Tootfinder

This https://arxiv.org/abs/2404.15104 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Identifying Fairness Issues in Automatically Generated Testing Content
Natural language generation tools are powerful and effective for generating content. However, language models are known to display bias and fairness issues, making them impractical to deploy for many use cases. We here focus on how fairness issues impact automatically generated test content, which can have stringent requirements to ensure the test measures only what it was intended to measure. Specifically, we identify test content that is focused on particular domains and experiences that only…

This https://arxiv.org/abs/2304.07548 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

MR-Scout: Automated Synthesis of Metamorphic Relations from Existing Test Cases
Metamorphic Testing (MT) alleviates the oracle problem by defining oracles based on metamorphic relations (MRs), that govern multiple related inputs and their outputs. However, designing MRs is challenging, as it requires domain-specific knowledge. This hinders the widespread adoption of MT. We observe that developer-written test cases can embed domain knowledge that encodes MRs. Such encoded MRs could be synthesized for testing not only their original programs but also other programs that shar…

This https://arxiv.org/abs/2312.03871 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Hidden yet quantifiable: A lower bound for confounding strength using randomized trials
In the era of fast-paced precision medicine, observational studies play a major role in properly evaluating new treatments in clinical practice. Yet, unobserved confounding can significantly compromise causal conclusions drawn from non-randomized data. We propose a novel strategy that leverages randomized trials to quantify unobserved confounding. First, we design a statistical test to detect unobserved confounding with strength above a given threshold. Then, we use the test to estimate an asym…

A Dual Geometric Test for Forward-Flatness
Bernd Kolar, Johannes Schrotshamer, Markus Sch\"oberl
https://arxiv.org/abs/2404.02816 https://

A Dual Geometric Test for Forward-Flatness
Forward-flatness is a generalization of static feedback linearizability and a special case of a more general flatness concept for discrete-time systems. Recently, it has been shown that this practically quite relevant property can be checked by computing a unique sequence of involutive distributions which generalizes the well-known static feedback linearization test. In this paper, a dual test for forward-flatness based on a unique sequence of integrable codistributions is derived. Since the ma…

This https://arxiv.org/abs/2312.09197 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Model-Free Change Point Detection for Mixing Processes
This paper considers the change point detection problem under dependent samples. In particular, we provide performance guarantees for the MMD-CUSUM test under exponentially $α$, $β$, and fast $ϕ$-mixing processes, which significantly expands its utility beyond the i.i.d. and Markovian cases used in previous studies. We obtain lower bounds for average-run-length (ARL) and upper bounds for average-detection-delay (ADD) in terms of the threshold parameter. We show that the MMD-CUSUM test enjoys…

Building test batteries based on analysing random number generator tests within the framework of algorithmic information theory
Boris Ryabko
https://arxiv.org/abs/2404.02708

Building test batteries based on analysing random number generator tests within the framework of algorithmic information theory
The problem of testing random number generators is considered and it is shown that an approach based on algorithmic information theory allows us to compare the power of different tests in some cases where the available methods of mathematical statistics do not distinguish between the tests. In particular, it is shown that tests based on data compression methods using dictionaries should be included in the test batteries.

Track2Act: Predicting Point Tracks from Internet Videos enables Diverse Zero-shot Robot Manipulation
Homanga Bharadhwaj, Roozbeh Mottaghi, Abhinav Gupta, Shubham Tulsiani
https://arxiv.org/abs/2405.01527

Track2Act: Predicting Point Tracks from Internet Videos enables Diverse Zero-shot Robot Manipulation
We seek to learn a generalizable goal-conditioned policy that enables zero-shot robot manipulation: interacting with unseen objects in novel scenes without test-time adaptation. While typical approaches rely on a large amount of demonstration data for such generalization, we propose an approach that leverages web videos to predict plausible interaction plans and learns a task-agnostic transformation to obtain robot actions in the real world. Our framework,Track2Act predicts tracks of how points…

This https://arxiv.org/abs/2112.13190 has been replaced.
link: https://scholar.google.com/scholar?q=a

Modularity and partially observed graphs
Suppose that there is an unknown underlying graph $G$ on a large vertex set, and we can test only a proportion of the possible edges to check whether they are present in $G$. If $G$ has high modularity, is the observed graph $G'$ likely to have high modularity? We see that this is indeed the case under a mild condition, in a natural model where we test edges at random. We find that $q^*(G') \geq q^*(G)-\varepsilon$ with probability at least $1-\varepsilon$, as long as the expected number edges …

COVID-19 Detection Based on Blood Test Parameters using Various Artificial Intelligence Methods
Kavian Khanjani, Seyed Rasoul Hosseini, Shahrzad Shashaani, Mohammad Teshnehlab
https://arxiv.org/abs/2404.02348

COVID-19 Detection Based on Blood Test Parameters using Various Artificial Intelligence Methods
In 2019, the world faced a new challenge: a COVID-19 disease caused by the novel coronavirus, SARS-CoV-2. The virus rapidly spread across the globe, leading to a high rate of mortality, which prompted health organizations to take measures to control its transmission. Early disease detection is crucial in the treatment process, and computer-based automatic detection systems have been developed to aid in this effort. These systems often rely on artificial intelligence (AI) approaches such as mach…

This https://arxiv.org/abs/2305.10817 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Robust inference of causality in high-dimensional dynamical processes from the Information Imbalance of distance ranks
We introduce an approach which allows detecting causal relationships between variables for which the time evolution is available. Causality is assessed by a variational scheme based on the Information Imbalance of distance ranks, a statistical test capable of inferring the relative information content of different distance measures. We test whether the predictability of a putative driven system Y can be improved by incorporating information from a potential driver system X, without explicitly m…

This https://arxiv.org/abs/2312.17188 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Development of a new CEDAR for kaon identification at the NA62 experiment at CERN
The NA62 experiment at CERN utilises a differential Cherenkov counter with achromatic ring focus (CEDAR) for tagging kaons within an unseparated monochromatic beam of charged hadrons. The CEDAR-H detector was developed to minimise the amount of material in the path of the beam by using hydrogen gas as the radiator medium. The detector was shown to satisfy the kaon tagging requirements in a test-beam before installation and commissioning at the experiment. The CEDAR-H performance was measured us…

Technical Report on BaumEvA Evolutionary Optimization Python-Library Testing
Vadim Tynchenko, Aleksei Kudryavtsev, Vladimir Nelyub, Aleksei Borodulin, Andrei Gantimurov
https://arxiv.org/abs/2405.00686

Technical Report on BaumEvA Evolutionary Optimization Python-Library Testing
This report presents the test results Python library BaumEvA, which implements evolutionary algorithms for optimizing various types of problems, including computer vision tasks accompanied by the search for optimal model architectures. Testing was carried out to evaluate the effectiveness and reliability of the pro-posed methods, as well as to determine their applicability in various fields. Dur-ing testing, various test functions and parameters of evolutionary algorithms were used, which made …

Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds
Adam R. Klivans, Konstantinos Stavropoulos, Arsen Vasilyan
https://arxiv.org/abs/2404.02364

Learning Intersections of Halfspaces with Distribution Shift: Improved Algorithms and SQ Lower Bounds
Recent work of Klivans, Stavropoulos, and Vasilyan initiated the study of testable learning with distribution shift (TDS learning), where a learner is given labeled samples from training distribution $\mathcal{D}$, unlabeled samples from test distribution $\mathcal{D}'$, and the goal is to output a classifier with low error on $\mathcal{D}'$ whenever the training samples pass a corresponding test. Their model deviates from all prior work in that no assumptions are made on $\mathcal{D}'$. Instea…

X-Shooting ULLYSES: Massive stars at low metallicity -- V. Effect of metallicity on surface abundances of O stars
F. Martins (CNRS & University of Montpellier), J. -C. Bouret (CNRS & University of Aix-Marseille), D. J. Hillier (University of Pittsburgh), S. A. Brands (University of Amsterdam), P. A. Crowther (University of Sheffield), A. Herrero (IAC, University of La Laguna), F. Najarro (CSIC-INTA), D. Pauli (University of Potsdam), J. Puls (University of Munich), V. Ramachand…

