Tootfinder

Is there a way to force a #Mastodon instance to fetch the follower number of an account again? I'm asking, because @… is growing, but the follower number I see stays steady.. (not only here, but on other instances too)

Well then, I guess I’ll have to replace that disk…
Except it’s a virtual disk, and should NOT be doing that. None of the other umpty-zillion VMs in that zone are showing trouble. Only this one. And the 3 other instances I launched before based on the the same original image, provided as a pre-built one for #OpenNebula from the

@… Do you know if SKH videos could get released through PeerTube at some point? They have sync options on most instances so you can set and forget it.

Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration
Zhenyu Lei, Jin-Kao Hao, Qinghua Wu
https://arxiv.org/abs/2506.17357 h…

Speeding up Local Optimization in Vehicle Routing with Tensor-based GPU Acceleration
Local search plays a central role in many effective heuristic algorithms for the vehicle routing problem (VRP) and its variants. However, neighborhood exploration is known to be computationally expensive and time consuming, especially for large instances or problems with complex constraints. In this study, we explore a promising direction to address this challenge by introducing an original tensor-based GPU acceleration method designed to speed up the commonly used local search operators in veh…

DRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy
Weitao Zhou, Bo Zhang, Zhong Cao, Xiang Li, Qian Cheng, Chunyang Liu, Yaqin Zhang, Diange Yang
https://arxiv.org/abs/2506.16720

DRARL: Disengagement-Reason-Augmented Reinforcement Learning for Efficient Improvement of Autonomous Driving Policy
With the increasing presence of automated vehicles on open roads under driver supervision, disengagement cases are becoming more prevalent. While some data-driven planning systems attempt to directly utilize these disengagement cases for policy improvement, the inherent scarcity of disengagement data (often occurring as a single instances) restricts training effectiveness. Furthermore, some disengagement data should be excluded since the disengagement may not always come from the failure of dri…

Don't miss today's Metacurity for the most critical infosec developments you might have missed over the weekend, including
--Foreign nation suspected in hack of Washington Post reporters’ emails,
--WestJet hit by cyber incident,
--Iran likely to retaliate with cyber ops,
--Zoomcar breach exposed customers' data,
--Qilin gang hit French insurer,
--Trump provided Medicaid data to deportation officials,
--46K Grafana instances remain unpatch…

Foreign nation suspected in hack of Washington Post reporters’ emails
WestJet hit by cyber incident, Iran likely to retaliate with cyber ops, Zoomcar breach exposed customers' data, Qilin gang hit French insurer, Trump provided Medicaid data to deportation officials, 46K+ Grafana instances remain unpatched, 10K VirtualMacOSX customers affected by breach, much more

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Chengpeng Hu, Ziming Wang, Bo Yuan, Jialin Liu, Chengqi Zhang, Xin Yao
https://arxiv.org/abs/2506.16795

Robust Dynamic Material Handling via Adaptive Constrained Evolutionary Reinforcement Learning
Dynamic material handling (DMH) involves the assignment of dynamically arriving material transporting tasks to suitable vehicles in real time for minimising makespan and tardiness. In real-world scenarios, historical task records are usually available, which enables the training of a decision policy on multiple instances consisting of historical records. Recently, reinforcement learning has been applied to solve DMH. Due to the occurrence of dynamic events such as new tasks, adaptability is hig…

@… What method did you use to set up cross-posting from Pinboard.in to Mastodon?

Does anyone have an IEEE DataPort subscription through your work or institution and would be open to sharing some files?
I'd love to get https://ieee-dataport.org/documents/cloud-telescope-internet-background-radiation-may-2023…

Spannende Themen wurden wieder diskutiert beim heutigen #fediverseModerationsTreff
Danke besonders an @… für die Vorstellung der föderierenden Plattform #Flohmarkt

flohmarkt instances
federated decentral classified ad software using activitypub

Bridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study
Olivier Saidi
https://arxiv.org/abs/2506.13810 https:…

Bridging Pattern-Aware Complexity with NP-Hard Optimization: A Unifying Framework and Empirical Study
NP hard optimization problems like the Traveling Salesman Problem (TSP) defy efficient solutions in the worst case, yet real-world instances often exhibit exploitable patterns. We propose a novel patternaware complexity framework that quantifies and leverages structural regularities e.g., clustering, symmetry to reduce effective computational complexity across domains, including financial forecasting and LLM optimization. With rigorous definitions, theorems, and a meta learning driven solver pi…

Human-Centred AI in FinTech: Developing a User Experience (UX) Research Point of View (PoV) Playbook
Festus Adedoyin, Huseyin Dogan
https://arxiv.org/abs/2506.15325

Human-Centred AI in FinTech: Developing a User Experience (UX) Research Point of View (PoV) Playbook
Advancements in Artificial Intelligence (AI) have significantly transformed the financial industry, enabling the development of more personalised and adaptable financial products and services. This research paper explores various instances where Human-Centred AI (HCAI) has facilitated these advancements, drawing from contemporary studies and industry progress. The paper examines how the application of HCAI-powered data analytics, machine learning, and natural language processing enables financi…

Compendium Manager: a tool for coordination of workflow management instances for bulk data processing in Python
Richard J. Abdill, Ran Blekhman
https://arxiv.org/abs/2505.11385

