Tootfinder

Brian Schottenheimer using lessons from the past to help in the present https://www.dallascowboys.com/news/brian-schottenheimer-using-lessons-from-the-past-to-help-in-the-present

Strange Parables - an #improv #poem
https://m…

Strange Parables - an #improv #poem
Stan Stewart - @muz4now

Monitor de lA de IPSOS 2025
Ayer escuché en la radio de este estudio sobre percepción de la IA en la población de varios países incluyendo a Chile.
https://www.ipsos.com/es-cl/conflicting-global-perceptions-around-ai-present-mixed-signa…

Brian Schottenheimer using lessons from the past to help in the present https://www.dallascowboys.com/news/brian-schottenheimer-using-lessons-from-the-past-to-help-in-the-present

citeseer: CiteSeer citations (2014)
Citations among papers indexed by the CiteSeer digital library. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present.
This network has 384413 nodes and 1751463 edges.
Tags: Informational, Citation, Unweighted

Querying Graph-Relational Data
Michael J. Sullivan, Zhibo Chen, Elvis Pranskevichus, Robert J. Simmons, Victor Petrovykh, Alja\v{z} Mur Er\v{z}en, Yury Selivanov
https://arxiv.org/abs/2507.16089

Querying Graph-Relational Data
For applications that store structured data in relational databases, there is an impedance mismatch between the flat representations encouraged by relational data models and the deeply nested information that applications expect to receive. In this work, we present the graph-relational database model, which provides a flexible, compositional, and strongly-typed solution to this "object-relational mismatch." We formally define the graph-relational database model and present a static and dynamic …

Mirror Eyes: Explainable Human-Robot Interaction at a Glance
Matti Kr\"uger, Daniel Tanneberg, Chao Wang, Stephan Hasler, Michael Gienger
https://arxiv.org/abs/2506.18466

Mirror Eyes: Explainable Human-Robot Interaction at a Glance
The gaze of a person tends to reflect their interest. This work explores what happens when this statement is taken literally and applied to robots. Here we present a robot system that employs a moving robot head with a screen-based eye model that can direct the robot's gaze to points in physical space and present a reflection-like mirror image of the attended region on top of each eye. We conducted a user study with 33 participants, who were asked to instruct the robot to perform pick-and-place…

50 years ago today, television in #cleveland, their 1st road gig. tape made by peter laughner, who almost joined the band not long after this. https://doomandgloomfromthetomb…

"Restoring sea floor after mining may not be possible, researchers warn"
#Sea #Oceans #Mining

Restoring sea floor after mining may not be possible, researchers warn
Scientists present at the latest effort to hash out international rules for deep-sea mining say it's unclear if it's possible to restore damaged seafloor ecosystems—or how long it would take.

Code Generation for Near-Roofline Finite Element Actions on GPUs from Symbolic Variational Forms
Kaushik Kulkarni, Andreas Kl\"ockner
https://arxiv.org/abs/2506.17471

Code Generation for Near-Roofline Finite Element Actions on GPUs from Symbolic Variational Forms
We present a novel parallelization strategy for evaluating Finite Element Method (FEM) variational forms on GPUs, focusing on those that are expressible through the Unified Form Language (UFL) on simplex meshes. We base our approach on code transformations, wherein we construct a space of scheduling candidates and rank them via a heuristic cost model to effectively handle the large diversity of computational workloads that can be expressed in this way. We present a design of a search space to w…

Ritüel Kaçış (Ritual Escape) #OriginalMusic #NowPlaying

Ritüel Kaçış (Ritual Escape) #PentatonicMusic #NowPlaying
Stan Stewart - @muz4now

Back when the US invaded Iraq there was a deck of cards bearing the names/photos/info on the Saddam goon hierarchy.
Is there such a deck for the present maga-goon hierarchy?
https://en.wikipedia.org/wiki/Most-wanted_Iraqi_playing_cards

Most-wanted Iraqi playing cards - Wikipedia

A Comprehensive Analysis of Rovibrational CO in the Era of JWST
D. Annie Dickson-Vandervelde, Colette Salyk, Geoffrey A. Blake, Clara Ross, Adwin Boogert, Klaus Pontoppidan
https://arxiv.org/abs/2507.16127

A Comprehensive Analysis of Rovibrational CO in the Era of JWST
We present an analysis of CO rovibrational emission lines in the 183 infrared spectra of nearby Class II objects obtained with the NIRSPEC instrument on the Keck II telescope over the past two decades. The sample includes a broad range of stellar mass (both T Tauri and Herbig Ae/Be) and disk evolutionary states (from full to debris disks). We find that 53% of the sample has CO rovibrational emission lines present in their spectrum with disk/stellar subtype detection rates of 82% for transition …

I increasingly think that we need mandatory formal training for PhD students in “research as a profession” (as it exists in other countries, apparently).
Yes, submitting a paper to a conference (in particular as a first author) constitutes an commitment to present the paper if it’s accepted. When working with coauthors, no, you can’t tacitly assume that they’ll take care of it.
And yes, a workshop on Monday from 09:00 to 12:30 takes place during “normal working hours.”

Tech companies think that, if they make products *look* futuristic, you will think that they are actually innovating. In reality what we get is not "Star Trek communicators inspired cell phones" but "every experience with your computer is going to be like begging HAL to open the pod bay doors" except less evil and more frustrating.

Imitating the future, breaking the present
Tech companies are only pretending to innovate, through copying futuristic aesthetics from science fiction without understanding their purpose.

@… I heard about it at least once a year in school growing up (Denmark), it was present, but it doesn’t sound like anywhere near the degree of Japan.
Agreed that I haven’t seen many (Any?) mentions since moving to the U.S.

TIL it's a verb (Wiktionary)
Verb
lint (third-person singular simple present lints, present participle linting, simple past and past participle linted)
(transitive, computing) To perform a static check on (source code) to detect stylistic or programmatic errors.
You should lint your JavaScript code before committing it.

Simultaneous observations of multiple ELVES and SPRITES at the Pierre #Auger Observatory: https://arxiv.org/abs/2507.11641 -> "the Pierre Auger Observatory has exploited a dedicated trigger and its very high time resolution to study ELVES and harvest record samples of multiple ELVES using the Fluorescence Detector (FD). In 2017, after extending the readout of trace lengths to 0.9 ms, we started observing other types of light transients from the base of the ionosphere, such as HALOS, which deserved further investigation. In December 2023 and April 2024, we installed two additional cameras (TLECAMs), which allow us to perform simultaneous detection of these transients with higher space resolution and longer integration times. Here, we present our first simultaneous observations of SPRITES and ELVES by both TLECAMs and FD."

