Tootfinder

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts.
TL;DR: Solar sails could make the trip take some 7 years, while thermonuclear fusion could take 10 years. Whereas with current engines it would take 30 years.
https://arxiv.org/abs/2506.17732

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts
Exploring the outer reaches of the Solar System presents significant propulsion and mission design challenges. This study assesses the feasibility of a mission to Sedna using two advanced propulsion concepts: the Direct Fusion Drive (DFD) rocket engine, based on D-$^{3}$He thermonuclear fusion, and a solar sail utilizing thermal desorption of its coating for propulsion. Both are evaluated for a one-way Earth-to-Sedna mission; however, due to the different performances the DFD would enable orbit…

Crypto and tech entrepreneurs are attending Network School, founded by Balaji Srinivasan in Forest City, Malaysia, to test his concepts about the Network State (Ryan Weeks/Bloomberg)
https://www.bloomberg.com/news/articles/20

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Xinghe Cheng, Zihan Zhang, Jiapu Wang, Liangda Fang, Chaobo He, Quanlong Guan, Shirui Pan, Weiqi Luo
https://arxiv.org/abs/2506.22303

Education-Oriented Graph Retrieval-Augmented Generation for Learning Path Recommendation
Learning path recommendation seeks to provide learners with a structured sequence of learning items (e.g., knowledge concepts or exercises) to optimize their learning efficiency. Despite significant efforts in this area, most existing methods primarily rely on prerequisite relationships, which present two major limitations: 1) Many educational datasets do not explicitly provide prerequisite relationships between knowledge concepts, hindering the application of current learning path recommendati…

ZIUM: Zero-Shot Intent-Aware Adversarial Attack on Unlearned Models
Hyun Jun Yook, Ga San Jhun, Jae Hyun Cho, Min Jeon, Donghyun Kim, Tae Hyung Kim, Youn Kyu Lee
https://arxiv.org/abs/2507.21985

ZIUM: Zero-Shot Intent-Aware Adversarial Attack on Unlearned Models
Machine unlearning (MU) removes specific data points or concepts from deep learning models to enhance privacy and prevent sensitive content generation. Adversarial prompts can exploit unlearned models to generate content containing removed concepts, posing a significant security risk. However, existing adversarial attack methods still face challenges in generating content that aligns with an attacker's intent while incurring high computational costs to identify successful prompts. To address th…

Multi-Ontology Integration with Dual-Axis Propagation for Medical Concept Representation
Mohsen Nayebi Kerdabadi, Arya Hadizadeh Moghaddam, Dongjie Wang, Zijun Yao
https://arxiv.org/abs/2508.21320

Multi-Ontology Integration with Dual-Axis Propagation for Medical Concept Representation
Medical ontology graphs map external knowledge to medical codes in electronic health records via structured relationships. By leveraging domain-approved connections (e.g., parent-child), predictive models can generate richer medical concept representations by incorporating contextual information from related concepts. However, existing literature primarily focuses on incorporating domain knowledge from a single ontology system, or from multiple ontology systems (e.g., diseases, drugs, and proce…

How (Not) To Write a Software Engineering Abstract
Lutz Prechelt, Lloyd Montgomery, Julian Frattini, Franz Zieris
https://arxiv.org/abs/2506.21634 https://…

How (Not) To Write a Software Engineering Abstract
Background: Abstracts are a particularly valuable element in a software engineering research article. However, not all abstracts are as informative as they could be. Objective: Characterize the structure of abstracts in high-quality software engineering venues. Observe and quantify deficiencies. Suggest guidelines for writing informative abstracts. Methods: Use qualitative open coding to derive concepts that explain relevant properties of abstracts. Identify the archetypical structure of abstra…

Abnormal and Contranormal L-Subgroups of an L-group
Ananya Manas, Iffat Jahan
https://arxiv.org/abs/2506.22528 https://arxiv.org/pdf/…

Abnormal and Contranormal L-Subgroups of an L-group
In this paper, the concepts of abnormal and contranormal L-subgroups of an L-group have been introduced using the notion of the conjugate. Then, the properties of abnormal and contranormal L-subgroups have been studied analogous to their group-theoretic counterparts. Thereafter, several relations of abnormality and contranormality have been investigated in context of normality, maximality, normalizer and normal closure of L-subgroups of an L-group.

Global Descent Method for Non-convex Multi-objective Optimization Problems
Bikram Adhikary, Md Abu Talhamainuddin Ansary, Savin Treanta
https://arxiv.org/abs/2507.22390 https://…

Global Descent Method for Non-convex Multi-objective Optimization Problems
In this paper, we develop a global descent method for non-convex multi-objective optimization problems. The proposed approach builds upon foundational concepts from single-objective global descent techniques while removing the need for predefined scalars or ordering information of objective functions. Initially, the proposed method identifies a local weak efficient solution using any suitable descent algorithm, then applies an auxiliary function termed the multi-objective global descent functio…

Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Dani Korpi, Rachel Wang, Jerry Wang, Abdelrahman Ibrahim, Carl Nuzman, Runxin Wang, Kursat Rasim Mestav, Dustin Zhang, Iraj Saniee, Shawn Winston, Gordana Pavlovic, Wei Ding, William J. Hillery, Chenxi Hao, Ram Thirunagari, Jung Chang, Jeehyun Kim, Bartek Kozicki, Dragan Samardzija, Taesang Yoo, Andreas Maeder, Tingfang Ji, Harish Viswanathan

Demonstrating Interoperable Channel State Feedback Compression with Machine Learning
Neural network-based compression and decompression of channel state feedback has been one of the most widely studied applications of machine learning (ML) in wireless networks. Various simulation-based studies have shown that ML-based feedback compression can result in reduced overhead and more accurate channel information. However, to the best of our knowledge, there are no real-life proofs of concepts demonstrating the benefits of ML-based channel feedback compression in a practical setting, …

Fault-Tolerant Matroid Bases
Matthias Bentert, Fedor V. Fomin, Petr A. Golovach, Laure Morelle
https://arxiv.org/abs/2506.22010 https://

Fault-Tolerant Matroid Bases
We investigate the problem of constructing fault-tolerant bases in matroids. Given a matroid M and a redundancy parameter k, a k-fault-tolerant basis is a minimum-size set of elements such that, even after the removal of any k elements, the remaining subset still spans the entire ground set. Since matroids generalize linear independence across structures such as vector spaces, graphs, and set systems, this problem unifies and extends several fault-tolerant concepts appearing in prior research. …

Representation Learning of Auxiliary Concepts for Improved Student Modeling and Exercise Recommendation
Yahya Badran, Christine Preisach
https://arxiv.org/abs/2508.16269 https:/…

Representation Learning of Auxiliary Concepts for Improved Student Modeling and Exercise Recommendation
Personalized recommendation is a key feature of intelligent tutoring systems, typically relying on accurate models of student knowledge. Knowledge Tracing (KT) models enable this by estimating a student's mastery based on their historical interactions. Many KT models rely on human-annotated knowledge concepts (KCs), which tag each exercise with one or more skills or concepts believed to be necessary for solving it. However, these KCs can be incomplete, error-prone, or overly general. In this …

The Impact of Foregrounds on Dark Ages Measurements with the Highly Redshifted 21 cm Line
Jonathan C. Pober, Willow Smith
https://arxiv.org/abs/2507.22993 https://

The Impact of Foregrounds on Dark Ages Measurements with the Highly Redshifted 21 cm Line
Studies of the cosmic dark ages ($30 \lesssim z \lesssim 150$) using the highly redshifted 21 cm line of neutral hydrogen offer unparalleled amounts of cosmological information, and recent years have seen the refinement of concepts for such experiments (e.g. CoDEX and FarView), nominally feasible with technology and resources in the next one to two decades. This work studies how the "foreground wedge" -- a term in the 21 cm cosmology literature referring to the contamination of power spectrum m…

Development and Evaluation of Adaptive LearningSupport System Based on Ontology of MultipleProgramming Languages
Lalita Na Nongkhai, Jingyun Wang, Takahiko Mendori
https://arxiv.org/abs/2507.19728