Compendium Manager: a tool for coordination of workflow management instances for bulk data processing in Python
Compendium Manager is a command-line tool written in Python to automate the provisioning, launch, and evaluation of bioinformatics pipelines. Although workflow management tools such as Snakemake and Nextflow enable users to automate the processing of samples within a single sequencing project, integrating many datasets in bulk requires launching and monitoring hundreds or thousands of pipelines. We present the Compendium Manager, a lightweight command-line tool to enable launching and monitorin…

There have been many instances documented, do a damn web search.
But forget that for a moment: What I’m doing is the same as what Netanyahu is doing? My opposing genocide is the same as a fucker perpetrating genocide?
Fuck you, Alfred.
Get some fucking perspective. https://mastodon.social/@amsz…

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Shuchang Wang, Xiaopeng Qiu, Yingxing Xue, Yanfu Li, Wei Yang
https://arxiv.org/abs/2506.14129

A Quantum Annealing Approach for Solving Optimal Feature Selection and Next Release Problems
Search-based software engineering (SBSE) addresses critical optimization challenges in software engineering, including the next release problem (NRP) and feature selection problem (FSP). While traditional heuristic approaches and integer linear programming (ILP) methods have demonstrated efficacy for small to medium-scale problems, their scalability to large-scale instances remains unknown. Here, we introduce quantum annealing (QA) as a subroutine to tackling multi-objective SBSE problems, leve…

fediverse: Fediverse network (2018)
An early snapshot of the federation network among web publishers using the ActivityPub protocol. Nodes are instances, and a directed edge exists if an instance follows another instance.
This network has 4860 nodes and 484164 edges.
Tags: Social, Online, Information
https://ne…

Affogato: Learning Open-Vocabulary Affordance Grounding with Automated Data Generation at Scale
Junha Lee, Eunha Park, Chunghyun Park, Dahyun Kang, Minsu Cho
https://arxiv.org/abs/2506.12009

Affogato: Learning Open-Vocabulary Affordance Grounding with Automated Data Generation at Scale
Affordance grounding-localizing object regions based on natural language descriptions of interactions-is a critical challenge for enabling intelligent agents to understand and interact with their environments. However, this task remains challenging due to the need for fine-grained part-level localization, the ambiguity arising from multiple valid interaction regions, and the scarcity of large-scale datasets. In this work, we introduce Affogato, a large-scale benchmark comprising 150K instances,…

Fair Bayesian Model-Based Clustering
Jihu Lee, Kunwoong Kim, Yongdai Kim
https://arxiv.org/abs/2506.12839 https://arxiv.org/pdf/2506.…

Fair Bayesian Model-Based Clustering
Fair clustering has become a socially significant task with the advancement of machine learning technologies and the growing demand for trustworthy AI. Group fairness ensures that the proportions of each sensitive group are similar in all clusters. Most existing group-fair clustering methods are based on the $K$-means clustering and thus require the distance between instances and the number of clusters to be given in advance. To resolve this limitation, we propose a fair Bayesian model-based cl…

Covering radii of $3$-zonotopes and the shifted Lonely Runner Conjecture
David Alc\'antara, Francisco Criado, Francisco Santos
https://arxiv.org/abs/2506.13379

Covering radii of $3$-zonotopes and the shifted Lonely Runner Conjecture
We show that the shifted Lonely Runner Conjecture (sLRC) holds for 5 runners. We also determine that there are exactly 3 primitive tight instances of the conjecture, only two of which are tight for the non-shifted conjecture (LRC). Our proof is computational, relying on a rephrasing of the sLRC in terms of covering radii of certain zonotopes (Henze and Malikiosis, 2017), and on an upper bound for the (integer) velocities to be checked (Malikiosis, Santos and Schymura, 2024+). As a tool for th…

Understanding uncertainty in Bayesian cluster analysis
Cecilia Balocchi, Sara Wade
https://arxiv.org/abs/2506.16295 https://arxiv.org…

Understanding uncertainty in Bayesian cluster analysis
The Bayesian approach to clustering is often appreciated for its ability to provide uncertainty in the partition structure. However, summarizing the posterior distribution over the clustering structure can be challenging, due the discrete, unordered nature and massive dimension of the space. While recent advancements provide a single clustering estimate to represent the posterior, this ignores uncertainty and may even be unrepresentative in instances where the posterior is multimodal. To enhanc…

Simpler, Better, Faster, Stronger: Revisiting a Successful Reduction Rule for Dominating Set
Lukas Geis, Alexander Leonhardt, Johannes Meintrup, Ulrich Meyer, Manuel Penschuck
https://arxiv.org/abs/2506.14564

Simpler, Better, Faster, Stronger: Revisiting a Successful Reduction Rule for Dominating Set
DominatingSet is a classical NP-complete problem and also known to be W[2]-hard. Thus, there is little hope for small kernels on general graphs. However, in practice, reduction rules to heuristically shrink instances are used. In this context, Rule1 by Alber et. al. is quite successful, yet at times somewhat expensive to execute. We propose a linear time algorithm implementing and surpassing the original Rule1 formulation. Our discussions and proofs yield interesting structural insights into th…