If this mechanism is indeed involved in the origin of life, then a form of life is likely to be present on innumerable habitable planets throughout the universe. Which is expected, of course, and will no-doubt be found at some point.
https://mastodon.social/@ScienceScholar/114734…

Good Morning #Canada
July 1840 - British parliament passed the Act of Union 1840, and it was proclaimed officially on February 10, 1841, in Montreal. The act abolished the legislatures of Lower Canada (basically the East coast and Quebec) and Upper Canada (most of present day Ontario) and established a new political entity, the Province of Canada to replace them. British objectives were to exert more control of their colony and suppress the French speaking population. In 1848, the Province of Canada was allowed "responsible government," giving them limited rights to pass laws, and some of the more repressive laws of the Act of Union were repealed.
#CanadaIsAwesome #History
https://www.thecanadianencyclopedia.ca/en/article/act-of-union

Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling
Yi Xin, Juncheng Yan, Qi Qin, Zhen Li, Dongyang Liu, Shicheng Li, Victor Shea-Jay Huang, Yupeng Zhou, Renrui Zhang, Le Zhuo, Tiancheng Han, Xiaoqing Sun, Siqi Luo, Mengmeng Wang, Bin Fu, Yuewen Cao, Hongsheng Li, Guangtao Zhai, Xiaohong Liu, Yu Qiao, Peng Gao
https://arxiv.org/abs/…

Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling
We present Lumina-mGPT 2.0, a stand-alone, decoder-only autoregressive model that revisits and revitalizes the autoregressive paradigm for high-quality image generation and beyond. Unlike existing approaches that rely on pretrained components or hybrid architectures, Lumina-mGPT 2.0 is trained entirely from scratch, enabling unrestricted architectural design and licensing freedom. It achieves generation quality on par with state-of-the-art diffusion models such as DALL-E 3 and SANA, while prese…

Andy Reid's office struck by bullet while Chiefs coach was present, per report

https://www.cbssports.com/nfl/news/andy-reids-office-struck-by-bullet-…

Persistent Patterns in Eye Movements: A Topological Approach to Emotion Recognition
Arsha Niksa, Hooman Zare, Ali Shahrabi, Hanieh Hatami, Mohammadreza Razvan
https://arxiv.org/abs/2507.17450

Persistent Patterns in Eye Movements: A Topological Approach to Emotion Recognition
We present a topological pipeline for automated multiclass emotion recognition from eye-tracking data. Delay embeddings of gaze trajectories are analyzed using persistent homology. From the resulting persistence diagrams, we extract shape-based features such as mean persistence, maximum persistence, and entropy. A random forest classifier trained on these features achieves up to $75.6\%$ accuracy on four emotion classes, which are the quadrants the Circumplex Model of Affect. The results demons…

Megrez2 Technical Report
Boxun Li, Yadong Li, Zhiyuan Li, Congyi Liu, Weilin Liu, Guowei Niu, Zheyue Tan, Haiyang Xu, Zhuyu Yao, Tao Yuan, Dong Zhou, Yueqing Zhuang, Bo Zhao, Guohao Dai, Yu Wang
https://arxiv.org/abs/2507.17728

Megrez2 Technical Report
We present Megrez2, a novel lightweight and high-performance language model architecture optimized for device native deployment. Megrez2 introduces a novel cross-layer expert sharing mechanism, which significantly reduces total parameter count by reusing expert modules across adjacent transformer layers while maintaining most of the model's capacity. It also incorporates pre-gated routing, enabling memory-efficient expert loading and faster inference. As the first instantiation of the Megrez2 a…

SMARTAPS: Tool-augmented LLMs for Operations Management
Timothy Tin Long Yu, Mahdi Mostajabdaveh, Jabo Serge Byusa, Rindra Ramamonjison, Giuseppe Carenini, Kun Mao, Zirui Zhou, Yong Zhang
https://arxiv.org/abs/2507.17927

SMARTAPS: Tool-augmented LLMs for Operations Management
Large language models (LLMs) present intriguing opportunities to enhance user interaction with traditional algorithms and tools in real-world applications. An advanced planning system (APS) is a sophisticated software that leverages optimization to help operations planners create, interpret, and modify an operational plan. While highly beneficial, many customers are priced out of using an APS due to the ongoing costs of consultants responsible for customization and maintenance. To address the n…

Spin-1/2 operators exactly mapped to spinful canonical Fermi operators present in two bands
Zsolt Gulacsi
https://arxiv.org/abs/2506.17734 https://

Spin-1/2 operators exactly mapped to spinful canonical Fermi operators present in two bands
Recently it has been shown that the quantum spin-1/2 spin operators can be exactly transformed not only in spinless, but also in spinful canonical Fermi operators in 1D [\cite{JW1}], and 2D [\cite{JW2}] as well. In this paper, using the same technique based on an extended Jordan-Wigner transformation, we show in 1D, that the quantum spin-1/2 operators can be exactly transformed also in spinful canonical Fermi operators of spin-1/2 fermions that are belong to two bands.

Transordinal Fixed-Point Operators and Self-Referential Games: A Categorical Framework for Reflective Semantic Convergence
Faruk Alpay, Hamdi Al Alakkad
https://arxiv.org/abs/2507.16620

Transordinal Fixed-Point Operators and Self-Referential Games: A Categorical Framework for Reflective Semantic Convergence
We present a new theoretical framework that unifies category-theoretic fixed-point constructions, transfinite recursion, and game-based semantics to model how interpretations of language can stabilize through unlimited self-reference. By iterating a meaning-refinement operator across all ordinal stages, we isolate a unique "transordinal" fixed point and show, via a hierarchy of reflective games, that this same object is the sole equilibrium of an infinite dialogue between a text and its interpr…

A Unified Toolbox for Multipartite Entanglement Certification
Ye-Chao Liu, Jannis Halbey, Sebastian Pokutta, S\'ebastien Designolle
https://arxiv.org/abs/2507.17435 https://…

A Unified Toolbox for Multipartite Entanglement Certification
We present a unified framework for multipartite entanglement characterization based on the conditional gradient (CG) method, incorporating both fast heuristic detection and rigorous witness construction with numerical error control. Our method enables entanglement certification in quantum systems of up to ten qubits and applies to arbitrary entanglement structures. We demonstrate its power by closing the gap between entanglement and separability bounds in white noise robustness benchmarks for a…

The remains of the Dutch coalition government (VVD-BBB), due to present the 2026 budget in three weeks from now, can count on 32 out of 150 seats in parliament.

Sampling conditioned diffusions via Pathspace Projected Monte Carlo
Tobias Grafke
https://arxiv.org/abs/2506.15743 https://arxiv.org/…

Sampling conditioned diffusions via Pathspace Projected Monte Carlo
We present an algorithm to sample stochastic differential equations conditioned on rather general constraints, including integral constraints, endpoint constraints, and stochastic integral constraints. The algorithm is a pathspace Metropolis-adjusted manifold sampling scheme, which samples stochastic paths on the submanifold of realizations that adhere to the conditioning constraint. We demonstrate the effectiveness of the algorithm by sampling a dynamical condensation phase transition, conditi…

VulGuard: An Unified Tool for Evaluating Just-In-Time Vulnerability Prediction Models
Duong Nguyen, Manh Tran-Duc, Thanh Le-Cong, Triet Huynh Minh Le, M. Ali Babar, Quyet-Thang Huynh
https://arxiv.org/abs/2507.16685

VulGuard: An Unified Tool for Evaluating Just-In-Time Vulnerability Prediction Models
We present VulGuard, an automated tool designed to streamline the extraction, processing, and analysis of commits from GitHub repositories for Just-In-Time vulnerability prediction (JIT-VP) research. VulGuard automatically mines commit histories, extracts fine-grained code changes, commit messages, and software engineering metrics, and formats them for downstream analysis. In addition, it integrates several state-of-the-art vulnerability prediction models, allowing researchers to train, evaluat…

LLMxCPG: Context-Aware Vulnerability Detection Through Code Property Graph-Guided Large Language Models
Ahmed Lekssays, Hamza Mouhcine, Khang Tran, Ting Yu, Issa Khalil
https://arxiv.org/abs/2507.16585

