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title string | abstract string | url string | category string | prediction string | probability float64 | arxiv_id string |
|---|---|---|---|---|---|---|
Credit card score prediction using machine learning models: A new dataset | The use of credit cards has recently increased, creating an essential need
for credit card assessment methods to minimize potential risks. This study
investigates the utilization of machine learning (ML) models for credit card
default prediction system. The main goal here is to investigate the
best-performing ML model ... | http://arxiv.org/abs/2310.02956v1 | cs.LG | new_dataset | 0.994289 | 2310.02956 |
Eye Fairness: A Large-Scale 3D Imaging Dataset for Equitable Eye Diseases Screening and Fair Identity Scaling | Fairness or equity in machine learning is profoundly important for societal
well-being, but limited public datasets hinder its progress, especially in the
area of medicine. It is undeniable that fairness in medicine is one of the most
important areas for fairness learning's applications. Currently, no large-scale
publi... | http://arxiv.org/abs/2310.02492v1 | cs.CV | new_dataset | 0.994452 | 2310.02492 |
Constructing Image-Text Pair Dataset from Books | Digital archiving is becoming widespread owing to its effectiveness in
protecting valuable books and providing knowledge to many people
electronically. In this paper, we propose a novel approach to leverage digital
archives for machine learning. If we can fully utilize such digitized data,
machine learning has the pote... | http://arxiv.org/abs/2310.01936v1 | cs.CV | new_dataset | 0.994403 | 2310.01936 |
Improving Dialogue Management: Quality Datasets vs Models | Task-oriented dialogue systems (TODS) have become crucial for users to
interact with machines and computers using natural language. One of its key
components is the dialogue manager, which guides the conversation towards a
good goal for the user by providing the best possible response. Previous works
have proposed rule... | http://arxiv.org/abs/2310.01339v1 | cs.CL | not_new_dataset | 0.991986 | 2310.01339 |
Natural Language Models for Data Visualization Utilizing nvBench Dataset | Translation of natural language into syntactically correct commands for data
visualization is an important application of natural language models and could
be leveraged to many different tasks. A closely related effort is the task of
translating natural languages into SQL queries, which in turn could be
translated into... | http://arxiv.org/abs/2310.00832v1 | cs.CL | not_new_dataset | 0.992239 | 2310.00832 |
Enhancing Mortality Prediction in Heart Failure Patients: Exploring Preprocessing Methods for Imbalanced Clinical Datasets | Heart failure (HF) is a critical condition in which the accurate prediction
of mortality plays a vital role in guiding patient management decisions.
However, clinical datasets used for mortality prediction in HF often suffer
from an imbalanced distribution of classes, posing significant challenges. In
this paper, we ex... | http://arxiv.org/abs/2310.00457v1 | cs.LG | not_new_dataset | 0.980858 | 2310.00457 |
Building Flexible, Scalable, and Machine Learning-ready Multimodal Oncology Datasets | The advancements in data acquisition, storage, and processing techniques have
resulted in the rapid growth of heterogeneous medical data. Integrating
radiological scans, histopathology images, and molecular information with
clinical data is essential for developing a holistic understanding of the
disease and optimizing... | http://arxiv.org/abs/2310.01438v1 | cs.LG | not_new_dataset | 0.989 | 2310.01438 |
Efficient Large Scale Medical Image Dataset Preparation for Machine Learning Applications | In the rapidly evolving field of medical imaging, machine learning algorithms
have become indispensable for enhancing diagnostic accuracy. However, the
effectiveness of these algorithms is contingent upon the availability and
organization of high-quality medical imaging datasets. Traditional Digital
Imaging and Communi... | http://arxiv.org/abs/2309.17285v1 | cs.CV | not_new_dataset | 0.978577 | 2309.17285 |
FENDA-FL: Personalized Federated Learning on Heterogeneous Clinical Datasets | Federated learning (FL) is increasingly being recognized as a key approach to
overcoming the data silos that so frequently obstruct the training and
deployment of machine-learning models in clinical settings. This work
contributes to a growing body of FL research specifically focused on clinical
applications along thre... | http://arxiv.org/abs/2309.16825v1 | cs.LG | not_new_dataset | 0.99214 | 2309.16825 |
ComPile: A Large IR Dataset from Production Sources | Code is increasingly becoming a core data modality of modern machine learning
research impacting not only the way we write code with conversational agents
like OpenAI's ChatGPT, Google's Bard, or Anthropic's Claude, the way we
translate code from one language into another, but also the compiler
infrastructure underlyin... | http://arxiv.org/abs/2309.15432v1 | cs.PL | new_dataset | 0.994593 | 2309.15432 |
Challenges of building medical image datasets for development of deep learning software in stroke | Despite the large amount of brain CT data generated in clinical practice, the
availability of CT datasets for deep learning (DL) research is currently
limited. Furthermore, the data can be insufficiently or improperly prepared for
machine learning and thus lead to spurious and irreproducible analyses. This
lack of acce... | http://arxiv.org/abs/2309.15081v1 | eess.IV | not_new_dataset | 0.992066 | 2309.15081 |
Real3D-AD: A Dataset of Point Cloud Anomaly Detection | High-precision point cloud anomaly detection is the gold standard for
identifying the defects of advancing machining and precision manufacturing.
