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Papers Dataset Generation

“Dataset Generation” 태그가 달린 논문 308편 · 필터 해제

Contextual Paralinguistic Data Creation for Multi-Modal Speech-LLM: Data Condensation and Spoken QA Generation

2025-05-19 · Qiongqiong Wang, Hardik B. Sailor, Tianchi Liu, Ai Ti Aw

Current speech-LLMs exhibit limited capability in contextual reasoning alongside paralinguistic understanding, primarily due to the lack of Question-Answer (QA) datasets that cover both aspects. We propose a novel framew…

Dataset Generation

Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents

2025-05-19 · CVPR 2025 1 · Yunseok Jang, Yeda Song, Sungryull Sohn, Lajanugen Logeswaran 외

Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have sparked significant interest in developing GUI visual agents. We introduce MONDAY (Mobile OS Navigation Task Dataset for Agents f…

Dataset GenerationOptical Character Recognition (OCR)

Event-based Star Tracking under Spacecraft Jitter: the e-STURT Dataset

2025-05-19 · Samya Bagchi, Peter Anastasiou, Matthew Tetlow, Tat-Jun Chin 외

Jitter degrades a spacecraft's fine-pointing ability required for optical communication, earth observation, and space domain awareness. Development of jitter estimation and compensation algorithms requires high-fidelity …

Dataset GenerationEarth Observation

Tiny QA Benchmark++: Ultra-Lightweight, Synthetic Multilingual Dataset Generation & Smoke-Tests for Continuous LLM Evaluation

2025-05-17 · Vincent Koc

Tiny QA Benchmark++ (TQB++) presents an ultra-lightweight, multilingual smoke-test suite designed to give large-language-model (LLM) pipelines a unit-test style safety net dataset that runs in seconds with minimal cost. …

Dataset GenerationGPULarge Language ModelMMLU+2

LoFT: LoRA-fused Training Dataset Generation with Few-shot Guidance

2025-05-16 · Jae Myung Kim, Stephan Alaniz, Cordelia Schmid, Zeynep Akata

Despite recent advances in text-to-image generation, using synthetically generated data seldom brings a significant boost in performance for supervised learning. Oftentimes, synthetic datasets do not faithfully recreate …

Dataset GenerationDiversityImage GenerationText to Image Generation+1

Noisemaker 3D: Comprehensive Framework for Mesh Noise Generation

2025-05-16 · 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2025) 2025 5 · Vladimir Mashurov, Vasilii Latonov, Anastasia Martynova, Natalia Semenova

In this article, we present a comprehensive library for generating node and topological noise in meshes. The library provides a versatile tool for creating corrupted mesh datasets, which are essential for learning-based …

3D Mesh Denoising3D Noise GenerationDataset GenerationDenoising

IrrMap: A Large-Scale Comprehensive Dataset for Irrigation Method Mapping

2025-05-13 · Nibir Chandra Mandal, Oishee Bintey Hoque, Abhijin Adiga, Samarth Swarup 외

We introduce IrrMap, the first large-scale dataset (1.1 million patches) for irrigation method mapping across regions. IrrMap consists of multi-resolution satellite imagery from LandSat and Sentinel, along with key auxil…

Dataset Generation

Guidance for Intra-cardiac Echocardiography Manipulation to Maintain Continuous Therapy Device Tip Visibility

2025-05-08 · Jaeyoung Huh, Ankur Kapoor, Young-Ho Kim

Intra-cardiac Echocardiography (ICE) plays a critical role in Electrophysiology (EP) and Structural Heart Disease (SHD) interventions by providing real-time visualization of intracardiac structures. However, maintaining …

Data AugmentationDataset Generation

Bounding Box-Guided Diffusion for Synthesizing Industrial Images and Segmentation Map

2025-05-06 · Alessandro Simoni, Francesco Pelosin

Synthetic dataset generation in Computer Vision, particularly for industrial applications, is still underexplored. Industrial defect segmentation, for instance, requires highly accurate labels, yet acquiring such data is…

Dataset GenerationSegmentation

Estimating Commonsense Scene Composition on Belief Scene Graphs

2025-05-05 · Mario A. V. Saucedo, Vignesh Kottayam Viswanathan, Christoforos Kanellakis, George Nikolakopoulos

This work establishes the concept of commonsense scene composition, with a focus on extending Belief Scene Graphs by estimating the spatial distribution of unseen objects. Specifically, the commonsense scene composition …

