Survey of assurances for trust in human-autonomy systems.
problem Ensuring trust in human-autonomy systems.
method Survey and review of existing research.
result Refined definition of assurances for trust.
On-device research index
arXiv research
A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
169,291 papers · 148 categories
Trend · papers per month
48 results for “assurances”
Survey of algorithmic assurances for trust in AI agents.
problem Ensuring trust in AI agents designed for human-autonomy relationships.
method Formal definition and classification of algorithmic assurances, synthesis of research across AI communities.
result Algorithmic assurances fall along a spectrum impacting agent core functionality.
Identifies open problems in quality assurance of safety-critical ML systems.
problem Quality assurance for safety-critical ML systems, especially in automated driving.
method Identified and classified open problems using automated-driving vehicles as an example.
result Open problems require interdisciplinary knowledge from various fields.
Survey of methods for ML assurance across its lifecycle stages.
problem Ensuring safety of ML in safety-critical applications.
method Comprehensive survey of methods at each ML lifecycle stage.
result Identification of open challenges in ML assurance.
Quantifier elimination enhances safety assurance of deep neural networks.
problem Rigorously assure safe operation of sophisticated, autonomous systems like DNNs.
method Use quantifier elimination as a formal method to enhance safety assurance.
result Initial results show QE can precisely analyze robustness of DNNs.
The paper optimizes exceptions in a statistical production system using machine learning.
problem Lack of curated and labeled training data for machine learning in data quality assurance.
method Explainable supervised machine learning to identify and prioritize exceptions.
result Improvement in the quality and efficiency of exceptions generated and authenticated by users.
A new process model for machine learning applications with quality assurance.
problem Lack of standard process model for machine learning applications.
method Six-phase process model with quality assurance methodology.
result Proposes a new process model for machine learning applications.
Proposes a mathematical model for safe and scalable self-driving cars.
problem Ensuring safety and scalability in self-driving cars.
method Introduces Responsibility-Sensitive Safety (RSS) model and scalable design.
result Proposes a mathematical model for safety assurance and scalable design.
The paper designs neural networks with assurance for controlling nonlinear systems.
problem Designing neural networks with assurance for nonlinear system control.
method Bounding the number of affine functions needed for a CPWA function, connecting it to a TLL NN architecture.
result The TLL NN architecture is parameterized by the number of affine functions in the CPWA function it realizes.
The paper uses conformal prediction to monitor CPS with machine learning components.
problem Ensuring trustworthy CPS with machine learning components.
method Conformal prediction framework for real-time assurance monitoring of CPS with machine learning.
result The method provides well-calibrated confidence and limits the number of alarms.
We provide sufficient conditions assuring that a suitably decorated 2-polyhedron can be thickened to a compact 4-dimensional Stein domain. We also study a class of flat polyhedra in 4-manifolds and find conditions assuring that they admit Stein, compact neighborhoods. We base our calculations on Turaev's shadows suitab…
Develops ML-DQA for healthcare data quality assurance.
problem Inconsistent use of real-world data in machine learning projects.
method Develops ML-DQA framework based on RWD best practices.
result Five generalizable practices emerge from ML-DQA implementation.
A novel ML verification technique using manifold learning.
problem Ensuring trust in machine learning systems.
method Variational autoencoder for extracting a low-dimensional manifold from high-dimensional training data.
result The manifold provides diverse test data, fault-revealing test cases, and independent runtime trust assessment.
Two novel models predict bus travel times with uncertainty, improving connection assurance.
problem Improving bus connection assurance by handling travel time uncertainty.
method Two novel approaches: Deep Quantile Regression (DQR) and Bayesian Recurrent Neural Networks (BRNN).
result DQR model performs best for 80%, 90%, and 95% prediction intervals, with small underestimation.
QANet estimates image segmentation quality without human inspection.
problem Quantitative evaluation of image segmentation quality.
method QANet is a Quality Assurance Network that solves a regression problem to estimate quality measures.
result QANet accurately estimates segmentation quality with respect to ground truth.
Given a properly embedded graph Gamma in a ball B and a punctured sphere Sigma properly embedded in B - Gamma, we examine the conditions on Gamma that are necessary to assure that Sigma is boundary parallel.
