Search is not available for this dataset
title
string
abstract
string
url
string
category
string
prediction
string
probability
float64
arxiv_id
string
Reporting existing datasets for automatic epilepsy diagnosis and seizure detection
More than 50 million individuals are affected by epilepsy, a chronic neurological disorder characterized by unprovoked, recurring seizures and psychological symptoms. Researchers are working to automatically detect or predict epileptic episodes through Electroencephalography (EEG) signal analysis, and machine, and deep...
http://arxiv.org/abs/2306.12292v1
eess.SP
new_dataset
0.99396
2306.12292
Winter Wheat Crop Yield Prediction on Multiple Heterogeneous Datasets using Machine Learning
Winter wheat is one of the most important crops in the United Kingdom, and crop yield prediction is essential for the nation's food security. Several studies have employed machine learning (ML) techniques to predict crop yield on a county or farm-based level. The main objective of this study is to predict winter wheat ...
http://arxiv.org/abs/2306.11946v1
cs.LG
not_new_dataset
0.992214
2306.11946
A Deep Learning Model for Heterogeneous Dataset Analysis -- Application to Winter Wheat Crop Yield Prediction
Western countries rely heavily on wheat, and yield prediction is crucial. Time-series deep learning models, such as Long Short Term Memory (LSTM), have already been explored and applied to yield prediction. Existing literature reported that they perform better than traditional Machine Learning (ML) models. However, the...
http://arxiv.org/abs/2306.11942v1
cs.LG
not_new_dataset
0.992006
2306.11942
Evaluation of Chinese-English Machine Translation of Emotion-Loaded Microblog Texts: A Human Annotated Dataset for the Quality Assessment of Emotion Translation
In this paper, we focus on how current Machine Translation (MT) tools perform on the translation of emotion-loaded texts by evaluating outputs from Google Translate according to a framework proposed in this paper. We propose this evaluation framework based on the Multidimensional Quality Metrics (MQM) and perform a det...
http://arxiv.org/abs/2306.11900v1
cs.CL
new_dataset
0.994139
2306.11900
GIO: Gradient Information Optimization for Training Dataset Selection
It is often advantageous to train models on a subset of the available train examples, because the examples are of variable quality or because one would like to train with fewer examples, without sacrificing performance. We present Gradient Information Optimization (GIO), a scalable, task-agnostic approach to this data ...
http://arxiv.org/abs/2306.11670v1
cs.LG
not_new_dataset
0.992043
2306.11670
EEG Decoding for Datasets with Heterogenous Electrode Configurations using Transfer Learning Graph Neural Networks
Brain-Machine Interfacing (BMI) has greatly benefited from adopting machine learning methods for feature learning that require extensive data for training, which are often unavailable from a single dataset. Yet, it is difficult to combine data across labs or even data within the same lab collected over the years due to...
http://arxiv.org/abs/2306.13109v1
eess.SP
not_new_dataset
0.992204
2306.13109
SeFNet: Bridging Tabular Datasets with Semantic Feature Nets
Machine learning applications cover a wide range of predictive tasks in which tabular datasets play a significant role. However, although they often address similar problems, tabular datasets are typically treated as standalone tasks. The possibilities of using previously solved problems are limited due to the lack of ...
http://arxiv.org/abs/2306.11636v1
cs.LG
not_new_dataset
0.992129
2306.11636
On Evaluating Multilingual Compositional Generalization with Translated Datasets
Compositional generalization allows efficient learning and human-like inductive biases. Since most research investigating compositional generalization in NLP is done on English, important questions remain underexplored. Do the necessary compositional generalization abilities differ across languages? Can models composit...
http://arxiv.org/abs/2306.11420v1
cs.CL
new_dataset
0.986937
2306.11420
DICES Dataset: Diversity in Conversational AI Evaluation for Safety
Machine learning approaches often require training and evaluation datasets with a clear separation between positive and negative examples. This risks simplifying and even obscuring the inherent subjectivity present in many tasks. Preserving such variance in content and diversity in datasets is often expensive and labor...
http://arxiv.org/abs/2306.11247v1
cs.HC
new_dataset
0.994477
2306.11247
AVOIDDS: Aircraft Vision-based Intruder Detection Dataset and Simulator
Designing robust machine learning systems remains an open problem, and there is a need for benchmark problems that cover both environmental changes and evaluation on a downstream task. In this work, we introduce AVOIDDS, a realistic object detection benchmark for the vision-based aircraft detect-and-avoid problem. We p...
