Tootfinder

Data Diversification Methods In Alignment Enhance Math Performance In LLMs
Berkan Dokmeci, Qingyang Wu, Ben Athiwaratkun, Ce Zhang, Shuaiwen Leon Song, James Zou
https://arxiv.org/abs/2507.02173

Data Diversification Methods In Alignment Enhance Math Performance In LLMs
While recent advances in preference learning have enhanced alignment in human feedback, mathematical reasoning remains a persistent challenge. We investigate how data diversification strategies in preference optimization can improve the mathematical reasoning abilities of large language models (LLMs). We evaluate three common data generation methods: temperature sampling, Chain-of-Thought prompting, and Monte Carlo Tree Search (MCTS), and introduce Diversified-ThinkSolve (DTS), a novel structur…

Holger #Zastrow wäre weniger Bürgerinnenbeteiligung beim Neubau der #Carolabrücke lieber gewesen.
Das kann man einfach mal so stehen lassen.

Schneller Carolabrückenbau: CDU, FDP und Team Zastrow stellen Änderungsantrag
Schneller Carolabrückenbau: CDU, FDP und Team Zastrow stellen Änderungsantrag | Wie soll die neue Carolabrücke aussehen? Für CDU, FDP/Freie Bürger und Team Zastrow ist die Antwort klar: leistungsfähig, schnell gebaut und mit vier Spuren …

Partial Weakly-Supervised Oriented Object Detection
Mingxin Liu, Peiyuan Zhang, Yuan Liu, Wei Zhang, Yue Zhou, Ning Liao, Ziyang Gong, Junwei Luo, Zhirui Wang, Yi Yu, Xue Yang
https://arxiv.org/abs/2507.02751

Partial Weakly-Supervised Oriented Object Detection
The growing demand for oriented object detection (OOD) across various domains has driven significant research in this area. However, the high cost of dataset annotation remains a major concern. Current mainstream OOD algorithms can be mainly categorized into three types: (1) fully supervised methods using complete oriented bounding box (OBB) annotations, (2) semi-supervised methods using partial OBB annotations, and (3) weakly supervised methods using weak annotations such as horizontal boxes o…

This https://arxiv.org/abs/2102.08600 has been replaced.
link: https://scholar.google.com/scholar?q=a

A new characterization of the convergence factor of two-level methods
Multilevel methods are among the most efficient numerical methods for solving large-scale systems of equations that arise from discretized partial differential equations. Two-level convergence theory plays a fundamental role in the analysis and design of multilevel methods. In this paper, we present a concise and easy-to-use identity for characterizing the convergence factor of two-level methods, whose hierarchical spaces can be either overlapping or non-overlapping. In order to illustrate its …

Graph-Embedding Empowered Entity Retrieval
Emma J. Gerritse, Faegheh Hasibi, Arjen P. de Vries
https://arxiv.org/abs/2506.03895 https://

Graph-Embedding Empowered Entity Retrieval
In this research, we investigate methods for entity retrieval using graph embeddings. While various methods have been proposed over the years, most utilize a single graph embedding and entity linking approach. This hinders our understanding of how different graph embedding and entity linking methods impact entity retrieval. To address this gap, we investigate the effects of three different categories of graph embedding techniques and five different entity linking methods. We perform a reranking…

Ich kannte den gar nicht, aber noch bis Montag läuft in der ARD Mediathek ein spektakulär guter Film:
The Hours: Über drei Frauen zu verschiedenen Zeiten nach Virginia Woolfs Roman 'Mrs. Dalloway', mit Meryl Streep, Julianne Moore und Nicole Kidman, die dafür einen Oscar bekam. Der Film hätte viel mehr verdient.

Operator-Theoretic Methods for Differential Games
Craig Bakker, Adam T. Rupe, Alexander Von Moll, Adam R. Gerlach
https://arxiv.org/abs/2507.02203 https://…

Operator-Theoretic Methods for Differential Games
Differential game theory offers an approach for modeling interactions between two or more agents that occur in continuous time. The goal of each agent is to optimize its objective cost functional. In this paper, we present two different methods, based on the Koopman Operator (KO), to solve a zero-sum differential game. The first approach uses the resolvent of the KO to calculate a continuous-time global feedback solution over the entire domain. The second approach uses a discrete-time, data-dri…

Rapid stellar and binary population synthesis with COMPAS: methods paper II
Ilya Mandel, Jeff Riley, Adam Boesky, Adam Brcek, Ryosuke Hirai, Veome Kapil, Mike Y. M. Lau, JD Merritt, Nicol\'as Rodr\'iguez-Segovia, Isobel Romero-Shaw, Yuzhe Song, Simon Stevenson, Avi Vajpeyi, L. A. C. van Son, Alejandro Vigna-G\'omez, Reinhold Willcox
https…

Rapid stellar and binary population synthesis with COMPAS: methods paper II
The COMPAS public rapid binary population synthesis code has undergone a number of key improvements since the original COMPAS methods paper (Team COMPAS: Riley et al., 2022) was published. These include more sophisticated and robust treatments of binary interactions: mass transfer physics, common-envelope events, tides and gravitational-wave radiation reaction; and updated prescriptions for stellar evolution, winds and supernovae. The code structure and outputs have also been updated, with a fo…

Symplectic Hamiltonian Hybridizable Discontinuous Galerkin Methods for Linearized Shallow Water Equations
C. N\'u\~nez (Facultad de Matem\'aticas, Pontificia Universidad Cat\'olica de Chile, Santiago, Chile), M. A. S\'anchez (Instituto de Ingenier\'ia Matem\'atica y Computacional, Facultad de Matem\'aticas y Escuela de Ingenier\'ia, Pontificia Universidad Cat\'olica de Chile, Santiago, Chile)

Symplectic Hamiltonian Hybridizable Discontinuous Galerkin Methods for Linearized Shallow Water Equations
This paper focuses on the numerical approximation of the linearized shallow water equations using hybridizable discontinuous Galerkin (HDG) methods, leveraging the Hamiltonian structure of the evolution system. First, we propose an equivalent formulation of the equations by introducing an auxiliary variable. Then, we discretize the space variables using HDG methods, resulting in a semi-discrete scheme that preserves a discrete version of the Hamiltonian structure. The use of an alternative form…

An Overview of GPU-based First-Order Methods for Linear Programming and Extensions
Haihao Lu, Jinwen Yang
https://arxiv.org/abs/2506.02174 https://

An Overview of GPU-based First-Order Methods for Linear Programming and Extensions
The rapid progress in GPU computing has revolutionized many fields, yet its potential in mathematical programming, such as linear programming (LP), has only recently begun to be realized. This survey aims to provide a comprehensive overview of recent advancements in GPU-based first-order methods for LP, with a particular focus on the design and development of cuPDLP. We begin by presenting the design principles and algorithmic foundation of the primal-dual hybrid gradient (PDHG) method, which f…