Development and Evaluation of Adaptive LearningSupport System Based on Ontology of MultipleProgramming Languages
This paper introduces an ontology-based approach within an adaptive learning support system for computer programming. This system (named ADVENTURE) is designed to deliver personalized programming exercises that are tailored to individual learners' skill levels. ADVENTURE utilizes an ontology, named CONTINUOUS, which encompasses common concepts across multiple programming languages. The system leverages this ontology not only to visualize programming concepts but also to provide hints during pra…

The Distributed and Unified Numerics Environment (DUNE), Version 2.10
Markus Blatt, Samuel Burbulla, Ansgar Burchardt, Andreas Dedner, Christian Engwer, Carsten Gr\"aser, Christoph Gr\"uninger, Robert Kl\"ofkorn, Timo Koch, Santiago Ospina De Los R\'ios, Simon Praetorius, Oliver Sander
https://arxiv.org/abs/25…

The Distributed and Unified Numerics Environment (DUNE), Version 2.10
Version 2.10 of the Distributed and Unified Numerics Environment DUNE introduces a range of enhancements across its core and extension modules, with a continued emphasis on modern C++ integration and improved usability. This release extends support for C++20 features, particularly concepts, through comprehensive refinements in dune-common and dune-grid, enabling safer and more expressive generic programming paradigms. A notable advancement is the improved support for curved geometries, includin…

Thermodynamics of Hard Sphere and Spherocylinder Mixtures -- Scaled Particle Theory and Monte Carlo Simulations
Volodymyr Shmotolokha (Eindhoven University of Technology, Eindhoven, Netherlands), Jonas Maier-Borst (University of Freiburg, Freiburg, Germany), Mark Vis (Eindhoven University of Technology, Eindhoven, Netherlands), Anja Kuhnhold (University of Freiburg, Freiburg, Germany), Remco Tuinier (Eindhoven University of Technology, Eindhoven, Netherlands)

Thermodynamics of Hard Sphere and Spherocylinder Mixtures -- Scaled Particle Theory and Monte Carlo Simulations
We review the literature on scaled particle theory (SPT) and its extensions and discuss results applied to describe the thermodynamics of hard particle mixtures. After explaining the basic concepts of scaled particle theory to compute the free energy of immersing a particle into a mixture, examples are discussed for the simple case of a hard sphere dispersion and the free volume fraction of ghost spheres in a hard sphere dispersion. Next, the concept is applied to mixtures, and general expressi…

Semantic Numeration Systems as Dynamical Systems
Alexander Yu. Chunikhin
https://arxiv.org/abs/2507.21295 https://arxiv.org/pdf/2507.21295

Semantic Numeration Systems as Dynamical Systems
The foundational concepts of semantic numeration systems theory are briefly outlined. The action of cardinal semantic operators unfolds over a set of cardinal abstract entities belonging to the cardinal semantic multeity. The cardinal abstract object (CAO) formed by them in a certain connectivity topology is proposed to be considered as a linear discrete dynamical system with nonlinear control. Under the assumption of ideal observability, the CAO state equations are provided for both stationary…

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos
Qiyue Sun, Qiming Huang, Yang Yang, Hongjun Wang, Jianbo Jiao
https://arxiv.org/abs/2508.21770

What Can We Learn from Harry Potter? An Exploratory Study of Visual Representation Learning from Atypical Videos
Humans usually show exceptional generalisation and discovery ability in the open world, when being shown uncommon new concepts. Whereas most existing studies in the literature focus on common typical data from closed sets, open-world novel discovery is under-explored in videos. In this paper, we are interested in asking: \textit{What if atypical unusual videos are exposed in the learning process?} To this end, we collect a new video dataset consisting of various types of unusual atypical data (…

LLMs exhibit "potemkin understanding"!
Hope the methodology here is better than the last LLM-hater arxiv paper that came through
Must read it more carefully...
https://mathstodon.xyz/@gregeganSF/114758840374128081

Greg Egan (@gregeganSF@mathstodon.xyz)
Attached: 1 image “Potemkin Understanding in Large Language Models” A detailed analysis of the incoherent application of concepts by LLMs, showing how benchmarks that reliably establish domain competence in humans can be passed by LLMs lacking similar competence. H/T @acowley@mastodon.social Link: https://arxiv.org/abs/2506.21521

Rises for Measuring Local Distributivity in Lattices
Mohammad Abdulla, Tobias Hille, Dominik D\"urrschnabel, Gerd Stumme
https://arxiv.org/abs/2506.23168

Rises for Measuring Local Distributivity in Lattices
Distributivity is a well-established and extensively studied notion in lattice theory. In the context of data analysis, particularly within Formal Concept Analysis (FCA), lattices are often observed to exhibit a high degree of distributivity. However, no standardized measure exists to quantify this property. In this paper, we introduce the notion of rises in (concept) lattices as a means to assess distributivity. Rises capture how the number of attributes or objects in covering concepts change …

Implementing Pseudofractal Designs in Graphene-Based Quantum Hall Arrays using Minkowski-Bouligand Algorithms
Dominick S. Scaletta, Ngoc Thanh Mai Tran, Marta Musso, Dean G. Jarrett, Heather M. Hill, Massimo Ortolano, David B. Newell, Albert F. Rigosi
https://arxiv.org/abs/2507.23625

Implementing Pseudofractal Designs in Graphene-Based Quantum Hall Arrays using Minkowski-Bouligand Algorithms
This work introduces a pseudofractal analysis for optimizing high-resistance graphene-based quantized Hall array resistance standards (QHARS). The development of resistance standard device designs through star-mesh transformations is detailed, aimed at minimizing element count. Building on a recent mathematical framework, the approach presented herein refines QHARS device concepts by considering designs incorporating pseudofractals (which may be expressed as star-mesh transformations). To under…

A Deterministic Model of Free Will
Tim Palmer
https://arxiv.org/abs/2506.21553 https://arxiv.org/pdf/2506.21553

A Deterministic Model of Free Will
The issue of whether we make decisions freely has vexed philosophers for millennia, Resolving this is vital for solving a diverse range of problems, from the physiology of how the brain makes decisions (and how we assign moral responsibility to those decisions) to the interpretation of experiments on entangled quantum particles. A deterministic model of free will is developed, based on two concepts. The first generalises the notion of initialisation of nonlinear systems where information cascad…

Am reading a bit about nations vs states & also about minorities in Ukraine, mentally comparing a couple of books.
It's early days but I'm realising that my concepts of what is a nation, what is a minority etc are maybe very different to concepts used in Europe??
My reaction to paragraphs about having multiple religions/languages in one nation is: yes, that's normal, mate.

Proton Pressure: A Simplified Model
Julliana Marinho Paszko, Mauro Rog\'erio Cosentino
https://arxiv.org/abs/2508.19266 https://arxiv.org/pdf/2508.1926…

Proton Pressure: A Simplified Model
In this work, the authors present a simplified method for determining proton pressure, based on concepts from statistical mechanics, quantum chromodynamics - specifically asymptotic freedom of quarks - and other well-established physical concepts. The result obtained for the proton pressure was $0.3570\times10^{35}$ Pa, which is consistent with recently reported experimental data.