http://arxiv.org/abs/2306.11203v1
cs.CV
new_dataset
0.994541
2306.11203
BioREx: Improving Biomedical Relation Extraction by Leveraging Heterogeneous Datasets
Biomedical relation extraction (RE) is the task of automatically identifying and characterizing relations between biomedical concepts from free text. RE is a central task in biomedical natural language processing (NLP) research and plays a critical role in many downstream applications, such as literature-based discover...
http://arxiv.org/abs/2306.11189v1
cs.CL
new_dataset
0.991113
2306.11189
GlyphNet: Homoglyph domains dataset and detection using attention-based Convolutional Neural Networks
Cyber attacks deceive machines into believing something that does not exist in the first place. However, there are some to which even humans fall prey. One such famous attack that attackers have used over the years to exploit the vulnerability of vision is known to be a Homoglyph attack. It employs a primary yet effect...
http://arxiv.org/abs/2306.10392v1
cs.CR
new_dataset
0.994462
2306.10392
Edge Learning for 6G-enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses
The ongoing deployment of the fifth generation (5G) wireless networks constantly reveals limitations concerning its original concept as a key driver of Internet of Everything (IoE) applications. These 5G challenges are behind worldwide efforts to enable future networks, such as sixth generation (6G) networks, to effici...
http://arxiv.org/abs/2306.10309v1
cs.CR
not_new_dataset
0.992275
2306.10309
Flow-Bench: A Dataset for Computational Workflow Anomaly Detection
A computational workflow, also known as workflow, consists of tasks that must be executed in a specific order to attain a specific goal. Often, in fields such as biology, chemistry, physics, and data science, among others, these workflows are complex and are executed in large-scale, distributed, and heterogeneous compu...
http://arxiv.org/abs/2306.09930v1
cs.DC
new_dataset
0.994468
2306.09930
DISC: a Dataset for Integrated Sensing and Communication in mmWave Systems
In this paper we present DISC, a dataset of millimeter-wave channel impulse response measurements for integrated human activity sensing and communication. This is the first dataset collected with a software-defined radio testbed that transmits 60 GHz IEEE 802-11ay-compliant packets and estimates the channel response in...
http://arxiv.org/abs/2306.09469v1
eess.SP
new_dataset
0.994489
2306.09469
Harvard Glaucoma Fairness: A Retinal Nerve Disease Dataset for Fairness Learning and Fair Identity Normalization
Fairness (also known as equity interchangeably) in machine learning is important for societal well-being, but limited public datasets hinder its progress. Currently, no dedicated public medical datasets with imaging data for fairness learning are available, though minority groups suffer from more health issues. To addr...
http://arxiv.org/abs/2306.09264v2
cs.CV
new_dataset
0.994415
2306.09264
DiPlomat: A Dialogue Dataset for Situated Pragmatic Reasoning
Pragmatic reasoning plays a pivotal role in deciphering implicit meanings that frequently arise in real-life conversations and is essential for the development of communicative social agents. In this paper, we introduce a novel challenge, DiPlomat, aiming at benchmarking machines' capabilities on pragmatic reasoning an...
http://arxiv.org/abs/2306.09030v2
cs.CL
new_dataset
0.994505
2306.09030
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
Modern climate projections lack adequate spatial and temporal resolution due to computational constraints. A consequence is inaccurate and imprecise predictions of critical processes such as storms. Hybrid methods that combine physics with machine learning (ML) have introduced a new generation of higher fidelity climat...
http://arxiv.org/abs/2306.08754v3
cs.LG
new_dataset
0.994532
2306.08754
MMASD: A Multimodal Dataset for Autism Intervention Analysis
Autism spectrum disorder (ASD) is a developmental disorder characterized by significant social communication impairments and difficulties perceiving and presenting communication cues. Machine learning techniques have been broadly adopted to facilitate autism studies and assessments. However, computational models are pr...