Despite some methodological advances in this area, the scarcity of datasets and
the lack of a systematic benchmark hinder its development. We introduce
Real3D-AD, a challengi... | http://arxiv.org/abs/2309.13226v2 | cs.CV | new_dataset | 0.994488 | 2309.13226 |
OSN-MDAD: Machine Translation Dataset for Arabic Multi-Dialectal Conversations on Online Social Media | While resources for English language are fairly sufficient to understand
content on social media, similar resources in Arabic are still immature. The
main reason that the resources in Arabic are insufficient is that Arabic has
many dialects in addition to the standard version (MSA). Arabs do not use MSA
in their daily ... | http://arxiv.org/abs/2309.12137v1 | cs.CL | new_dataset | 0.994525 | 2309.12137 |
Dataset Factory: A Toolchain For Generative Computer Vision Datasets | Generative AI workflows heavily rely on data-centric tasks - such as
filtering samples by annotation fields, vector distances, or scores produced by
custom classifiers. At the same time, computer vision datasets are quickly
approaching petabyte volumes, rendering data wrangling difficult. In addition,
the iterative nat... | http://arxiv.org/abs/2309.11608v1 | cs.AI | not_new_dataset | 0.9875 | 2309.11608 |
SignBank+: Multilingual Sign Language Translation Dataset | This work advances the field of sign language machine translation by focusing
on dataset quality and simplification of the translation system. We introduce
SignBank+, a clean version of the SignBank dataset, optimized for machine
translation. Contrary to previous works that employ complex factorization
techniques for t... | http://arxiv.org/abs/2309.11566v1 | cs.CL | new_dataset | 0.994233 | 2309.11566 |
GECTurk: Grammatical Error Correction and Detection Dataset for Turkish | Grammatical Error Detection and Correction (GEC) tools have proven useful for
native speakers and second language learners. Developing such tools requires a
large amount of parallel, annotated data, which is unavailable for most
languages. Synthetic data generation is a common practice to overcome the
scarcity of such ... | http://arxiv.org/abs/2309.11346v1 | cs.CL | new_dataset | 0.994401 | 2309.11346 |
Benchmarks for Pirá 2.0, a Reading Comprehension Dataset about the Ocean, the Brazilian Coast, and Climate Change | Pir\'a is a reading comprehension dataset focused on the ocean, the Brazilian
coast, and climate change, built from a collection of scientific abstracts and
reports on these topics. This dataset represents a versatile language resource,
particularly useful for testing the ability of current machine learning models
to a... | http://arxiv.org/abs/2309.10945v1 | cs.CL | new_dataset | 0.994546 | 2309.10945 |
Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning | Pathology diagnosis based on EEG signals and decoding brain activity holds
immense importance in understanding neurological disorders. With the
advancement of artificial intelligence methods and machine learning techniques,
the potential for accurate data-driven diagnoses and effective treatments has
grown significantl... | http://arxiv.org/abs/2309.10910v1 | cs.LG | not_new_dataset | 0.992257 | 2309.10910 |
A Configurable Library for Generating and Manipulating Maze Datasets | Understanding how machine learning models respond to distributional shifts is
a key research challenge. Mazes serve as an excellent testbed due to varied
generation algorithms offering a nuanced platform to simulate both subtle and
pronounced distributional shifts. To enable systematic investigations of model
behavior ... | http://arxiv.org/abs/2309.10498v1 | cs.LG | new_dataset | 0.992489 | 2309.10498 |
RenderIH: A Large-scale Synthetic Dataset for 3D Interacting Hand Pose Estimation | The current interacting hand (IH) datasets are relatively simplistic in terms
of background and texture, with hand joints being annotated by a machine
annotator, which may result in inaccuracies, and the diversity of pose
distribution is limited. However, the variability of background, pose
distribution, and texture ca... | http://arxiv.org/abs/2309.09301v3 | cs.CV | new_dataset | 0.994482 | 2309.09301 |
HealthFC: A Dataset of Health Claims for Evidence-Based Medical Fact-Checking | Seeking health-related advice on the internet has become a common practice in
the digital era. Determining the trustworthiness of medical claims found online
and finding appropriate evidence for this information is increasingly
challenging. Fact-checking has emerged as an approach to assess the veracity of
factual clai... | http://arxiv.org/abs/2309.08503v1 | cs.CL | new_dataset | 0.994519 | 2309.08503 |
Let's Roll: Synthetic Dataset Analysis for Pedestrian Detection Across Different Shutter Types | Computer vision (CV) pipelines are typically evaluated on datasets processed
by image signal processing (ISP) pipelines even though, for
resource-constrained applications, an important research goal is to avoid as
many ISP steps as possible. In particular, most CV datasets consist of global
shutter (GS) images even tho... | http://arxiv.org/abs/2309.08136v1 | cs.CV | not_new_dataset | 0.992204 | 2309.08136 |
Multi-Source Domain Adaptation meets Dataset Distillation through Dataset Dictionary Learning | In this paper, we consider the intersection of two problems in machine
learning: Multi-Source Domain Adaptation (MSDA) and Dataset Distillation (DD).