Mean-Variance Optimization and Algorithm for Finite-Horizon Markov Decision Processes
Li Xia, Zhihui Yu
https://arxiv.org/abs/2507.22327 https://arxiv.org/…

Mean-Variance Optimization and Algorithm for Finite-Horizon Markov Decision Processes
Multi-period mean-variance optimization is a long-standing problem, caused by the failure of dynamic programming principle. This paper studies the mean-variance optimization in a setting of finite-horizon discrete-time Markov decision processes (MDPs), where the objective is to maximize the combined metrics of mean and variance of the accumulated rewards at terminal stage. By introducing the concepts of pseudo mean and pseudo variance, we convert the original mean-variance MDP to a bilevel MDP,…

Aligning Core Aspects: Improving Vulnerability Proof-of-Concepts via Cross-Source Insights
Lingxiao Wang, Wenjing Dang, Mengyao Zhang, Yue Wang, Xianzong Wu, Sen Chen
https://arxiv.org/abs/2508.18109

Aligning Core Aspects: Improving Vulnerability Proof-of-Concepts via Cross-Source Insights
For vulnerabilities, Proof-of-Concept (PoC) plays an irreplaceable role in demonstrating the exploitability. PoC reports may include critical information such as specific usage, test platforms, and more, providing essential insights for researchers. However, in reality, due to various PoC templates across PoC platforms, PoC reports extensively suffer from information deficiency, leading the suboptimal quality and limited usefulness. Fortunately, we found that information deficiency of PoC repor…

SUB: Benchmarking CBM Generalization via Synthetic Attribute Substitutions
Jessica Bader, Leander Girrbach, Stephan Alaniz, Zeynep Akata
https://arxiv.org/abs/2507.23784 https:/…

SUB: Benchmarking CBM Generalization via Synthetic Attribute Substitutions
Concept Bottleneck Models (CBMs) and other concept-based interpretable models show great promise for making AI applications more transparent, which is essential in fields like medicine. Despite their success, we demonstrate that CBMs struggle to reliably identify the correct concepts under distribution shifts. To assess the robustness of CBMs to concept variations, we introduce SUB: a fine-grained image and concept benchmark containing 38,400 synthetic images based on the CUB dataset. To create…

Planckian charged black holes and their cosmological ramifications
Athanasios G. Tzikas
https://arxiv.org/abs/2507.21344 https://arxiv.org/pdf/2507.21344…

Planckian charged black holes and their cosmological ramifications
The application of nonlinear electrodynamics at high energy scales has led to a variety of interesting phenomena in recent years, particularly within the context of non-singular spacetime geometries. Additionally, it is postulated that gravity near the Planck scale is governed by a minimal cut-off length, which acts as a renormalization scale against ultraviolet pathologies. Within this framework, we combine both concepts by introducing modifications to the electric and matter sectors of a blac…

LLMSymGuard: A Symbolic Safety Guardrail Framework Leveraging Interpretable Jailbreak Concepts
Darpan Aswal, C\'eline Hudelot
https://arxiv.org/abs/2508.16325 https://

LLMSymGuard: A Symbolic Safety Guardrail Framework Leveraging Interpretable Jailbreak Concepts
Large Language Models have found success in a variety of applications; however, their safety remains a matter of concern due to the existence of various types of jailbreaking methods. Despite significant efforts, alignment and safety fine-tuning only provide a certain degree of robustness against jailbreak attacks that covertly mislead LLMs towards the generation of harmful content. This leaves them prone to a number of vulnerabilities, ranging from targeted misuse to accidental profiling of us…

Marked multi-colorings and marked chromatic polynomials of hypergraphs and subspace arrangements
Chaithra P, Shushma Rani, R. Venkatesh
https://arxiv.org/abs/2507.20847 https://…

Marked multi-colorings and marked chromatic polynomials of hypergraphs and subspace arrangements
We introduce the concepts of marked multi-colorings, marked chromatic polynomials, and marked (multivariate) independence series for hypergraphs. We show that the coefficients of the q-th power of the marked independence series of a hypergraph coincide with its marked chromatic polynomials in q, thereby generalizing a corresponding result for graphs established in Chaithra et al. 2025 (arXiv:2503.11230). These notions are then naturally extended to subspace arrangements. In particular, we prove…

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
Ruichen Zhang, Guangyuan Liu, Yinqiu Liu, Changyuan Zhao, Jiacheng Wang, Yunting Xu, Dusit Niyato, Jiawen Kang, Yonghui Li, Shiwen Mao, Sumei Sun, Xuemin Shen, Dong In Kim
https://arxiv.org/abs/2508.18725

Toward Edge General Intelligence with Agentic AI and Agentification: Concepts, Technologies, and Future Directions
The rapid expansion of sixth-generation (6G) wireless networks and the Internet of Things (IoT) has catalyzed the evolution from centralized cloud intelligence towards decentralized edge general intelligence. However, traditional edge intelligence methods, characterized by static models and limited cognitive autonomy, fail to address the dynamic, heterogeneous, and resource-constrained scenarios inherent to emerging edge networks. Agentic artificial intelligence (Agentic AI) emerges as a transf…

Data Visualization for Improving Financial Literacy: A Systematic Review
Meng Du, Robert Amor, Kwan-Liu Ma, Burkhard C. W\"unsche
https://arxiv.org/abs/2506.20901

Data Visualization for Improving Financial Literacy: A Systematic Review
Financial literacy empowers individuals to make informed and effective financial decisions, improving their overall financial well-being and security. However, for many people understanding financial concepts can be daunting and only half of US adults are considered financially literate. Data visualization simplifies these concepts, making them accessible and engaging for learners of all ages. This systematic review analyzes 37 research papers exploring the use of data visualization and visual …

AI-Driven Media & Synthetic Knowledge: Rethinking Society in Generative Futures
Katalin Feher
https://arxiv.org/abs/2507.19877 https://arxiv.org/pdf/25…

AI-Driven Media & Synthetic Knowledge: Rethinking Society in Generative Futures
Generative AI is not just a technological lea- it is a societal stress test, reshaping trust, identity, equity, and authorship. This exploratory PhD seminar examined emerging academic trends in AI-driven synthetic media and worlds, emphasizing ethical risks and societal implications. In Part One, students explored core concepts such as generative AI, fake media, and synthetic knowledge production. In Part Two, they critically engaged with these challenges, producing actionable insights. The two…

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts
Elena Ancona, Roman Ya. Kezerashvili, Savino Longo
https://arxiv.org/abs/2506.17732

Feasibility study of a mission to Sedna -- Nuclear propulsion and advanced solar sailing concepts
Exploring the outer reaches of the Solar System presents significant propulsion and mission design challenges. This study assesses the feasibility of a mission to Sedna using two advanced propulsion concepts: the Direct Fusion Drive (DFD) rocket engine, based on D-$^{3}$He thermonuclear fusion, and a solar sail utilizing thermal desorption of its coating for propulsion. Both are evaluated for a one-way Earth-to-Sedna mission; however, due to the different performances the DFD would enable orbit…

Comparing Visual Qubit Representations in Quantum Education: The Bloch sphere Enhances Task Efficiency
Linda Qerimi, Sarah Malone, Eva Rexigel, Jochen Kuhn, Stefan K\"uchemann
https://arxiv.org/abs/2507.21721

Comparing Visual Qubit Representations in Quantum Education: The Bloch sphere Enhances Task Efficiency
Visual-graphical qubit representations offer a means to introduce abstract quantum concepts - such as quantum state, superposition, or measurement - in an accessible manner, particularly for learners with low prior knowledge. Building on a previous expert rating of mechanisms of qubit representations, this study compared two representations - Bloch sphere and Quantum Bead - in terms of learning outcomes, task performance, cognitive load, and mid-term retention. The study was conducted with N=14…

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
Jiacheng Wang, Changyuan Zhao, Zehui Xiong, Tao Xiang, Dusit Niyato, Xianbin Wang, Shiwen Mao, Dong In Kim
https://arxiv.org/abs/2507.19837

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications
AI-enabled wireless communications have attracted tremendous research interest in recent years, particularly with the rise of novel paradigms such as low-altitude integrated sensing and communication (ISAC) networks. Within these systems, feature engineering plays a pivotal role by transforming raw wireless data into structured representations suitable for AI models. Hence, this paper offers a comprehensive investigation of feature engineering techniques in AI-driven wireless communications. Sp…

Computation of Interpolants for Description Logic Concepts in Hard Cases
Jean Christoph Jung, J\k{e}drzej Ko{\l}odziejski, Frank Wolter
https://arxiv.org/abs/2507.15689

Computation of Interpolants for Description Logic Concepts in Hard Cases
While the computation of Craig interpolants for description logics (DLs) with the Craig Interpolation Property (CIP) is well understood, very little is known about the computation and size of interpolants for DLs without CIP or if one aims at interpolating concepts in a weaker DL than the DL of the input ontology and concepts. In this paper, we provide the first elementary algorithms computing (i) ALC-interpolants between ALC-concepts under ALCH-ontologies and (ii) ALC-interpolants between ALCQ…