X-Shooting ULLYSES: Massive stars at low metallicity -- V. Effect of metallicity on surface abundances of O stars
Massive stars rotate faster, on average, than lower mass stars. Stellar rotation triggers hydrodynamical instabilities which transport angular momentum and chemical species from the core to the surface. Models of high-mass stars that include these processes predict that chemical mixing is stronger at lower metallicity. We aim to test this prediction by comparing the surface abundances of massive stars at different metallicities. We performed a spectroscopic analysis of single O stars in the Mag…

This https://arxiv.org/abs/2310.06729 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

CMB-S4: Iterative Internal Delensing and $r$ Constraints
The tightest constraints on the tensor-to-scalar ratio $r$ can only be obtained after removing a substantial fraction of the lensing $B$-mode sample variance. The planned CMB-S4 experiment will remove the lensing $B$-mode signal internally by reconstructing the gravitational lenses from high-resolution observations. We document here a first lensing reconstruction pipeline able to achieve this optimally for arbitrary sky coverage. We make it part of a map-based framework to test CMB-S4 delensing…

Natural Language to Verilog: Design of a Recurrent Spiking Neural Network using Large Language Models and ChatGPT
Paola Vitolo, George Psaltakis, Michael Tomlinson, Gian Domenico Licciardo, Andreas G. Andreou
https://arxiv.org/abs/2405.01419

Natural Language to Verilog: Design of a Recurrent Spiking Neural Network using Large Language Models and ChatGPT
This paper investigates the use of Large Language Models (LLMs) for automating the generation of hardware description code, aiming to explore their potential in supporting and enhancing the development of efficient neuromorphic computing architectures. Building on our prior work, we employ OpenAI's ChatGPT4 and natural language prompts to synthesize a RTL Verilog module of a programmable recurrent spiking neural network, while also generating test benches to assess the system's correctness. The…

This https://arxiv.org/abs/2402.10962 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCL_…

Measuring and Controlling Instruction (In)Stability in Language Model Dialogs
System-prompting is a standard tool for customizing language-model chatbots, enabling them to follow a specific instruction. An implicit assumption in the use of system prompts is that they will be stable, so the chatbot will continue to generate text according to the stipulated instructions for the duration of a conversation. We propose a quantitative benchmark to test this assumption, evaluating instruction stability via self-chats between two instructed chatbots. Testing popular models like …

ForTune: Running Offline Scenarios to Estimate Impact on Business Metrics
Georges DupretLeo, Konstantin SozinovLeo, Carmen Barcena GonzalezLeo, Ziggy ZacksLeo, Amber YuanLeo, Benjamin CarteretteLeo, Manuel MaiLeo, Shubham BansalLeo, Gwo LiangLeo, Lien, Andrey Gatash, Roberto Sanchis Ojeda, Mounia Lalmas
https://arxiv.org/abs/24…

ForTune: Running Offline Scenarios to Estimate Impact on Business Metrics
Making ideal decisions as a product leader in a web-facing company is extremely difficult. In addition to navigating the ambiguity of customer satisfaction and achieving business goals, one must also pave a path forward for ones' products and services to remain relevant, desirable, and profitable. Data and experimentation to test product hypotheses are key to informing product decisions. Online controlled experiments by A/B testing may provide the best data to support such decisions with high c…

This https://arxiv.org/abs/2401.11632 has been replaced.
link: https://scholar.google.com/scholar?q=a

What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders
In the past decade, deep learning (DL) models have gained prominence for their exceptional accuracy on benchmark datasets in recommender systems (RecSys). However, their evaluation has primarily relied on offline metrics, overlooking direct user perception and experience. To address this gap, we conduct a human-centric evaluation case study of four leading DL-RecSys models in the movie domain. We test how different DL-RecSys models perform in personalized recommendation generation by conducting…

An approach for performance requirements verification and test environments generation
Waleed Abdeen, Xingru Chen, Michael Unterkalmsteiner
https://arxiv.org/abs/2403.00099

An approach for performance requirements verification and test environments generation
Model-based testing (MBT) is a method that supports the design and execution of test cases by models that specify the intended behaviors of a system under test. While systematic literature reviews on MBT in general exist, the state of the art on modeling and testing performance requirements has seen much less attention. Therefore, we conducted a systematic mapping study on model-based performance testing. Then, we studied natural language software requirements specifications in order to underst…

This https://arxiv.org/abs/2402.03472 has been replaced.
link: https://scholar.google.com/scholar?q=a

An efficient prescription to search for linear gravitational wave memory in pulsar timing array data and its application to the NANOGrav 12.5-year dataset
Burst with memory events are potential transient gravitational wave sources for the maturing pulsar timing array (PTA) efforts. We provide a computationally efficient prescription to model pulsar timing residuals induced by supermassive black hole pairs in general relativistic hyperbolic trajectories employing a Keplerian-type parametric solution. Injection studies have been pursued on the resulting bursts with linear GW memory (LGWM) events with simulated datasets to test the performance of ou…

This https://arxiv.org/abs/2307.03894 has been replaced.
initial toot: https://mastoxiv.page/@ar…

The Performance of AC-coupled Strip LGAD developed by IHEP
The AC-coupled Strip LGAD (Strip AC-LGAD) is a novel LGAD design that diminishes the density of readout electronics through the use of strip electrodes, enabling the simultaneous measurement of time and spatial information. The Institute of High Energy Physics has designed a long Strip AC-LGAD prototype with a strip electrode length of 5.7 mm and pitches of 150 $μm$, 200 $μm$, and 250 $μm$. Spatial and timing resolutions of the long Strip AC-LGAD are studied by pico-second laser test and bet…

Impact of Diffusion on synchronization pattern of epidemics in nonidentical metapopulation networks
Anika Roy, Ujjwal Shekhar, Aditi Bose, Subrata Ghosh, Santosh Nannuru, Syamal Kumar Dana, Chittaranjan Hens
https://arxiv.org/abs/2403.00681

Impact of Diffusion on synchronization pattern of epidemics in nonidentical metapopulation networks
In a prior study, a novel deterministic compartmental model known as the SEIHRK model was introduced, shedding light on the pivotal role of test kits as an intervention strategy for mitigating epidemics. Particularly in heterogeneous networks, it was empirically demonstrated that strategically distributing a limited number of test kits among nodes with higher degrees substantially diminishes the outbreak size. The network's dynamics were explored under varying values of infection rate. In this …

Unification in the description logic $\mathcal{FL}_\bot$
Barbara Morawska
https://arxiv.org/abs/2405.00912 https://arxiv.org/pdf/2405…

Unification in the description logic $\mathcal{FL}_\bot$
Description Logics are a formalism used in the knowledge representation, where the knowledge is captured in the form of concepts constructed in a controlled way from a restricted vocabulary. This allows one to test effectively for consistency of and the subsumption between the concepts. Unification of concepts may likewise become a useful tool in analysing the relations between concepts. The unification problem has been solved for the description logics $\mathcal{FL}_0$ and $\mathcal{EL}$. Thes…

This https://arxiv.org/abs/2401.12362 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

VC dimension of Graph Neural Networks with Pfaffian activation functions
Graph Neural Networks (GNNs) have emerged in recent years as a powerful tool to learn tasks across a wide range of graph domains in a data-driven fashion; based on a message passing mechanism, GNNs have gained increasing popularity due to their intuitive formulation, closely linked with the Weisfeiler-Lehman (WL) test for graph isomorphism, to which they have proven equivalent. From a theoretical point of view, GNNs have been shown to be universal approximators, and their generalization capabil…

This https://arxiv.org/abs/2109.10561 has been replaced.
link: https://scholar.google.com/scholar?q=a