Dataset Generation

Document Retrieval Augmented Fine-Tuning (DRAFT) for safety-critical software assessments

2025-05-02 · Regan Bolton, Mohammadreza Sheikhfathollahi, Simon Parkinson, Vanessa Vulovic 외

Safety critical software assessment requires robust assessment against complex regulatory frameworks, a process traditionally limited by manual evaluation. This paper presents Document Retrieval-Augmented Fine-Tuning (DR…

Dataset GenerationLanguage ModelingLanguage ModellingLarge Language Model+3

TF1-EN-3M: Three Million Synthetic Moral Fables for Training Small, Open Language Models

2025-04-29 · Mihai Nadas, Laura Diosan, Andrei Piscoran, Andreea Tomescu

Moral stories are a time-tested vehicle for transmitting values, yet modern NLP lacks a large, structured corpus that couples coherent narratives with explicit ethical lessons. We close this gap with TF1-EN-3M, the first…

BenchmarkingDataset GenerationGPUInstruction Following

V$^2$R-Bench: Holistically Evaluating LVLM Robustness to Fundamental Visual Variations

2025-04-23 · Zhiyuan Fan, Yumeng Wang, Sandeep Polisetty, Yi R. Fung

Large Vision Language Models (LVLMs) excel in various vision-language tasks. Yet, their robustness to visual variations in position, scale, orientation, and context that objects in natural scenes inevitably exhibit due t…

Dataset GenerationObject RecognitionPosition

MirrorVerse: Pushing Diffusion Models to Realistically Reflect the World

2025-04-21 · CVPR 2025 1 · Ankit Dhiman, Manan Shah, R Venkatesh Babu

Diffusion models have become central to various image editing tasks, yet they often fail to fully adhere to physical laws, particularly with effects like shadows, reflections, and occlusions. In this work, we address the…

Dataset Generation

Unreal Robotics Lab: A High-Fidelity Robotics Simulator with Advanced Physics and Rendering

2025-04-19 · Jonathan Embley-Riches, Jianwei Liu, Simon Julier, Dimitrios Kanoulas

High-fidelity simulation is essential for robotics research, enabling safe and efficient testing of perception, control, and navigation algorithms. However, achieving both photorealistic rendering and accurate physics mo…

BenchmarkingDataset GenerationVisual Navigation

Geometric Generality of Transformer-Based Gröbner Basis Computation

2025-04-16 · Yuta Kambe, Yota Maeda, Tristan Vaccon

The intersection of deep learning and symbolic mathematics has seen rapid progress in recent years, exemplified by the work of Lample and Charton. They demonstrated that effective training of machine learning models for …

Dataset Generation

DeepWheel: Generating a 3D Synthetic Wheel Dataset for Design and Performance Evaluation

2025-04-15 · Soyoung Yoo, Namwoo Kang

Data-driven design is emerging as a powerful strategy to accelerate engineering innovation. However, its application to vehicle wheel design remains limited due to the lack of large-scale, high-quality datasets that incl…

3D geometryDataset GenerationDepth Estimation

Reasoning Inconsistencies and How to Mitigate Them in Deep Learning

2025-04-03 · Erik Arakelyan

The recent advancements in Deep Learning models and techniques have led to significant strides in performance across diverse tasks and modalities. However, while the overall capabilities of models show promising growth, …

Dataset GenerationDeep LearningFairnessKnowledge Graphs

Concept-Aware LoRA for Domain-Aligned Segmentation Dataset Generation

2025-03-28 · Minho Park, Sunghyun Park, Jungsoo Lee, Hyojin Park 외

This paper addresses the challenge of data scarcity in semantic segmentation by generating datasets through text-to-image (T2I) generation models, reducing image acquisition and labeling costs. Segmentation dataset gener…

Dataset GenerationDomain GeneralizationScene SegmentationSegmentation+1

ColabSfM: Collaborative Structure-from-Motion by Point Cloud Registration

2025-03-21 · CVPR 2025 1 · Johan Edstedt, André Mateus, Alberto Jaenal

Structure-from-Motion (SfM) is the task of estimating 3D structure and camera poses from images. We define Collaborative SfM (ColabSfM) as sharing distributed SfM reconstructions. Sharing maps requires estimating a joint…

Dataset GenerationPoint Cloud Registration
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