Semi-local observables, edge modes and quantum reference frames in quantum electromagnetism: an algebraic approach
Christopher J. Fewster, Daan W. Janssen, Kasia Rejzner
https://arxiv.org/abs/2508.20939

Semi-local observables, edge modes and quantum reference frames in quantum electromagnetism: an algebraic approach
Boundaries and corners of spacetime play a vital role in understanding physical concepts including entanglement entropy, the infrared problem in QFT and quantum gravity. Standard local quantum field theory struggles to accommodate such boundary-sensitive observables. In this paper we develop an algebraic framework for \emph{semi-local quantum electromagnetism} on finite Cauchy lenses: a class of compact spacetimes with boundaries and corner. At the classical level, we establish a decomposition …

As I'm learning Dutch, I'm reminded that the idea that there are people who believe that the bible is to be taken literally. The idea that a several hundred year old translation of a collection of texts in multiple languages, that were themselves translated multiple times between languages, before the whole thing was translated to Latin, then being translated to English, could somehow perfectly reflect the original text... Yeah, it's only possible to believe that if you have no idea how languages work and have never learned another language.
Like, just from linguistic drift alone if the bible were written in King James English you're losing *so* much context. But Hebrew, Aramaic, and Greek translated to Latin, then to English, then to English again?
There are so many things that erg can't be translated, even as a beginner. Dutch and English are two of the closest languages that exist, they're both Germanic languages and they're the closest to each other (other than Friesian). You can't really be much closer, and yet, there are so many things you can't mutually represent. Hebrew and Latin, Aramaic and Latin, Latin and English, Greek and English, these aren't even the same families at all... They're extremely distant. There's absolutely no way to represent concepts from one to another without another book's worth of explanation.
And that ignores all the cultural context, which is mostly lost and a library and decade of education to get the stuff that we *do* know.
Only monolingual Americans could come up with an idea so incredibly asinine.

Transient Concepts in Streaming Graphs
Aida Sheshbolouki, M. Tamer Ozsu
https://arxiv.org/abs/2506.17451 https://arxiv.org/pdf/2506.1…

Transient Concepts in Streaming Graphs
Concept Drift (CD) occurs when a change in a hidden context can induce changes in a target concept. CD is a natural phenomenon in non-stationary settings such as data streams. Understanding, detection, and adaptation to CD in streaming data is (i) vital for effective and efficient analytics as reliable output depends on adaptation to fresh input, (ii) challenging as it requires efficient operations as well as effective performance evaluations, and (iii) impactful as it applies to a variety of u…

"Reflections on CoLIS 2025" [International Conference on Concepts of Library and Information Science] https://libraryblogs.is.ed.ac.uk/datablog/2025/07/16/reflections-on-colis-2025/

Attention is also needed for form design
B. Sankar, Dibakar Sen
https://arxiv.org/abs/2508.19708 https://arxiv.org/pdf/2508.19708

Attention is also needed for form design
Conventional product design is a cognitively demanding process, limited by its time-consuming nature, reliance on subjective expertise, and the opaque translation of inspiration into tangible concepts. This research introduces a novel, attention-aware framework that integrates two synergistic systems: EUPHORIA, an immersive Virtual Reality environment using eye-tracking to implicitly capture a designer's aesthetic preferences, and RETINA, an agentic AI pipeline that translates these implicit pr…

Besov spaces associated with the Harmonic oscillator
Reika Fukuizumi, Tsukasa Iwabuchi
https://arxiv.org/abs/2508.20436 https://arxiv.org/pdf/2508.20436

Besov spaces associated with the Harmonic oscillator
The Besov space associated with the harmonic oscillator is introduced and thoroughly explored in this paper. It provides a comprehensive summary of the fundamental concepts of the Besov spaces, their embedding properties, bilinear estimates, and related topics.

Towards a Large Physics Benchmark
Kristian G. Barman, Sascha Caron, Faegheh Hasibi, Eugene Shalugin, Yoris Marcet, Johannes Otte, Henk W. de Regt, Merijn Moody
https://arxiv.org/abs/2507.21695

Towards a Large Physics Benchmark
We introduce a benchmark framework developed by and for the scientific community to evaluate, monitor and steer large language model development in fundamental physics. Building on philosophical concepts of scientific understanding and creativity, we develop a scoring system in which each question is scored by an expert for its correctness, difficulty, and surprise. The questions are of three forms: (i) multiple-choice questions for conceptual understanding, (ii) analytical problems requiring m…

Introduction to AT Protocol – mackuba.eu https://mackuba.eu/2025/08/20/introduction-to-atproto/

Introduction to AT Protocol
Walkthrough of the various parts and concepts in Bluesky's AT Protocol (ATProto), the types of servers involved and how it all fits together

Sources: Disney is on the hunt for original movie concepts to lure young men aged 13-28 back to the brand, as audiences dwindle for the superhero genre (Matt Donnelly/Variety)
https://variety.com/2025/film/news/disney-marvel-lucasfilm-gen-z-1236494681/…

Disney Urgently Seeking Movies for Gen Z Men
As Marvel and Lucasfilm stumble, Disney hopes originals will lure Gen Z audiences.

Topological photonics in nanoscaled systems with far field radiation and polarization singularities
Grazia Salerno
https://arxiv.org/abs/2508.20487 https://

Topological photonics in nanoscaled systems with far field radiation and polarization singularities
Topology is a powerful framework for controlling and manipulating light, minimizing detrimental perturbations on the photonic properties. Combining nanophotonics with topological concepts presents opportunities for both fundamental physics and technological applications. Although most topological photonic realizations have been inspired by condensed-matter analogue models, new topological ideas have just begun to be realized at the nanoscale. Nanophotonics is characterized by subtle phenomena t…

The Autonomous Data Language -- Concepts, Design and Formal Verification
Tom T. P. Franken, Thomas Neele, Jan Friso Groote
https://arxiv.org/abs/2506.19457

The Autonomous Data Language -- Concepts, Design and Formal Verification
Nowadays, the main advances in computational power are due to parallelism. However, most parallel languages have been designed with a focus on processors and threads. This makes dealing with data and memory in programs hard, which distances the implementation from its original algorithm. We propose a new paradigm for parallel programming, the data-autonomous paradigm, where computation is performed by autonomous data elements. Programs in this paradigm are focused on making the data collaborate…

How Well Do LLMs Predict Prerequisite Skills? Zero-Shot Comparison to Expert-Defined Concepts
Ngoc Luyen Le, Marie-H\'el\`ene Abel
https://arxiv.org/abs/2507.18479 https://

How Well Do LLMs Predict Prerequisite Skills? Zero-Shot Comparison to Expert-Defined Concepts
Prerequisite skills - foundational competencies required before mastering more advanced concepts - are important for supporting effective learning, assessment, and skill-gap analysis. Traditionally curated by domain experts, these relationships are costly to maintain and difficult to scale. This paper investigates whether large language models (LLMs) can predict prerequisite skills in a zero-shot setting, using only natural language descriptions and without task-specific fine-tuning. We introdu…

Tangent Lie Algebras of Automorphism Groups of Free Algebras
Ivan Shestakov, Ualbai Umirbaev
https://arxiv.org/abs/2507.20486 https://arxiv.org/pdf/2507.20…

Tangent Lie Algebras of Automorphism Groups of Free Algebras
We study an analogue of the Andreadakis-Johnson filtration for automorphism groups of free algebras and introduce the notion of tangent Lie algebras for certain automorphism groups, defined as subalgebras of the Lie algebra of derivations. We show that, for many classical varieties of algebras, the tangent Lie algebra is contained in the Lie algebra of derivations with constant divergence. We also introduce the concepts of approximately tame and absolutely wild automorphisms of free algebras in…

Ontological Definition of Seamless Digital Engineering Based on ISO/IEC 25000-Series SQuaRE Product Quality Model
James S. Wheaton, Daniel R. Herber
https://arxiv.org/abs/2507.17171