LLMxCPG: Context-Aware Vulnerability Detection Through Code Property Graph-Guided Large Language Models
Software vulnerabilities present a persistent security challenge, with over 25,000 new vulnerabilities reported in the Common Vulnerabilities and Exposures (CVE) database in 2024 alone. While deep learning based approaches show promise for vulnerability detection, recent studies reveal critical limitations in terms of accuracy and robustness: accuracy drops by up to 45% on rigorously verified datasets, and performance degrades significantly under simple code modifications. This paper presents L…

Full-body WPT: wireless powering with meandered e-textiles
Ryo Takahashi, Takashi Sato, Wakako Yukita, Tomoyuki Yokota, Takao Someya, Yoshihiro Kawahara
https://arxiv.org/abs/2506.17606

Full-body WPT: wireless powering with meandered e-textiles
We present Full-body WPT, wireless power networking around the human body using a meandered textile coil. Unlike traditional inductive systems that emit strong fields into the deep tissue inside the body, the meander coil enables localized generation of strong magnetic field constrained to the skin surface, even when scaled to the size of the human body. Such localized inductive system enhances both safety and efficiency of wireless power around the body. Furthermore, the use of low-loss conduc…

dblp_cite: DBLP citations (2014)
Citations among papers contained in the DBLP computer science bibliography. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. This snapshot from May 2014.
This network has 12590 nodes and 49759 edges.
Tags: Informational, Citation, Unweighted

A unified approach to total irregular labeling
Aleams Barra
https://arxiv.org/abs/2506.17922 https://arxiv.org/pdf/2506.17922

A unified approach to total irregular labeling
We present a unified approach to compute the total vertex irregularity strength (tvs) of various graphs, employing a novel technique recently proposed by Barra et al. For graphs such as cycles, paths, prisms, wheels, complete graphs, helm graphs, friendship graphs, and $K_{n,n}$ , we offer simplified and unified proofs of their previously established tvs values. Furthermore, we resolve an open problem by determining the tvs for simple 2-regular graphs.

Abuse in Buddhism: The Law of Silence https://openbuddhism.org/library/videos/2022/elodie-emery-wandrille-lanos-present-buddhism-the-unspeakable-truth/

‘Abuse in Buddhism: The Law of Silence’
In a brief video in English, the French filmmakers Élodie Emery and Wandrille Lanos introduce their documentary ‘Abuse in Buddhism: The Law of Silence’ (Arte, 2022). It can be watched here.

Proofs that Modify Proofs, 1/2
Henry Towsner
https://arxiv.org/abs/2506.16491 https://arxiv.org/pdf/2506.16491

Proofs that Modify Proofs, 1/2
This paper is a prelude and elaboration on Proofs that Modify Proofs. Here we present an ordinal analysis of a fragment of the $μ$-calculus around the strength of parameter-free $Π^1_2$-comprehension using the same approach as that paper, interpreting functions on proofs as proofs in an expanded system. We build up the ordinal analysis in several stages, beginning by illustrating the method systems at the strength of paremeter-free $Π^1_1$-comprehension and full $Π^1_1$-comprehension.

Teaching Complex Systems based on Microservices
Renato Cordeiro Ferreira (University of S\~ao Paulo), Thatiane de Oliveira Rosa (University of S\~ao Paulo, Federal Institute of Tocantins), Alfredo Goldman (University of S\~ao Paulo), Eduardo Guerra (Free University of Bozen-Bolzano)
https://arxiv.org/abs/2506.16492

Teaching Complex Systems based on Microservices
Developing complex systems using microservices is a current challenge. In this paper, we present our experience with teaching this subject to more than 80 students at the University of São Paulo (USP), fostering team work and simulating the industry's environment. We show it is possible to teach such advanced concepts for senior undergraduate students of Computer Science and related fields.

On Fermat's Last Theorem over the $\mathbb{Z}_3$-extension of $\mathbb{Q}$ and other fields
Luis Dieulefait, Franco Golfieri Madriaga
https://arxiv.org/abs/2507.16883

On Fermat's Last Theorem over the $\mathbb{Z}_3$-extension of $\mathbb{Q}$ and other fields
The main result of the present article is a proof of Fermat's Last Theorem for sufficiently large prime exponents $p$ with $p \equiv 2 \pmod{3}$ over certain number fields. A particular case of these fields are the maximal real subfields of the cyclotomic extensions $\mathbb{Q}(ζ_{3^n})$ for every $n$. Our strategy consists in combining the modular method with a generalization of an arithmetic result of Pomey to these fields.

Spectral Methods for Polynomial Optimization
Elvira Moreno, Venkat Chandrasekaran
https://arxiv.org/abs/2507.16272 https://arxiv.org/…

Spectral Methods for Polynomial Optimization
We present a hierarchy of tractable relaxations to obtain lower bounds on the minimum value of a polynomial over a constraint set defined by polynomial equations. In contrast to previous convex relaxation techniques for this problem, our method is based on computing the smallest generalized eigenvalue of a pair of matrices derived from the problem data, which can be accomplished for large problem instances using off-the-shelf software. We characterize the algebraic structure in a problem that f…

One Ring to Rule Them All: A Unified Topological Framework for 4D Superconformal Anomalies
Camillo Imbimbo, Ludovico Porro
https://arxiv.org/abs/2507.16505

One Ring to Rule Them All: A Unified Topological Framework for 4D Superconformal Anomalies
We present a unified topological description of anomalies that generalizes the Chern-Simons formulation of Yang-Mills anomalies to encompass all 4-dimensional superconformal anomalies. The key innovation is our characterization of anomalies through the constraint ideal in the polynomial ring of generalized curvatures and connections of the underlying symmetry (super)-Lie algebra. We demonstrate that anomalies in dimension $d$ are captured by the cohomology $H_δ(W_{d+2})$ of the generalized B…

cora: CORA citations (1998)
Citations among papers indexed by CORA, from 1998, an early computer science research paper search engine. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present. The dates of these snapshots are uncertain.
This network has 23166 nodes and 91500 edges.
Tags: Informational, Citation, Unweighted

PyG 2.0: Scalable Learning on Real World Graphs
Matthias Fey, Jinu Sunil, Akihiro Nitta, Rishi Puri, Manan Shah, Bla\v{z} Stojanovi\v{c}, Ramona Bendias, Alexandria Barghi, Vid Kocijan, Zecheng Zhang, Xinwei He, Jan Eric Lenssen, Jure Leskovec
https://arxiv.org/abs/2507.16991

PyG 2.0: Scalable Learning on Real World Graphs
PyG (PyTorch Geometric) has evolved significantly since its initial release, establishing itself as a leading framework for Graph Neural Networks. In this paper, we present Pyg 2.0 (and its subsequent minor versions), a comprehensive update that introduces substantial improvements in scalability and real-world application capabilities. We detail the framework's enhanced architecture, including support for heterogeneous and temporal graphs, scalable feature/graph stores, and various optimization…

Understanding Haskell-style Overloading via Open Data and Open Functions
Andrew Marmaduke, Apoorv Ingle, J. Garrett Morris
https://arxiv.org/abs/2507.16086

Understanding Haskell-style Overloading via Open Data and Open Functions
We present a new, uniform semantics for Haskell-style overloading. We realize our approach in a new core language, System F$_\mathrm{D}$, whose metatheory we mechanize in the Lean4 interactive theorem prover. System F$_\mathrm{D}$ is distinguished by its open data types and open functions, each given by a collection of instances rather than by a single definition. We show that System F$_\mathrm{D}$ can encode advanced features of Haskell's of type class systems, more expressively than current s…