A Few-Shot Learning Approach for Sound Source Distance Estimation Using Relation Networks
In this paper, we study the performance of few-shot learning, specifically meta learning empowered few-shot relation networks, over supervised deep learning and conventional machine learning approaches in the problem of Sound Source Distance Estimation (SSDE). In previous research on deep supervised SSDE, low accuracies have often resulted from the mismatch between the training data (from known environments) and the test data (from unknown environments). By performing comparative experiments on…

Neural-Parareal: Dynamically Training Neural Operators as Coarse Solvers for Time-Parallelisation of Fusion MHD Simulations
S. J. P. Pamela, N. Carey, J. Brandstetter, R. Akers, L. Zanisi, J. Buchanan, V. Gopakumar, M. Hoelzl, G. Huijsmans, K. Pentland, T. James, G. Antonucci, the JOREK Team
https://arxiv.org/abs/2405.01355

Neural-Parareal: Dynamically Training Neural Operators as Coarse Solvers for Time-Parallelisation of Fusion MHD Simulations
The fusion research facility ITER is currently being assembled to demonstrate that fusion can be used for industrial energy production, while several other programmes across the world are also moving forward, such as EU-DEMO, CFETR, SPARC and STEP. The high engineering complexity of a tokamak makes it an extremely challenging device to optimise, and test-based optimisation would be too slow and too costly. Instead, digital design and optimisation must be favored, which requires strongly-coupled…

This https://arxiv.org/abs/2402.13892 has been replaced.
initial toot: https://mastoxiv.page/@arXi…

Variational Umbrella Seeding for Calculating Nucleation Barriers
In this work, we introduce Variational Umbrella Seeding, a novel technique for computing nucleation barriers. This new method, a refinement of the original seeding approach, is far less sensitive to the choice of order parameter for measuring the size of a nucleus. Consequently, it surpasses seeding in accuracy, and Umbrella Sampling in computational speed. We test the method extensively and demonstrate excellent accuracy for crystal nucleation of nearly hard spheres and of two distinct models …

Nearly Optimum Properties of Certain Multi-Decision Sequential Rules for General Non-i.i.d. Stochastic Models
Alexander G. Tartakovsky
https://arxiv.org/abs/2405.00928

Nearly Optimum Properties of Certain Multi-Decision Sequential Rules for General Non-i.i.d. Stochastic Models
Dedicated to the memory of Professor Tze Leung Lai, this paper introduces three multi-hypothesis sequential tests. These tests are derived from one-sided versions of the sequential probability ratio test and its modifications. They are proven to be first-order asymptotically optimal for testing simple and parametric composite hypotheses when error probabilities are small. These tests exhibit near optimality properties not only in classical i.i.d. observation models but also in general non-i.i.d…

Penalty-free discontinuous Galerkin method
Jan Ja\'skowiec, N. Sukumar
https://arxiv.org/abs/2403.00125 https://arxiv.org/pdf/240…

Penalty-free discontinuous Galerkin method
In this paper, we present a new high-order discontinuous Galerkin (DG) method, in which neither a penalty parameter nor a stabilization parameter is needed. We refer to this method as penalty-free DG (\PFDG). In this method, the trial and test functions belong to the broken Sobolev space, in which the functions are in general discontinuous on the mesh skeleton and do not meet the Dirichlet boundary conditions. However, a subset can be distinguished in this space, where the functions are continu…

Size-Mass Relations for Simulated Low-Mass Galaxies: Mock Imaging versus Intrinsic Properties
Courtney Klein, James S. Bullock, Jorge Moreno, Francisco J. Mercado, Philip F. Hopkins, Rachel K. Cochrane, Jose A. Benavides
https://arxiv.org/abs/2404.02373

Size-Mass Relations for Simulated Low-Mass Galaxies: Mock Imaging versus Intrinsic Properties
The observationally-inferred size versus stellar-mass relationship for low-mass galaxies provides an important test for galaxy formation models. However, the relationship relies on assumptions that relate observed luminosity profiles to underlying stellar mass profiles. We use the Feedback in Realistic Environments (FIRE-2) simulations of low-mass galaxies to explore how the predicted size-mass relation (SMR) changes depending on whether one uses star-particle counts directly or mock observatio…

Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems
Lennart Vater, Sven Tarlowski, Lutz Eckstein
https://arxiv.org/abs/2404.02599

Determining the Tactical Challenge of Scenarios to Efficiently Test Automated Driving Systems
The selection of relevant test scenarios for the scenario-based testing and safety validation of automated driving systems (ADSs) remains challenging. An important aspect of the relevance of a scenario is the challenge it poses for an ADS. Existing methods for calculating the challenge of a scenario aim to express the challenge in terms of a metric value. Metric values are useful to select the least or most challenging scenario. However, they fail to provide human-interpretable information on t…

This https://arxiv.org/abs/2311.13359 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Experimental determination of axion signal power of dish antennas and dielectric haloscopes using the reciprocity approach
The reciprocity approach is a powerful method to determine the expected signal power of axion haloscopes in a model-independent way. Especially for open and broadband setups like the MADMAX dielectric haloscope the sensitivity to the axion field is difficult to calibrate since they do not allow discrete eigenmode analysis and are optically too large to fully simulate. The central idea of the reciprocity approach is to measure a reflection-induced test field in the setup instead of trying to sim…

This https://arxiv.org/abs/2402.15640 has been replaced.
initial toot: https://mastoxiv.page/@arX…

In-Depth Search for a Coupling between Gravity and Electromagnetism with Steady Fields
Any means to control gravity like electromagnetism is currently out of reach by many orders of magnitude even under extreme laboratory conditions. Some often poorly executed experiments or pseudoscience theories appear from time to time claiming for example anomalous forces from capacitors that suggest a connection between the two fields. We developed novel and high resolution horizontal-, vertical- and rotation-balances that allow to test electric devices completely shielded and remotely contr…

Curiosity-driven Red-teaming for Large Language Models
Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang, Aldo Pareja, James Glass, Akash Srivastava, Pulkit Agrawal
https://arxiv.org/abs/2402.19464

Curiosity-driven Red-teaming for Large Language Models
Large language models (LLMs) hold great potential for many natural language applications but risk generating incorrect or toxic content. To probe when an LLM generates unwanted content, the current paradigm is to recruit a \textit{red team} of human testers to design input prompts (i.e., test cases) that elicit undesirable responses from LLMs. However, relying solely on human testers is expensive and time-consuming. Recent works automate red teaming by training a separate red team LLM with rein…

Motion of test particles in quasi anti-de Sitter regular black holes
Dario Corona, Roberto Giamb\`o, Orlando Luongo
https://arxiv.org/abs/2402.18997 https:…

Motion of test particles in quasi anti-de Sitter regular black holes
We explore the characteristics of two novel regular spacetimes that exhibit a non-zero vacuum energy term, under the form of a (quasi) anti-de Sitter phase. Specifically, the first metric is spherical, while the second, derived by applying the generalized Newman-Janis algorithm to the first, is axisymmetric. We show that the equations of state of the effective fluids associated with the two metrics asymptotically tend to negative values, resembling quintessence. In addition, we study test parti…

This https://arxiv.org/abs/2309.08660 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Astronomaly at scale: searching for anomalies amongst 4 million galaxies
Modern astronomical surveys are producing datasets of unprecedented size and richness, increasing the potential for high-impact scientific discovery. This possibility, coupled with the challenge of exploring a large number of sources, has led to the development of novel machine-learning-based anomaly detection approaches, such as Astronomaly. For the first time, we test the scalability of Astronomaly by applying it to almost 4 million images of galaxies from the Dark Energy Camera Legacy Survey…

A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio
Heather Prince, Erminia Calabrese, Jo Dunkley
https://arxiv.org/abs/2403.00085

A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio
The current limit on the tensor-to-scalar ratio from the BICEP/Keck Collaboration (with r<0.036 at 95% confidence) puts pressure on early universe models, with less than 10% of the error on r attributed to uncertainty in Galactic foregrounds. We use the BICEP/Keck BK18 public multi-frequency likelihood to test some further assumptions made in the foreground modeling, finding little impact on the estimate for r. We then estimate foreground-marginalized cosmic microwave background (CMB) B-mode po…