We study the geometry of the leaf closure space of regular and singular Riemannian foliations. We give conditions which assure that this leaf space is a singular symplectic or Kähler space.
New framework uses OR to ensure AI systems make safe decisions.
problem Ensuring generative AI systems make safe decisions as they gain autonomy.
method Developed a conceptual framework combining flow-based models and adversarial robustness.
result Increased autonomy requires new OR approaches for feasibility, robustness, and stress testing.
GRAND ensures node-level differential privacy for network data.
problem Lack of node-level differential privacy for network data.
method Proposes GRAND, the first mechanism for releasing networks with node-level differential privacy and preserving structural properties.
result GRAND releases networks while ensuring node-level differential privacy and preserving structural properties.
This paper introduces modal epistemic tools for risk management.
problem Identifying and certifying risk claims when institutions lack the necessary epistemic stance.
method Develops crisp and fuzzy modal semantics for assurance and working commitment, distinguishing between object-level risk claims and meta-level epistemic diagnostics.
result Risk governance should model evidential incompleteness and failures of escalation, not just hazards and losses.
Real Lie groups' invariant theory matches that of their affine counterparts.
problem Matching invariant theory of real Lie groups with affine groups.
method Simple remark showing coincidence.
result Invariant theory of real Lie groups equals that of their affine counterparts.
The paper finds sign-changing solutions for a specific type of elliptic equation.
problem Existence of sign-changing solutions for a Yamabe type equation.
method Investigates a critical elliptic equation with a Yamabe type operator on a compact manifold with boundary.
result Existence of sign-changing solutions assured under certain geometric conditions.
RAGuard improves safety in LLMs for offshore wind maintenance.
problem Conventional LLMs fail with specialised or unexpected scenarios in offshore wind maintenance.
method Integrates safety-critical documents alongside technical manuals in RAG framework.
result RAGuard increases safety recall from almost 0% to over 50% while maintaining technical recall above 60%.
Paper explores cohomology classes on non-compact almost Kähler manifolds.
problem Understanding cohomology classes induced by symplectic forms.
method Provides criteria for non-trivial classes in cohomology.
result Symplectic forms induce non-trivial classes in cohomology.
A new framework uses deep reinforcement learning to improve aircraft separation in busy airspace.
problem Improving aircraft separation in high-density, dynamic airspace constrained by human controllers.
method Proximal Policy Optimization with an attention network for distributed vehicle autonomy.
result The framework significantly reduces offline training time and increases performance.
Formula for branching coefficients of symmetric pairs.
problem Understanding the action of symmetric pairs on flag varieties.
method Proposes a formula for branching coefficients using orbits.
result Formula provides a finite number of orbits for the action.
Explains properties of multisymplectic manifolds.
problem None explicitly stated; focuses on defining and characterizing multisymplectic manifolds.
method Review and introduction of multisymplectic geometry concepts.
result Characterization of multisymplectic manifolds and their Hamiltonian structures.
This paper classifies stablecoin designs to mitigate volatility risks.
problem Mitigating the volatility of stablecoins.
method Systematic design classification, component analysis, and future direction identification.
result Identified strengths and drawbacks of existing stablecoin designs.
In this paper, we present the principal components of an economic scenario generator (ESG), both for the theoretical design and for practical implementation. The choice of these components should be linked to the ultimate vocation of the economic scenario generator, which can be either a tool for pricing financial prod…
Existence of hypersurfaces in warped product manifolds proven.
problem Existence of closed hypersurfaces in warped product manifolds.
method Standard degree theory based on a priori estimates.
result Existence of solutions to prescribed Weingarten curvature equations.
The article presents a general discrete time dividend valuation model when the dividend growth rate is a general continuous variable. The main assumption is that the dividend growth rate follows a discrete time semi-Markov chain with measurable space. The paper furnishes sufficient conditions that assure finiteness of …
Pseudo-slice knotsmath.GT
For n >1, if the Seifert form of a knotted 2n-1 sphere K in S^{2n+1} has a metabolizer, then the knot is slice. Casson and Gordon proved that this is false in dimension three (n = 1). However, in the three dimensional case it is true that if the metabolizer has a basis represented by a strongly slice link then K is sli…
Origami solves real cubic equations, revealing a specific curve.
problem Solving real cubic equations using origami.
method Investigating a specific real cubic curve and analyzing its properties.
result The shape of Beloch's curve is determined by the Hessian at its singular point.