Yume: An Interactive World Generation Model
Xiaofeng Mao, Shaoheng Lin, Zhen Li, Chuanhao Li, Wenshuo Peng, Tong He, Jiangmiao Pang, Mingmin Chi, Yu Qiao, Kaipeng Zhang
https://arxiv.org/abs/2507.17744

Yume: An Interactive World Generation Model
Yume aims to use images, text, or videos to create an interactive, realistic, and dynamic world, which allows exploration and control using peripheral devices or neural signals. In this report, we present a preview version of \method, which creates a dynamic world from an input image and allows exploration of the world using keyboard actions. To achieve this high-fidelity and interactive video world generation, we introduce a well-designed framework, which consists of four main components, incl…

Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks
Giulio Pelosio, Devesh Batra, No\'emie Bovey, Robert Hankache, Cristovao Iglesias, Greig Cowan, Raad Khraishi
https://arxiv.org/abs/2507.16989

Obscured but Not Erased: Evaluating Nationality Bias in LLMs via Name-Based Bias Benchmarks
Large Language Models (LLMs) can exhibit latent biases towards specific nationalities even when explicit demographic markers are not present. In this work, we introduce a novel name-based benchmarking approach derived from the Bias Benchmark for QA (BBQ) dataset to investigate the impact of substituting explicit nationality labels with culturally indicative names, a scenario more reflective of real-world LLM applications. Our novel approach examines how this substitution affects both bias magni…

Airalogy: AI-empowered universal data digitization for research automation
Zijie Yang, Qiji Zhou, Fang Guo, Sijie Zhang, Yexun Xi, Jinglei Nie, Yudian Zhu, Liping Huang, Chou Wu, Yonghe Xia, Xiaoyu Ma, Yingming Pu, Panzhong Lu, Junshu Pan, Mingtao Chen, Tiannan Guo, Yanmei Dou, Hongyu Chen, Anping Zeng, Jiaxing Huang, Tian Xu, Yue Zhang
https://

Airalogy: AI-empowered universal data digitization for research automation
Research data are the foundation of Artificial Intelligence (AI)-driven science, yet current AI applications remain limited to a few fields with readily available, well-structured, digitized datasets. Achieving comprehensive AI empowerment across multiple disciplines is still out of reach. Present-day research data collection is often fragmented, lacking unified standards, inefficiently managed, and difficult to share. Creating a single platform for standardized data digitization needs to overc…

Extended Kalman Smoothing of Free Spin Precession Signals for Precise Magnetic Field Determination
Jasper Riebesehl, Lutz Mertensk\"otter, Wiebke Pohlandt, Wilhelm Stannat, Wolfgang Kilian
https://arxiv.org/abs/2507.17602

Extended Kalman Smoothing of Free Spin Precession Signals for Precise Magnetic Field Determination
We present a novel application of the Extended Kalman Smoother (EKS) for high-precision frequency estimation from free spin precession signals of polarized $^3$He. Traditional approaches often rely on nonlinear least-squares fitting, which can suffer from limited robustness to signal decay and time-dependent frequency shifts. By contrast, our EKS-based method captures both amplitude and frequency variations with minimal tuning, adapting automatically to fluctuations via an expectation-maximizat…

On Expansions of Monadic Second-Order Logic with Dynamical Predicates
Joris Nieuwveld, Jo\"el Ouaknine
https://arxiv.org/abs/2507.16581 https://

On Expansions of Monadic Second-Order Logic with Dynamical Predicates
Expansions of the monadic second-order (MSO) theory of the structure $\langle \mathbb{N} ; < \rangle$ have been a fertile and active area of research ever since the publication of the seminal papers of Büchi and Elgot & Rabin on the subject in the 1960s. In the present paper, we establish decidability of the MSO theory of $\langle \mathbb{N} ; <,P \rangle$, where $P$ ranges over a large class of unary ''dynamical'' predicates, i.e., sets of non-negative values assumed by certain integer linear…

Bayesian preference elicitation for decision support in multiobjective optimization
Felix Huber, Sebastian Rojas Gonzalez, Raul Astudillo
https://arxiv.org/abs/2507.16999

Bayesian preference elicitation for decision support in multiobjective optimization
We present a novel approach to help decision-makers efficiently identify preferred solutions from the Pareto set of a multi-objective optimization problem. Our method uses a Bayesian model to estimate the decision-maker's utility function based on pairwise comparisons. Aided by this model, a principled elicitation strategy selects queries interactively to balance exploration and exploitation, guiding the discovery of high-utility solutions. The approach is flexible: it can be used interactively…

Scaling GR(1) Synthesis via a Compositional Framework for LTL Discrete Event Control
Hern\'an Gagliardi, Victor Braberman, Sebastian Uchitel
https://arxiv.org/abs/2506.16557

Scaling GR(1) Synthesis via a Compositional Framework for LTL Discrete Event Control
We present a compositional approach to controller synthesis of discrete event system controllers with linear temporal logic (LTL) goals. We exploit the modular structure of the plant to be controlled, given as a set of labelled transition systems (LTS), to mitigate state explosion that monolithic approaches to synthesis are prone to. Maximally permissive safe controllers are iteratively built for subsets of the plant LTSs by solving weaker control problems. Observational synthesis equivalence i…

Reproducible Evaluation of Camera Auto-Exposure Methods in the Field: Platform, Benchmark and Lessons Learned
Olivier Gamache, Jean-Michel Fortin, Mat\v{e}j Boxan, Fran\c{c}ois Pomerleau, Philippe Gigu\`ere
https://arxiv.org/abs/2506.18844

Reproducible Evaluation of Camera Auto-Exposure Methods in the Field: Platform, Benchmark and Lessons Learned
Standard datasets often present limitations, particularly due to the fixed nature of input data sensors, which makes it difficult to compare methods that actively adjust sensor parameters to suit environmental conditions. This is the case with Automatic-Exposure (AE) methods, which rely on environmental factors to influence the image acquisition process. As a result, AE methods have traditionally been benchmarked in an online manner, rendering experiments non-reproducible. Building on our prior…

Evaluation of the effects of frame time variation on VR task performance
Benjamin Watson, Victoria Spaulding, Neff Walker, William Ribarsky
https://arxiv.org/abs/2507.17139 http…

Evaluation of the effects of frame time variation on VR task performance
We present a first study of the effects of frame time variations, in both deviation around mean frame times and period of fluctuation, on task performance in a virtual environment (VE). Chosen are open and closed loop tasks that are typical for current applications or likely to be prominent in future ones. The results show that at frame times in the range deemed acceptable for many applications, fairly large deviations in amplitude over a fairly wide range of periods do not significantly affect…

Quantum $\mathfrak{gl}$-weight system and its average values
Mikhail Zaitsev
https://arxiv.org/abs/2506.17706 https://arxiv.org/pdf/2…

Quantum $\mathfrak{gl}$-weight system and its average values
We present a proof of a recent conjecture due to M. Kazarian, E. Krasilnikov, S. Lando, and M. Shapiro, which describes the average value of the universal $\mathfrak{gl}$-weight system on permutations. The proof uses a quantum analogue of the $\mathfrak{gl}$-weight system on Hecke algebras of type $A$, which leads to a one-parameter deformation of the average value of the universal ${\mathfrak{gl}}$-weight system. We show that the average value of the quantum weight system is a linear combinati…

kegg_metabolic: Metabolic networks from KEGG (2006)
109 metabolic networks of various species, as extracted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database in March 2006. Nodes are substances involved in enzymatic reactions present in the organism, and edges represent reactant-product pairs as extracted from the KEGG ligand database and matched against the present enzymes.
This network has 822 nodes and 2026 edges.
Tags: Biological, Metabolic, Unweighted

