesis and Analysis
Esteban Guti\'errez, Frederic Font, Xavier Serra, Lonce Wyse
https://arxiv.org/abs/2506.04073

A Statistics-Driven Differentiable Approach for Sound Texture Synthesis and Analysis
In this work, we introduce TexStat, a novel loss function specifically designed for the analysis and synthesis of texture sounds characterized by stochastic structure and perceptual stationarity. Drawing inspiration from the statistical and perceptual framework of McDermott and Simoncelli, TexStat identifies similarities between signals belonging to the same texture category without relying on temporal structure. We also propose using TexStat as a validation metric alongside Frechet Audio Dista…

Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
Christian Tinauer, Maximilian Sackl, Stefan Ropele, Christian Langkammer
https://arxiv.org/abs/2506.03890

Identifying Alzheimer's Disease Prediction Strategies of Convolutional Neural Network Classifiers using R2* Maps and Spectral Clustering
Deep learning models have shown strong performance in classifying Alzheimer's disease (AD) from R2* maps, but their decision-making remains opaque, raising concerns about interpretability. Previous studies suggest biases in model decisions, necessitating further analysis. This study uses Layer-wise Relevance Propagation (LRP) and spectral clustering to explore classifier decision strategies across preprocessing and training configurations using R2* maps. We trained a 3D convolutional neural net…

Looking for Attention: Randomized Attention Test Design for Validator Monitoring in Optimistic Rollups
Suhyeon Lee
https://arxiv.org/abs/2505.24393 https:/…

Looking for Attention: Randomized Attention Test Design for Validator Monitoring in Optimistic Rollups
Optimistic Rollups (ORUs) significantly enhance blockchain scalability but inherently suffer from the verifier's dilemma, particularly concerning validator attentiveness. Current systems lack mechanisms to proactively ensure validators are diligently monitoring L2 state transitions, creating a vulnerability where fraudulent states could be finalized. This paper introduces the Randomized Attention Test (RAT), a novel L1-based protocol designed to probabilistically challenge validators in ORUs, t…

This https://arxiv.org/abs/2506.01222 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Learning collective variables that preserve transition rates
Collective variables (CVs) play a crucial role in capturing rare events in high-dimensional systems, motivating the continual search for principled approaches to their design. In this work, we revisit the framework of quantitative coarse graining and identify the orthogonality condition from Legoll and Lelievre (2010) as a key criterion for constructing CVs that accurately preserve the statistical properties of the original process. We establish that satisfaction of the orthogonality condition …

Large Neighborhood and Hybrid Genetic Search for Inventory Routing Problems
Jingyi Zhao, Claudia Archetti, Tuan Anh Pham, Thibaut Vidal
https://arxiv.org/abs/2506.03172

Large Neighborhood and Hybrid Genetic Search for Inventory Routing Problems
The inventory routing problem (IRP) focuses on jointly optimizing inventory and distribution operations from a supplier to retailers over multiple days. Compared to other problems from the vehicle routing family, the interrelations between inventory and routing decisions render IRP optimization more challenging and call for advanced solution techniques. A few studies have focused on developing large neighborhood search approaches for this class of problems, but this remains a research area with…