Abelianization of $\text{SL}_2$ over Dedekind domains of arithmetic type
Behrooz Mirzaii, Bruno R. Ramos, Thiago Verissimo
https://arxiv.org/abs/2506.12638

Abelianization of $\text{SL}_2$ over Dedekind domains of arithmetic type
We determine the exact group structure of the abelianization of $\text{SL}_2(A)$, where $A$ is a Dedekind domain of arithmetic type with infinitely many units. In particular, our results show that $\text{SL}_2(A)^\text{ab}$ is finite, with exponent dividing $12$ when $\text{char}(A)=0$, and dividing $6$ when $\text{char}(A)>0$. As illustrative cases, we compute $\text{SL}_2(A)^\text{ab}$ explicitly for instances where $A$ is the ring of integers of a real quadratic field or a cyclotomic extensi…

I know I shouldn't still be using this curséd website
but what is happening here with your lesson planning, Duo
Employ humans to write QA validations to keep these questions from being this silly
And stop using LLMs. Please.

The Hexablock: a domain associated with the $\mu$-synthesis in $M_2(\mathbb C)$
Indranil Biswas, Sourav Pal, Nitin Tomar
https://arxiv.org/abs/2506.15149 h…

The Hexablock: a domain associated with the $μ$-synthesis in $M_2(\mathbb C)$
We study a new domain in $\mathbb C^4$, namely the hexablock $\mathbb{H}$ that arises in connection with a special case of the $μ$-synthesis problem in $M_2(\mathbb C)$. Previous attempts to study a few instances of the $μ$-synthesis problem led to domains such as symmetrized bidisc $\mathbb G_2$, tetrablock $\mathbb E$ and pentablock $\mathbb P$. Throughout, the relations of $\mathbb{H}$ with these three domains are explored. Several characterizations of the hexablock are established. We det…

The L-Shaped Method for Stochastic Programs with Decision-Dependent Uncertainty
Giovanni Pantuso, Mike Hewitt
https://arxiv.org/abs/2506.12753 https://

The L-Shaped Method for Stochastic Programs with Decision-Dependent Uncertainty
In this paper we extend the well-known L-Shaped method to solve two-stage stochastic programming problems with decision-dependent uncertainty. The method is based on a novel, unifying, formulation and on distribution-specific optimality and feasibility cuts for both linear and integer stochastic programs. Extensive tests on three production planning problems illustrate that the method is extremely effective on large-scale instances.

Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices
Jiaqi Sun, Dingyu Yang, Shiyou Qian, Jian Cao, Guangtao Xue
https://arxiv.org/abs/2506.15523

Atys: An Efficient Profiling Framework for Identifying Hotspot Functions in Large-scale Cloud Microservices
To handle the high volume of requests, large-scale services are comprised of thousands of instances deployed in clouds. These services utilize diverse programming languages and are distributed across various nodes as encapsulated containers. Given their vast scale, even minor performance enhancements can lead to significant cost reductions. In this paper, we introduce Atys1, an efficient profiling framework specifically designed to identify hotspot functions within large-scale distributed servi…

Happy defederation day to all who celebrate! Apparently Hands Off protests are a troll magnet. If other admins want to check our blocklist, it just got four instances longer today. #fediblock

OCPQ: Object-Centric Process Querying & Constraints
Aaron K\"usters, Wil M. P. van der Aalst
https://arxiv.org/abs/2506.11541 https://

OCPQ: Object-Centric Process Querying & Constraints
Process querying is used to extract information and insights from process execution data. Similarly, process constraints can be checked against input data, yielding information on which process instances violate them. Traditionally, such process mining techniques use case-centric event data as input. However, with the uptake of Object-Centric Process Mining (OCPM), existing querying and constraint checking techniques are no longer applicable. Object-Centric Event Data (OCED) removes the require…

This https://arxiv.org/abs/2504.11284 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
Bipartite ranking is a fundamental supervised learning problem, with the goal of learning a ranking over instances with maximal Area Under the ROC Curve (AUC) against a single binary target label. However, one may often observe multiple binary target labels, e.g., from distinct human annotators. How can one synthesize such labels into a single coherent ranking? In this work, we formally analyze two approaches to this problem -- loss aggregation and label aggregation -- by characterizing their B…

I’m really glad Mastodon 4.4.0 will allow server admins to opt into sending the Referer header, and I hope admins of large instances will turn it on.
https://github.com/mastodon/mastodon/releases/tag/v4.4.0-beta.1
I also hope that third-party mobil…

Kinetic formulation of compartmental epidemic models
Carolina Strecht-Fernandes, Fabio A. C. C. Chalub
https://arxiv.org/abs/2506.13551 https://

Kinetic formulation of compartmental epidemic models
We introduce a kinetic model that couples the movement of a population of individuals with the dynamics of a pathogen in the same population. The model is formally shown to generalize the well-known compartmental models in mathematical epidemiology. We prove the existence and uniqueness of solutions in appropriate spaces for particular instances of the model. We finish with some examples, and discuss possible applications of this modeling approach.