Cellular Automata as Generators of Interleaving Sequences
Sara D. Cardell
https://arxiv.org/abs/2506.18848 https://arxiv.org/pdf/2506…

Cellular Automata as Generators of Interleaving Sequences
An interleaving sequence is obtained by combining or intertwining elements from two or more sequences. On the other hand, cellular automata are known to be generators for keystream sequences. In this paper we present two families of one-dimensional cellular automata as generators of interleaving sequences. This study aims to close a notable gap within the current body of literature by exploring the capacity of cellular automata to generate interleaving sequences. While previous works have separ…

Implementation and Evaluation of Fast Raft for Hierarchical Consensus
Anton Melnychuk, Bryan SebaRaj
https://arxiv.org/abs/2506.17793 https://

Implementation and Evaluation of Fast Raft for Hierarchical Consensus
We present the first open-source implementation and evaluation of Fast Raft, a hierarchical consensus protocol designed for dynamic, distributed environments. Fast Raft reduces the number of message rounds needed to commit log entries compared to standard Raft by introducing a fast-track mechanism and reducing leader dependence. Our implementation uses gRPC and Kubernetes-based deployment across AWS availability zones. Experimental results demonstrate a throughput improvement and reduced commit…

Non-Linear Dynamics and Critical Phenomena in the Aretakis Instability of Extremal Black p-Branes
Behnam Pourhassan
https://arxiv.org/abs/2507.16023 https:…

Non-Linear Dynamics and Critical Phenomena in the Aretakis Instability of Extremal Black p-Branes
We present the first comprehensive investigation of the non-linear evolution of the Aretakis instability in extremal black $p$-branes. Building on recent insights into the linear behavior of perturbations in near-horizon AdS$_{p+2} \times S^{D-p-2}$ geometries, we explore the full non-linear regime using a combination of analytical scaling arguments and numerical simulations. We uncover a universal critical behavior governed by scaling exponents that depend only on the spacetime dimension $D$ a…

Can Large Language Models Be Trusted Paper Reviewers? A Feasibility Study
Chuanlei Li, Xu Hu, Minghui Xu, Kun Li, Yue Zhang, Xiuzhen Cheng
https://arxiv.org/abs/2506.17311

Can Large Language Models Be Trusted Paper Reviewers? A Feasibility Study
Academic paper review typically requires substantial time, expertise, and human resources. Large Language Models (LLMs) present a promising method for automating the review process due to their extensive training data, broad knowledge base, and relatively low usage cost. This work explores the feasibility of using LLMs for academic paper review by proposing an automated review system. The system integrates Retrieval Augmented Generation (RAG), the AutoGen multi-agent system, and Chain-of-Though…

Enhanced PDHG for Linear Programming with Online Preconditioning
Haihao Lu, Wanyu Zhang
https://arxiv.org/abs/2506.17650 https://arxi…

Enhanced PDHG for Linear Programming with Online Preconditioning
We present an online preconditioning technique for the primal-dual hybrid gradient (PDHG) algorithm for linear programming (LP). The method adaptively updates primal and dual preconditioners using an online optimization framework. To improve its practical performance, we introduce several algorithmic enhancements, including using normalized online loss functions and updating preconditioners infrequently. We implement the technique on top of vanilla PDHG and the GPU-based LP solver cuPDLP.jl, an…

Fast-VAT: Accelerating Cluster Tendency Visualization using Cython and Numba
MSR Avinash (Presidency University, Bangalore), Ismael Lachheb (EPITA School of Engineering,Computer Science, Paris, France)
https://arxiv.org/abs/2507.15904

Fast-VAT: Accelerating Cluster Tendency Visualization using Cython and Numba
Visual Assessment of Cluster Tendency (VAT) is a widely used unsupervised technique to assess the presence of cluster structure in unlabeled datasets. However, its standard implementation suffers from significant performance limitations due to its O(n^2) time complexity and inefficient memory usage. In this work, we present Fast-VAT, a high-performance reimplementation of the VAT algorithm in Python, augmented with Numba's Just-In-Time (JIT) compilation and Cython's static typing and low-level …

Weighted Assumption Based Argumentation to reason about ethical principles and actions
Paolo Baldi, Fabio Aurelio D'Asaro, Abeer Dyoub, Francesca Alessandra Lisi
https://arxiv.org/abs/2506.18056

Weighted Assumption Based Argumentation to reason about ethical principles and actions
We augment Assumption Based Argumentation (ABA for short) with weighted argumentation. In a nutshell, we assign weights to arguments and then derive the weight of attacks between ABA arguments. We illustrate our proposal through running examples in the field of ethical reasoning, and present an implementation based on Answer Set Programming.

CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models
Naiming Liu, Richard Baraniuk, Shashank Sonkar
https://arxiv.org/abs/2506.17180 http…

CLEAR-3K: Assessing Causal Explanatory Capabilities in Language Models
We introduce CLEAR-3K, a dataset of 3,000 assertion-reasoning questions designed to evaluate whether language models can determine if one statement causally explains another. Each question present an assertion-reason pair and challenge language models to distinguish between semantic relatedness and genuine causal explanatory relationships. Through comprehensive evaluation of 21 state-of-the-art language models (ranging from 0.5B to 72B parameters), we identify two fundamental findings. First, l…

A Comprehensive Evaluation Framework for the Study of the Effects of Facial Filters on Face Recognition Accuracy
Kagan Ozturk, Louisa Conwill, Jacob Gutierrez, Kevin Bowyer, Walter J. Scheirer
https://arxiv.org/abs/2507.17729

A Comprehensive Evaluation Framework for the Study of the Effects of Facial Filters on Face Recognition Accuracy
Facial filters are now commonplace for social media users around the world. Previous work has demonstrated that facial filters can negatively impact automated face recognition performance. However, these studies focus on small numbers of hand-picked filters in particular styles. In order to more effectively incorporate the wide ranges of filters present on various social media applications, we introduce a framework that allows for larger-scale study of the impact of facial filters on automated …

From Few to Many Emitters Cavity QED: Energy Levels and Emission Spectra From Weak to Deep-Strong Coupling
Andrea Zappal\'a, Alberto Mercurio, Daniele Lamberto, Samuel Napoli, Omar Di Stefano, Salvatore Savasta
https://arxiv.org/abs/2506.18763

From Few to Many Emitters Cavity QED: Energy Levels and Emission Spectra From Weak to Deep-Strong Coupling
We present a systematic study of the properties of systems composed of $N$ two-level quantum emitters coupled to a single cavity mode, for light-matter interaction strengths ranging from the weak to the ultrastrong and deep-strong coupling regimes. Beginning with an analysis of the energy spectrum as a function of the light-matter coupling strength, we examine systems with varying numbers of emitters, from a pair to large collections, approaching the thermodynamic limit ($N \to \infty$). Additi…

Cowboys WRs present major opportunity for fantasy football owners https://www.si.com/nfl/cowboys/news/dallas-cowboys-wrs-present-major-opportunity-for-fantasy-football-owners

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Christoph Jung, C. F. Bolz-Tereick
https://arxiv.org/abs/2506.16883 https://…

Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
Compared to the more commonly used time-based profiling, allocation profiling provides an alternate view of the execution of allocation heavy dynamically typed languages. However, profiling every single allocation in a program is very inefficient. We present a sampling allocation profiler that is deeply integrated into the garbage collector of PyPy, a Python virtual machine. This integration ensures tunable low overhead for the allocation profiler, which we measure and quantify. Enabling alloca…

An Adequate While-Language for Stochastic Hybrid Computation
Renato Neves, Jos\'e Proen\c{c}a, Juliana Souza
https://arxiv.org/abs/2507.15913 https://

An Adequate While-Language for Stochastic Hybrid Computation
We introduce a language for formally reasoning about programs that combine differential constructs with probabilistic ones. The language harbours, for example, such systems as adaptive cruise controllers, continuous-time random walks, and physical processes involving multiple collisions, like in Einstein's Brownian motion. We furnish the language with an operational semantics and use it to implement a corresponding interpreter. We also present a complementary, denotational semantics and estab…

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Teng Guo, Baichuan Huang, Jingjin Yu
https://arxiv.org/abs/2506.17110 https://

Monocular One-Shot Metric-Depth Alignment for RGB-Based Robot Grasping
Accurate 6D object pose estimation is a prerequisite for successfully completing robotic prehensile and non-prehensile manipulation tasks. At present, 6D pose estimation for robotic manipulation generally relies on depth sensors based on, e.g., structured light, time-of-flight, and stereo-vision, which can be expensive, produce noisy output (as compared with RGB cameras), and fail to handle transparent objects. On the other hand, state-of-the-art monocular depth estimation models (MDEMs) provid…

Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)
Megha Quamara, Viktor Schmuck, Cristina Iani, Axel Primavesi, Alexander Plaum, Luca Vigano
https://arxiv.org/abs/2507.16562

Evaluating Social Acceptance of eXtended Reality (XR) Agent Technology: A User Study (Extended Version)
In this paper, we present the findings of a user study that evaluated the social acceptance of eXtended Reality (XR) agent technology, focusing on a remotely accessible, web-based XR training system developed for journalists. This system involves user interaction with a virtual avatar, enabled by a modular toolkit. The interactions are designed to provide tailored training for journalists in digital-remote settings, especially for sensitive or dangerous scenarios, without requiring specialized …

Evaluating the Use of LLMs for Documentation to Code Traceability
Ebube Alor, SayedHassan Khatoonabadi, Emad Shihab
https://arxiv.org/abs/2506.16440 https:…

Evaluating the Use of LLMs for Documentation to Code Traceability
Large Language Models (LLMs) offer new potential for automating documentation-to-code traceability, yet their capabilities remain underexplored. We present a comprehensive evaluation of LLMs (Claude 3.5 Sonnet, GPT-4o, and o3-mini) in establishing trace links between various software documentation (including API references and user guides) and source code. We create two novel datasets from two open-source projects (Unity Catalog and Crawl4AI). Through systematic experiments, we assess three key…

Distributed P2P quantile tracking with relative value error
Marco Pulimeno, Italo Epicoco, Massimo Cafaro
https://arxiv.org/abs/2507.17458 https://arxiv.or…

Distributed P2P quantile tracking with relative value error
In this paper we present \textsc{DUDDSketch}, a distributed version of the \textsc{UDDSketch} algorithm for accurate tracking of quantiles. The algorithm is a fully decentralized, gossip-based distributed protocol working in the context of unstructured P2P networks. We discuss the algorithm's design and formally prove its correctness. We also show, through extensive experimental results, that the algorithm converges to the results provided by the sequential algorithm, which is a fundamental and…

Zero-Knowledge Proof-of-Location Protocols for Vehicle Subsidies and Taxation Compliance
Dan Bogdanov, Eduardo Brito, Annika Jaakson, Peeter Laud, Raul-Martin Rebane
https://arxiv.org/abs/2506.16812

Zero-Knowledge Proof-of-Location Protocols for Vehicle Subsidies and Taxation Compliance
This paper introduces a new set of privacy-preserving mechanisms for verifying compliance with location-based policies for vehicle taxation, or for (electric) vehicle (EV) subsidies, using Zero-Knowledge Proofs (ZKPs). We present the design and evaluation of a Zero-Knowledge Proof-of-Location (ZK-PoL) system that ensures a vehicle's adherence to territorial driving requirements without disclosing specific location data, hence maintaining user privacy. Our findings suggest a promising approach t…

Ethics through the Facets of Artificial Intelligence
Flavio Soares Correa da Silva
https://arxiv.org/abs/2507.17020 https://arxiv.org…

Ethics through the Facets of Artificial Intelligence
Artificial Intelligence (AI) has received unprecedented attention in recent years, raising ethical concerns about the development and use of AI technology. In the present article, we advocate that these concerns stem from a blurred understanding of AI, how it can be used, and how it has been interpreted in society. We explore the concept of AI based on three descriptive facets and consider ethical issues related to each facet. Finally, we propose a framework for the ethical assessment of the us…

An improved input-constrained funnel controller for nonlinear systems
Thomas Berger
https://arxiv.org/abs/2506.18417 https://arxiv.or…

An improved input-constrained funnel controller for nonlinear systems
We present an improvement of a recent funnel controller design for uncertain nonlinear multi-input, multi-output systems modeled by higher order functional differential equations in the presence of input constraints. The objective is to guarantee the evolution of the tracking error within a performance funnel with prescribed desired shape for the case of inactive saturation. Compared to its precursor, controller complexity is significantly reduced, much fewer design parameters are involved and …

RDMA: Cost Effective Agent-Driven Rare Disease Discovery within Electronic Health Record Systems
John Wu, Adam Cross, Jimeng Sun
https://arxiv.org/abs/2507.15867

RDMA: Cost Effective Agent-Driven Rare Disease Discovery within Electronic Health Record Systems
Rare diseases affect 1 in 10 Americans, yet standard ICD coding systems fail to capture these conditions in electronic health records (EHR), leaving crucial information buried in clinical notes. Current approaches struggle with medical abbreviations, miss implicit disease mentions, raise privacy concerns with cloud processing, and lack clinical reasoning abilities. We present Rare Disease Mining Agents (RDMA), a framework that mirrors how medical experts identify rare disease patterns in EHR. R…

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Shreya Saxena, Siva Prasad, Zishan Ahmad, Vishal Vaddina
https://arxiv.org/abs/2507.16478

ACT: Bridging the Gap in Code Translation through Synthetic Data Generation & Adaptive Training
Code translation is a crucial process in software development and migration projects, enabling interoperability between different programming languages and enhancing software adaptability and thus longevity. Traditional automated translation methods rely heavily on handcrafted transformation rules, which often lack flexibility and scalability. Meanwhile, advanced language models present promising alternatives but are often limited by proprietary, API-based implementations that raise concerns ov…

Is Tracking really more challenging in First Person Egocentric Vision?
Matteo Dunnhofer, Zaira Manigrasso, Christian Micheloni
https://arxiv.org/abs/2507.16015

Is Tracking really more challenging in First Person Egocentric Vision?
Visual object tracking and segmentation are becoming fundamental tasks for understanding human activities in egocentric vision. Recent research has benchmarked state-of-the-art methods and concluded that first person egocentric vision presents challenges compared to previously studied domains. However, these claims are based on evaluations conducted across significantly different scenarios. Many of the challenging characteristics attributed to egocentric vision are also present in third person …

Finite-size security analysis for quantum protocols: A Python framework using the Entropy Accumulation Theorem with graphical interface
Piotr Mironowicz, Mohamed Bourennane
https://arxiv.org/abs/2506.18888