On the one hand, the first considers adapting multiple heterogeneous labeled
source domains to an unlabeled target domain. On the other hand, the second
attacks the probl... | http://arxiv.org/abs/2309.07666v1 | cs.LG | not_new_dataset | 0.991879 | 2309.07666 |
SIB-200: A Simple, Inclusive, and Big Evaluation Dataset for Topic Classification in 200+ Languages and Dialects | Despite the progress we have recorded in the last few years in multilingual
natural language processing, evaluation is typically limited to a small set of
languages with available datasets which excludes a large number of low-resource
languages. In this paper, we created SIB-200 -- a large-scale open-sourced
benchmark ... | http://arxiv.org/abs/2309.07445v1 | cs.CL | new_dataset | 0.994486 | 2309.07445 |
ProMap: Datasets for Product Mapping in E-commerce | The goal of product mapping is to decide, whether two listings from two
different e-shops describe the same products. Existing datasets of matching and
non-matching pairs of products, however, often suffer from incomplete product
information or contain only very distant non-matching products. Therefore,
while predictiv... | http://arxiv.org/abs/2309.06882v1 | cs.LG | new_dataset | 0.99443 | 2309.06882 |
Scalable neural network models and terascale datasets for particle-flow reconstruction | We study scalable machine learning models for full event reconstruction in
high-energy electron-positron collisions based on a highly granular detector
simulation. Particle-flow (PF) reconstruction can be formulated as a supervised
learning task using tracks and calorimeter clusters or hits. We compare a graph
neural n... | http://arxiv.org/abs/2309.06782v1 | physics.data-an | new_dataset | 0.960086 | 2309.06782 |
Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation | Many components of data analysis in high energy physics and beyond require
morphing one dataset into another. This is commonly solved via reweighting, but
there are many advantages of preserving weights and shifting the data points
instead. Normalizing flows are machine learning models with impressive
precision on a va... | http://arxiv.org/abs/2309.06472v1 | hep-ph | not_new_dataset | 0.992158 | 2309.06472 |
MADLAD-400: A Multilingual And Document-Level Large Audited Dataset | We introduce MADLAD-400, a manually audited, general domain 3T token
monolingual dataset based on CommonCrawl, spanning 419 languages. We discuss
the limitations revealed by self-auditing MADLAD-400, and the role data
auditing had in the dataset creation process. We then train and release a
10.7B-parameter multilingual... | http://arxiv.org/abs/2309.04662v1 | cs.CL | new_dataset | 0.994489 | 2309.04662 |
Beyond Static Datasets: A Deep Interaction Approach to LLM Evaluation | Large Language Models (LLMs) have made progress in various real-world tasks,
which stimulates requirements for the evaluation of LLMs. Existing LLM
evaluation methods are mainly supervised signal-based which depends on static
datasets and cannot evaluate the ability of LLMs in dynamic real-world
scenarios where deep in... | http://arxiv.org/abs/2309.04369v1 | cs.CL | not_new_dataset | 0.991883 | 2309.04369 |
Dataset Generation and Bonobo Classification from Weakly Labelled Videos | This paper presents a bonobo detection and classification pipeline built from
the commonly used machine learning methods. Such application is motivated by
the need to test bonobos in their enclosure using touch screen devices without
human assistance. This work introduces a newly acquired dataset based on bonobo
record... | http://arxiv.org/abs/2309.03671v1 | cs.CV | new_dataset | 0.993644 | 2309.03671 |
ORL-AUDITOR: Dataset Auditing in Offline Deep Reinforcement Learning | Data is a critical asset in AI, as high-quality datasets can significantly
improve the performance of machine learning models. In safety-critical domains
such as autonomous vehicles, offline deep reinforcement learning (offline DRL)
is frequently used to train models on pre-collected datasets, as opposed to
training th... | http://arxiv.org/abs/2309.03081v1 | cs.CR | not_new_dataset | 0.992096 | 2309.03081 |
Augmenting Chest X-ray Datasets with Non-Expert Annotations | The advancement of machine learning algorithms in medical image analysis
requires the expansion of training datasets. A popular and cost-effective
approach is automated annotation extraction from free-text medical reports,
primarily due to the high costs associated with expert clinicians annotating
chest X-ray images. ... | http://arxiv.org/abs/2309.02244v1 | cs.CV | not_new_dataset | 0.991341 | 2309.02244 |
Artificial Empathy Classification: A Survey of Deep Learning Techniques, Datasets, and Evaluation Scales | From the last decade, researchers in the field of machine learning (ML) and
assistive developmental robotics (ADR) have taken an interest in artificial
empathy (AE) as a possible future paradigm for human-robot interaction (HRI).
Humans learn empathy since birth, therefore, it is challenging to instill this
sense in ro... | http://arxiv.org/abs/2310.00010v1 | cs.RO | not_new_dataset | 0.992233 | 2310.00010 |
DiffuGen: Adaptable Approach for Generating Labeled Image Datasets using Stable Diffusion Models | Generating high-quality labeled image datasets is crucial for training
accurate and robust machine learning models in the field of computer vision.
However, the process of manually labeling real images is often time-consuming
and costly. To address these challenges associated with dataset generation, we
introduce "Diff... | http://arxiv.org/abs/2309.00248v1 | cs.CV | not_new_dataset | 0.992016 | 2309.00248 |
Learning to Taste: A Multimodal Wine Dataset | We present WineSensed, a large multimodal wine dataset for studying the
relations between visual perception, language, and flavor. The dataset
encompasses 897k images of wine labels and 824k reviews of wines curated from
the Vivino platform. It has over 350k unique vintages, annotated with year,
region, rating, alcohol... | http://arxiv.org/abs/2308.16900v3 | cs.LG | new_dataset | 0.994486 | 2308.16900 |
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants | We present Belebele, a multiple-choice machine reading comprehension (MRC)
dataset spanning 122 language variants. Significantly expanding the language
coverage of natural language understanding (NLU) benchmarks, this dataset
enables the evaluation of text models in high-, medium-, and low-resource
languages. Each ques... | http://arxiv.org/abs/2308.16884v1 | cs.CL | new_dataset | 0.994427 | 2308.16884 |
Speech Wikimedia: A 77 Language Multilingual Speech Dataset | The Speech Wikimedia Dataset is a publicly available compilation of audio
with transcriptions extracted from Wikimedia Commons. It includes 1780 hours
(195 GB) of CC-BY-SA licensed transcribed speech from a diverse set of
scenarios and speakers, in 77 different languages. Each audio file has one or
more transcriptions ... | http://arxiv.org/abs/2308.15710v1 | cs.AI | new_dataset | 0.994538 | 2308.15710 |
Probabilistic Dataset Reconstruction from Interpretable Models | Interpretability is often pointed out as a key requirement for trustworthy
machine learning. However, learning and releasing models that are inherently
interpretable leaks information regarding the underlying training data. As such
disclosure may directly conflict with privacy, a precise quantification of the
privacy i... | http://arxiv.org/abs/2308.15099v1 | cs.AI | not_new_dataset | 0.992246 | 2308.15099 |
Generating tabular datasets under differential privacy | Machine Learning (ML) is accelerating progress across fields and industries,
but relies on accessible and high-quality training data. Some of the most
important datasets are found in biomedical and financial domains in the form of
spreadsheets and relational databases. But this tabular data is often sensitive
in nature... | http://arxiv.org/abs/2308.14784v1 | cs.LG | not_new_dataset | 0.991477 | 2308.14784 |
TpuGraphs: A Performance Prediction Dataset on Large Tensor Computational Graphs | Precise hardware performance models play a crucial role in code
optimizations. They can assist compilers in making heuristic decisions or aid
autotuners in identifying the optimal configuration for a given program. For
example, the autotuner for XLA, a machine learning compiler, discovered 10-20%
speedup on state-of-th... | http://arxiv.org/abs/2308.13490v1 | cs.LG | new_dataset | 0.994445 | 2308.13490 |
Misinformation Concierge: A Proof-of-Concept with Curated Twitter Dataset on COVID-19 Vaccination | We demonstrate the Misinformation Concierge, a proof-of-concept that provides
actionable intelligence on misinformation prevalent in social media.