The Complexity of the Set of Validities of a Theory
Denis Hirschfeldt, Henry Towsner, Scott Weinstein
https://arxiv.org/abs/2506.08901 https://

The Complexity of the Set of Validities of a Theory
We study the collection of first-order logical schemata all of whose instances are theorems of a given theory $T$; we call these the validities of $T$ ($\mathsf{V}(T)$). It is easy to see that if $T$ is a decidable theory, then $\mathsf{V}(T)$ is distinct from the set of valid formulas of first-order logic as customarily understood. We provide a complete model-theoretic characterization of the complexity, in the sense of Turing degree, of $\mathsf{V}(T)$ for decidable theories $T$, and answer a…

🎉 perfSONAR turns 20! 🎉
What started with a single line of code in 2001 has grown into a worldwide network performance monitoring infrastructure, spanning all 7 continents with:
✅ 20 years of continuous operation
✅ 6 leading R&E networks driving its development
✅ over 2,000 registered instances deployed across 1,000 organizations
Learn more about perfSONAR’s journey and impact over the past 20 years:

perfSONAR Celebrates 20 Years of Simplifying Global Research Collaboration Through Standardized Network Measurement and Testing | GÉANT CONNECT Online
April 2, 2025 — The global research and education (R&E) community is celebrating a major milestone in high-performance networking and collaboration: the 20th anniversary of perfSONAR. Since April 2005, this powerful, open-source toolkit has enabled researchers and network operators to measure and troubleshoot performance across diverse network environments. perfSONAR’s reach has extended to all seven

Fractional Orlicz-Sobolev embeddings into Campanato type spaces
Angela Alberico, Andrea Cianchi, Lubo\v{s} Pick, Lenka Slav\'ikov\'a
https://arxiv.org/abs/2506.13669

Fractional Orlicz-Sobolev embeddings into Campanato type spaces
Optimal embeddings for fractional Orlicz-Sobolev spaces into (generalized) Campanato spaces on the Euclidean space are exhibited. Embeddings into vanishing Campanato spaces are also characterized. Sharp embeddings into $\operatorname{BMO}(\mathbb R^n)$ and $\operatorname{VMO}(\mathbb R^n)$ are derived as special instances. Dissimilarities to corresponding embeddings for classical fractional Sobolev spaces are pointed out.

Online Fair Division for Personalized $2$-Value Instances
Georgios Amanatidis, Alexandros Lolos, Evangelos Markakis, Victor Turmel
https://arxiv.org/abs/2505.22174

Online Fair Division for Personalized $2$-Value Instances
We study an online fair division setting, where goods arrive one at a time and there is a fixed set of $n$ agents, each of whom has an additive valuation function over the goods. Once a good appears, the value each agent has for it is revealed and it must be allocated immediately and irrevocably to one of the agents. It is known that without any assumptions about the values being severely restricted or coming from a distribution, very strong impossibility results hold in this setting. To bypass…

Je viens de créer cette issue concernant les #ElasticMetal #Scaleway « Elastic Metal: Add protected feature for Elastic Metal »
…

This https://arxiv.org/abs/2406.13785 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qu…

Efficient Implementation of a Quantum Search Algorithm for Arbitrary N
This paper presents an enhancement to Grover's search algorithm for instances where the number of items (or the size of the search problem) $N$ is not a power of 2. By employing an efficient algorithm for the preparation of uniform quantum superposition states over a subset of the computational basis states, we demonstrate that a considerable reduction in the number of oracle calls (and Grover's iterations) can be achieved in many cases. For special cases (i.e., when $N$ is of the form such tha…

This https://arxiv.org/abs/2502.12012 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csET_…

Evolving Hard Maximum Cut Instances for Quantum Approximate Optimization Algorithms
Variational quantum algorithms, such as the Recursive Quantum Approximate Optimization Algorithm (RQAOA), have become increasingly popular, offering promising avenues for employing Noisy Intermediate-Scale Quantum devices to address challenging combinatorial optimization tasks like the maximum cut problem. In this study, we utilize an evolutionary algorithm equipped with a unique fitness function. This approach targets hard maximum cut instances within the latent space of a Graph Autoencoder, i…

Multi-Language Detection of Design Pattern Instances
Hugo Andrade, Jo\~ao Bispo, Filipe F. Correia
https://arxiv.org/abs/2506.03903 https://

Multi-Language Detection of Design Pattern Instances
Code comprehension is often supported by source code analysis tools which provide more abstract views over software systems, such as those detecting design patterns. These tools encompass analysis of source code and ensuing extraction of relevant information. However, the analysis of the source code is often specific to the target programming language. We propose DP-LARA, a multi-language pattern detection tool that uses the multi-language capability of the LARA framework to support finding p…

TL;DR Amazon's SES in sandbox mode only sends to validated addresses and identities defined in the configuration.
https://winkelwagen.de/2025/05/29/aws-ses-message-rejected-email-address-is-not-verified/

AWS SES Message rejected: Email address is not verified.
I configured one of our Magento 2 stage instances today to use Amazon SES to send emails instead of dumping them into mailhog. But I got the following error: Message rejected: Email address is not …

Woocomerce is used by million of people. Look for the latest 9.8 vulnerability: #wordpress

GitHub - d0n601/CVE-2025-5058: eMagicOne Store Manager for WooCommerce <= 1.2.5 - Unauthenticated Arbitrary File Upload via set_image Task
eMagicOne Store Manager for WooCommerce <= 1.2.5 - Unauthenticated Arbitrary File Upload via set_image Task - d0n601/CVE-2025-5058