http://arxiv.org/abs/2306.08243v3
cs.CV
new_dataset
0.994475
2306.08243
Assessing the Effectiveness of GPT-3 in Detecting False Political Statements: A Case Study on the LIAR Dataset
The detection of political fake statements is crucial for maintaining information integrity and preventing the spread of misinformation in society. Historically, state-of-the-art machine learning models employed various methods for detecting deceptive statements. These methods include the use of metadata (W. Wang et al...
http://arxiv.org/abs/2306.08190v1
cs.CL
not_new_dataset
0.992134
2306.08190
Getting the Most from Eye-Tracking: User-Interaction Based Reading Region Estimation Dataset and Models
A single digital newsletter usually contains many messages (regions). Users' reading time spent on, and read level (skip/skim/read-in-detail) of each message is important for platforms to understand their users' interests, personalize their contents, and make recommendations. Based on accurate but expensive-to-collect ...
http://arxiv.org/abs/2306.07455v1
cs.HC
new_dataset
0.993873
2306.07455
RB-Dust -- A Reference-based Dataset for Vision-based Dust Removal
Dust in the agricultural landscape is a significant challenge and influences, for example, the environmental perception of autonomous agricultural machines. Image enhancement algorithms can be used to reduce dust. However, these require dusty and dust-free images of the same environment for validation. In fact, to date...
http://arxiv.org/abs/2306.07244v1
cs.CV
new_dataset
0.994516
2306.07244
Generating Synthetic Datasets by Interpolating along Generalized Geodesics
Data for pretraining machine learning models often consists of collections of heterogeneous datasets. Although training on their union is reasonable in agnostic settings, it might be suboptimal when the target domain -- where the model will ultimately be used -- is known in advance. In that case, one would ideally pret...
http://arxiv.org/abs/2306.06866v1
cs.LG
not_new_dataset
0.992183
2306.06866
Gamified Crowdsourcing as a Novel Approach to Lung Ultrasound Dataset Labeling
Study Objective: Machine learning models have advanced medical image processing and can yield faster, more accurate diagnoses. Despite a wealth of available medical imaging data, high-quality labeled data for model training is lacking. We investigated whether a gamified crowdsourcing platform enhanced with inbuilt qual...
http://arxiv.org/abs/2306.06773v1
cs.CY
not_new_dataset
0.991899
2306.06773
Neural Architecture Design and Robustness: A Dataset
Deep learning models have proven to be successful in a wide range of machine learning tasks. Yet, they are often highly sensitive to perturbations on the input data which can lead to incorrect decisions with high confidence, hampering their deployment for practical use-cases. Thus, finding architectures that are (more)...
http://arxiv.org/abs/2306.06712v1
cs.LG
new_dataset
0.994279
2306.06712
Aria Digital Twin: A New Benchmark Dataset for Egocentric 3D Machine Perception
We introduce the Aria Digital Twin (ADT) - an egocentric dataset captured using Aria glasses with extensive object, environment, and human level ground truth. This ADT release contains 200 sequences of real-world activities conducted by Aria wearers in two real indoor scenes with 398 object instances (324 stationary an...
http://arxiv.org/abs/2306.06362v2
cs.CV
new_dataset
0.994546
2306.06362
Machine Learning Based Missing Values Imputation in Categorical Datasets
This study explored the use of machine learning algorithms for predicting and imputing missing values in categorical datasets. We focused on ensemble models that use the error correction output codes (ECOC) framework, including SVM-based and KNN-based ensemble models, as well as an ensemble classifier that combines SVM...
http://arxiv.org/abs/2306.06338v1
cs.LG
not_new_dataset
0.992207
2306.06338
2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learning
Recent research in computational imaging largely focuses on developing machine learning (ML) techniques for image reconstruction, which requires large-scale training datasets consisting of measurement data and ground-truth images. However, suitable experimental datasets for X-ray Computed Tomography (CT) are scarce, an...
http://arxiv.org/abs/2306.05907v1
eess.IV
new_dataset
0.994512
2306.05907
DynaBench: A benchmark dataset for learning dynamical systems from low-resolution data
Previous work on learning physical systems from data has focused on high-resolution grid-structured measurements. However, real-world knowledge of such systems (e.g. weather data) relies on sparsely scattered measuring stations. In this paper, we introduce a novel simulated benchmark dataset, DynaBench, for learning dy...