Ontological Definition of Seamless Digital Engineering Based on ISO/IEC 25000-Series SQuaRE Product Quality Model
Since the introduction of Digital Engineering (DE) as a well-defined concept in 2018, organizations and industry groups have been working to interpret the DE concepts to establish consistent meta-models of those interrelated concepts for integration into their DE processes and tools. To reach the breadth and depth of DE concept definitions, the interpretation of international standard sources is necessary, including ISO/IEC/IEEE 15288, 24765, 42000-series, 15408, 15206, 27000-series, and 25000-…

Univariate amenable functions
Carlos Beltr\'an
https://arxiv.org/abs/2507.17404 https://arxiv.org/pdf/2507.17404

Univariate amenable functions
The concepts of amenable and compatible functions have been introduced in a recent work, in order to state precise mathematical theorems that guarantee that a backward stable algorithm is also forward stable, and that the composition of two stable algorithms results in an stable algorithm. In this work, we elaborate in this theory for univariate real analytic functions, providing simple tests for both concepts and producing tables for a number of elementary functions which are or fail to be ame…

Strong Correlations, Green's Function Zeros and Topological Transitions in Orbital-Symmetry-Controlled Chemical Reactions
Ziren Xie, Amir Mirzanejad, Lukas Muechler
https://arxiv.org/abs/2506.18984

Strong Correlations, Green's Function Zeros and Topological Transitions in Orbital-Symmetry-Controlled Chemical Reactions
We integrate concepts from topological band theory and strong-correlation physics with the principle of orbital symmetry conservation, which characterizes reactions as symmetry allowed or forbidden based on whether molecular orbitals cross along the reaction coordinate. Using a $4π$ electrocyclization as an example, we show how Green's functions generalize the concepts of symmetry allowed and symmetry forbidden reactions even in the presence of strong multi-reference correlations. We demonstra…

Weird flex, both @… and @… are mentioned on "Introduction to AT Protocol" https://

Introduction to AT Protocol
Walkthrough of the various parts and concepts in Bluesky's AT Protocol (ATProto), the types of servers involved and how it all fits together

For the first time AI systems crossed the gold-medal scoring threshold at the International Mathematical Olympiad for high-school students.
Both Google and OpenAI's models solved five out of six problems,
-- achieving the result using general-purpose “reasoning” models that processed mathematical concepts using natural language, in contrast to the previous approaches used by AI firms.
OpenAI’s breakthrough was achieved with a new experimental model centered on massively …

Series C, Episode 05 - The Harvest of Kairos
JARVIK: I shall expect both courage and enterprise.
SHAD: You will have both, sir.
SERVALAN: Such old-fashioned concepts, Jarvik. Are they really necessary?
JARVIK: With machines, no. With men, yes.
https://blake.torpidity.net/m/305/258

Symmetry Classification of Magnetic Orders and Emergence of Spin-Orbit Magnetism
Yuntian Liu, Xiaobing Chen, Yutong Yu, Qihang Liu
https://arxiv.org/abs/2506.20739

Symmetry Classification of Magnetic Orders and Emergence of Spin-Orbit Magnetism
Magnetism, a fundamental concept predating condensed matter physics, has achieved significant advancements in recent decades, driven by its potential for next-generation storage devices. Meanwhile, the classification of magnetic orders, even for the most fundamental concepts like ferromagnetism (FM) and antiferromagnetism (AFM), has encountered unprecedented challenges since the discovery of unconventional magnets and advancements in antiferromagnetic spintronics. Here, we present a rigorous cl…

Tissue Concepts v2: a Supervised Foundation Model for whole slide images
Till Nicke, Daniela Scharcherer, Jan Raphael Sch\"afer, Natalia Artysh, Antje Prasse, Andr\'e Homeyer, Andrea Schenk, Henning H\"ofener, Johannes Lotz
https://arxiv.org/abs/2507.05742

Tissue Concepts v2: a Supervised Foundation Model for whole slide images
Foundation models (FMs) are transforming the field of computational pathology by offering new approaches to analyzing histopathology images. Typically relying on weeks of training on large databases, the creation of FMs is a resource-intensive process in many ways. In this paper, we introduce the extension of our supervised foundation model, Tissue Concepts, to whole slide images, called Tissue Concepts v2 (TCv2), a supervised foundation model for whole slide images to address the issue above. …

Wow, how did I sleep on the catalog of neat small pen-and-paper RPGs on Itch? So many interesting concepts there. Particularly stuck on "They should have sent a poet", which self-describes as "a solo journalling game about searching alone for the impossible among the stars, and desperately, hopefully, unfathomably holding on to your mission and humanity." Seems like a really cool concept, definitely got to try this out, as story-writing and worldbuilding is catnip to me w…

They Should Have Sent a Poet by Telling Games
A solo journalling game about searching among the stars, and desperately holding on to your mission and humanity.

Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications
Naoki Ishikawa, Giuseppe Thadeu Freitas de Abreu, Petar Popovski, Robert W. Heath Jr
https://arxiv.org/abs/2506.20863

Quantum-Accelerated Wireless Communications: Concepts, Connections, and Implications
Quantum computing is poised to redefine the algorithmic foundations of communication systems. While quantum superposition and entanglement enable quadratic or exponential speedups for specific problems, identifying use cases where these advantages yield engineering benefits is, however, still nontrivial. This article presents the fundamentals of quantum computing in a style familiar to the communications society, outlining the current limits of fault-tolerant quantum computing and uncovering a …

Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks
Pietro Giuseppe Fr\'e, Federico Milanesio, Guido Sanguinetti, Matteo Santoro
https://arxiv.org/abs/2507.16871

Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks
Recent work has identified non-compact symmetric spaces U/H as a promising class of homogeneous manifolds to develop a geometrically consistent theory of neural networks. An initial implementation of these concepts has been presented in a twin paper under the moniker of Cartan Neural Networks, showing both the feasibility and the performance of these geometric concepts in a machine learning context. The current paper expands on the mathematical structures underpinning Cartan Neural Networks, de…

Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump's Presidential Campaigns
Ilias Chalkidis, Stephanie Brandl, Paris Aslanidis
https://arxiv.org/abs/2507.19303

Identifying Fine-grained Forms of Populism in Political Discourse: A Case Study on Donald Trump's Presidential Campaigns
Large Language Models (LLMs) have demonstrated remarkable capabilities across a wide range of instruction-following tasks, yet their grasp of nuanced social science concepts remains underexplored. This paper examines whether LLMs can identify and classify fine-grained forms of populism, a complex and contested concept in both academic and media debates. To this end, we curate and release novel datasets specifically designed to capture populist discourse. We evaluate a range of pre-trained (larg…

Replaced article(s) found for stat.ML. https://arxiv.org/list/stat.ML/new
[2/2]:
- Graph Neural Networks in Supply Chain Analytics and Optimization: Concepts, Perspectives, Dataset...
Azmine Toushik Wasi, MD Shafikul Islam, Adipto Raihan Akib, Mahathir Mohammad Bappy

Quantum Beatings in Optical Cavities
Ishaan Ganti, Jianshu Cao
https://arxiv.org/abs/2507.17339 https://arxiv.org/pdf/2507.17339

Quantum Beatings in Optical Cavities
Cavity polaritons, quasiparticles formed by coherent light-matter coupling, are at the heart of fundamental concepts of quantum optics. The quintessential signature of this coherent coupling is the Rabi oscillation, which results from the neglect of the counter-rotating-wave (CRW) effect in the weak-coupling regime. The goal of this letter is to predict resonant beatings that envelop the Rabi oscillation on the second or higher excitation manifold. These polariton beatings arise from the CRW te…

Information Field Theory -- Concepts, Applications, and AI-Perspective
Torsten En{\ss}lin
https://arxiv.org/abs/2508.17269 https://arxiv.org/pdf/2508.17269…

