Tootfinder

The complete weight distribution of a family of irreducible cyclic codes of dimension two
Gerardo Vega, F\'elix Hern\'andez
https://arxiv.org/abs/2506.11349

The complete weight distribution of a family of irreducible cyclic codes of dimension two
An important family of codes for data storage systems, cryptography, consumer electronics, and network coding for error control in digital communications are the so-called cyclic codes. This kind of linear codes are also important due to their efficient encoding and decoding algorithms. Because of this, cyclic codes have been studied for many years, however their complete weight distributions are known only for a few cases. The complete weight distribution has a wide range of applications in ma…

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches
Lukasz Mazur, Nenad Petrovic, James Pontes Miranda, Ansgar Radermacher, Robert Rasche, Alois Knoll
https://arxiv.org/abs/2506.13171

Querying Large Automotive Software Models: Agentic vs. Direct LLM Approaches
Large language models (LLMs) offer new opportunities for interacting with complex software artifacts, such as software models, through natural language. They present especially promising benefits for large software models that are difficult to grasp in their entirety, making traditional interaction and analysis approaches challenging. This paper investigates two approaches for leveraging LLMs to answer questions over software models: direct prompting, where the whole software model is provided …

A visco-plastic constitutive model for accurate densification and shape predictions in powder metallurgy hot isostatic pressing
Subrato Sarkar, Jason R Mayeur, KPK Ajjarapu, Fred A List III, Soumya Nag, Ryan R Dehoff
https://arxiv.org/abs/2506.11946

A visco-plastic constitutive model for accurate densification and shape predictions in powder metallurgy hot isostatic pressing
Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that produces near net shape parts with high material utilization and uniform microstructures. Despite being used frequently to produce small-scale components, the application of PM-HIP to large-scale components is limited due to inadequate understanding of its complex mechanisms that cause unpredictable post-HIP shape distortions. A computational model can provide necessary information about the intermediate…

Probabilistic patient risk profiling with pair-copula constructions
\"Ozge \c{S}ahin
https://arxiv.org/abs/2506.13731 https://ar…

Probabilistic patient risk profiling with pair-copula constructions
We present, to our knowledge, the first clinical application of vine copula-based classifiers for probabilistic perioperative risk prediction. We obtain full joint probability models for mixed continuous-ordinal variables by fitting a separate vine copula to each outcome class, capturing nonlinear and tail-asymmetric dependence. In a cohort of 767 elective bowel surgeries (81 serious vs. 686 non-serious complications), posterior probabilities from the fitted classification models are used to al…

Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation
Narges Nemati, Mostafa Haghir Chehreghani
https://arxiv.org/abs/2506.10658

Contrastive Matrix Completion with Denoising and Augmented Graph Views for Robust Recommendation
Matrix completion is a widely adopted framework in recommender systems, as predicting the missing entries in the user-item rating matrix enables a comprehensive understanding of user preferences. However, current graph neural network (GNN)-based approaches are highly sensitive to noisy or irrelevant edges--due to their inherent message-passing mechanisms--and are prone to overfitting, which limits their generalizability. To overcome these challenges, we propose a novel method called Matrix Comp…

Competition Complexity in Multi-Item Auctions: Beyond VCG and Regularity
Hedyeh Beyhaghi, Linda Cai, Yiding Feng, Yingkai Li, S. Matthew Weinberg
https://arxiv.org/abs/2506.09291 …

Competition Complexity in Multi-Item Auctions: Beyond VCG and Regularity
We quantify the value of the monopoly's bargaining power in terms of competition complexity--that is, the number of additional bidders the monopoly must attract in simple auctions to match the expected revenue of the optimal mechanisms (c.f., Bulow and Klemperer, 1996, Eden et al., 2017)--within the setting of multi-item auctions. We show that for simple auctions that sell items separately, the competition complexity is $Θ(\frac{n}α)$ in an environment with $n$ original bidders under the slig…

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment
Amritha Premkumar, Prajit T Rajendran, Vignesh V Menon
https://arxiv.org/abs/2506.09795

Learning Quality from Complexity and Structure: A Feature-Fused XGBoost Model for Video Quality Assessment
This paper presents a novel approach for reduced-reference video quality assessment (VQA), developed as part of the recent VQA Grand Challenge. Our method leverages low-level complexity and structural information from reference and test videos to predict perceptual quality scores. Specifically, we extract spatio-temporal features using Video Complexity Analyzer (VCA) and compute SSIM values from the test video to capture both texture and structural characteristics. These features are aggregated…

Generate Realistic Test Scenes for V2X Communication Systems
An Guo, Xinyu Gao, Chunrong Fang, Haoxiang Tian, Weisong Sun, Yanzhou Mu, Shuncheng Tang, Lei Ma, Zhenyu Chen
https://arxiv.org/abs/2506.07419

Generate Realistic Test Scenes for V2X Communication Systems
Accurately perceiving complex driving environments is essential for ensuring the safe operation of autonomous vehicles. With the tremendous progress in deep learning and communication technologies, cooperative perception with Vehicle-to-Everything (V2X) technologies has emerged as a solution to overcome the limitations of single-agent perception systems in perceiving distant objects and occlusions. Despite the considerable advancements, V2X cooperative perception systems require thorough testin…

A voice for minorities: diversity in approval-based committee elections under incomplete or inaccurate information
Feline Lindeboom, Martijn Brehm, Davide Grossi, Pradeep Murukannaiah
https://arxiv.org/abs/2506.10843

A voice for minorities: diversity in approval-based committee elections under incomplete or inaccurate information
We study diversity in approval-based committee elections with incomplete or inaccurate information. As standard in the literature on approval-based multi-winner voting, we define diversity according to the maximum coverage problem, which is known to be NP-complete, with a best attainable polynomial time approximation ratio of $1-1/\e$. In the incomplete information model, voters can vote on only a small portion of the candidates. We suggest a greedy algorithm and a local search algorithm that q…

Scalable Software Testing in Fast Virtual Platforms: Leveraging SystemC, QEMU and Containerization
Lukas J\"unger, Jan Henrik Weinstock, Tim Kraus
https://arxiv.org/abs/2506.10624

Scalable Software Testing in Fast Virtual Platforms: Leveraging SystemC, QEMU and Containerization
The ever-increasing complexity of HW/SW systems presents a persistent challenge, particularly in safety-critical domains like automotive, where extensive testing is imperative. However, the availability of hardware often lags behind, hindering early-stage software development. To address this, Virtual Platforms (VPs) based on the SystemC TLM-2.0 standard have emerged as a pivotal solution, enabling pre-silicon execution and testing of unmodified target software. In this study, we propose an app…