This https://arxiv.org/abs/2405.10144 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

A characterization of physical measures for systems with mixed central behavior
We show that the existence of physical measures for $C^\infty$ smooth instances of certain partially hyperbolic dynamics, both continuous and discrete, exhibiting mixed behavior (positive and negative Lyapunov exponents) along the central non-uniformly hyperbolic multidimensional invariant direction, is equivalent to the existence of certain types of ``regular points'' on positive volume subsets, including Lyapunov regular points. This encompasses the $C^3$ robust class of multidimensional non-…

An extension of Dembo-Hammer's reduction algorithm for the 0-1 knapsack problem
Yang Yang
https://arxiv.org/abs/2506.06138 https://

An extension of Dembo-Hammer's reduction algorithm for the 0-1 knapsack problem
Dembo-Hammer's Reduction Algorithm (DHR) is one of the classical algorithms for the 0-1 Knapsack Problem (0-1 KP) and its variants, which reduces an instance of the 0-1 KP to a sub-instance of smaller size with reduction time complexity $O(n)$. We present an extension of DHR (abbreviated as EDHR), which reduces an instance of 0-1 KP to at most $n^i$ sub-instances for any positive integer $i$. In practice, $i$ can be set as needed. In particular, if we choose $i=1$ then EDHR is exactly DHR. Fina…

This https://arxiv.org/abs/2505.00858 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Duality on the Thermodynamics of the Kirchhoff-Law-Johnson-Noise (KLJN) Secure Key Exchange Scheme
This study investigates a duality approach to information leak detection in the generalized Kirchhoff-Law-Johnson-Noise secure key exchange scheme proposed by Vadai, Mingesz, and Gingl (VMG-KLJN). While previous work by Chamon and Kish sampled voltages at zero-current instances, this research explores sampling currents at zero-voltage crossings. The objective is to determine if this dual approach can reveal information leaks in non-equilibrium KLJN systems. Results indicate that the duality met…

El0ps: An Exact L0-regularized Problems Solver
Th\'eo Guyard, C\'edric Herzet, Cl\'ement Elvira
https://arxiv.org/abs/2506.06373 https://

El0ps: An Exact L0-regularized Problems Solver
This paper presents El0ps, a Python toolbox providing several utilities to handle L0-regularized problems related to applications in machine learning, statistics, and signal processing, among other fields. In contrast to existing toolboxes, El0ps allows users to define custom instances of these problems through a flexible framework, provides a dedicated solver achieving state-of-the-art performance, and offers several built-in machine learning pipelines. Our aim with El0ps is to provide a compr…

Telescoping Algorithms for $\Sigma^*$-Extensions via Complete Reductions
Shaoshi Chen, Yiman Gao, Hui Huang, Carsten Schneider
https://arxiv.org/abs/2506.08767

Telescoping Algorithms for $Σ^*$-Extensions via Complete Reductions
A complete reduction on a difference field is a linear operator that enables one to decompose an element of the field as the sum of a summable part and a remainder such that the given element is summable if and only if the remainder is equal to zero. In this paper, we present a complete reduction in a tower of $Σ^*$-extensions that turns to a new efficient framework for the parameterized telescoping problem. Special instances of such $Σ^*$-extensions cover iterative sums such as the harmonic …

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Rolf Drechsler
https://arxiv.org/abs/2505.23311 https://

Towards LLM-based Generation of Human-Readable Proofs in Polynomial Formal Verification
Verification is one of the central tasks in circuit and system design. While simulation and emulation are widely used, complete correctness can only be ensured based on formal proof techniques. But these approaches often have very high run time and memory requirements. Recently, Polynomial Formal Verification (PFV) has been introduced showing that for many instances of practical relevance upper bounds on needed resources can be given. But proofs have to be provided that are human-readable. He…

AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
Zixuan Jiang, Renjing Xu
https://arxiv.org/abs/2506.07035 https://

AnnoDPO: Protein Functional Annotation Learning with Direct Preference Optimization
Deciphering protein function remains a fundamental challenge in protein representation learning. The task presents significant difficulties for protein language models (PLMs) due to the sheer volume of functional annotation categories and the highly imbalanced distribution of annotated instances across biological ontologies. Inspired by the remarkable success of reinforcement learning from human feedback (RLHF) in large language model (LLM) alignment, we propose AnnoDPO, a novel multi-modal fra…

Distributionally-Constrained Adversaries in Online Learning
Mo\"ise Blanchard, Samory Kpotufe
https://arxiv.org/abs/2506.10293 https://

Distributionally-Constrained Adversaries in Online Learning
There has been much recent interest in understanding the continuum from adversarial to stochastic settings in online learning, with various frameworks including smoothed settings proposed to bridge this gap. We consider the more general and flexible framework of distributionally constrained adversaries in which instances are drawn from distributions chosen by an adversary within some constrained distribution class [RST11]. Compared to smoothed analysis, we consider general distributional classe…

The Interplay of Polar and Nematic Order in Active Matter: Implications for Non-Equilibrium Physics and Biology
Varun Venkatesh, Niels de Graaf Sousa, Amin Doostmohammadi
https://arxiv.org/abs/2506.05931

