This paper evaluates conformance measures in process mining using conformance propositions.
problem Lack of formal definition and evaluation of conformance measures in process mining.
method Formulated 21 conformance propositions to evaluate existing measures.
result Identified challenges and requirements for conformance measures in process mining.
Study how past radiation determines present matter in Penrose's cyclic cosmology.
problem Determining matter content in the present eon from past radiation in Penrose's cyclic cosmology.
method Solve Einstein's equations for a spherical wave in the past eon, then apply reciprocity to find the present eon's matter content.
result The present eon is filled with three types of radiation: a damped wave, an in-going wave, and randomly scattered waves.
As a generalization of semi-invariant submersions, we introduce conformal semi-invariant submersions from almost Hermitian manifolds onto Riemannian manifolds. We give examples, investigate the geometry of foliations which are arisen from the definition of a conformal submersion and show that there are certain product …
We introduce conformal anti-invariant submersions from almost Hermitian manifolds onto Riemannian manifolds. We give examples, investigate the geometry of foliations which are arisen from the definition of a conformal submersion and find necessary and sufficient conditions for a conformal anti-invariant submersion to b…
ToolChain-CRC addresses the risk-control problem for retrieval-augmented and tool-using agents under drift.
problem Risk-control problem for retrieval-augmented and tool-using agents under drift.
method ToolChain-CRC uses conformal risk-control under exchangeable calibration runs.
result Trajectory-level risk control keeps accepted-trajectory risk below the target.
PCS-UQ framework improves uncertainty quantification for machine learning models.
problem Ensuring trustworthy uncertainty quantification for machine learning models in high-stakes domains.
method PCS-UQ framework based on Predictability, Computability, and Stability principles, integrating prediction-checking, bootstrap samples, and multiplicative calibration.
result PCS-UQ maintains target coverage while outperforming or matching conformal methods in interval width and subgroup coverage.
We study the Yamabe invariants of cylindrical manifolds and compact orbifolds with a finite number of singularities, by means of conformal geometry and the Atiyah-Patodi-Singer L2-index theory. For an n-orbifold M with singularities ΣΓ={(pˇ1,Γ1),...,(pˇs,Γs)} (where each group $Γ_j<O…
Study on CPSRM from/to Kähler manifolds, deriving integrability and geodesic results.
problem Existence and properties of CPSRM from/to Kähler manifolds.
method Analytical derivation of properties, examples, and conditions for homotheticity and harmonicity.
result Derived integrability and geodesic conditions for CPSRM.
A deep neural network based architecture was constructed to predict amino acid side chain conformation with unprecedented accuracy. Amino acid side chain conformation prediction is essential for protein homology modeling and protein design. Current widely-adopted methods use physics-based energy functions to evaluate s…
Paper constructs new non-Anosov Partially Hyperbolic Geodesic flows using conformal deformations.
problem Creating new non-Anosov Partially Hyperbolic Geodesic flows.
method Using conformal deformations to produce examples of partially hyperbolic geodesic flows.
result Proves ergodicity for the Liouville measure and uniqueness of the measure of maximal entropy.
We find necessary and sufficient conditions ensuring that the vacuum development of an initial data set of the Einstein's field equations admits a conformal Killing vector. We refer to these conditions as conformal Killing initial data (CKID) and they extend the well-known Killing initial data (KID) that have been know…
New test ensures quality of shared data in machine learning.
problem Ensuring quality of external data in machine learning tasks.
method Distribution-free two-sample testing procedures grounded in conformal outlier detection.
result Identifies valuable external data agents for model personalization.
New functions derived from arrow diagrams for spherical curves, invariant under certain deformations.
problem Defining and analyzing integer-valued functions on spherical curves.
method Introducing new functions and relators to study spherical curves and their isotopy classes.
result Functions derived from arrow diagrams are invariant under specific deformations.
The paper studies curvature surfaces in conformally flat hypersurfaces and their extensions and approximations.
problem Analyzing curvature surfaces in conformally flat hypersurfaces and their properties.
method Using the Poincaré metric to determine curvature surfaces and extending them analytically.
result Curvature surfaces extend to certain sets in \(\mathbb{R}^2\) and have specific properties like parallel small circles at limits.
This paper deforms complex tori and their mirrors using gerbes.
problem Deforming complex tori and their mirror partners.
method Using flat gerbes to deform complex tori and their mirrors, constructing holomorphic line bundles over deformed objects.
result Deformed complex tori and their mirrors can be studied using flat gerbes.