http://arxiv.org/abs/2306.05805v2
cs.LG
new_dataset
0.994491
2306.05805
JABBERWOCK: A Tool for WebAssembly Dataset Generation and Its Application to Malicious Website Detection
Machine learning is often used for malicious website detection, but an approach incorporating WebAssembly as a feature has not been explored due to a limited number of samples, to the best of our knowledge. In this paper, we propose JABBERWOCK (JAvascript-Based Binary EncodeR by WebAssembly Optimization paCKer), a tool...
http://arxiv.org/abs/2306.05698v1
cs.CR
not_new_dataset
0.992107
2306.05698
Mesogeos: A multi-purpose dataset for data-driven wildfire modeling in the Mediterranean
We introduce Mesogeos, a large-scale multi-purpose dataset for wildfire modeling in the Mediterranean. Mesogeos integrates variables representing wildfire drivers (meteorology, vegetation, human activity) and historical records of wildfire ignitions and burned areas for 17 years (2006-2022). It is designed as a cloud-f...
http://arxiv.org/abs/2306.05144v1
cs.CV
new_dataset
0.994537
2306.05144
SANGEET: A XML based Open Dataset for Research in Hindustani Sangeet
It is very important to access a rich music dataset that is useful in a wide variety of applications. Currently, available datasets are mostly focused on storing vocal or instrumental recording data and ignoring the requirement of its visual representation and retrieval. This paper attempts to build an XML-based public...
http://arxiv.org/abs/2306.04148v1
cs.SD
new_dataset
0.994489
2306.04148
VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research
Researchers have used machine learning approaches to identify motion sickness in VR experience. These approaches demand an accurately-labeled, real-world, and diverse dataset for high accuracy and generalizability. As a starting point to address this need, we introduce `VR.net', a dataset offering approximately 12-hour...
http://arxiv.org/abs/2306.03381v1
cs.AI
new_dataset
0.994542
2306.03381
AVIDa-hIL6: A Large-Scale VHH Dataset Produced from an Immunized Alpaca for Predicting Antigen-Antibody Interactions
Antibodies have become an important class of therapeutic agents to treat human diseases. To accelerate therapeutic antibody discovery, computational methods, especially machine learning, have attracted considerable interest for predicting specific interactions between antibody candidates and target antigens such as vir...
http://arxiv.org/abs/2306.03329v1
cs.LG
new_dataset
0.994501
2306.03329
Towards Coding Social Science Datasets with Language Models
Researchers often rely on humans to code (label, annotate, etc.) large sets of texts. This kind of human coding forms an important part of social science research, yet the coding process is both resource intensive and highly variable from application to application. In some cases, efforts to automate this process have ...
http://arxiv.org/abs/2306.02177v1
cs.AI
not_new_dataset
0.992015
2306.02177
DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation
Many machine learning problems require performing dataset valuation, i.e. to quantify the incremental gain, to some relevant pre-defined utility, of aggregating an individual dataset to others. As seminal examples, dataset valuation has been leveraged in collaborative and federated learning to create incentives for dat...
http://arxiv.org/abs/2306.02071v1
cs.AI
not_new_dataset
0.992206
2306.02071
DeepfakeArt Challenge: A Benchmark Dataset for Generative AI Art Forgery and Data Poisoning Detection
The tremendous recent advances in generative artificial intelligence techniques have led to significant successes and promise in a wide range of different applications ranging from conversational agents and textual content generation to voice and visual synthesis. Amid the rise in generative AI and its increasing wides...
http://arxiv.org/abs/2306.01272v2
cs.CV
new_dataset
0.994516
2306.01272
MindBigData 2023 MNIST-8B The 8 billion datapoints Multimodal Dataset of Brain Signals
MindBigData 2023 MNIST-8B is the largest, to date (June 1st 2023), brain signals open dataset created for Machine Learning, based on EEG signals from a single subject captured using a custom 128 channels device, replicating the full 70,000 digits from Yaan LeCun et all MNIST dataset. The brain signals were captured whi...
http://arxiv.org/abs/2306.00455v1
cs.LG
new_dataset
0.994517
2306.00455
Sea Ice Extraction via Remote Sensed Imagery: Algorithms, Datasets, Applications and Challenges
The deep learning, which is a dominating technique in artificial intelligence, has completely changed the image understanding over the past decade. As a consequence, the sea ice extraction (SIE) problem has reached a new era. We present a comprehensive review of four important aspects of SIE, including algorithms, data...