The Interplay of Polar and Nematic Order in Active Matter: Implications for Non-Equilibrium Physics and Biology
Active matter has played a pivotal role in advancing our understanding of non-equilibrium systems, leading to a fundamental shift in the study of biophysical phenomena. The foundation of active matter research is built on assumptions regarding the symmetry of microscopic constituents. While these assumptions have been validated extensively, instances of mixed or joint symmetries are prevalent in biological systems. This review explores the coexistence of polar and nematic order in active matter…

On conformal Komar currents in LRS spacetimes
Abbas M. Sherif
https://arxiv.org/abs/2506.04888 https://arxiv.org/pdf/2506.04888

On conformal Komar currents in LRS spacetimes
For locally rotationally symmetric (LRS) spacetimes, we construct two equivalent forms of the Komar current derived from a conformal Killing vector. One is a kinematic construction and the other is in terms of the matter quantities on the spacetime. The required conservation condition for the current is derived and discussed in various instances, and the implications of the conservation of the current, and in the case of a vanishing current, are analyzed. A relationship between the conservation…

Congruence conditions for the mod $\lambda$ values of the Fourier coefficients of classical eigenforms
Michael A. Daas
https://arxiv.org/abs/2506.08865 htt…

Congruence conditions for the mod $λ$ values of the Fourier coefficients of classical eigenforms
We classify all instances of the condition $a_{p}(f) \equiv x \bmod λ$ being related to a congruence on the prime $p$, where $a_{p}(f)$ denotes the $p$th Fourier coefficient of a classical normalised cuspidal eigenform $f$ and $λ$ is a prime in the number field generated by the Fourier coefficients of $f$. This classification is done in terms of the (projective) image of the mod $λ$ Galois representation associated with $f$ and extends work by Swinnerton-Dyer. We highlight that for $x = 0$, …

On the integrality Gap of Small Asymmetric Traveling Salesman Problems: A Polyhedral and Computational Approach
Eleonora Vercesi, Janos Barta, Luca Maria Gambardella, Stefano Gualandi, Monaldo Mastrolilli
https://arxiv.org/abs/2506.10671

On the integrality Gap of Small Asymmetric Traveling Salesman Problems: A Polyhedral and Computational Approach
In this paper, we investigate the integrality gap of the Asymmetric Traveling Salesman Problem (ATSP) with respect to the linear relaxation given by the Asymmetric Subtour Elimination Problem (ASEP) for instances with $n$ nodes, where $n$ is small. In particular, we focus on the geometric properties and symmetries of the ASEP polytope ($P^{n}_{ASEP}$) and its vertices. The polytope's symmetries are exploited to design a heuristic pivoting algorithm to search vertices where the integrality gap i…

This https://arxiv.org/abs/2505.21652 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csRO_…

PartInstruct: Part-level Instruction Following for Fine-grained Robot Manipulation
Fine-grained robot manipulation, such as lifting and rotating a bottle to display the label on the cap, requires robust reasoning about object parts and their relationships with intended tasks. Despite recent advances in training general-purpose robot manipulation policies guided by language instructions, there is a notable lack of large-scale datasets for fine-grained manipulation tasks with part-level instructions and diverse 3D object instances annotated with part-level labels. In this work,…

#mastodontips mb?
#mastodon #firefoxaddons

Estimating the Euclidean distortion of an orbit space
Ben Blum-Smith, Harm Derksen, Dustin G. Mixon, Yousef Qaddura, Brantley Vose
https://arxiv.org/abs/2506.04425

Estimating the Euclidean distortion of an orbit space
Given a finite-dimensional inner product space $V$ and a group $G$ of isometries, we consider the problem of embedding the orbit space $V/G$ into a Hilbert space in a way that preserves the quotient metric as well as possible. This inquiry is motivated by applications to invariant machine learning. We introduce several new theoretical tools before using them to tackle various fundamental instances of this problem.

Improved Approximate EFX Guarantees for Multigraphs
Alireza Kaviani, Alireza Keshavarz, Masoud Seddighin, AmirMohammad Shahrezaei
https://arxiv.org/abs/2506.09288

Improved Approximate EFX Guarantees for Multigraphs
In recent years, a new line of work in fair allocation has focused on EFX allocations for \((p, q)\)-bounded valuations, where each good is relevant to at most \(p\) agents, and any pair of agents share at most \(q\) relevant goods. For the case \(p = 2\) and \(q = \infty\), such instances can be equivalently represented as multigraphs whose vertices are the agents and whose edges represent goods, each edge incident to exactly the one or two agents for whom the good is relevant. A recent result…

SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Lianghong Guo, Yanlin Wang, Caihua Li, Pengyu Yang, Jiachi Chen, Wei Tao, Yingtian Zou, Duyu Tang, Zibin Zheng
https://arxiv.org/abs/2506.10954

SWE-Factory: Your Automated Factory for Issue Resolution Training Data and Evaluation Benchmarks
Constructing large-scale datasets for the GitHub issue resolution task is crucial for both training and evaluating the software engineering capabilities of Large Language Models (LLMs). However, the traditional process for creating such benchmarks is notoriously challenging and labor-intensive, particularly in the stages of setting up evaluation environments, grading test outcomes, and validating task instances. In this paper, we propose SWE-Factory, an automated pipeline designed to address th…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Chen Xiong, Pin-Yu Chen, Tsung-Yi Ho
https://arxiv.org/abs/2506.00781 ht…

