Tootfinder

This https://arxiv.org/abs/2402.18573 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCV_…

UniMODE: Unified Monocular 3D Object Detection
Realizing unified monocular 3D object detection, including both indoor and outdoor scenes, holds great importance in applications like robot navigation. However, involving various scenarios of data to train models poses challenges due to their significantly different characteristics, e.g., diverse geometry properties and heterogeneous domain distributions. To address these challenges, we build a detector based on the bird's-eye-view (BEV) detection paradigm, where the explicit feature projectio…

Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model
Connall Garrod, Jonathan P. Keating
https://arxiv.org/abs/2404.06106

Unifying Low Dimensional Observations in Deep Learning Through the Deep Linear Unconstrained Feature Model
Modern deep neural networks have achieved high performance across various tasks. Recently, researchers have noted occurrences of low-dimensional structure in the weights, Hessian's, gradients, and feature vectors of these networks, spanning different datasets and architectures when trained to convergence. In this analysis, we theoretically demonstrate these observations arising, and show how they can be unified within a generalized unconstrained feature model that can be considered analytically…

This https://arxiv.org/abs/2402.04690 has been replaced.
link: https://scholar.google.com/scholar?q=a

On the early stages of vapor bubble growth: From the surface-tension to the inertial regime
This paper presents a new analytical model for the early stages of vapor bubble growth in superheated liquids. The model bridges a gap in current knowledge by focusing on the surface tension-controlled, near-equilibrium growth regime and its transition to an inertia-controlled regime. A unified analytical model is derived by combining a perturbation method for the initial growth regime with a complementary outer solution to model the subsequent bubble growth rate. The model successfully predict…

Flashback 1975: The Packers Shocked the Cowboys as Bart Starr Earned His First Win as Head Coach https://www.yardbarker.com/nfl/articles/flashback_1975_the_packers_shocked_the_cowbo…

Optical Photon Emission in Extended Airshowers -- Hybrid computing in the context of CORSIKA 8
Dominik Baack
https://arxiv.org/abs/2405.04229 https://

Optical Photon Emission in Extended Airshowers -- Hybrid computing in the context of CORSIKA 8
With the motivation to improve experimental gains and precision, established astroparticle experiments are currently undergoing massive upgrades. In addition, several new experiments are being built or planned. With the resulting gain in observational quality, the amount and accuracy of simulated data required for the analysis is also rising. In order to meet the increasing requirements and complexity due to the experiments' growth and to provide a unified software ecosystem, it was decided to …

This https://arxiv.org/abs/2211.07762 has been replaced.
link: https://scholar.google.com/scholar?q=a

Unified synthetic Ricci curvature lower bounds for Riemannian and sub-Riemannian structures
Recent advances in the theory of metric measures spaces on the one hand, and of sub-Riemannian ones on the other hand, suggest the possibility of a "great unification" of Riemannian and sub-Riemannian geometries in a comprehensive framework of synthetic Ricci curvature lower bounds. With the aim of achieving such a unification program, in this paper we initiate the study of gauge metric measure spaces.

Unbuttoned Podcast
Great Australian Pods Podcast Directory: #GreatAusPods

Unbuttoned | Great Australian Pods Podcast Directory
Podcast: Unbuttoned Podcast Host: Andrew Felix Category: Arts Sub-Category: Commentary & Conversations, Crafts & Creativity, Visual Arts First Episode: 2023 Where we talk about photography, modelling…

Fake it to make it: Using synthetic data to remedy the data shortage in joint multimodal speech-and-gesture synthesis
Shivam Mehta, Anna Deichler, Jim O'Regan, Birger Mo\"ell, Jonas Beskow, Gustav Eje Henter, Simon Alexanderson
https://arxiv.org/abs/2404.19622 https://arxiv.org/pdf/2404.19622
arXiv:2404.19622v1 Announce Type: new
Abstract: Although humans engaged in face-to-face conversation simultaneously communicate both verbally and non-verbally, methods for joint and unified synthesis of speech audio and co-speech 3D gesture motion from text are a new and emerging field. These technologies hold great promise for more human-like, efficient, expressive, and robust synthetic communication, but are currently held back by the lack of suitably large datasets, as existing methods are trained on parallel data from all constituent modalities. Inspired by student-teacher methods, we propose a straightforward solution to the data shortage, by simply synthesising additional training material. Specifically, we use unimodal synthesis models trained on large datasets to create multimodal (but synthetic) parallel training data, and then pre-train a joint synthesis model on that material. In addition, we propose a new synthesis architecture that adds better and more controllable prosody modelling to the state-of-the-art method in the field. Our results confirm that pre-training on large amounts of synthetic data improves the quality of both the speech and the motion synthesised by the multimodal model, with the proposed architecture yielding further benefits when pre-trained on the synthetic data. See https://shivammehta25.github.io/MAGI/ for example output.

A Unified Debugging Approach via LLM-Based Multi-Agent Synergy
Cheryl Lee, Chunqiu Steven Xia, Jen-tse Huang, Zhouruixin Zhu, Lingming Zhang, Michael R. Lyu
https://arxiv.org/abs/2404.17153

A Unified Debugging Approach via LLM-Based Multi-Agent Synergy
Tremendous efforts have been devoted to automating software debugging, a time-consuming process involving fault localization and repair generation. Recently, Large Language Models (LLMs) have shown great potential in automated debugging. However, we identified three challenges posed to traditional and LLM-based debugging tools: 1) the upstream imperfection of fault localization affects the downstream repair, 2) the deficiency in handling complex logic errors, and 3) the ignorance of program con…

A Unified Editing Method for Co-Speech Gesture Generation via Diffusion Inversion
Zeyu Zhao, Nan Gao, Zhi Zeng, Guixuan Zhang, Jie Liu, Shuwu Zhang
https://arxiv.org/abs/2404.02411

A Unified Editing Method for Co-Speech Gesture Generation via Diffusion Inversion
Diffusion models have shown great success in generating high-quality co-speech gestures for interactive humanoid robots or digital avatars from noisy input with the speech audio or text as conditions. However, they rarely focus on providing rich editing capabilities for content creators other than high-level specialized measures like style conditioning. To resolve this, we propose a unified framework utilizing diffusion inversion that enables multi-level editing capabilities for co-speech gestu…