Novel approach ensures stability of compact schemes for variable PDEs.
problem Ensuring stability of compact schemes for variable coefficient PDEs.
method Difference equation approach to derive stability conditions.
result Derives sufficient condition for unconditional stability.
Is Your Imitation Learning Policy Better than Mine? Policy Comparison with Near-Optimal Stoppingcs.RO
Paper proposes a sequential statistical test for comparing imitation learning policies with near-optimal stopping.
problem Challenges in rigorously comparing imitation learning policies due to small sample sizes and potential p-hacking.
method Sequential statistical test that adapts the number of trials based on intermediate results, achieving near-optimal stopping.
result Reduces the number of evaluation trials by up to 32% compared to state-of-the-art baselines, saving significant time and effort.
The Relation Between Global Migration and Trade Networksphysics.soc-ph
In this paper we develop a methodology to analyze and compare multiple global networks. We focus our analysis on the relation between human migration and trade. First, we identify the subset of products for which the presence of a community of migrants significantly increases trade intensity. To assure comparability ac…
New method constructs asymptotic convex hypersurfaces via equidistant hyperplanes.
problem Constructing asymptotic convex hypersurfaces in hyperbolic space.
method Approximating hypersurface by geodesic graphs over equidistant hyperplanes.
result Existence of complete, strictly locally convex hypersurfaces with prescribed asymptotic boundary.
The paper explains why combining Sobol sequences and polynomials improves LSMC stability.
problem Improving numerical stability in LSMC algorithms.
method Theoretical justification and derivation of a bound for numerical stability.
result Explicit bound for the number of outer scenarios for numerical stability.
Almost holomorphic embeddings in Grassmannians with applications to singular simplectic submanifoldsmath.DG
We use Donaldson's approximately holomorphic techniques to build embeddings of a closed symplectic manifold with symplectic form of integer class in the grassmannians Gr(r,N). We assure that these embeddings are asymptotically holomorphic in a precise sense. We study first the particular case of embeddings in the proje…
Develops a deep metric learning approach for detecting bugs in video games.
problem Automated detection of bugs in video games.
method State-State Siamese Networks (S3N) for deep metric learning.
result S3N learns meaningful embeddings to identify various types of bugs.
We are interested in comparing probability distributions defined on Riemannian manifold. The traditional approach to study a distribution relies on locating its mean point and finding the dispersion about that point. On a general manifold however, even if two distributions are sufficiently concentrated and have unique …
In life sciences, the experts generally use empirical knowledge to recode variables, choose interactions and perform selection by classical approach. The aim of this work is to perform automatic learning algorithm for variables selection which can lead to know if experts can be help in they decision or simply replaced …
Study of Dirac equation with non-local nonlinearity on spheres.
problem Conformally invariant Dirac equation with non-local nonlinearity.
method Investigation of compactness, bubbling, and energy quantization of energy functional; characterization of ground state solutions; proof of Aubin-type inequality and Brezis-Nirenberg type result.
result Existence of solutions to the conformal Einstein-Dirac problem in dimension 4.
modAL simplifies active learning in Python.
problem Making active learning research and practice easier.
method Clear, modular design; compatibility with scikit-learn.
result Facilitates fast prototyping and algorithm development.
A new likelihood ratio metric for GANs training stability.
problem Training consistency and stability in GANs.
method Likelihood ratio approach for adversarial optimization.
result New metric for online convergence and stability assessment.
Paper proposes a new method to estimate transportation technology risks.
problem Estimating risks associated with new transportation technologies.
method Multifidelity simulation combining low-fidelity and high-fidelity data.
result Allows evaluation of new technologies at conception stage.
Develops an off-policy method for improving chatbots with noisy rewards.
problem Improving chatbots with noisy and expensive rewards.
method Batch policy gradient method (BPG).
result Demonstrates the efficacy of BPG through synthetic and real-world experiments.
We study the propagation of bosonic strings in singular target space-times. For describing this, we assume this target space to be the quotient of a smooth manifold by a singular foliation on it. Using the technical tool of a gauge theory, we propose a smooth functional for this scenario, such that the p…