Weighted low-lying zeros of L-functions attached to Siegel modular forms
Shifan Zhao
https://arxiv.org/abs/2403.19687 https://arxiv.o…

Weighted low-lying zeros of L-functions attached to Siegel modular forms
In this paper, we study weighted low-lying zeros of spinor and standard $L$-functions attached to degree 2 Siegel modular forms. We show the symmetry type of weighted low-lying zeros of spinor $L$-functions is symplectic, for test functions whose Fourier transform have support in $(-1,1)$, extending the previous range $(-\frac{4}{15},\frac{4}{15})$ by E. Kowalski, A. Saha and J. Tsimerman . We then show the symmetry type of weighted low-lying zeros of standard $L$-functions is also symplectic. …

Overcoming model uncertainty -- how equivalence tests can benefit from model averaging
Niklas Hagemann, Kathrin M\"ollenhoff
https://arxiv.org/abs/2405.00827

Overcoming model uncertainty -- how equivalence tests can benefit from model averaging
A common problem in numerous research areas, particularly in clinical trials, is to test whether the effect of an explanatory variable on an outcome variable is equivalent across different groups. In practice, these tests are frequently used to compare the effect between patient groups, e.g. based on gender, age or treatments. Equivalence is usually assessed by testing whether the difference between the groups does not exceed a pre-specified equivalence threshold. Classical approaches are based…

Karma: An Experimental Study
Ezzat Elokda, Heinrich Nax, Saverio Bolognani, Florian D\"orfler
https://arxiv.org/abs/2404.02687 https://

Karma: An Experimental Study
A system of non-tradable credits that flow between individuals like karma, hence proposed under that name, is a mechanism for repeated resource allocation that comes with attractive efficiency and fairness properties, in theory. In this study, we test karma in an online experiment in which human subjects repeatedly compete for a resource with time-varying and stochastic individual preferences or urgency to acquire the resource. We confirm that karma has significant and sustained welfare benefit…

Stochastic fluids with transport noise: Approximating diffusion from data using SVD and ensemble forecast back-propagation
James Woodfield
https://arxiv.org/abs/2405.00640

Stochastic fluids with transport noise: Approximating diffusion from data using SVD and ensemble forecast back-propagation
We introduce and test methods for the calibration of the diffusion term in Stochastic Partial Differential Equations (SPDEs) describing fluids. We take two approaches, one uses ideas from the singular value decomposition and the Biot-Savart law. The other backpropagates through an ensemble forecast, with respect to diffusion parameters, to minimise a probabilistic ensemble forecasting metric. We describe the approaches in the specific context of solutions to SPDEs describing the evolution of fl…

This https://arxiv.org/abs/2204.00473 has been replaced.
link: https://scholar.google.com/scholar?q=a

Finite Sample Inference in Incomplete Models
We propose confidence regions for the parameters of incomplete models with exact coverage of the true parameter in finite samples. Our confidence region inverts a test, which generalizes Monte Carlo tests to incomplete models. The test statistic is a discrete analogue of a new optimal transport characterization of the sharp identified region. Both test statistic and critical values rely on simulation drawn from the distribution of latent variables and are computed using solutions to discrete op…

Automated User Story Generation with Test Case Specification Using Large Language Model
Tajmilur Rahman, Yuecai Zhu
https://arxiv.org/abs/2404.01558 https:…

Automated User Story Generation with Test Case Specification Using Large Language Model
Modern Software Engineering era is moving fast with the assistance of artificial intelligence (AI), especially Large Language Models (LLM). Researchers have already started automating many parts of the software development workflow. Requirements Engineering (RE) is a crucial phase that begins the software development cycle through multiple discussions on a proposed scope of work documented in different forms. RE phase ends with a list of user-stories for each unit task identified through discus…

Test function approach to fully nonlinear equations in thin domains
Isabeau Birindelli, Ariela Briani, Hitoshi Ishii
https://arxiv.org/abs/2404.19577 https://arxiv.org/pdf/2404.19577
arXiv:2404.19577v1 Announce Type: new
Abstract: In this note we extend to fully nonlinear operators the well known result on thin domains of Hale and Raugel. The result is more general even in the case of the Laplacian.

https://dice.camp/@seedling/111925053586704530
The layout is done - I think I figured out an overly complicated way to get some things to the edge of my page on the printer.
Also finished the Goblin-Cat Stamp of Limited Edition Handmade Zines

The ancient Egyptian personification of the Milky Way as the Sky Goddess Nut: an astronomical and cross-cultural analysis
Or Graur
https://arxiv.org/abs/2404.01458

The ancient Egyptian personification of the Milky Way as the Sky Goddess Nut: an astronomical and cross-cultural analysis
The Milky Way's name and role in ancient Egyptian culture remain unclear. One suggestion is that the Milky Way may have been a celestial depiction of the sky goddess Nut. In this work, I test this association using an interdisciplinary approach. In the first part of this paper, I combine astronomical simulations of the ancient Egyptian night sky with primary Egyptian sources to map the goddess Nut onto the Milky Way. With her head and groin firmly associated by primary texts with the western an…

FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality
Sai Li, Linjun Zhang
https://arxiv.org/abs/2404.01608

FAIRM: Learning invariant representations for algorithmic fairness and domain generalization with minimax optimality
Machine learning methods often assume that the test data have the same distribution as the training data. However, this assumption may not hold due to multiple levels of heterogeneity in applications, raising issues in algorithmic fairness and domain generalization. In this work, we address the problem of fair and generalizable machine learning by invariant principles. We propose a training environment-based oracle, FAIRM, which has desirable fairness and domain generalization properties under …

The Convergence of AI and Synthetic Biology: The Looming Deluge
Cindy Vindman, Benjamin Trump, Christopher Cummings, Madison Smith, Alexander J. Titus, Ken Oye, Valentina Prado, Eyup Turmus, Igor Linkov
https://arxiv.org/abs/2404.18973 https://arxiv.org/pdf/2404.18973
arXiv:2404.18973v1 Announce Type: new
Abstract: The convergence of artificial intelligence (AI) and synthetic biology is rapidly accelerating the pace of biological discovery and engineering. AI techniques, such as large language models and biological design tools, are enabling the automated design, build, test, and learning cycles for engineered biological systems. This convergence promises to democratize synthetic biology and unlock novel applications across domains from medicine to environmental sustainability. However, it also poses significant risks around reliability, dual use, and governance. The opacity of AI models, the deskilling of workforces, and the outdated nature of current regulatory frameworks present challenges in ensuring responsible development. Urgent attention is needed to update governance structures, integrate human oversight into increasingly automated workflows, and foster a culture of responsibility among the growing community of bioengineers. Only by proactively addressing these issues can we realize the transformative potential of AI-driven synthetic biology while mitigating its risks.

A Framework for Leveraging Human Computation Gaming to Enhance Knowledge Graphs for Accuracy Critical Generative AI Applications
Steph Buongiorno, Corey Clark
https://arxiv.org/abs/2404.19729 https://arxiv.org/pdf/2404.19729
arXiv:2404.19729v1 Announce Type: new
Abstract: External knowledge graphs (KGs) can be used to augment large language models (LLMs), while simultaneously providing an explainable knowledge base of facts that can be inspected by a human. This approach may be particularly valuable in domains where explainability is critical, like human trafficking data analysis. However, creating KGs can pose challenges. KGs parsed from documents may comprise explicit connections (those directly stated by a document) but miss implicit connections (those obvious to a human although not directly stated). To address these challenges, this preliminary research introduces the GAME-KG framework, standing for "Gaming for Augmenting Metadata and Enhancing Knowledge Graphs." GAME-KG is a federated approach to modifying explicit as well as implicit connections in KGs by using crowdsourced feedback collected through video games. GAME-KG is shown through two demonstrations: a Unity test scenario from Dark Shadows, a video game that collects feedback on KGs parsed from US Department of Justice (DOJ) Press Releases on human trafficking, and a following experiment where OpenAI's GPT-4 is prompted to answer questions based on a modified and unmodified KG. Initial results suggest that GAME-KG can be an effective framework for enhancing KGs, while simultaneously providing an explainable set of structured facts verified by humans.