Specifically, it uses language processing and machine learning tools to
identify subtopics of discourse and discern non/misleading posts; presents
statistical reports for po... | http://arxiv.org/abs/2309.00639v1 | cs.CL | new_dataset | 0.993733 | 2309.00639 |
Towards Synthesizing Datasets for IEEE 802.1 Time-sensitive Networking | IEEE 802.1 Time-sensitive Networking (TSN) protocols have recently been
proposed to replace legacy networking technologies across different
mission-critical systems (MCSs). Design, configuration, and maintenance of TSN
within MCSs require advanced methods to tackle the highly complex and
interconnected nature of those ... | http://arxiv.org/abs/2308.10255v1 | cs.NI | not_new_dataset | 0.992071 | 2308.10255 |
DatasetEquity: Are All Samples Created Equal? In The Quest For Equity Within Datasets | Data imbalance is a well-known issue in the field of machine learning,
attributable to the cost of data collection, the difficulty of labeling, and
the geographical distribution of the data. In computer vision, bias in data
distribution caused by image appearance remains highly unexplored. Compared to
categorical distr... | http://arxiv.org/abs/2308.09878v2 | cs.CV | not_new_dataset | 0.991977 | 2308.09878 |
Leak Proof PDBBind: A Reorganized Dataset of Protein-Ligand Complexes for More Generalizable Binding Affinity Prediction | Many physics-based and machine-learned scoring functions (SFs) used to
predict protein-ligand binding free energies have been trained on the PDBBind
dataset. However, it is controversial as to whether new SFs are actually
improving since the general, refined, and core datasets of PDBBind are
cross-contaminated with pro... | http://arxiv.org/abs/2308.09639v1 | physics.bio-ph | new_dataset | 0.994495 | 2308.09639 |
Spatial LibriSpeech: An Augmented Dataset for Spatial Audio Learning | We present Spatial LibriSpeech, a spatial audio dataset with over 650 hours
of 19-channel audio, first-order ambisonics, and optional distractor noise.
Spatial LibriSpeech is designed for machine learning model training, and it
includes labels for source position, speaking direction, room acoustics and
geometry. Spatia... | http://arxiv.org/abs/2308.09514v1 | cs.SD | new_dataset | 0.99442 | 2308.09514 |
Advancing continual lifelong learning in neural information retrieval: definition, dataset, framework, and empirical evaluation | Continual learning refers to the capability of a machine learning model to
learn and adapt to new information, without compromising its performance on
previously learned tasks. Although several studies have investigated continual
learning methods for information retrieval tasks, a well-defined task
formulation is still... | http://arxiv.org/abs/2308.08378v1 | cs.IR | not_new_dataset | 0.991048 | 2308.08378 |
Action Class Relation Detection and Classification Across Multiple Video Datasets | The Meta Video Dataset (MetaVD) provides annotated relations between action
classes in major datasets for human action recognition in videos. Although
these annotated relations enable dataset augmentation, it is only applicable to
those covered by MetaVD. For an external dataset to enjoy the same benefit, the
relations... | http://arxiv.org/abs/2308.07558v1 | cs.CV | new_dataset | 0.771928 | 2308.07558 |
MDB: Interactively Querying Datasets and Models | As models are trained and deployed, developers need to be able to
systematically debug errors that emerge in the machine learning pipeline. We
present MDB, a debugging framework for interactively querying datasets and
models. MDB integrates functional programming with relational algebra to build
expressive queries over... | http://arxiv.org/abs/2308.06686v1 | cs.DB | not_new_dataset | 0.991822 | 2308.06686 |
How complex is the microarray dataset? A novel data complexity metric for biological high-dimensional microarray data | Data complexity analysis quantifies the hardness of constructing a predictive
model on a given dataset. However, the effectiveness of existing data
complexity measures can be challenged by the existence of irrelevant features
and feature interactions in biological micro-array data. We propose a novel
data complexity me... | http://arxiv.org/abs/2308.06430v1 | cs.CE | not_new_dataset | 0.9914 | 2308.06430 |
Composable Core-sets for Diversity Approximation on Multi-Dataset Streams | Core-sets refer to subsets of data that maximize some function that is
commonly a diversity or group requirement. These subsets are used in place of
the original data to accomplish a given task with comparable or even enhanced
performance if biases are removed. Composable core-sets are core-sets with the
property that ... | http://arxiv.org/abs/2308.05878v1 | cs.LG | not_new_dataset | 0.991313 | 2308.05878 |
JEDI: Joint Expert Distillation in a Semi-Supervised Multi-Dataset Student-Teacher Scenario for Video Action Recognition | We propose JEDI, a multi-dataset semi-supervised learning method, which
efficiently combines knowledge from multiple experts, learned on different
datasets, to train and improve the performance of individual, per dataset,
student models. Our approach achieves this by addressing two important problems
in current machine... | http://arxiv.org/abs/2308.04934v1 | cs.CV | not_new_dataset | 0.991983 | 2308.04934 |
An Analytical Study of Covid-19 Dataset using Graph-Based Clustering Algorithms | Corona VIrus Disease abbreviated as COVID-19 is a novel virus which is
initially identified in Wuhan of China in December of 2019 and now this deadly
disease has spread all over the world. According to World Health Organization
(WHO), a total of 3,124,905 people died from 2019 to 2021, April. In this case,
many methods... | http://arxiv.org/abs/2308.04697v1 | cs.LG | not_new_dataset | 0.991305 | 2308.04697 |