CoP: Agentic Red-teaming for Large Language Models using Composition of Principles
Recent advances in Large Language Models (LLMs) have spurred transformative applications in various domains, ranging from open-source to proprietary LLMs. However, jailbreak attacks, which aim to break safety alignment and user compliance by tricking the target LLMs into answering harmful and risky responses, are becoming an urgent concern. The practice of red-teaming for LLMs is to proactively explore potential risks and error-prone instances before the release of frontier AI technology. This …

This https://arxiv.org/abs/2412.06552 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCC_…

Direct Sums for Parity Decision Trees
Direct sum theorems state that the cost of solving $k$ instances of a problem is at least $Ω(k)$ times the cost of solving a single instance. We prove the first such results in the randomised parity decision tree model. We show that a direct sum theorem holds whenever (1) the lower bound for parity decision trees is proved using the discrepancy method; or (2) the lower bound is proved relative to a product distribution.

This https://arxiv.org/abs/2406.14930 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

An independence of the MIN principle from the PHP principle
The minimization principle $\textsf{MIN}(\triangleleft)$ studied in bounded arithmetic says that a strict linear ordering $\triangleleft$ on any finite interval $[0,\dots,n)$ has the minimal element. We shall prove that bounded arithmetic theory $\textsf{T}^1_2(\triangleleft)$ augmented by instances of the pigeonhole principle for all $Δ^b_1(\triangleleft)$ formulas does not prove $\textsf{MIN}(\triangleleft)$.

SkyLB: A Locality-Aware Cross-Region Load Balancer for LLM Inference
Tian Xia, Ziming Mao, Jamison Kerney, Ethan J. Jackson, Zhifei Li, Jiarong Xing, Scott Shenker, Ion Stoica
https://arxiv.org/abs/2505.24095

SkyLB: A Locality-Aware Cross-Region Load Balancer for LLM Inference
Serving Large Language Models (LLMs) efficiently in multi-region setups remains a challenge. Due to cost and GPU availability concerns, providers typically deploy LLMs in multiple regions using instance with long-term commitments, like reserved instances or on-premise clusters, which are often underutilized due to their region-local traffic handling and diurnal traffic variance. In this paper, we introduce SkyLB, a locality-aware multi-region load balancer for LLM inference that aggregates regi…

Decomposing Words for Enhanced Compression: Exploring the Number of Runs in the Extended Burrows-Wheeler Transform
Florian Ingels, Ana\"is Denis, Bastien Cazaux
https://arxiv.org/abs/2506.04926

Decomposing Words for Enhanced Compression: Exploring the Number of Runs in the Extended Burrows-Wheeler Transform
The Burrows-Wheeler Transform (BWT) is a fundamental component in many data structures for text indexing and compression, widely used in areas such as bioinformatics and information retrieval. The extended BWT (eBWT) generalizes the classical BWT to multisets of strings, providing a flexible framework that captures many BWT-like constructions. Several known variants of the BWT can be viewed as instances of the eBWT applied to specific decompositions of a word. A central property of the BWT, ess…

PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
Huikang Liu, Yicheng Huang, Hongpei Li, Dongdong Ge, Yinyu Ye
https://arxiv.org/abs/2506.06258

PDHCG: A Scalable First-Order Method for Large-Scale Competitive Market Equilibrium Computation
Large-scale competitive market equilibrium problems arise in a wide range of important applications, including economic decision-making and intelligent manufacturing. Traditional solution methods, such as interior-point algorithms and certain projection-based approaches, often fail to scale effectively to large problem instances. In this paper, we propose an efficient computational framework that integrates the primal-dual hybrid conjugate gradient (PDHCG) algorithm with GPU-based parallel comp…

Decidability of multiplicative matrix equations and related Diophantine problems
Sebastian Heintze, Armand Noubissie, Robert F. Tichy
https://arxiv.org/abs/2506.03932

Decidability of multiplicative matrix equations and related Diophantine problems
Some new decidability results for multiplicative matrix equations over algebraic number fields are established. In particular, special instances of the so-called knapsack problem are considered. The proofs are based on effective methods for Diophantine problems in finitely generated domains as presented in the recent book of Evertse and Györy. The focus lies on explicit bounds for the size of the solutions in terms of heights as well as on bounds for the number of solutions. This approach also…

This https://arxiv.org/abs/2506.03903 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Multi-Language Detection of Design Pattern Instances
Code comprehension is often supported by source code analysis tools which provide more abstract views over software systems, such as those detecting design patterns. These tools encompass analysis of source code and ensuing extraction of relevant information. However, the analysis of the source code is often specific to the target programming language. We propose DP-LARA, a multi-language pattern detection tool that uses the multi-language capability of the LARA framework to support finding p…

A Ranking Framework for Network Resource Allocation and Scheduling via Hypergraphs
Rajpreet Singh, Novak Bo\v{s}kov, Aditya Gudal, Manzoor A. Khan
https://arxiv.org/abs/2506.01571