Interplay between Vector-like Lepton and Seesaw Mechanism:Oblique Corrections
Shuyang Han, Zhaofeng Kang, Jiang Zhu
https://arxiv.org/abs/2404.19502 https://arxiv.org/pdf/2404.19502
arXiv:2404.19502v1 Announce Type: new
Abstract: The non-vanishing neutrino mass strongly hints the existence of right-handed neutrinos (RHNs), singlets of the standard model (SM). However, they are highly decoupled from the SM and difficult to probe. In this work, we consider the Majorana RHNs from the type-I seesaw mechanism may well mix with the heavy neutral lepton dwelling in certain vector-like lepton (VLL), thus acquiring a sizable electroweak charge. Such a simple scenario yields many interesting consequences, and the imprint on oblique corrections, well expected from the mass splitting between components of VLL by virtue of VLL-RHN mixing, is our focus here. We analytically calculate the Peskin-Takeuchi parameters S, T and U with full details, carefully treating the Majorana loop to obtain the self consistent expressions free of divergence. Then, we constrain on the VLL-RHN system which only gives a sizable $T$ parameter using the PDG-2021 data and CDF-II data, separately, by imposing $T\lesssim{\cal O}(0.1)$. It is found that for the RHN and VLL below the TeV scale, with a properly large mixing, stands in the frontier of the electroweak precision test such as W-boson mass.

Trans-series from condensates
Marcos Marino, Ramon Miravitllas
https://arxiv.org/abs/2402.19356 https://arxiv.org/pdf/2402.19356

Trans-series from condensates
The Shifman--Vainshtein--Zakharov (SVZ) sum rules provide a method to obtain trans-series expansions in many quantum field theories, in which exponentially small corrections are calculated by combining the operator product expansion with the assumption of vacuum condensates. In some solvable models, exact expressions for trans-series can be obtained from non-perturbative results, and this makes it possible to test the SVZ method by comparing its predictions to these exact trans-series. In this …

This https://arxiv.org/abs/2403.18442 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Backpropagation-free Network for 3D Test-time Adaptation
Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test-Time Adaptation (TTA) methods tend to apply computationally heavy and memory-intensive backpropagation-based approaches to handle this. Here, we propose a novel method that uses a backpropagation-free approach for TTA for the specific case of 3D data. Our model uses a two-stream architecture to maintain knowledge about the source domain as well as complementary target-domain-sp…

When should PIC simulations be applied to atmospheric pressure plasmas? Impact of correlation heating
M. Acciarri, C. Moore, L. P. Beving, S. D. Baalrud
https://arxiv.org/abs/2403.00656

When should PIC simulations be applied to atmospheric pressure plasmas? Impact of correlation heating
Molecular dynamics simulations are used to test when the particle-in-cell (PIC) method applies to atmospheric pressure plasmas. It is found that PIC applies only when the plasma density and macroparticle weight are sufficiently small because of two effects associated with correlation heating. The first is the physical effect of disorder-induced heating (DIH). This occurs if the plasma density is large enough that a species (typically ions) is strongly correlated in the sense that the Coulomb co…

This https://arxiv.org/abs/2212.09201 has been replaced.
link: https://scholar.google.com/scholar?q=a

Spectral Regularized Kernel Two-Sample Tests
Over the last decade, an approach that has gained a lot of popularity to tackle nonparametric testing problems on general (i.e., non-Euclidean) domains is based on the notion of reproducing kernel Hilbert space (RKHS) embedding of probability distributions. The main goal of our work is to understand the optimality of two-sample tests constructed based on this approach. First, we show the popular MMD (maximum mean discrepancy) two-sample test to be not optimal in terms of the separation boundary…

A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio
Heather Prince, Erminia Calabrese, Jo Dunkley
https://arxiv.org/abs/2403.00085

A foreground-marginalized 'BK-lite' likelihood for the tensor-to-scalar ratio
The current limit on the tensor-to-scalar ratio from the BICEP/Keck Collaboration (with r<0.036 at 95% confidence) puts pressure on early universe models, with less than 10% of the error on r attributed to uncertainty in Galactic foregrounds. We use the BICEP/Keck BK18 public multi-frequency likelihood to test some further assumptions made in the foreground modeling, finding little impact on the estimate for r. We then estimate foreground-marginalized cosmic microwave background (CMB) B-mode po…

This https://arxiv.org/abs/2403.06756 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

One-Bit Target Detection in Collocated MIMO Radar with Colored Background Noise
One-bit sampling has emerged as a promising technique in multiple-input multiple-output (MIMO) radar systems due to its ability to significantly reduce data volume and processing requirements. Nevertheless, current detection methods have not adequately addressed the impact of colored noise, which is frequently encountered in real scenarios. In this paper, we present a novel detection method that accounts for colored noise in MIMO radar systems. Specifically, we derive Rao's test by computing th…

This https://arxiv.org/abs/2401.15906 has been replaced.
link: https://scholar.google.com/scholar?q=a

Mean Estimation with User-Level Privacy for Spatio-Temporal IoT Datasets
This paper considers the problem of the private release of sample means of speed values from traffic datasets. Our key contribution is the development of user-level differentially private algorithms that incorporate carefully chosen parameter values to ensure low estimation errors on real-world datasets, while ensuring privacy. We test our algorithms on ITMS (Intelligent Traffic Management System) data from an Indian city, where the speeds of different buses are drawn in a potentially non-i.i.d…

Using this CSS with broken image ref:
```
::before {
content: url(foo) / "Panda";
}
```
Safari / macOS / iPadOS does not show the alt.
Until you turn on VO. Or turn it off. But it goes away if you refresh.
More accurately, it resizes the placeholder; if your alt is small enough to fit *then* it shows.
Attached video shows it in action.
So. What the deal is?
Test page:

Image Fallbacks
...

This https://arxiv.org/abs/2310.09690 has been replaced.
link: https://scholar.google.com/scholar?q=a

Configuration Validation with Large Language Models
Misconfigurations are major causes of software failures. Existing practices rely on developer-written rules or test cases to validate configurations, which are expensive. Machine learning (ML) for configuration validation is considered a promising direction, but has been facing challenges such as the need of large-scale field data and system-specific models. Recent advances in Large Language Models (LLMs) show promise in addressing some of the long-lasting limitations of ML-based configuration …

Lifelong Benchmarks: Efficient Model Evaluation in an Era of Rapid Progress
Ameya Prabhu, Vishaal Udandarao, Philip Torr, Matthias Bethge, Adel Bibi, Samuel Albanie
https://arxiv.org/abs/2402.19472

Lifelong Benchmarks: Efficient Model Evaluation in an Era of Rapid Progress
Standardized benchmarks drive progress in machine learning. However, with repeated testing, the risk of overfitting grows as algorithms over-exploit benchmark idiosyncrasies. In our work, we seek to mitigate this challenge by compiling ever-expanding large-scale benchmarks called Lifelong Benchmarks. As exemplars of our approach, we create Lifelong-CIFAR10 and Lifelong-ImageNet, containing (for now) 1.69M and 1.98M test samples, respectively. While reducing overfitting, lifelong benchmarks intr…

This https://arxiv.org/abs/2310.15717 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Breakdown Performance of Guard Ring Designs for Pixel Detectors in $150~\mathrm{nm}$ CMOS Technology
Silicon pixel sensors manufactured using commercial CMOS processes are promising instruments for high-energy particle physics experiments due to their high yield and proven radiation hardness. As one of the essential factors for the operation of detectors, the breakdown performance of pixel sensors constitutes the upper limit of the operating voltage. Six types of passive CMOS test structures were fabricated on high-resistivity wafers. Each of them features a combination of different inter-pixe…

