Tootfinder

Adding All Flavors: A Hybrid Random Number Generator for dApps and Web3
Ranjith Chodavarapu, Rabimba Karanjai, Xinxin Fan, Weidong Shi, Lei Xu
https://arxiv.org/abs/2510.12062 h…

Adding All Flavors: A Hybrid Random Number Generator for dApps and Web3
Random numbers play a vital role in many decentralized applications (dApps), such as gaming and decentralized finance (DeFi) applications. Existing random number provision mechanisms can be roughly divided into two categories, on-chain, and off-chain. On-chain approaches usually rely on the blockchain as the major input and all computations are done by blockchain nodes. The major risk for this type of method is that the input itself is susceptible to the adversary's influence. Off-chain…

Regular sequences for triangulated categories
Antonia Kekkou, Janina C. Letz, Marc Stephan
https://arxiv.org/abs/2509.09941 https://arxiv.org/pdf/2509.0994…

Regular sequences for triangulated categories
This paper systematically develops a notion of regular sequences in the context of $R$-linear triangulated categories for a graded-commutative ring $R$. The notion has equivalent characterizations involving Koszul objects and local cohomology. The main examples are in the context of the Hochschild cohomology ring or the group cohomology ring acting on derived or stable categories. As applications, lengths of regular sequences provide lower bounds for level and Rouquier dimension.

Influence and Connectivity in Networks: A Generating Function Approach
Yang Sun, Wei Zhao, Junjie Zhou
https://arxiv.org/abs/2508.09492 https://arxiv.org/p…

Influence and Connectivity in Networks: A Generating Function Approach
Many widely used network centralities are based on counting walks that meet specific criteria. This paper introduces a systematic framework for walk enumeration using generating functions. We introduce a first-passage decomposition that uniquely divides any walk passing through specified nodes or links into two components: a first-reaching walk and a subsequent walk. This decomposition yields a system of interconnected equations that relate three disjoint categories of walks: unrestricted walks…

Leveraging LLM-Based Agents for Intelligent Supply Chain Planning
Yongzhi Qi, Jiaheng Yin, Jianshen Zhang, Dongyang Geng, Zhengyu Chen, Hao Hu, Wei Qi, Zuo-Jun Max Shen
https://arxiv.org/abs/2509.03811

Leveraging LLM-Based Agents for Intelligent Supply Chain Planning
In supply chain management, planning is a critical concept. The movement of physical products across different categories, from suppliers to warehouse management, to sales, and logistics transporting them to customers, entails the involvement of many entities. It covers various aspects such as demand forecasting, inventory management, sales operations, and replenishment. How to collect relevant data from an e-commerce platform's perspective, formulate long-term plans, and dynamically adjust the…

Sparse Multiview Open-Vocabulary 3D Detection
Olivier Moliner, Viktor Larsson, Kalle {\AA}str\"om
https://arxiv.org/abs/2509.15924 https://arxiv.org/p…

Sparse Multiview Open-Vocabulary 3D Detection
The ability to interpret and comprehend a 3D scene is essential for many vision and robotics systems. In numerous applications, this involves 3D object detection, i.e.~identifying the location and dimensions of objects belonging to a specific category, typically represented as bounding boxes. This has traditionally been solved by training to detect a fixed set of categories, which limits its use. In this work, we investigate open-vocabulary 3D object detection in the challenging yet practical s…

Multiple Hypothesis Testing To Estimate The Number Of Communities in Stochastic Block Models
Chetkar Jha, Mingyao Li, Ian Barnett
https://arxiv.org/abs/2507.15471

Multiple Hypothesis Testing To Estimate The Number Of Communities in Stochastic Block Models
Clustering of single-cell RNA sequencing (scRNA-seq) datasets can give key insights into the biological functions of cells. Therefore, it is not surprising that network-based community detection methods (one of the better clustering methods) are increasingly being used for the clustering of scRNA-seq datasets. The main challenge in implementing network-based community detection methods for scRNA-seq datasets is that these methods \emph{apriori} require the true number of communities or blocks f…

Invariant Modeling for Joint Distributions
Christopher P. Chambers, Yusufcan Masatlioglu, Ruodu Wang
https://arxiv.org/abs/2509.15165 https://arxiv.org/pdf…

Invariant Modeling for Joint Distributions
A common theme underlying many problems in statistics and economics involves the determination of a systematic method of selecting a joint distribution consistent with a specified list of categorical marginals, some of which have an ordinal structure. We propose guidance in narrowing down the set of possible methods by introducing Invariant Aggregation (IA), a natural property that requires merging adjacent categories in one marginal not to alter the joint distribution over unaffected values. W…