Information Field Theory -- Concepts, Applications, and AI-Perspective
Information field theory (IFT) is the application of probabilistic reasoning to fields. Physical fields are mathematical functions over continuous spaces that exhibit certain properties of regularity, such as limited variance and finite gradients. Inferring a field from an observational dataset should exploit these regularities. However, the finite number of constraints that the data provides is insufficient to determine the infinite number of degrees of freedom of a field. IFT enables us to de…

Bridging the Gap in Vision Language Models in Identifying Unsafe Concepts Across Modalities
Yiting Qu, Michael Backes, Yang Zhang
https://arxiv.org/abs/2507.11155

Bridging the Gap in Vision Language Models in Identifying Unsafe Concepts Across Modalities
Vision-language models (VLMs) are increasingly applied to identify unsafe or inappropriate images due to their internal ethical standards and powerful reasoning abilities. However, it is still unclear whether they can recognize various unsafe concepts when presented in different modalities, such as text and images. To address this, we first compile the UnsafeConcepts dataset, featuring 75 unsafe concepts, i.e., ``Swastika,'' ``Sexual Harassment,'' and ``Assaults,'' along with associated 1.5K im…

Boson peak in covalent network glasses: Isostaticity and marginal stability
Hideyuki Mizuno, Tatsuya Mori, Giacomo Baldi, Emi Minamitani
https://arxiv.org/abs/2508.20481 https:/…

Boson peak in covalent network glasses: Isostaticity and marginal stability
The boson peak (BP) stands as a key feature in understanding glasses and amorphous materials. It directly underlies their anomalous material properties, including thermal behaviors such as excess specific heat and low thermal conductivity, as well as mechanical characteristics such as nonaffine elasticity and fragile plasticity. Despite its importance, understanding of the BP remains limited in covalent network glasses. The most promising concepts are isostaticity and marginal stability, which …

KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks
Daniil Karol, Elizaveta Artser, Ilya Vlasov, Yaroslav Golubev, Hieke Keuning, Anastasiia Birillo
https://arxiv.org/abs/2506.21266

KOALA: a Configurable Tool for Collecting IDE Data When Solving Programming Tasks
Collecting data of students solving programming tasks is incredibly valuable for researchers and educators. It allows verifying that the students correctly apply the features and concepts they are taught, or finding students' misconceptions. However, existing data collection tools have limitations, e.g., no control over the granularity of the collected code, not collecting the specific events of the programming environment used, and overall being hard to configure. To overcome these limitatio…

Towards direct nonlinear compression of energetic sub-nanosecond pulses to the ultrafast regime
Gaspard Beaufort, Nayla Jimenez, Gunnar Arisholm, Victor Hariton, Ayhan Tajalli, Ingmar Hartl, Anne-Lise Viotti, Marcus Seidel
https://arxiv.org/abs/2507.20883

Towards direct nonlinear compression of energetic sub-nanosecond pulses to the ultrafast regime
Applications of terawatt-class lasers can enormously benefit from pulse trains with kHz repetition rates. The associated unprecedented combinations of peak and average powers require the development of new concepts for scalable ultrashort pulse generation. We propose using multi-mirror multi-pass cells as a compact and cost-efficient solution for the direct post-compression of sub-nanosecond pulses into the femtosecond regime. We simulate spectral broadening of 100-mJ, 300-ps pulses to a sub-ps…

Inference Time Debiasing Concepts in Diffusion Models
Lucas S. Kupssinsk\"u, Marco N. Bochernitsan, Jordan Kopper, Ot\'avio Parraga, Rodrigo C. Barros
https://arxiv.org/abs/2508.14933

Inference Time Debiasing Concepts in Diffusion Models
We propose DeCoDi, a debiasing procedure for text-to-image diffusion-based models that changes the inference procedure, does not significantly change image quality, has negligible compute overhead, and can be applied in any diffusion-based image generation model. DeCoDi changes the diffusion process to avoid latent dimension regions of biased concepts. While most deep learning debiasing methods require complex or compute-intensive interventions, our method is designed to change only the inferen…

Kullback-Leibler Potential for Non-Ergodic Replication Dynamics:An Information-Theoretic Second Law
Tatsuaki Tsuruyama
https://arxiv.org/abs/2508.19894 https://

Kullback-Leibler Potential for Non-Ergodic Replication Dynamics:An Information-Theoretic Second Law
This study aims to quantify and visualize the degradation of fidelity (information degradation) that inevitably accompanies the replication of information within the framework of information thermodynamics and to propose an information-theoretic formulation of the second law based on this phenomenon. While previous research in information thermodynamics has focused on the thermodynamic costs associated with information "erasure'' or "measurement'' through concepts such as Landauer's principle a…

Enriching Moral Perspectives on AI: Concepts of Trust amongst Africans
Lameck Mbangula Amugongo, Nicola J Bidwell, Joseph Mwatukange
https://arxiv.org/abs/2508.14116 https://

Enriching Moral Perspectives on AI: Concepts of Trust amongst Africans
The trustworthiness of AI is considered essential to the adoption and application of AI systems. However, the meaning of trust varies across industry, research and policy spaces. Studies suggest that professionals who develop and use AI regard an AI system as trustworthy based on their personal experiences and social relations at work. Studies about trust in AI and the constructs that aim to operationalise trust in AI (e.g., consistency, reliability, explainability and accountability). However,…

Insights into User Interface Innovations from a Design Thinking Workshop at deRSE25
Maximilian Frank, Simon Lund
https://arxiv.org/abs/2508.18784 https://a…

Insights into User Interface Innovations from a Design Thinking Workshop at deRSE25
Large Language Models have become widely adopted tools due to their versatile capabilities, yet their user interfaces remain limited, often following rigid, linear interaction paradigms. In this paper, we present insights from a design thinking workshop held at the deRSE25 conference aiming at collaboratively developing innovative user interface concepts for LLMs. During the workshop, participants identified common use cases, evaluated the strengths and shortcomings of current LLM interfaces, a…

Between Markov and restriction: Two more monads on categories for relations
Cipriano Junior Cioffo, Fabio Gadducci, Davide Trotta
https://arxiv.org/abs/2508.20054 https://

Between Markov and restriction: Two more monads on categories for relations
The study of categories abstracting the structural properties of relations has been extensively developed over the years, resulting in a rich and diverse body of work. A previous paper offered a survey providing a modern and comprehensive presentation of these ``categories for relations'' as instances of gs-monoidal categories, showing how they arise as Kleisli categories of suitable symmetric monoidal monads. The end result was a taxonomy that organised numerous related concepts in the literat…

Locality-aware Concept Bottleneck Model
Sujin Jeon, Hyundo Lee, Eungseo Kim, Sanghack Lee, Byoung-Tak Zhang, Inwoo Hwang
https://arxiv.org/abs/2508.14562 https://

Locality-aware Concept Bottleneck Model
Concept bottleneck models (CBMs) are inherently interpretable models that make predictions based on human-understandable visual cues, referred to as concepts. As obtaining dense concept annotations with human labeling is demanding and costly, recent approaches utilize foundation models to determine the concepts existing in the images. However, such label-free CBMs often fail to localize concepts in relevant regions, attending to visually unrelated regions when predicting concept presence. To th…

Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation - A Systematic Literature Review
Eduardo Vyhmeister, Bastien Pietropaoli, Alejando Martinez Molina, Montserrat Gonzalez-Ferreiro, Gabriel Gonzalez-Castane, Jordi Arjona Aroca, Andrea Visentin
https://arxiv.org/abs/2508.18331

Metrics, KPIs, and Taxonomy for Data Valuation and Monetisation - A Systematic Literature Review
Data valuation and data monetisation are complex subjects but essential to most organisations today. Unfortunately, they still lack standard procedures and frameworks for organisations to follow. In this survey, we introduce the reader to the concepts by providing the definitions and the background required to better understand data, monetisation strategies, and finally metrics and KPIs used in these strategies. We have conducted a systematic literature review on metrics and KPIs used in data v…

Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
Felipe Olivares, Massimiliano Zanin
https://arxiv.org/abs/2507.20927 h…

Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
Within the continuous endeavour of improving the efficiency and resilience of air transport, the trend of using concepts and metrics from statistical physics has recently gained momentum. This scientific discipline, which integrates elements from physics and statistics, aims at extracting knowledge about the microscale rules governing a (potentially complex) system when only its macroscale is observable. Translated to air transport, this entails extracting information about how individual opera…

Knowing or Guessing? Robust Medical Visual Question Answering via Joint Consistency and Contrastive Learning
Songtao Jiang, Yuxi Chen, Sibo Song, Yan Zhang, Yeying Jin, Yang Feng, Jian Wu, Zuozhu Liu
https://arxiv.org/abs/2508.18687

Knowing or Guessing? Robust Medical Visual Question Answering via Joint Consistency and Contrastive Learning
In high-stakes medical applications, consistent answering across diverse question phrasings is essential for reliable diagnosis. However, we reveal that current Medical Vision-Language Models (Med-VLMs) exhibit concerning fragility in Medical Visual Question Answering, as their answers fluctuate significantly when faced with semantically equivalent rephrasings of medical questions. We attribute this to two limitations: (1) insufficient alignment of medical concepts, leading to divergent reasoni…

Concepts for Composing Finite Element Function Space Bases
Christian Engwer, Carsten Gr\"aser, Steffen M\"uthing, Simon Praetorius, Oliver Sander
https://arxiv.org/abs/2508.10125

Concepts for Composing Finite Element Function Space Bases
Finite Element discretizations of coupled multi-physics partial differential equation models require the handling of composed function spaces. In this paper we discuss software concepts and abstractions to handle the composition of function spaces, based on a representation of product spaces as trees of simpler bases. From this description, many different numberings of degrees of freedom by multi-indices can be derived in a natural way, allowing to adapt the function spaces to very different da…

GIFT: Gradient-aware Immunization of diffusion models against malicious Fine-Tuning with safe concepts retention
Amro Abdalla, Ismail Shaheen, Dan DeGenaro, Rupayan Mallick, Bogdan Raita, Sarah Adel Bargal
https://arxiv.org/abs/2507.13598

GIFT: Gradient-aware Immunization of diffusion models against malicious Fine-Tuning with safe concepts retention
We present \textbf{GIFT}: a \textbf{G}radient-aware \textbf{I}mmunization technique to defend diffusion models against malicious \textbf{F}ine-\textbf{T}uning while preserving their ability to generate safe content. Existing safety mechanisms like safety checkers are easily bypassed, and concept erasure methods fail under adversarial fine-tuning. GIFT addresses this by framing immunization as a bi-level optimization problem: the upper-level objective degrades the model's ability to represent ha…

Introduction to Regularization and Learning Methods for Inverse Problems
Danielle Bednarski, Tim Roith
https://arxiv.org/abs/2508.18178 https://arxiv.org/p…

Introduction to Regularization and Learning Methods for Inverse Problems
These lecture notes evolve around mathematical concepts arising in inverse problems. We start by introducing inverse problems through examples such as differentiation, deconvolution, computed tomography and phase retrieval. This then leads us to the framework of well-posedness and first considerations regarding reconstruction and inversion approaches. The second chapter then first deals with classical regularization theory of inverse problems in Hilbert spaces. After introducing the pseudo-inve…

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
David Chanin, Adri\`a Garriga-Alonso
https://arxiv.org/abs/2508.16560 https://

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders
Sparse Autoencoders (SAEs) extract features from LLM internal activations, meant to correspond to single concepts. A core SAE training hyperparameter is L0: how many features should fire per token on average. Existing work compares SAE algorithms using sparsity--reconstruction tradeoff plots, implying L0 is a free parameter with no single correct value. In this work we study the effect of L0 on BatchTopK SAEs, and show that if L0 is not set precisely, the SAE fails to learn the underlying featu…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/4]:
- Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution
Park, Lai, Hayakawa, Takida, Murata, Liao, Choi, Cheuk, Koo, Mitsufuji

Agile and Student-Centred Teaching of Agile/Scrum Concepts
Maria Spichkova
https://arxiv.org/abs/2506.14369 https://arxiv.org/pdf/250…

Agile and Student-Centred Teaching of Agile/Scrum Concepts
In this paper, we discuss our experience in designing and teaching a course on Software Engineering Project Management, where the focus is on Agile/Scrum development and Requirement Engineering activities. The course has undergone fundamental changes since 2020 to make the teaching approach more student-centred and flexible. As many universities abandoned having face-to-face exams at the end of the semester, authentic assessments now play an even more important role than before. This makes asse…

Do Students Learn Better Together? Teaching Design Patterns and the OSI Model with the Aronson Method
Daniel San Martin, Carlos Manzano, Valter Vieira de Camargo
https://arxiv.org/abs/2508.16770

Do Students Learn Better Together? Teaching Design Patterns and the OSI Model with the Aronson Method
Abstract concepts like software design patterns and the OSI model often pose challenges for engineering students, and traditional methods may fall short in promoting deep understanding and individual accountability. This study explores the use of the Aronson Jigsaw method to enhance learning and engagement in two foundational computing topics. The intervention was applied to two 2025 cohorts, with student progress measured using a Collaborative Learning Index derived from formative assessments.…

Advanced For-Loop for QML algorithm search
FuTe Wong
https://arxiv.org/abs/2506.18260 https://arxiv.org/pdf/2506.18260

Advanced For-Loop for QML algorithm search
This paper introduces an advanced framework leveraging Large Language Model-based Multi-Agent Systems (LLMMA) for the automated search and optimization of Quantum Machine Learning (QML) algorithms. Inspired by Google DeepMind's FunSearch, the proposed system works on abstract level to iteratively generates and refines quantum transformations of classical machine learning algorithms (concepts), such as the Multi-Layer Perceptron, forward-forward and backpropagation algorithms. As a proof of conc…

An efficient co-simulation and control approach to tackle complex multi-domain energetic systems: concepts and applications of the PEGASE platform
Mathieu Vallee (DTCH), Roland Baviere (DTCH), Val\'erie Seguin (DTCH), Val\'ery Vuillerme (DTCH), Nicolas Lamaison (DTCH), Michael Nikhil Descamps (DTCH), Antoine Aurousseau (DTCH)
https://

An efficient co-simulation and control approach to tackle complex multi-domain energetic systems: concepts and applications of the PEGASE platform
In this paper, we present a novel research software, called PEGASE, suitable for the design, validation and deployment of advanced control strategies for complex multi-domain energy systems. PEGASE especially features a highly efficient cosimulation engine, together with integrated solutions for defining both rule-based control strategies and Model-Predictive Control (MPC). The main principle behind the PEGASE platform is divide-and-conquer. Indeed, rather than trying to solve a problem as a mo…

Conceptual Modelling for Life Sciences Based on Systemist Foundations
R. Lukyanenko, O. Pastor, V. C. Storey
https://arxiv.org/abs/2506.18742 https://

Conceptual Modelling for Life Sciences Based on Systemist Foundations
All aspects of our society, including the life sciences, need a mechanism for people working within them to represent the concepts they employ to carry out their research. For the information systems being designed and developed to support researchers and scientists in conducting their work, conceptual models of the relevant domains are usually designed as both blueprints for a system being developed and as a means of communication between the designer and developer. Most conceptual modelling c…

Language models align with brain regions that represent concepts across modalities
Maria Ryskina, Greta Tuckute, Alexander Fung, Ashley Malkin, Evelina Fedorenko
https://arxiv.org/abs/2508.11536

Language models align with brain regions that represent concepts across modalities
Cognitive science and neuroscience have long faced the challenge of disentangling representations of language from representations of conceptual meaning. As the same problem arises in today's language models (LMs), we investigate the relationship between LM--brain alignment and two neural metrics: (1) the level of brain activation during processing of sentences, targeting linguistic processing, and (2) a novel measure of meaning consistency across input modalities, which quantifies how consiste…

Replaced article(s) found for cs.LO. https://arxiv.org/list/cs.LO/new
[1/1]:
- Learning Concepts Definable in First-Order Logic with Counting
Steffen van Bergerem

Enhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings
Yahya Badran, Christine Preisach
https://arxiv.org/abs/2508.17092 https://arx…