Towards a Completeness Argumentation for Scenario Concepts
Christoph Glasmacher, Hendrik Weber, Lutz Eckstein
https://arxiv.org/abs/2404.01934 https://

Towards a Completeness Argumentation for Scenario Concepts
Scenario-based testing has become a promising approach to overcome the complexity of real-world traffic for safety assurance of automated vehicles. Within scenario-based testing, a system under test is confronted with a set of predefined scenarios. This set shall ensure more efficient testing of an automated vehicle operating in an open context compared to real-world testing. However, the question arises if a scenario catalog can cover the open context sufficiently to allow an argumentation for…

https://dice.camp/@seedling/111925053586704530
The layout is done - I think I figured out an overly complicated way to get some things to the edge of my page on the printer.
Also finished the Goblin-Cat Stamp of Limited Edition Handmade Zines

This https://arxiv.org/abs/2307.12852 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_hepe…

Observation of $D^+_s\to η^\prime μ^+ν_μ$, Precision Test of Lepton Flavor Universality with $D^+_s\to η^{(\prime)} \ell^+ν_\ell$, and First Measurements of $D^+_s\to η^{(\prime)}μ^+ν_μ$ Decay Dynamics
By analyzing 7.33 fb$^{-1}$ of $e^+e^-$ annihilation data collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector, we report the observation of the semileptonic decay $D^+_s\to η^\prime μ^+ν_μ$, with a statistical significance larger than 10$σ$, and the measurements of the $D_s^+ \to ημ^+ν_μ$ and $D_s^+ \to η^\primeμ^+ν_μ$ decay dynamics for the first time. The branching fractions of $D_s^+ \to ημ^+ν_μ$ and $D_s^+ \to η^\primeμ^+ν_μ$ are de…

A Concept for Semi-Automatic Configuration of Sufficiently Valid Simulation Setups for Automated Driving Systems
Niklas Braun, Markus Steimle, Martin T\"orngren, Markus Maurer
https://arxiv.org/abs/2404.19356

A Concept for Semi-Automatic Configuration of Sufficiently Valid Simulation Setups for Automated Driving Systems
As simulation is increasingly used in scenario-based approaches to test Automated Driving Systems, the credibility of simulation results is a major concern. Arguably, credibility depends on the validity of the simulation setup and simulation models. When selecting appropriate simulation models, a trade-off must be made between validity, often connected to the model's fidelity, and cost of computation. However, due to the large number of test cases, expert-based methods to create sufficiently va…

scenario.center: Methods from Real-world Data to a Scenario Database
Michael Schuldes, Christoph Glasmacher, Lutz Eckstein
https://arxiv.org/abs/2404.02561

scenario.center: Methods from Real-world Data to a Scenario Database
Scenario-based testing is a promising method to develop, verify and validate automated driving systems (ADS) since pure on-road testing seems inefficient for complex traffic environments. A major challenge for this approach is the provision and management of a sufficient number of scenarios to test a system. The provision, generation, and management of scenario at scale is investigated in current research. This paper presents the scenario database scenario.center ( https://scenario.center ) to …

This https://arxiv.org/abs/2102.08809 has been replaced.
link: https://scholar.google.com/scholar?q=a

Testing for Nonlinear Cointegration under Heteroskedasticity
This article discusses tests for nonlinear cointegration in the presence of variance breaks. We build on cointegration test approaches under heteroskedasticity (Cavaliere and Taylor, 2006, Journal of Time Series Analysis) and nonlinearity (Choi and Saikkonen, 2010, Econometric Theory) to propose a bootstrap test and prove its consistency. A Monte Carlo study shows the approach to have satisfactory finite-sample properties. We provide an empirical application to the environmental Kuznets curves …

ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening
Gianmarco Accordi, Davide Gadioli, Giorgio Seguini, Andrea R. Beccari, Gianluca Palermo
https://arxiv.org/abs/2404.19391

ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening
Virtual screening is a technique used in drug discovery to select the most promising molecules to test in a lab. To perform virtual screening, we need a large set of molecules as input, and storing these molecules can become an issue. In fact, extreme-scale high-throughput virtual screening applications require a big dataset of input molecules and produce an even bigger dataset as output. These molecules' databases occupy tens of TB of storage space, and domain experts frequently sample a small…

This https://arxiv.org/abs/2308.01243 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Quasinormal modes of the Schwarzchild black hole with a deficit solid angle and quintessence-like matter: Improved asymptotic iteration method
We study the quasinormal modes (QNM) for scalar, and electromagnetic perturbations in the Schwarzchild black hole with a deficit solid angle and quintessence-like matter. Using the sixth--order WKB approximation and the improved asymptotic iteration method (AIM) we can determine the dependence of the quasinormal modes on the parameters of the black hole and the parameters on the test fields. The values of the real part and imaginary parts of the quasi--normal modes increase with the decrease of…

This https://arxiv.org/abs/2010.11970 has been replaced.
link: https://scholar.google.com/scholar?q=a

Two-sample Test using Projected Wasserstein Distance
We develop a projected Wasserstein distance for the two-sample test, a fundamental problem in statistics and machine learning: given two sets of samples, to determine whether they are from the same distribution. In particular, we aim to circumvent the curse of dimensionality in Wasserstein distance: when the dimension is high, it has diminishing testing power, which is inherently due to the slow concentration property of Wasserstein metrics in the high dimension space. A key contribution is to …

This https://arxiv.org/abs/2311.07740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Towards a classification of isolated $j$-invariants
We develop an algorithm to test whether a non-CM elliptic curve $E/\mathbb{Q}$ gives rise to an isolated point of any degree on any modular curve of the form $X_1(N)$. This builds on prior work of Zywina which gives a method for computing the image of the adelic Galois representation associated to $E$. Running this algorithm on all elliptic curves presently in the $L$-functions and Modular Forms Database and the Stein-Watkins Database gives strong evidence for the conjecture that $E$ gives rise…

PaECTER: Patent-level Representation Learning using Citation-informed Transformers
Mainak Ghosh, Sebastian Erhardt, Michael E. Rose, Erik Buunk, Dietmar Harhoff
https://arxiv.org/abs/2402.19411

PaECTER: Patent-level Representation Learning using Citation-informed Transformers
PaECTER is a publicly available, open-source document-level encoder specific for patents. We fine-tune BERT for Patents with examiner-added citation information to generate numerical representations for patent documents. PaECTER performs better in similarity tasks than current state-of-the-art models used in the patent domain. More specifically, our model outperforms the next-best patent specific pre-trained language model (BERT for Patents) on our patent citation prediction test dataset on two…

GenAI Distortion: The Effect of GenAI Fluency and Positive Affect
Xiantong Yang, Mengmeng Zhang
https://arxiv.org/abs/2404.17822 https://

GenAI Distortion: The Effect of GenAI Fluency and Positive Affect
The introduction of generative artificial intelligence (GenAI) into educational practices has been transformative, yet it brings a crucial concern about the potential distortion of users' beliefs. Given the prevalence of GenAI among college students, examining the psychological mechanisms that lead to GenAI distortion from both technological factors and the individual's psychological processes is a critical priority. A mixed-methods approach is employed to test the proposed hypotheses. Study 1 …

This https://arxiv.org/abs/2404.13016 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

Optimizing Calibration by Gaining Aware of Prediction Correctness
Model calibration aims to align confidence with prediction correctness. The Cross-Entropy CE) loss is widely used for calibrator training, which enforces the model to increase confidence on the ground truth class. However, we find the CE loss has intrinsic limitations. For example, for a narrow misclassification, a calibrator trained by the CE loss often produces high confidence on the wrongly predicted class (e.g., a test sample is wrongly classified and its softmax score on the ground truth c…

This https://arxiv.org/abs/2402.13301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSD_…