Finite-size security analysis for quantum protocols: A Python framework using the Entropy Accumulation Theorem with graphical interface
We present a comprehensive software framework for the finite-size security analysis of quantum random number generation (QRNG) and quantum key distribution (QKD) protocols, based on the Entropy Accumulation Theorem (EAT). Our framework includes both a Python API and an intuitive graphical user interface (GUI), designed to support protocol designers and experimentalists in certifying randomness and key rates under realistic, finite-resource conditions. At its core, the framework automates the co…

Finance Language Model Evaluation (FLaME)
Glenn Matlin, Mika Okamoto, Huzaifa Pardawala, Yang Yang, Sudheer Chava
https://arxiv.org/abs/2506.15846 https://…

Finance Language Model Evaluation (FLaME)
Language Models (LMs) have demonstrated impressive capabilities with core Natural Language Processing (NLP) tasks. The effectiveness of LMs for highly specialized knowledge-intensive tasks in finance remains difficult to assess due to major gaps in the methodologies of existing evaluation frameworks, which have caused an erroneous belief in a far lower bound of LMs' performance on common Finance NLP (FinNLP) tasks. To demonstrate the potential of LMs for these FinNLP tasks, we present the first…

Learning Accurate Whole-body Throwing with High-frequency Residual Policy and Pullback Tube Acceleration
Yuntao Ma, Yang Liu, Kaixian Qu, Marco Hutter
https://arxiv.org/abs/2506.16986

Learning Accurate Whole-body Throwing with High-frequency Residual Policy and Pullback Tube Acceleration
Throwing is a fundamental skill that enables robots to manipulate objects in ways that extend beyond the reach of their arms. We present a control framework that combines learning and model-based control for prehensile whole-body throwing with legged mobile manipulators. Our framework consists of three components: a nominal tracking policy for the end-effector, a high-frequency residual policy to enhance tracking accuracy, and an optimization-based module to improve end-effector acceleration co…

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape
Vladislav Belozerov, Peter J Barclay, Askhan Sami
https://arxiv.org/abs/2506.16653

LLMs in Coding and their Impact on the Commercial Software Engineering Landscape
Large-language-model coding tools are now mainstream in software engineering. But as these same tools move human effort up the development stack, they present fresh dangers: 10% of real prompts leak private data, 42% of generated snippets hide security flaws, and the models can even ``agree'' with wrong ideas, a trait called sycophancy. We argue that firms must tag and review every AI-generated line of code, keep prompts and outputs inside private or on-premises deployments, obey emerging safet…

A Novel Approach to Differential Privacy with Alpha Divergence
Yifeng Liu, Zehua Wang
https://arxiv.org/abs/2506.17012 https://arxiv.…

A Novel Approach to Differential Privacy with Alpha Divergence
As data-driven technologies advance swiftly, maintaining strong privacy measures becomes progressively difficult. Conventional $(ε, δ)$-differential privacy, while prevalent, exhibits limited adaptability for many applications. To mitigate these constraints, we present alpha differential privacy (ADP), an innovative privacy framework grounded in alpha divergence, which provides a more flexible assessment of privacy consumption. This study delineates the theoretical underpinnings of ADP and co…

Anticipate, Simulate, Reason (ASR): A Comprehensive Generative AI Framework for Combating Messaging Scams
Xue Wen Tan, Kenneth See, Stanley Kok
https://arxiv.org/abs/2507.17543 …

Anticipate, Simulate, Reason (ASR): A Comprehensive Generative AI Framework for Combating Messaging Scams
The rapid growth of messaging scams creates an escalating challenge for user security and financial safety. In this paper, we present the Anticipate, Simulate, Reason (ASR) framework, a generative AI method that enables users to proactively identify and comprehend scams within instant messaging platforms. Using large language models, ASR predicts scammer responses, creates realistic scam conversations, and delivers real-time, interpretable support to end-users. We develop ScamGPT-J, a domain-sp…

PhysUniBench: An Undergraduate-Level Physics Reasoning Benchmark for Multimodal Models
Lintao Wang, Encheng Su, Jiaqi Liu, Pengze Li, Peng Xia, Jiabei Xiao, Wenlong Zhang, Xinnan Dai, Xi Chen, Yuan Meng, Mingyu Ding, Lei Bai, Wanli Ouyang, Shixiang Tang, Aoran Wang, Xinzhu Ma
https://arxiv.org/abs/2506.17667

PhysUniBench: An Undergraduate-Level Physics Reasoning Benchmark for Multimodal Models
Physics problem-solving is a challenging domain for large AI models, requiring integration of conceptual understanding, mathematical reasoning, and interpretation of physical diagrams. Current evaluation methodologies show notable limitations in capturing the breadth and complexity of undergraduate-level physics, underscoring the need for more rigorous assessments. To this end, we present PhysUniBench, a large-scale multimodal benchmark designed to evaluate and improve the reasoning capabilitie…

citeseer: CiteSeer citations (2014)
Citations among papers indexed by the CiteSeer digital library. If a paper i cites a paper j also in this data set, then a directed edge connects i to j. (Papers not in the data set are excluded.) Self-loops may be present.
This network has 384413 nodes and 1751463 edges.
Tags: Informational, Citation, Unweighted

Quantum optical model of an artificial neuron
Vivek Mehta, Utpal Roy
https://arxiv.org/abs/2507.17349 https://arxiv.org/pdf/2507.17349

Quantum optical model of an artificial neuron
Magnini \emph{et al.} [\emph{Mach. Learn.: Sci. Technol. 1 (2020) 045008}] recently introduced a qubit-based model of an artificial neuron, along with its applications. The design of its quantum circuit is pivotal for effective implementation. In this context, we present two quantum circuit synthesis algorithms tailored for the realisation of the quantum neuron. Comprehensive circuit simulations are conducted, and the resulting performance is assessed using the circuit cost metric. Additionally…

Integrating Maneuverable Planning and Adaptive Control for Robot Cart-Pushing under Disturbances
Zhe Zhang, Peijia Xie, Zhirui Sun, Bingyi Xia, Bi-Ke Zhu, Jiankun Wang
https://arxiv.org/abs/2506.18410

Integrating Maneuverable Planning and Adaptive Control for Robot Cart-Pushing under Disturbances
Precise and flexible cart-pushing is a challenging task for mobile robots. The motion constraints during cart-pushing and the robot's redundancy lead to complex motion planning problems, while variable payloads and disturbances present complicated dynamics. In this work, we propose a novel planning and control framework for flexible whole-body coordination and robust adaptive control. Our motion planning method employs a local coordinate representation and a novel kinematic model to solve a non…

Challenges and Practices in Quantum Software Testing and Debugging: Insights from Practitioners
Jake Zappin, Trevor Stalnaker, Oscar Chaparro, Denys Poshyvanyk
https://arxiv.org/abs/2506.17306

Challenges and Practices in Quantum Software Testing and Debugging: Insights from Practitioners
Quantum software engineering is an emerging discipline with distinct challenges, particularly in testing and debugging. As quantum computing transitions from theory to implementation, developers face issues not present in classical software development, such as probabilistic execution, limited observability, shallow abstractions, and low awareness of quantum-specific tools. To better understand current practices, we surveyed 26 quantum software developers from academia and industry and conducte…

DataWink: Reusing and Adapting SVG-based Visualization Examples with Large Multimodal Models
Liwenhan Xie, Yanna Lin, Can Liu, Huamin Qu, Xinhuan Shu
https://arxiv.org/abs/2507.17734