We present a number of conditions which are necessary for an n-dimensional projective structure (M,[nabla]) to include the Levi-Civita connection nabla of some metric on M. We provide an algorithm, which effectively checks if a Levi-Civita connection is in the projective class and, in the positive, which finds this con…
Statistical model checking for PCTL on MDPs using reinforcement learning.
problem Model checking PCTL specifications on MDPs with statistical methods.
method Reinforcement learning for policy search, statistical model checking with UCB-based Q-learning.
result Provably guaranteed statistical model checking method for PCTL specifications on MDPs.
Research aims to make fact-checking models more transparent.
problem Making fact-checking models explainable in a complex field.
method Combines fact-checking methods with explainable AI techniques.
result Developed initial solutions for explainable fact-checking.
Derives formulas for extrinsic Paneitz operator and Q-curvature in general dimensions.
problem Calculating extrinsic conformal invariants for hypersurfaces in Riemannian manifolds.
method Explicit formulas derived using local conformal invariants and non-trivial local conformal invariant C. result Explicit formulas for extrinsic Paneitz operator and Q-curvature in general dimensions. FAKTA automates fact checking across media sources.
problem Automating fact checking across diverse media sources.
method Unified framework integrating document retrieval, stance detection, evidence extraction, and linguistic analysis.
result FAKTA predicts factuality and provides evidence for claims.
New neural network solves Nirenberg problem for curvature on sphere.
problem Prescribing Gaussian curvature on S2 for metrics conformal to the round metric. method Mesh-free physics-informed neural network (PINN) that directly parametrises the conformal factor.
result Neural network achieves very low losses for realisable curvatures, distinguishing them from non-realisable ones.
Time-aware fact-checking improves veracity predictions for time-sensitive claims.
problem Fact-checking decisions should consider temporal information of claims and evidence.
method Investigated four temporal ranking methods to optimize evidence ranking for fact-checking models.
result Time-aware evidence ranking surpasses relevance assumptions and improves veracity predictions for time-sensitive claims.
DC-Check helps guide ML development by considering data-centric aspects.
problem Lack of standardized framework for data-centric considerations in ML.
method DC-Check is a checklist-style framework for data-centric AI at ML pipeline stages.
result Promotes thoughtfulness and transparency in ML development.
It is a classical fact that the cotangent bundle $T^* \M$ of a differentiable manifold $\M$ enjoys a canonical symplectic form Ω∗. If $(\M,\j,g,ω)$ is a pseudo-Kähler or para-Kähler 2n-dimensional manifold, we prove that the tangent bundle $T\M$ also enjoys a natural pseudo-Kähler or para-Kähler structure $(\J,\G,…
Ranked second in fact-checking task, using DRR NN with embeddings.
problem Fact-checking questions in community forums.
method Deeply Regularized Residual Neural Network (DRR NN) with Universal Sentence Encoder embeddings, ensemble methods.
result Ranked second in fact-checking task.
Proves SYZ mirror symmetry for del Pezzo and rational elliptic surfaces.
problem Proving mirror symmetry for specific Calabi-Yau surfaces.
method Adapting Hein's work, constructing asymptotically semi-flat Calabi-Yau metrics, and defining a mirror map.
result Existence and uniqueness of Calabi-Yau metrics on Y∖D. We describe the infinitesimal moduli space of pairs (Y,V) where Y is a manifold with G2 holonomy, and V is a vector bundle on Y with an instanton connection. These structures arise in connection to the moduli space of heterotic string compactifications on compact and non-compact seven dimensional spaces, e.…
Social networks are getting closer to our real physical world. People share the exact location and time of their check-ins and are influenced by their friends. Modeling the spatio-temporal behavior of users in social networks is of great importance for predicting the future behavior of users, controlling the users' mov…
By the SYZ construction, a mirror pair (X,Xˇ) of a complex torus X and a mirror partner Xˇ of the complex torus X is described as the special Lagrangian torus fibrations X→B and Xˇ→B on the same base space B. Then, by the SYZ transform, we can construct a simpl…
We prove the following result announced in Todorov and Valov: Any homogeneous, metric ANR-continuum is a VGn-continuum provided dimGX=n≥1 and Hˇn(X;G)=0, where G is a principal ideal domain. This implies that any homogeneous n-dimensional metric ANR-continuum with $\check{H}^n(X;G)\neq…
We specify a result of Yokoi \cite{yo} by proving that if G is an abelian group and X is a homogeneous metric ANR compactum with dimGX=n and Hˇn(X;G)=0, then X is an (n,G)-bubble. This implies that any such space X has the following properties: Hˇn−1(A;G)=0 for every closed…
We create a large dataset for fact checking claims and improve prediction accuracy.
problem Fact checking claims from multiple sources is challenging.
method We created a comprehensive dataset and developed a novel method for automatic veracity prediction.
result Our model achieves a Macro F1 of 49.2%, showing significant performance improvements.
