arXiv research

Benchmarking AutoML for tables with text fields, achieving top performance.

Following great success in the image processing field, the idea of adversarial training has been applied to tasks in the natural language processing (NLP) field. One promising approach directly applies adversarial training developed in the image processing field to the input word embedding space instead of the discrete…

Classifies manifolds with specific spinors and constructs parallel spinors.

ETM identifies field-specific keywords in text classification.

Tool uses text mining to define innovative tech fields from abstracts.

Classifies 3-manifolds with Killing vector fields, extending results from Riemannian to Lorentzian.

This work proposes an efficient autoregressive model for text generation.

Study on cohomology of special linear groups over Euclidean number rings.

Automatic understanding of domain specific texts in order to extract useful relationships for later use is a non-trivial task. One such relationship would be between railroad accidents' causes and their correspondent descriptions in reports. From 2001 to 2016 rail accidents in the U.S. cost more than $4.6B. Railroads i…

Paper solves curvature prescription problem on surfaces with boundary.

BioFinBERT analyzes sentiment of biotech press releases and financial text around inflection points.

The moduli space of Hermitian-Einstein connections on certain manifolds has a strong Kähler with torsion structure.

Model improves BERT for answering multiple-choice questions in large texts.

The paper explores geometric and algebraic structures on Lie groups.

DreamFusion uses text-to-image diffusion models to create 3D images efficiently.

Proves helicity is the only regular Casimir for 3D hydrodynamics.

Estimates the degree of trace fields of hyperbolic Dehn fillings.

This is the text from a talk at the Arbeitstagung 2011, which can serve as an introduction to arxiv:1009.0736 and arXiv:1007.0907. I first discuss how a global field is determined by a certain dynamical system, and how this relates to abelian L-series determining those fields. I then discuss an analog in Riemannian geo…

In this text we introduce the torsion of spinor connections. In terms of the torsion we give conditions on a spinor connection to produce Killing vector fields. We relate the Bianchi type identities for the torsion of spinor connections with Jacobi identities for vector fields on supermanifolds. Furthermore, we discuss…

Develops Weil bundles over \( p \)-adic manifolds for arithmetic geometry.

The polysymplectic $(n+1)$-form is introduced as an analogue of the symplectic form for the De Donder-Weyl polymomentum Hamiltonian formulation of field theory. The corresponding Poisson brackets on differential forms are constructed. The analogues of the Poisson algebra are shown to be generalized (non-commutative and…

As the Portable Document Format (PDF) file format increases in popularity, research in analysing its structure for text extraction and analysis is necessary. Detecting headings can be a crucial component of classifying and extracting meaningful data. This research involves training a supervised learning model to detect…

Solutions to a quadratic matrix equation are linked to strongly regular graphs and multiplicative characters.

A new test assesses text similarity between two groups of documents.

Early detection of preventable diseases is important for better disease management, improved inter-ventions, and more efficient health-care resource allocation. Various machine learning approacheshave been developed to utilize information in Electronic Health Record (EHR) for this task. Majorityof previous attempts, ho…

Projective resolves symplectic Steinberg module for number rings.

System identifies high impact research from academic papers.

Develops Schouten-Nijenhuis bracket on infinite-dimensional manifolds.

For any compact oriented manifold $M$, we show that that the top degree multi-vector fields transverse to the zero section of $\wedge^{\text{top}}TM$ are classified, up to orientation preserving diffeomorphism, in terms of the topology of the arrangement of its zero locus and a finite number of numerical invariants. Th…

Learning representations that accurately capture long-range dependencies in sequential inputs -- including text, audio, and genomic data -- is a key problem in deep learning. Feed-forward convolutional models capture only feature interactions within finite receptive fields while recurrent architectures can be slow and …

This paper addresses the problem of predicting duration of unplanned power outages, using historical outage records to train a series of neural network predictors. The initial duration prediction is made based on environmental factors, and it is updated based on incoming field reports using natural language processing …

Combines supergeometry and supersymmetry for new geometric structures.

We adapt the Newman-Penrose formalism in general relativity to the setting of three-dimensional Riemannian geometry, and prove the following results. Given a Riemannian 3-manifold without boundary and a smooth unit vector field ${\boldsymbol k}$ with geodesic flow, if an integral curve of ${\boldsymbol k}$ is hypersurf…

Novel alignment framework for text-to-image generation using diffusion models and flow matching.

In this text we give a decomposition result on polynomial poly-vector fields generalizing a result on the decomposition of homogeneous Poisson structures. We discuss consequences of this decomposition result in particular for low dimensions and low degrees. We provide the tools to calculate simple cubic Poisson structu…

Given a regular bounded domain $Ω\subset\R{2m}$, we describe the limiting behavior of sequences of solutions to the mean field equation of order $2m$, $m\geq 1$, $(-Δ)^m u=ρ\frac{e^{2mu}}{\int_Ωe^{2mu}dx}\quad\text{in}Ω,$ under the Dirichlet boundary condition and the bound $0<ρ\leq C$. We emphasize the connection wi…

Study quantifies properties of PMC hypersurfaces with area bounds.

Graphs and networks are a key research tool for a variety of science fields, most notably chemistry, biology, engineering and social sciences. Modeling and generation of graphs with efficient sampling is a key challenge for graphs. In particular, the non-uniqueness, high dimensionality of the vertices and local depende…

Essential tori in certain 3-manifolds are missed by ideal points in character varieties.

Proposes CLRS-Text, a new benchmark for evaluating LM reasoning capabilities.

Projective geometry aids in analyzing fields near compact manifolds.

A new text classification method using separable convolution reduces memory consumption.

We present PubMed 200k RCT, a new dataset based on PubMed for sequential sentence classification. The dataset consists of approximately 200,000 abstracts of randomized controlled trials, totaling 2.3 million sentences. Each sentence of each abstract is labeled with their role in the abstract using one of the following …

The abstract defines and studies a Tits building for commutative rings and proves a Solomon-Tits theorem under certain conditions.

Speech Translation has always been about giving source text or audio input and waiting for system to give translated output in desired form. In this paper, we present the Acoustic Dialect Decoder (ADD) - a voice to voice ear-piece translation device. We introduce and survey the recent advances made in the field of Spee…

Improved text generation with constraints using discrete auto-regressive biasing.

A selfsimiar manifold is a Riemannian manifold $\left(M,g\right)$ endowed with a homothetic vector field $ξ$. We characterize global selfsimilar manifolds and describe the structure of local selfsimilar manifolds. We prove that any selfsimilar manifold with a potential homothetic vector field is a conical Riemannian ma…

Historically, games of all kinds have often been the subject of study in scientific works of Computer Science, including the field of machine learning. By using machine learning techniques and applying them to a game with defined rules or a structured dataset, it's possible to learn and improve on the already existing …