DataWink: Reusing and Adapting SVG-based Visualization Examples with Large Multimodal Models
Creating aesthetically pleasing data visualizations remains challenging for users without design expertise or familiarity with visualization tools. To address this gap, we present DataWink, a system that enables users to create custom visualizations by adapting high-quality examples. Our approach combines large multimodal models (LMMs) to extract data encoding from existing SVG-based visualization examples, featuring an intermediate representation of visualizations that bridges primitive SVG an…

The Postman: A Journey of Ethical Hacking in PosteID/SPID Borderland
Gabriele Costa
https://arxiv.org/abs/2507.17007 https://arxiv.org/pdf/2507.17007

The Postman: A Journey of Ethical Hacking in PosteID/SPID Borderland
This paper presents a vulnerability assessment activity that we carried out on PosteID, the implementation of the Italian Public Digital Identity System (SPID) by Poste Italiane. The activity led to the discovery of a critical privilege escalation vulnerability, which was eventually patched. The overall analysis and disclosure process represents a valuable case study for the community of ethical hackers. In this work, we present both the technical steps and the details of the disclosure process.

Reflective Verbal Reward Design for Pluralistic Alignment
Carter Blair, Kate Larson, Edith Law
https://arxiv.org/abs/2506.17834 https://

Reflective Verbal Reward Design for Pluralistic Alignment
AI agents are commonly aligned with "human values" through reinforcement learning from human feedback (RLHF), where a single reward model is learned from aggregated human feedback and used to align an agent's behavior. However, human values are not homogeneous--different people hold distinct and sometimes conflicting values. Aggregating feedback into a single reward model risks disproportionately suppressing minority preferences. To address this, we present a novel reward modeling approach for …

Hardware-efficient quantum phase estimation via local control
Benjamin F. Schiffer, Dominik S. Wild, Nishad Maskara, Mikhail D. Lukin, J. Ignacio Cirac
https://arxiv.org/abs/2506.18765

Hardware-efficient quantum phase estimation via local control
Quantum phase estimation plays a central role in quantum simulation as it enables the study of spectral properties of many-body quantum systems. Most variants of the phase estimation algorithm require the application of the global unitary evolution conditioned on the state of one or more auxiliary qubits, posing a significant challenge for current quantum devices. In this work, we present an approach to quantum phase estimation that uses only locally controlled operations, resulting in a signif…

Online Adaptation for Flying Quadrotors in Tight Formations
Pei-An Hsieh, Kong Yao Chee, M. Ani Hsieh
https://arxiv.org/abs/2506.17488 https://

Online Adaptation for Flying Quadrotors in Tight Formations
The task of flying in tight formations is challenging for teams of quadrotors because the complex aerodynamic wake interactions can destabilize individual team members as well as the team. Furthermore, these aerodynamic effects are highly nonlinear and fast-paced, making them difficult to model and predict. To overcome these challenges, we present L1 KNODE-DW MPC, an adaptive, mixed expert learning based control framework that allows individual quadrotors to accurately track trajectories while …

Large Language Model Unlearning for Source Code
Xue Jiang, Yihong Dong, Zheng Fang, Yingwei Ma, Tangxinyu Wang, Rongyu Cao, Binhua Li, Zhi Jin, Wenpin Jiao, Yongbin Li, Ge Li
https://arxiv.org/abs/2506.17125

Large Language Model Unlearning for Source Code
LLM4SE has demonstrated significant success, but LLMs' potential memorization of sensitive or outdated training data introduces critical risks to legal compliance, software security, and code quality. LLM unlearning techniques, which can eliminate the influence of undesired data from LLMs in a post-training way, present a promising solution to address these concerns. While recent efforts in LLM unlearning show effectiveness in natural language, their applicability to source code remains underex…

Sudoku: Decomposing DRAM Address Mapping into Component Functions
Minbok Wi, Seungmin Baek, Seonyong Park, Mattan Erez, Jung Ho Ahn
https://arxiv.org/abs/2506.15918

Sudoku: Decomposing DRAM Address Mapping into Component Functions
Decomposing DRAM address mappings into component-level functions is critical for understanding memory behavior and enabling precise RowHammer attacks, yet existing reverse-engineering methods fall short. We introduce novel timing-based techniques leveraging DRAM refresh intervals and consecutive access latencies to infer component-specific functions. Based on this, we present Sudoku, the first software-based tool to automatically decompose full DRAM address mappings into channel, rank, bank gro…

T-CPDL: A Temporal Causal Probabilistic Description Logic for Developing Logic-RAG Agent
Hong Qing Yu
https://arxiv.org/abs/2506.18559 https://

T-CPDL: A Temporal Causal Probabilistic Description Logic for Developing Logic-RAG Agent
Large language models excel at generating fluent text but frequently struggle with structured reasoning involving temporal constraints, causal relationships, and probabilistic reasoning. To address these limitations, we propose Temporal Causal Probabilistic Description Logic (T-CPDL), an integrated framework that extends traditional Description Logic with temporal interval operators, explicit causal relationships, and probabilistic annotations. We present two distinct variants of T-CPDL: one ca…

Distilling On-device Language Models for Robot Planning with Minimal Human Intervention
Zachary Ravichandran, Ignacio Hounie, Fernando Cladera, Alejandro Ribeiro, George J. Pappas, Vijay Kumar
https://arxiv.org/abs/2506.17486

Distilling On-device Language Models for Robot Planning with Minimal Human Intervention
Large language models (LLMs) provide robots with powerful contextual reasoning abilities and a natural human interface. Yet, current LLM-enabled robots typically depend on cloud-hosted models, limiting their usability in environments with unreliable communication infrastructure, such as outdoor or industrial settings. We present PRISM, a framework for distilling small language model (SLM)-enabled robot planners that run on-device with minimal human supervision. Starting from an existing LLM-ena…

Evaluation Guidelines for Empirical Studies in Software Engineering involving LLMs
Sebastian Baltes, Florian Angermeir, Chetan Arora, Marvin Mu\~noz Bar\'on, Chunyang Chen, Lukas B\"ohme, Fabio Calefato, Neil Ernst, Davide Falessi, Brian Fitzgerald, Davide Fucci, Marcos Kalinowski, Stefano Lambiase, Daniel Russo, Mircea Lungu, Lutz Prechelt, Paul Ralph, Christoph Treude, Stefan Wagner

Evaluation Guidelines for Empirical Studies in Software Engineering involving LLMs
Large language models (LLMs) are increasingly being integrated into software engineering (SE) research and practice, yet their non-determinism, opaque training data, and evolving architectures complicate the reproduction and replication of empirical studies. We present a community effort to scope this space, introducing a taxonomy of LLM-based study types together with eight guidelines for designing and reporting empirical studies involving LLMs. The guidelines present essential (must) criteria…

Exploring Large Language Models for Analyzing and Improving Method Names in Scientific Code
Gunnar Larsen, Carol Wong, Anthony Peruma
https://arxiv.org/abs/2507.16439

Exploring Large Language Models for Analyzing and Improving Method Names in Scientific Code
Research scientists increasingly rely on implementing software to support their research. While previous research has examined the impact of identifier names on program comprehension in traditional programming environments, limited work has explored this area in scientific software, especially regarding the quality of method names in the code. The recent advances in Large Language Models (LLMs) present new opportunities for automating code analysis tasks, such as identifier name appraisals and …