Enhancing Knowledge Tracing through Leakage-Free and Recency-Aware Embeddings
Knowledge Tracing (KT) aims to predict a student's future performance based on their sequence of interactions with learning content. Many KT models rely on knowledge concepts (KCs), which represent the skills required for each item. However, some of these models are vulnerable to label leakage, in which input data inadvertently reveal the correct answer, particularly in datasets with multiple KCs per question. We propose a straightforward yet effective solution to prevent label leakage by mas…

Shape2Animal: Creative Animal Generation from Natural Silhouettes
Quoc-Duy Tran, Anh-Tuan Vo, Dinh-Khoi Vo, Tam V. Nguyen, Minh-Triet Tran, Trung-Nghia Le
https://arxiv.org/abs/2506.20616

Shape2Animal: Creative Animal Generation from Natural Silhouettes
Humans possess a unique ability to perceive meaningful patterns in ambiguous stimuli, a cognitive phenomenon known as pareidolia. This paper introduces Shape2Animal framework to mimics this imaginative capacity by reinterpreting natural object silhouettes, such as clouds, stones, or flames, as plausible animal forms. Our automated framework first performs open-vocabulary segmentation to extract object silhouette and interprets semantically appropriate animal concepts using vision-language model…

Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection
Lei Yu, Zhirong Huang, Hang Yuan, Shiqi Cheng, Li Yang, Fengjun Zhang, Chenjie Shen, Jiajia Ma, Jingyuan Zhang, Junyi Lu, Chun Zuo
https://arxiv.org/abs/2506.18245

Smart-LLaMA-DPO: Reinforced Large Language Model for Explainable Smart Contract Vulnerability Detection
Smart contract vulnerability detection remains a major challenge in blockchain security. Existing vulnerability detection methods face two main issues: (1) Existing datasets lack comprehensive coverage and high-quality explanations for preference learning. (2) Large language models (LLMs) often struggle with accurately interpreting specific concepts in smart contract security. Empirical analysis shows that even after continual pre-training (CPT) and supervised fine-tuning (SFT), LLMs may misint…

LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research
Shuo Yan, Ruochen Li, Ziming Luo, Zimu Wang, Daoyang Li, Liqiang Jing, Kaiyu He, Peilin Wu, George Michalopoulos, Yue Zhang, Ziyang Zhang, Mian Zhang, Zhiyu Chen, Xinya Du
https://arxiv.org/abs/2506.17335…

LMR-BENCH: Evaluating LLM Agent's Ability on Reproducing Language Modeling Research
Large language model (LLM) agents have demonstrated remarkable potential in advancing scientific discovery. However, their capability in the fundamental yet crucial task of reproducing code from research papers, especially in the NLP domain, remains underexplored. This task includes unique complex reasoning challenges in the intellectual synthesis of abstract concepts and the comprehension of code repositories with interdependent files. Motivated by this gap, we present LMR-BENCH, a benchmark d…

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
Ji-Youn Jung, Devansh Saxena, Minjung Park, Jini Kim, Jodi Forlizzi, Kenneth Holstein, John Zimmerman
https://arxiv.org/abs/2506.17494

Making the Right Thing: Bridging HCI and Responsible AI in Early-Stage AI Concept Selection
AI projects often fail due to financial, technical, ethical, or user acceptance challenges -- failures frequently rooted in early-stage decisions. While HCI and Responsible AI (RAI) research emphasize this, practical approaches for identifying promising concepts early remain limited. Drawing on Research through Design, this paper investigates how early-stage AI concept sorting in commercial settings can reflect RAI principles. Through three design experiments -- including a probe study with ind…

GenOM: Ontology Matching with Description Generation and Large Language Model
Yiping Song, Jiaoyan Chen, Renate A. Schmidt
https://arxiv.org/abs/2508.10703 https://

GenOM: Ontology Matching with Description Generation and Large Language Model
Ontology matching (OM) plays an essential role in enabling semantic interoperability and integration across heterogeneous knowledge sources, particularly in the biomedical domain which contains numerous complex concepts related to diseases and pharmaceuticals. This paper introduces GenOM, a large language model (LLM)-based ontology alignment framework, which enriches the semantic representations of ontology concepts via generating textual definitions, retrieves alignment candidates with an embe…

Potemkin Understanding in Large Language Models
Marina Mancoridis, Bec Weeks, Keyon Vafa, Sendhil Mullainathan
https://arxiv.org/abs/2506.21521 https://arxiv.org/pdf/2506.21521 https://arxiv.org/html/2506.21521
arXiv:2506.21521v1 Announce Type: new
Abstract: Large language models (LLMs) are regularly evaluated using benchmark datasets. But what justifies making inferences about an LLM's capabilities based on its answers to a curated set of questions? This paper first introduces a formal framework to address this question. The key is to note that the benchmarks used to test LLMs -- such as AP exams -- are also those used to test people. However, this raises an implication: these benchmarks are only valid tests if LLMs misunderstand concepts in ways that mirror human misunderstandings. Otherwise, success on benchmarks only demonstrates potemkin understanding: the illusion of understanding driven by answers irreconcilable with how any human would interpret a concept. We present two procedures for quantifying the existence of potemkins: one using a specially designed benchmark in three domains, the other using a general procedure that provides a lower-bound on their prevalence. We find that potemkins are ubiquitous across models, tasks, and domains. We also find that these failures reflect not just incorrect understanding, but deeper internal incoherence in concept representations.
toXiv_bot_toot

When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?
Romy M\"uller
https://arxiv.org/abs/2506.17936

When concept-based XAI is imprecise: Do people distinguish between generalisations and misrepresentations?
Concept-based explainable artificial intelligence (C-XAI) can help reveal the inner representations of AI models. Understanding these representations is particularly important in complex tasks like safety evaluation. Such tasks rely on high-level semantic information (e.g., about actions) to make decisions about abstract categories (e.g., whether a situation is dangerous). In this context, it may desirable for C-XAI concepts to show some variability, suggesting that the AI is capable of general…

PasteTrace: A Single Source Plagiarism Detection Tool For Introductory Programming Courses
Jesse McDonald, Scott Robertson, Anthony Peruma
https://arxiv.org/abs/2506.17355

PasteTrace: A Single Source Plagiarism Detection Tool For Introductory Programming Courses
Introductory Computer Science classes are important for laying the foundation for advanced programming courses. However, students without prior programming experience may find these courses challenging, leading to difficulties in understanding concepts and engaging in academic dishonesty such as plagiarism. While there exists plagiarism detection techniques and tools, not all of them are suitable for academic settings, especially in introductory programming courses. This paper introduces PasteT…

MV-RAG: Retrieval Augmented Multiview Diffusion
Yosef Dayani, Omer Benishu, Sagie Benaim
https://arxiv.org/abs/2508.16577 https://arxiv.org/pdf/2508.16577

MV-RAG: Retrieval Augmented Multiview Diffusion
Text-to-3D generation approaches have advanced significantly by leveraging pretrained 2D diffusion priors, producing high-quality and 3D-consistent outputs. However, they often fail to produce out-of-domain (OOD) or rare concepts, yielding inconsistent or inaccurate results. To this end, we propose MV-RAG, a novel text-to-3D pipeline that first retrieves relevant 2D images from a large in-the-wild 2D database and then conditions a multiview diffusion model on these images to synthesize consiste…

SPARC: Concept-Aligned Sparse Autoencoders for Cross-Model and Cross-Modal Interpretability
Ali Nasiri-Sarvi, Hassan Rivaz, Mahdi S. Hosseini
https://arxiv.org/abs/2507.06265

SPARC: Concept-Aligned Sparse Autoencoders for Cross-Model and Cross-Modal Interpretability
Understanding how different AI models encode the same high-level concepts, such as objects or attributes, remains challenging because each model typically produces its own isolated representation. Existing interpretability methods like Sparse Autoencoders (SAEs) produce latent concepts individually for each model, resulting in incompatible concept spaces and limiting cross-model interpretability. To address this, we introduce SPARC (Sparse Autoencoders for Aligned Representation of Concepts), a…