Paper checks SSC for matrix factorizations using Gurobi.
problem Checking the SSC for various matrix factorizations.
method Formulated as a non-convex quadratic optimization problem over a bounded set, solved with Gurobi.
result SSC can be checked in reasonable time for realistic scenarios.
The paper proposes a tool to detect invalid inputs in DL models.
problem Vulnerability of DL models to invalid inputs during runtime.
method Design and implementation of a tool that extracts data flow footprints and conducts assertion-based validation.
result The assertion-based data sanity check mechanism effectively identifies invalid input cases.
New method evaluates language model forecasters by checking consistency of predictions.
problem Evaluating the performance of language model forecasters is difficult due to lack of ground truth.
method Developed a consistency check framework based on arbitrage to evaluate forecasters.
result Consistency metrics correlate with ground truth performance of LLM forecasters.
Paper verifies RNNs using automata learning and model checking.
problem Verifying the correctness of RNNs is challenging.
method Learn a deterministic finite automaton from RNN, use model checking for verification.
result Can discover and generalize counterexamples to faulty flows.
The choice of model class is fundamental in statistical learning and system identification, no matter whether the class is derived from physical principles or is a generic black-box. We develop a method to evaluate the specified model class by assessing its capability of reproducing data that is similar to the observed…
SANST uses self-attentive networks with spatial and temporal embeddings for better POI recommendations.
problem Next point-of-interest (POI) recommendation for users based on their history.
method SANST incorporates spatio-temporal patterns into self-attentive networks.
result SANST outperforms state-of-the-art models by up to 13.65% in nDCG@10.
This paper enhances privacy in statistical model checking of cyber-physical systems.
problem Privacy concerns in consumer-level applications due to statistical model checking.
method Proposes expected differential privacy and a new exponential mechanism for sequential algorithms.
result Demonstrates a novel mechanism to preserve privacy in statistical model checking.
Constructing brane quantization for An-resolutions using SYZ mirror symmetry.
problem Quantizing branes on singular fibers using SYZ mirror symmetry.
method Constructing coisotropic A-branes and their mirrors via fiberwise geometric quantization.
result Establishing a mirror isomorphism between endomorphism algebras.
A machine-checked Itô calculus for Brownian motion on [0,T]
problem Developing an L2 Itô calculus for Brownian motion method Formalized in Lean 4 on top of Mathlib and the BrownianMotion package
result First machine-checked proof of Itô's formula and construction of Itô integral as martingale-valued process
Randomly initialized networks can perform as well as pruned networks.
problem Understanding and improving network pruning methods.
method Sanity checks on recent pruning methods, proposing random tickets.
result Randomly initialized networks can perform as well as pruned networks.
In this paper, we investigate the properties of the full colored HOMFLYPT invariants in the full skein of the annulus C. We show that the full colored HOMFLYPT invariant has a nice structure when q→1. The composite invariant is a combination of the full colored HOMFLYPT invariants. In order to …
A novel fact-checking method using debate dynamics on knowledge graphs.
problem Fact-checking on knowledge graphs with user comprehension and interactive reasoning.
method Reinforcement learning agents debate on paths in the graph to classify facts as true or false.
result Interactive reasoning and user understanding of AI decisions on knowledge graphs.
We propose a novel approach for analysis of the composition of an equity mutual fund based on the time series decomposition of the price movements of the individual stocks of the fund. The proposed scheme can be applied to check whether the style proclaimed for a mutual fund actually matches with the fund composition. …
The paper proposes a method to evaluate superhuman models by checking for logical inconsistencies.
problem Evaluating superhuman models when ground truth is hard to obtain.
method A framework using consistency checks to identify logical inconsistencies in model decisions.
result Logical inconsistencies can be discovered in superhuman model decisions across various tasks.
The chapter improves deep learning models by interpreting and improving their performance.
problem Deep learning models often lack interpretability, leading to poor understanding of their predictions.
method The approach involves attributing importance to features and feature groups, including interactions, to improve model performance.
result The proposed attributions provide insights across various domains and can be used to improve model generalization.
Scalable model checking for stochastic systems using Gaussian Processes and Bayesian Neural Networks.
problem Efficiently verifying properties of stochastic systems with high-dimensional parameter spaces.
method Stochastic Variational Smoothed Model Checking (SV-smMC) using Gaussian Processes and Bayesian Neural Networks.
result SV-smMC scales to larger datasets and enables application to high-dimensional parameter spaces.