When More is Less: Incorporating Additional Datasets Can Hurt Performance By Introducing Spurious Correlations | In machine learning, incorporating more data is often seen as a reliable
strategy for improving model performance; this work challenges that notion by
demonstrating that the addition of external datasets in many cases can hurt the
resulting model's performance. In a large-scale empirical study across
combinations of fo... | http://arxiv.org/abs/2308.04431v1 | cs.LG | not_new_dataset | 0.992204 | 2308.04431 |
A Dataset and Analysis of Open-Source Machine Learning Products | Machine learning (ML) components are increasingly incorporated into software
products, yet developers face challenges in transitioning from ML prototypes to
products. Academic researchers struggle to propose solutions to these
challenges and evaluate interventions because they often do not have access to
close-sourced ... | http://arxiv.org/abs/2308.04328v1 | cs.SE | new_dataset | 0.994491 | 2308.04328 |
A Comparative Study on TF-IDF feature Weighting Method and its Analysis using Unstructured Dataset | Text Classification is the process of categorizing text into the relevant
categories and its algorithms are at the core of many Natural Language
Processing (NLP). Term Frequency-Inverse Document Frequency (TF-IDF) and NLP
are the most highly used information retrieval methods in text classification.
We have investigate... | http://arxiv.org/abs/2308.04037v1 | cs.CL | not_new_dataset | 0.992044 | 2308.04037 |
Balanced Face Dataset: Guiding StyleGAN to Generate Labeled Synthetic Face Image Dataset for Underrepresented Group | For a machine learning model to generalize effectively to unseen data within
a particular problem domain, it is well-understood that the data needs to be of
sufficient size and representative of real-world scenarios. Nonetheless,
real-world datasets frequently have overrepresented and underrepresented
groups. One solut... | http://arxiv.org/abs/2308.03495v1 | cs.CV | new_dataset | 0.994295 | 2308.03495 |
SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs | In this work, we present SciGraphQA, a synthetic multi-turn question-answer
dataset related to academic graphs. SciGraphQA is 13 times larger than
ChartVQA, the previously largest chart-visual question-answering dataset. It is
also the largest open-sourced chart VQA dataset with non-synthetic charts. To
build our datas... | http://arxiv.org/abs/2308.03349v1 | cs.CL | new_dataset | 0.994439 | 2308.03349 |
Generalized Oversampling for Learning from Imbalanced datasets and Associated Theory | In supervised learning, it is quite frequent to be confronted with real
imbalanced datasets. This situation leads to a learning difficulty for standard
algorithms. Research and solutions in imbalanced learning have mainly focused
on classification tasks. Despite its importance, very few solutions exist for
imbalanced r... | http://arxiv.org/abs/2308.02966v1 | stat.ML | not_new_dataset | 0.992111 | 2308.02966 |
Meta-Analysis and Systematic Review for Anomaly Network Intrusion Detection Systems: Detection Methods, Dataset, Validation Methodology, and Challenges | Intrusion detection systems (IDSs) built on artificial intelligence (AI) are
presented as latent mechanisms for actively detecting fresh attacks over a
complex network. Although review papers are used the systematic review or
simple methods to analyse and criticize the anomaly NIDS works, the current
review uses a trad... | http://arxiv.org/abs/2308.02805v2 | cs.CR | not_new_dataset | 0.992102 | 2308.02805 |
Sinhala-English Parallel Word Dictionary Dataset | Parallel datasets are vital for performing and evaluating any kind of
multilingual task. However, in the cases where one of the considered language
pairs is a low-resource language, the existing top-down parallel data such as
corpora are lacking in both tally and quality due to the dearth of human
annotation. Therefore... | http://arxiv.org/abs/2308.02234v1 | cs.CL | new_dataset | 0.994423 | 2308.02234 |
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images | In computational pathology, automatic nuclei instance segmentation plays an
essential role in whole slide image analysis. While many computerized
approaches have been proposed for this task, supervised deep learning (DL)
methods have shown superior segmentation performances compared to classical
machine learning and im... | http://arxiv.org/abs/2308.01760v1 | eess.IV | new_dataset | 0.994392 | 2308.01760 |
VisAlign: Dataset for Measuring the Degree of Alignment between AI and Humans in Visual Perception | AI alignment refers to models acting towards human-intended goals,
preferences, or ethical principles. Given that most large-scale deep learning
models act as black boxes and cannot be manually controlled, analyzing the
similarity between models and humans can be a proxy measure for ensuring AI
safety. In this paper, w... | http://arxiv.org/abs/2308.01525v2 | cs.CV | new_dataset | 0.994517 | 2308.01525 |
Data Collaboration Analysis applied to Compound Datasets and the Introduction of Projection data to Non-IID settings | Given the time and expense associated with bringing a drug to market,
numerous studies have been conducted to predict the properties of compounds
based on their structure using machine learning. Federated learning has been
applied to compound datasets to increase their prediction accuracy while
safeguarding potentially... | http://arxiv.org/abs/2308.00280v1 | cs.LG | not_new_dataset | 0.992131 | 2308.00280 |
A Suite of Fairness Datasets for Tabular Classification | There have been many papers with algorithms for improving fairness of
machine-learning classifiers for tabular data. Unfortunately, most use only
very few datasets for their experimental evaluation. We introduce a suite of
functions for fetching 20 fairness datasets and providing associated fairness