A Ranking Framework for Network Resource Allocation and Scheduling via Hypergraphs
Resource allocation and scheduling are a common problem in various distributed systems. Although widely studied, the state-of-the-art solutions either do not scale or lack the expressive power to capture the most complex instances of the problem. To that end, we present a mathematical framework for hypergraph ranking and analysis, unifying graph theory, lattice theory, and semantic analysis. In our fundamental theorem, we prove the existence of partial order on entities of hypergraphs, extendin…

Designing Algorithmic Delegates: The Role of Indistinguishability in Human-AI Handoff
Sophie Greenwood, Karen Levy, Solon Barocas, Hoda Heidari, Jon Kleinberg
https://arxiv.org/abs/2506.03102

Designing Algorithmic Delegates: The Role of Indistinguishability in Human-AI Handoff
As AI technologies improve, people are increasingly willing to delegate tasks to AI agents. In many cases, the human decision-maker chooses whether to delegate to an AI agent based on properties of the specific instance of the decision-making problem they are facing. Since humans typically lack full awareness of all the factors relevant to this choice for a given decision-making instance, they perform a kind of categorization by treating indistinguishable instances -- those that have the same o…

Lions and Muons: Optimization via Stochastic Frank-Wolfe
Maria-Eleni Sfyraki, Jun-Kun Wang
https://arxiv.org/abs/2506.04192 https://a…

Lions and Muons: Optimization via Stochastic Frank-Wolfe
Stochastic Frank-Wolfe is a classical optimization method for solving constrained optimization problems. On the other hand, recent optimizers such as Lion and Muon have gained quite significant popularity in deep learning. In this work, we provide a unifying perspective by interpreting these seemingly disparate methods through the lens of Stochastic Frank-Wolfe. Specifically, we show that Lion and Muon with weight decay can be viewed as special instances of a Stochastic Frank-Wolfe, and we esta…

An LLM Agent for Functional Bug Detection in Network Protocols
Mingwei Zheng, Chengpeng Wang, Xuwei Liu, Jinyao Guo, Shiwei Feng, Xiangyu Zhang
https://arxiv.org/abs/2506.00714

An LLM Agent for Functional Bug Detection in Network Protocols
Functional correctness is critical for ensuring the reliability and security of network protocol implementations. Functional bugs, instances where implementations diverge from behaviors specified in RFC documents, can lead to severe consequences, including faulty routing, authentication bypasses, and service disruptions. Detecting these bugs requires deep semantic analysis across specification documents and source code, a task beyond the capabilities of traditional static analysis tools. This p…

Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Qiming Zhu, Jialun Cao, Xuanang Chen, Yaojie Lu, Hongyu Lin, Xianpei Han, Le Sun, Shing-Chi Cheung
https://arxiv.org/abs/2506.03535

Across Programming Language Silos: A Study on Cross-Lingual Retrieval-augmented Code Generation
Current research on large language models (LLMs) with retrieval-augmented code generation (RACG) mainly focuses on single-language settings, leaving cross-lingual effectiveness and security unexplored. Multi-lingual RACG systems are valuable for migrating code-bases across programming languages (PLs), yet face risks from error (e.g. adversarial data corruption) propagation in cross-lingual transfer. We construct a dataset spanning 13 PLs with nearly 14k instances to explore utility and robustne…

This https://arxiv.org/abs/2505.14547 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGT_…

GUARD: Constructing Realistic Two-Player Matrix and Security Games for Benchmarking Game-Theoretic Algorithms
Game-theoretic algorithms are commonly benchmarked on recreational games, classical constructs from economic theory such as congestion and dispersion games, or entirely random game instances. While the past two decades have seen the rise of security games -- grounded in real-world scenarios like patrolling and infrastructure protection -- their practical evaluation has been hindered by limited access to the datasets used to generate them. In particular, although the structural components of the…

This https://arxiv.org/abs/2505.01136 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Descriptor: C++ Self-Admitted Technical Debt Dataset (CppSATD)
In software development, technical debt (TD) refers to suboptimal implementation choices made by the developers to meet urgent deadlines and limited resources, posing challenges for future maintenance. Self-Admitted Technical Debt (SATD) is a sub-type of TD, representing specific TD instances ``openly admitted'' by the developers and often expressed through source code comments. Previous research on SATD has focused predominantly on the Java programming language, revealing a significant gap in …

This https://arxiv.org/abs/2410.20448 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

New results related to cutters and to an extrapolated block-iterative method for finding a common fixed point of a collection of them
Given a Hilbert space and a finite family of operators defined on the space, the common fixed point problem (CFPP) is to find a point in the intersection of the fixed point sets of these operators. Instances of the problem have numerous applications in science and engineering. We consider an extrapolated block-iterative method with dynamic weights for solving the CFPP assuming the operators belong to a wide class of operators called cutters. Global convergence is proved in two different scenari…

This https://arxiv.org/abs/2410.20448 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

New results related to cutters and to an extrapolated block-iterative method for finding a common fixed point of a collection of them
Given a Hilbert space and a finite family of operators defined on the space, the common fixed point problem (CFPP) is to find a point in the intersection of the fixed point sets of these operators. Instances of the problem have numerous applications in science and engineering. We consider an extrapolated block-iterative method with dynamic weights for solving the CFPP assuming the operators belong to a wide class of operators called cutters. Global convergence is proved in two different scenari…