Structure-informed Positional Encoding for Music Generation
Music generated by deep learning methods often suffers from a lack of coherence and long-term organization. Yet, multi-scale hierarchical structure is a distinctive feature of music signals. To leverage this information, we propose a structure-informed positional encoding framework for music generation with Transformers. We design three variants in terms of absolute, relative and non-stationary positional information. We comprehensively test them on two symbolic music generation tasks: next-tim…

Testing for common structures in high-dimensional factor models
Marie-Christine D\"uker, Vladas Pipiras
https://arxiv.org/abs/2403.19818 https://

Testing for common structures in high-dimensional factor models
This work proposes a novel procedure to test for common structures across two high-dimensional factor models. The introduced test allows to uncover whether two factor models are driven by the same loading matrix up to some linear transformation. The test can be used to discover inter individual relationships between two data sets. In addition, it can be applied to test for structural changes over time in the loading matrix of an individual factor model. The test aims to reduce the set of possib…

Using this CSS with broken image ref:
```
::before {
content: url(foo) / "Panda";
}
```
Safari / macOS / iPadOS does not show the alt.
Until you turn on VO. Or turn it off. But it goes away if you refresh.
More accurately, it resizes the placeholder; if your alt is small enough to fit *then* it shows.
Attached video shows it in action.
So. What the deal is?
Test page:

Image Fallbacks
...

Processing HSV Colored Medical Images and Adapting Color Thresholds for Computational Image Analysis: a Practical Introduction to an open-source tool
Lie Cai, Andre Pfob
https://arxiv.org/abs/2404.17878 https://arxiv.org/pdf/2404.17878
arXiv:2404.17878v1 Announce Type: new
Abstract: Background: Using artificial intelligence (AI) techniques for computational medical image analysis has shown promising results. However, colored images are often not readily available for AI analysis because of different coloring thresholds used across centers and physicians as well as the removal of clinical annotations. We aimed to develop an open-source tool that can adapt different color thresholds of HSV-colored medical images and remove annotations with a simple click.
Materials and Methods: We built a function using MATLAB and used multi-center international shear wave elastography data (NCT 02638935) to test the function. We provide step-by-step instructions with accompanying code lines.
Results: We demonstrate that the newly developed pre-processing function successfully removed letters and adapted different color thresholds of HSV-colored medical images.
Conclusion: We developed an open-source tool for removing letters and adapting different color thresholds in HSV-colored medical images. We hope this contributes to advancing medical image processing for developing robust computational imaging algorithms using diverse multi-center big data. The open-source Matlab tool is available at https://github.com/cailiemed/image-threshold-adapting.

This https://arxiv.org/abs/2401.09095 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Signal in the Hyperfine Structure Line of the Ground State of Atomic Hydrogen from the Dark Ages as a Cosmological Test
We analyze the formation of the signal in the 21 cm hydrogen line of the Dark Ages ($30\le z\le300$) in different cosmological models and discuss the possibility of its detection by decameter-wavelength radio telescopes. To study the dependence of the intensity and profile of the line on the values of cosmological parameters and physical conditions in the intergalactic medium, the evolution of the global (averaged over the sky) differential brightness temperature in this line was calculated in …

Parameter Selection by GCV and a $\chi^2$ test within Iterative Methods for $\ell_1$-regularized Inverse Problems
Brian Sweeney, Rosemary Renaut, Malena Espa\~nol
https://arxiv.org/abs/2404.19156

Parameter Selection by GCV and a $χ^2$ test within Iterative Methods for $\ell_1$-regularized Inverse Problems
$\ell_1$ regularization is used to preserve edges or enforce sparsity in a solution to an inverse problem. We investigate the Split Bregman and the Majorization-Minimization iterative methods that turn this non-smooth minimization problem into a sequence of steps that include solving an $\ell_2$-regularized minimization problem. We consider selecting the regularization parameter in the inner generalized Tikhonov regularization problems that occur at each iteration in these $\ell_1$ iterative me…

Do Large Language Models Understand Conversational Implicature -- A case study with a chinese sitcom
Shisen Yue, Siyuan Song, Xinyuan Cheng, Hai Hu
https://arxiv.org/abs/2404.19509 https://arxiv.org/pdf/2404.19509
arXiv:2404.19509v1 Announce Type: new
Abstract: Understanding the non-literal meaning of an utterance is critical for large language models (LLMs) to become human-like social communicators. In this work, we introduce SwordsmanImp, the first Chinese multi-turn-dialogue-based dataset aimed at conversational implicature, sourced from dialogues in the Chinese sitcom $\textit{My Own Swordsman}$. It includes 200 carefully handcrafted questions, all annotated on which Gricean maxims have been violated. We test eight close-source and open-source LLMs under two tasks: a multiple-choice question task and an implicature explanation task. Our results show that GPT-4 attains human-level accuracy (94%) on multiple-choice questions. CausalLM demonstrates a 78.5% accuracy following GPT-4. Other models, including GPT-3.5 and several open-source models, demonstrate a lower accuracy ranging from 20% to 60% on multiple-choice questions. Human raters were asked to rate the explanation of the implicatures generated by LLMs on their reasonability, logic and fluency. While all models generate largely fluent and self-consistent text, their explanations score low on reasonability except for GPT-4, suggesting that most LLMs cannot produce satisfactory explanations of the implicatures in the conversation. Moreover, we find LLMs' performance does not vary significantly by Gricean maxims, suggesting that LLMs do not seem to process implicatures derived from different maxims differently. Our data and code are available at https://github.com/sjtu-compling/llm-pragmatics.

ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening
Gianmarco Accordi, Davide Gadioli, Giorgio Seguini, Andrea R. Beccari, Gianluca Palermo
https://arxiv.org/abs/2404.19391

ZSMILES: an approach for efficient SMILES storage for random access in Virtual Screening
Virtual screening is a technique used in drug discovery to select the most promising molecules to test in a lab. To perform virtual screening, we need a large set of molecules as input, and storing these molecules can become an issue. In fact, extreme-scale high-throughput virtual screening applications require a big dataset of input molecules and produce an even bigger dataset as output. These molecules' databases occupy tens of TB of storage space, and domain experts frequently sample a small…

This https://arxiv.org/abs/2311.07740 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Towards a classification of isolated $j$-invariants
We develop an algorithm to test whether a non-CM elliptic curve $E/\mathbb{Q}$ gives rise to an isolated point of any degree on any modular curve of the form $X_1(N)$. This builds on prior work of Zywina which gives a method for computing the image of the adelic Galois representation associated to $E$. Running this algorithm on all elliptic curves presently in the $L$-functions and Modular Forms Database and the Stein-Watkins Database gives strong evidence for the conjecture that $E$ gives rise…

This https://arxiv.org/abs/2312.03383 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Correlations for an anisotropic polarized stochastic gravitational wave background in pulsar timing arrays
The recent compelling observation of the nanohertz stochastic gravitational wave background has brought to light a new galactic arena to test gravity. In this paper, we derive a formula for the most general expression of the stochastic gravitational wave background correlation that could be tested with pulsar timing and future square kilometer arrays. Our expressions extends the harmonic space analysis, also often referred to as the power spectrum approach, to predict the correlation signatures…

Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks
Melissa Ailem, Katerina Marazopoulou, Charlotte Siska, James Bono
https://arxiv.org/abs/2404.16966

Examining the robustness of LLM evaluation to the distributional assumptions of benchmarks
Benchmarks have emerged as the central approach for evaluating Large Language Models (LLMs). The research community often relies on a model's average performance across the test prompts of a benchmark to evaluate the model's performance. This is consistent with the assumption that the test prompts within a benchmark represent a random sample from a real-world distribution of interest. We note that this is generally not the case; instead, we hold that the distribution of interest varies accordin…

This https://arxiv.org/abs/2310.05765 has been replaced.
link: https://scholar.google.com/scholar?q=a