metadata. Hopefully... | http://arxiv.org/abs/2308.00133v1 | cs.LG | new_dataset | 0.971144 | 2308.00133 |
No Fair Lunch: A Causal Perspective on Dataset Bias in Machine Learning for Medical Imaging | As machine learning methods gain prominence within clinical decision-making,
addressing fairness concerns becomes increasingly urgent. Despite considerable
work dedicated to detecting and ameliorating algorithmic bias, today's methods
are deficient with potentially harmful consequences. Our causal perspective
sheds new... | http://arxiv.org/abs/2307.16526v1 | cs.LG | not_new_dataset | 0.992025 | 2307.16526 |
ERCPMP: An Endoscopic Image and Video Dataset for Colorectal Polyps Morphology and Pathology | In the recent years, artificial intelligence (AI) and its leading subtypes,
machine learning (ML) and deep learning (DL) and their applications are
spreading very fast in various aspects such as medicine. Today the most
important challenge of developing accurate algorithms for medical prediction,
detection, diagnosis, ... | http://arxiv.org/abs/2307.15444v1 | eess.IV | new_dataset | 0.994434 | 2307.15444 |
Decoding the Secrets of Machine Learning in Malware Classification: A Deep Dive into Datasets, Feature Extraction, and Model Performance | Many studies have proposed machine-learning (ML) models for malware detection
and classification, reporting an almost-perfect performance. However, they
assemble ground-truth in different ways, use diverse static- and
dynamic-analysis techniques for feature extraction, and even differ on what
they consider a malware fa... | http://arxiv.org/abs/2307.14657v1 | cs.CR | not_new_dataset | 0.992034 | 2307.14657 |
BubbleML: A Multi-Physics Dataset and Benchmarks for Machine Learning | In the field of phase change phenomena, the lack of accessible and diverse
datasets suitable for machine learning (ML) training poses a significant
challenge. Existing experimental datasets are often restricted, with limited
availability and sparse ground truth data, impeding our understanding of this
complex multiphys... | http://arxiv.org/abs/2307.14623v2 | cs.LG | new_dataset | 0.994481 | 2307.14623 |
Deep Learning Hyperspectral Pansharpening on large scale PRISMA dataset | In this work, we assess several deep learning strategies for hyperspectral
pansharpening. First, we present a new dataset with a greater extent than any
other in the state of the art. This dataset, collected using the ASI PRISMA
satellite, covers about 262200 km2, and its heterogeneity is granted by
randomly sampling t... | http://arxiv.org/abs/2307.11666v2 | eess.IV | new_dataset | 0.994024 | 2307.11666 |
A Dataset and Strong Baselines for Classification of Czech News Texts | Pre-trained models for Czech Natural Language Processing are often evaluated
on purely linguistic tasks (POS tagging, parsing, NER) and relatively simple
classification tasks such as sentiment classification or article classification
from a single news source. As an alternative, we present
CZEch~NEws~Classification~dat... | http://arxiv.org/abs/2307.10666v1 | cs.CL | new_dataset | 0.99444 | 2307.10666 |
Novel Batch Active Learning Approach and Its Application to Synthetic Aperture Radar Datasets | Active learning improves the performance of machine learning methods by
judiciously selecting a limited number of unlabeled data points to query for
labels, with the aim of maximally improving the underlying classifier's
performance. Recent gains have been made using sequential active learning for
synthetic aperture ra... | http://arxiv.org/abs/2307.10495v1 | cs.LG | not_new_dataset | 0.991471 | 2307.10495 |
A Step Towards Worldwide Biodiversity Assessment: The BIOSCAN-1M Insect Dataset | In an effort to catalog insect biodiversity, we propose a new large dataset
of hand-labelled insect images, the BIOSCAN-Insect Dataset. Each record is
taxonomically classified by an expert, and also has associated genetic
information including raw nucleotide barcode sequences and assigned barcode
index numbers, which a... | http://arxiv.org/abs/2307.10455v1 | cs.CV | new_dataset | 0.994528 | 2307.10455 |
MVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results | Small Object Detection (SOD) is an important machine vision topic because (i)
a variety of real-world applications require object detection for distant
objects and (ii) SOD is a challenging task due to the noisy, blurred, and
less-informative image appearances of small objects. This paper proposes a new
SOD dataset con... | http://arxiv.org/abs/2307.09143v1 | cs.CV | new_dataset | 0.994389 | 2307.09143 |
Analyzing Dataset Annotation Quality Management in the Wild | Data quality is crucial for training accurate, unbiased, and trustworthy
machine learning models and their correct evaluation. Recent works, however,
have shown that even popular datasets used to train and evaluate
state-of-the-art models contain a non-negligible amount of erroneous
annotations, bias or annotation arti... | http://arxiv.org/abs/2307.08153v2 | cs.CL | not_new_dataset | 0.991888 | 2307.08153 |
Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C++ | In this study, we present a novel dataset for training machine learning
models translating between OpenMP Fortran and C++ code. To ensure reliability
and applicability, the dataset is created from a range of representative
open-source OpenMP benchmarks. It is also refined using a meticulous code
similarity test. The ef... | http://arxiv.org/abs/2307.07686v4 | cs.SE | new_dataset | 0.994482 | 2307.07686 |
IntelliGraphs: Datasets for Benchmarking Knowledge Graph Generation | Knowledge Graph Embedding (KGE) models are used to learn continuous
representations of entities and relations. A key task in the literature is
predicting missing links between entities. However, Knowledge Graphs are not
just sets of links but also have semantics underlying their structure.
Semantics is crucial in sever... | http://arxiv.org/abs/2307.06698v3 | cs.AI | new_dataset | 0.99407 | 2307.06698 |
A New Dataset and Comparative Study for Aphid Cluster Detection | Aphids are one of the main threats to crops, rural families, and global food
security. Chemical pest control is a necessary component of crop production for
maximizing yields, however, it is unnecessary to apply the chemical approaches
to the entire fields in consideration of the environmental pollution and the
cost. T... | http://arxiv.org/abs/2307.05929v1 | cs.CV | new_dataset | 0.994511 | 2307.05929 |
Grain and Grain Boundary Segmentation using Machine Learning with Real and Generated Datasets | We report significantly improved accuracy of grain boundary segmentation
using Convolutional Neural Networks (CNN) trained on a combination of real and
generated data. Manual segmentation is accurate but time-consuming, and
existing computational methods are faster but often inaccurate. To combat this
dilemma, machine ... | http://arxiv.org/abs/2307.05911v1 | cond-mat.mtrl-sci | new_dataset | 0.994335 | 2307.05911 |
AnuraSet: A dataset for benchmarking Neotropical anuran calls identification in passive acoustic monitoring | Global change is predicted to induce shifts in anuran acoustic behavior,
which can be studied through passive acoustic monitoring (PAM). Understanding
changes in calling behavior requires the identification of anuran species,
which is challenging due to the particular characteristics of neotropical
soundscapes. In this... | http://arxiv.org/abs/2307.06860v1 | cs.SD | new_dataset | 0.99454 | 2307.06860 |
MD-HIT: Machine learning for materials property prediction with dataset redundancy control | Materials datasets are usually featured by the existence of many redundant
(highly similar) materials due to the tinkering material design practice over
the history of materials research. For example, the materials project database
has many perovskite cubic structure materials similar to SrTiO$_3$. This sample
redundan... | http://arxiv.org/abs/2307.04351v1 | cond-mat.mtrl-sci | not_new_dataset | 0.992068 | 2307.04351 |
Learning to Group Auxiliary Datasets for Molecule | The limited availability of annotations in small molecule datasets presents a
challenge to machine learning models. To address this, one common strategy is
to collaborate with additional auxiliary datasets. However, having more data
does not always guarantee improvements. Negative transfer can occur when the
knowledge ... | http://arxiv.org/abs/2307.04052v1 | q-bio.BM | not_new_dataset | 0.991931 | 2307.04052 |
Physics-Infused Machine Learning Based Prediction of VTOL Aerodynamics with Sparse Datasets | Complex optimal design and control processes often require repeated
evaluations of expensive objective functions and consist of large design
spaces. Data-driven surrogates such as neural networks and Gaussian processes
provide an attractive alternative to simulations and are utilized frequently to
represent these objec... | http://arxiv.org/abs/2307.03286v1 | cs.CE | not_new_dataset | 0.992038 | 2307.03286 |
The FormAI Dataset: Generative AI in Software Security Through the Lens of Formal Verification | This paper presents the FormAI dataset, a large collection of 112, 000
AI-generated compilable and independent C programs with vulnerability
classification. We introduce a dynamic zero-shot prompting technique
constructed to spawn diverse programs utilizing Large Language Models (LLMs).
The dataset is generated by GPT-... | http://arxiv.org/abs/2307.02192v2 | cs.DB | new_dataset | 0.99451 | 2307.02192 |
Externally validating the IoTDevID device identification methodology using the CIC IoT 2022 Dataset | In the era of rapid IoT device proliferation, recognizing, diagnosing, and
securing these devices are crucial tasks. The IoTDevID method (IEEE Internet of
Things 2022) proposes a machine learning approach for device identification
using network packet features. In this article we present a validation study of
the IoTDe... | http://arxiv.org/abs/2307.08679v1 | cs.NI | new_dataset | 0.994149 | 2307.08679 |
A Critical Re-evaluation of Benchmark Datasets for (Deep) Learning-Based Matching Algorithms | Entity resolution (ER) is the process of identifying records that refer to
the same entities within one or across multiple databases. Numerous techniques
have been developed to tackle ER challenges over the years, with recent
emphasis placed on machine and deep learning methods for the matching phase.