Examining the simulation-to-reality gap of a wheel loader digging in deformable terrain
We investigate how well a physics-based simulator can replicate a real wheel loader performing bucket filling in a pile of soil. The comparison is made using field test time series of the vehicle motion and actuation forces, loaded mass, and total work. The vehicle was modeled as a rigid multibody system with frictional contacts, driveline, and linear actuators. For the soil, we tested discrete element models of different resolutions, with and without multiscale acceleration. The spatio-tempora…

COTS: Connected OpenAPI Test Synthesis for RESTful Applications
Christian Bartolo Burl\`o, Adrian Francalanza, Alceste Scalas, Emilio Tuosto
https://arxiv.org/abs/2404.19614

COTS: Connected OpenAPI Test Synthesis for RESTful Applications
We present a novel model-driven approach for testing RESTful applications. We introduce a (i) domain-specific language for OpenAPI specifications and (ii) a tool to support our methodology. Our DSL is inspired by session types and enables the modelling of communication protocols between a REST client and server. Our tool, dubbed COTS, generates (randomised) model-based test executions and reports software defects. We evaluate the effectiveness of our approach by applying it to test several open…

This https://arxiv.org/abs/2301.12648 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Large-scale motions and growth rate from forward-modelling Tully-Fisher peculiar velocities
Peculiar velocities are an important probe of the mass distribution in the Universe and the growth rate of structure, directly measuring the effects of gravity on the largest scales and providing a test for theories of gravity. Comparing peculiar velocities predicted from the density field mapped by a galaxy redshift survey with peculiar velocities measured using a distance estimator such as the Tully-Fisher relation yields the growth factor for large-scale structure. We present a method for fo…

Tokenization Is More Than Compression
Craig W. Schmidt, Varshini Reddy, Haoran Zhang, Alec Alameddine, Omri Uzan, Yuval Pinter, Chris Tanner
https://arxiv.org/abs/2402.18376

Tokenization Is More Than Compression
Tokenization is a foundational step in Natural Language Processing (NLP) tasks, bridging raw text and language models. Existing tokenization approaches like Byte-Pair Encoding (BPE) originate from the field of data compression, and it has been suggested that the effectiveness of BPE stems from its ability to condense text into a relatively small number of tokens. We test the hypothesis that fewer tokens lead to better downstream performance by introducing PathPiece, a new tokenizer that segment…

This https://arxiv.org/abs/2310.05765 has been replaced.
link: https://scholar.google.com/scholar?q=a

Examining the simulation-to-reality gap of a wheel loader digging in deformable terrain
We investigate how well a physics-based simulator can replicate a real wheel loader performing bucket filling in a pile of soil. The comparison is made using field test time series of the vehicle motion and actuation forces, loaded mass, and total work. The vehicle was modeled as a rigid multibody system with frictional contacts, driveline, and linear actuators. For the soil, we tested discrete element models of different resolutions, with and without multiscale acceleration. The spatio-tempora…

This https://arxiv.org/abs/2312.02295 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Higher Memory Effects in Numerical Simulations of Binary Black Hole Mergers
Gravitational memory effects are predictions of general relativity that are characterized by an observable effect that persists after the passage of gravitational waves. In recent years, they have garnered particular interest, both due to their connection to asymptotic symmetries and soft theorems and because their observation would serve as a unique test of the nonlinear nature of general relativity. Apart from the more commonly known displacement and spin memories, however, there are other me…

JEL ratio test for independence between a continuous and a categorical random variable
Saparya Suresh, Sudheesh K. Kattumannil
https://arxiv.org/abs/2402.18105

JEL ratio test for independence between a continuous and a categorical random variable
The categorical Gini covariance is a dependence measure between a numerical variable and a categorical variable. The Gini covariance measures dependence by quantifying the difference between the conditional and unconditional distributional functions. A value of zero for the categorical Gini covariance implies independence of the numerical variable and the categorical variable. We propose a non-parametric test for testing the independence between a numerical and categorical variable using the ca…

This https://arxiv.org/abs/2309.16120 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csSE_…

Test-Case-Driven Programming Understanding in Large Language Models for Better Code Generation
Code generation is to automatically generate source code conforming to a given programming specification, which has received extensive attention especially with the development of large language models (LLMs). Due to the inherent difficulty of code generation, the code generated by LLMs may be not aligned with the specification. To improve the performance of LLMs in code generation, some thought-eliciting prompting techniques have been proposed to guide LLMs for specification understanding. How…

This https://arxiv.org/abs/2312.17053 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_…

Galaxy-galaxy lensing data: $f(T)$ gravity challenges General Relativity
We use galaxy-galaxy lensing data to test General Relativity and $f(T)$ gravity at galaxies scales. We consider an exact spherically symmetric solution of $f(T)$ theory which is obtained from an approximate quadratic correction, and thus it is expected to hold for every realistic deviation from General Relativity. Quantifying the deviation by a single parameter $Q$, and following the post-Newtonian approximation, we obtain the corresponding deviation in the gravitational potential, shear compon…

Towards a Fault-Injection Benchmarking Suite
Tianhao Wang, Robin Thunig, Horst Schirmeier
https://arxiv.org/abs/2403.20319 https://ar…

Towards a Fault-Injection Benchmarking Suite
Soft errors in memories and logic circuits are known to disturb program execution. In this context, the research community has been proposing a plethora of fault-tolerance (FT) solutions over the last decades, as well as fault-injection (FI) approaches to test, measure and compare them. However, there is no agreed-upon benchmarking suite for demonstrating FT or FI approaches. As a replacement, authors pick benchmarks from other domains, e.g. embedded systems. This leads to little comparability …

Generating Minimalist Adversarial Perturbations to Test Object-Detection Models: An Adaptive Multi-Metric Evolutionary Search Approach
Cristopher McIntyre-Garcia, Adrien Heymans, Beril Borali, Won-Sook Lee, Shiva Nejati
https://arxiv.org/abs/2404.17020

Generating Minimalist Adversarial Perturbations to Test Object-Detection Models: An Adaptive Multi-Metric Evolutionary Search Approach
Deep Learning (DL) models excel in computer vision tasks but can be susceptible to adversarial examples. This paper introduces Triple-Metric EvoAttack (TM-EVO), an efficient algorithm for evaluating the robustness of object-detection DL models against adversarial attacks. TM-EVO utilizes a multi-metric fitness function to guide an evolutionary search efficiently in creating effective adversarial test inputs with minimal perturbations. We evaluate TM-EVO on widely-used object-detection DL models…

PrescientFuzz: A more effective exploration approach for grey-box fuzzing
Daniel Blackwell, David Clark
https://arxiv.org/abs/2404.18887 https://

PrescientFuzz: A more effective exploration approach for grey-box fuzzing
In this paper, we introduce an approach for improving the early exploration of grey-box fuzzing campaigns; allowing the fuzzer to reach the interesting coverage earlier. To do this, it leverages information from the system under test's (SUT's) control flow graph in order to decide which inputs are likely to lead to discovering most coverage when mutated.

This https://arxiv.org/abs/2404.00566 has been replaced.
link: https://scholar.google.com/scholar?q=a

CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
To facilitate evaluation of code generation systems across diverse scenarios, we present CodeBenchGen, a framework to create scalable execution-based benchmarks that only requires light guidance from humans. Specifically, we leverage a large language model (LLM) to convert an arbitrary piece of code into an evaluation example, including test cases for execution-based evaluation. We illustrate the usefulness of our framework by creating a dataset, Exec-CSN, which includes 1,931 examples involvin…

A Catalog of Transformations to Remove Smells From Natural Language Tests
Manoel Aranda, Naelson Oliveira, Elvys Soares, M\'arcio Ribeiro, Davi Rom\~ao, Ullyanne Patriota, Rohit Gheyi, Emerson Souza, Ivan Machado
https://arxiv.org/abs/2404.16992

A Catalog of Transformations to Remove Smells From Natural Language Tests
Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensively addressed test smells in automated software tests but little attention has been given to smells in natural language tests. While some research has identified and catalogued such smells, there is a lack of systematic approaches for their removal. Consequently, there is also a lack of tools to automatically identify a…