However, the qual... | http://arxiv.org/abs/2307.01231v1 | cs.DB | not_new_dataset | 0.992238 | 2307.01231 |
Dataset balancing can hurt model performance | Machine learning from training data with a skewed distribution of examples
per class can lead to models that favor performance on common classes at the
expense of performance on rare ones. AudioSet has a very wide range of priors
over its 527 sound event classes. Classification performance on AudioSet is
usually evalua... | http://arxiv.org/abs/2307.00079v1 | cs.LG | not_new_dataset | 0.991947 | 2307.00079 |
X-RiSAWOZ: High-Quality End-to-End Multilingual Dialogue Datasets and Few-shot Agents | Task-oriented dialogue research has mainly focused on a few popular languages
like English and Chinese, due to the high dataset creation cost for a new
language. To reduce the cost, we apply manual editing to automatically
translated data. We create a new multilingual benchmark, X-RiSAWOZ, by
translating the Chinese Ri... | http://arxiv.org/abs/2306.17674v1 | cs.CL | new_dataset | 0.994459 | 2306.17674 |
TTSWING: a Dataset for Table Tennis Swing Analysis | We introduce TTSWING, a novel dataset designed for table tennis swing
analysis. This dataset comprises comprehensive swing information obtained
through 9-axis sensors integrated into custom-made racket grips, accompanied by
anonymized demographic data of the players. We detail the data collection and
annotation procedu... | http://arxiv.org/abs/2306.17550v1 | cs.LG | new_dataset | 0.994443 | 2306.17550 |
Surgical Phase and Instrument Recognition: How to identify appropriate Dataset Splits | Purpose: The development of machine learning models for surgical workflow and
instrument recognition from temporal data represents a challenging task due to
the complex nature of surgical workflows. In particular, the imbalanced
distribution of data is one of the major challenges in the domain of surgical
workflow reco... | http://arxiv.org/abs/2306.16879v1 | cs.LG | not_new_dataset | 0.991637 | 2306.16879 |
MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era | We introduce the first large-scale dataset, MNISQ, for both the Quantum and
the Classical Machine Learning community during the Noisy Intermediate-Scale
Quantum era. MNISQ consists of 4,950,000 data points organized in 9
subdatasets. Building our dataset from the quantum encoding of classical
information (e.g., MNIST d... | http://arxiv.org/abs/2306.16627v1 | quant-ph | new_dataset | 0.99445 | 2306.16627 |
Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift | Statistical machine learning methods often face the challenge of limited data
available from the population of interest. One remedy is to leverage data from
auxiliary source populations, which share some conditional distributions or are
linked in other ways with the target domain. Techniques leveraging such
\emph{datas... | http://arxiv.org/abs/2306.16406v2 | stat.ME | not_new_dataset | 0.992208 | 2306.16406 |
MyDigitalFootprint: an extensive context dataset for pervasive computing applications at the edge | The widespread diffusion of connected smart devices has contributed to the
rapid expansion and evolution of the Internet at its edge. Personal mobile
devices interact with other smart objects in their surroundings, adapting
behavior based on rapidly changing user context. The ability of mobile devices
to process this d... | http://arxiv.org/abs/2306.15990v1 | cs.LG | new_dataset | 0.994506 | 2306.15990 |
Probing the Transition to Dataset-Level Privacy in ML Models Using an Output-Specific and Data-Resolved Privacy Profile | Differential privacy (DP) is the prevailing technique for protecting user
data in machine learning models. However, deficits to this framework include a
lack of clarity for selecting the privacy budget $\epsilon$ and a lack of
quantification for the privacy leakage for a particular data row by a
particular trained mode... | http://arxiv.org/abs/2306.15790v1 | cs.LG | not_new_dataset | 0.992298 | 2306.15790 |
Constructing Multilingual Code Search Dataset Using Neural Machine Translation | Code search is a task to find programming codes that semantically match the
given natural language queries. Even though some of the existing datasets for
this task are multilingual on the programming language side, their query data
are only in English. In this research, we create a multilingual code search
dataset in f... | http://arxiv.org/abs/2306.15604v1 | cs.CL | new_dataset | 0.994473 | 2306.15604 |
Assessing Dataset Quality Through Decision Tree Characteristics in Autoencoder-Processed Spaces | In this paper, we delve into the critical aspect of dataset quality
assessment in machine learning classification tasks. Leveraging a variety of
nine distinct datasets, each crafted for classification tasks with varying
complexity levels, we illustrate the profound impact of dataset quality on
model training and perfor... | http://arxiv.org/abs/2306.15392v1 | cs.LG | not_new_dataset | 0.992243 | 2306.15392 |
Uncovering Political Hate Speech During Indian Election Campaign: A New Low-Resource Dataset and Baselines | The detection of hate speech in political discourse is a critical issue, and
this becomes even more challenging in low-resource languages. To address this
issue, we introduce a new dataset named IEHate, which contains 11,457 manually
annotated Hindi tweets related to the Indian Assembly Election Campaign from
November ... | http://arxiv.org/abs/2306.14764v2 | cs.CL | new_dataset | 0.994459 | 2306.14764 |
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine Learning | Super-Resolution (SR) techniques aim to enhance data resolution, enabling the
retrieval of finer details, and improving the overall quality and fidelity of
the data representation. There is growing interest in applying SR methods to
complex spatiotemporal systems within the Scientific Machine Learning (SciML)
community... | http://arxiv.org/abs/2306.14070v1 | cs.CV | new_dataset | 0.994497 | 2306.14070 |
Unleashing Realistic Air Quality Forecasting: Introducing the Ready-to-Use PurpleAirSF Dataset | Air quality forecasting has garnered significant attention recently, with
data-driven models taking center stage due to advancements in machine learning
and deep learning models. However, researchers face challenges with complex
data acquisition and the lack of open-sourced datasets, hindering efficient
model validatio... | http://arxiv.org/abs/2306.13948v1 | cs.LG | new_dataset | 0.994467 | 2306.13948 |
Data Coverage for Detecting Representation Bias in Image Datasets: A Crowdsourcing Approach | Existing machine learning models have proven to fail when it comes to their
performance for minority groups, mainly due to biases in data. In particular,
datasets, especially social data, are often not representative of minorities.
In this paper, we consider the problem of representation bias identification on
image da... | http://arxiv.org/abs/2306.13868v1 | cs.DB | not_new_dataset | 0.992141 | 2306.13868 |
DISCO-10M: A Large-Scale Music Dataset | Music datasets play a crucial role in advancing research in machine learning
for music. However, existing music datasets suffer from limited size,
accessibility, and lack of audio resources. To address these shortcomings, we
present DISCO-10M, a novel and extensive music dataset that surpasses the
largest previously av... | http://arxiv.org/abs/2306.13512v1 | cs.SD | new_dataset | 0.994343 | 2306.13512 |
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