http://arxiv.org/abs/2306.00303v1
cs.CV
not_new_dataset
0.992056
2306.00303
Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks using a Malware Dataset: A Comparative Analysis
The burgeoning fields of machine learning (ML) and quantum machine learning (QML) have shown remarkable potential in tackling complex problems across various domains. However, their susceptibility to adversarial attacks raises concerns when deploying these systems in security sensitive applications. In this study, we p...
http://arxiv.org/abs/2305.19593v1
cs.LG
not_new_dataset
0.991994
2305.19593
VSTAR: A Video-grounded Dialogue Dataset for Situated Semantic Understanding with Scene and Topic Transitions
Video-grounded dialogue understanding is a challenging problem that requires machine to perceive, parse and reason over situated semantics extracted from weakly aligned video and dialogues. Most existing benchmarks treat both modalities the same as a frame-independent visual understanding task, while neglecting the int...
http://arxiv.org/abs/2305.18756v1
cs.CV
new_dataset
0.994436
2305.18756
A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets
The development of large language models (LLMs) such as ChatGPT has brought a lot of attention recently. However, their evaluation in the benchmark academic datasets remains under-explored due to the difficulty of evaluating the generative outputs produced by this model against the ground truth. In this paper, we aim t...
http://arxiv.org/abs/2305.18486v4
cs.CL
not_new_dataset
0.992341
2305.18486
TotalDefMeme: A Multi-Attribute Meme dataset on Total Defence in Singapore
Total Defence is a defence policy combining and extending the concept of military defence and civil defence. While several countries have adopted total defence as their defence policy, very few studies have investigated its effectiveness. With the rapid proliferation of social media and digitalisation, many social stud...
http://arxiv.org/abs/2305.17911v1
cs.SI
new_dataset
0.994474
2305.17911
InDL: A New Dataset and Benchmark for In-Diagram Logic Interpretation based on Visual Illusion
This paper introduces a novel approach to evaluating deep learning models' capacity for in-diagram logic interpretation. Leveraging the intriguing realm of visual illusions, we establish a unique dataset, InDL, designed to rigorously test and benchmark these models. Deep learning has witnessed remarkable progress in do...
http://arxiv.org/abs/2305.17716v4
cs.CV
new_dataset
0.994493
2305.17716
HaVQA: A Dataset for Visual Question Answering and Multimodal Research in Hausa Language
This paper presents HaVQA, the first multimodal dataset for visual question-answering (VQA) tasks in the Hausa language. The dataset was created by manually translating 6,022 English question-answer pairs, which are associated with 1,555 unique images from the Visual Genome dataset. As a result, the dataset provides 12...
http://arxiv.org/abs/2305.17690v1
cs.CL
new_dataset
0.994489
2305.17690
ArPanEmo: An Open-Source Dataset for Fine-Grained Emotion Recognition in Arabic Online Content during COVID-19 Pandemic
Emotion recognition is a crucial task in Natural Language Processing (NLP) that enables machines to comprehend the feelings conveyed in the text. The applications of emotion recognition are diverse, including mental health diagnosis, student support, and the detection of online suspicious behavior. Despite the substant...
http://arxiv.org/abs/2305.17580v1
cs.CL
new_dataset
0.994488
2305.17580
Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence
Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to utilize large neuroimaging datasets, including maps of the brain which capture neuron ...
http://arxiv.org/abs/2305.17300v1
cs.NE
not_new_dataset
0.9922
2305.17300
BIG-C: a Multimodal Multi-Purpose Dataset for Bemba
We present BIG-C (Bemba Image Grounded Conversations), a large multimodal dataset for Bemba. While Bemba is the most populous language of Zambia, it exhibits a dearth of resources which render the development of language technologies or language processing research almost impossible. The dataset is comprised of multi-t...
http://arxiv.org/abs/2305.17202v1
cs.CL
new_dataset
0.994515
2305.17202
DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization
Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter-university Consortium for Political and Social Research (ICPSR), offer standardized metadata and search tools to support data search. Metadata standards emphasize t...
http://arxiv.org/abs/2305.18358v1
cs.IR
not_new_dataset
0.989342
2305.18358
DataFinder: Scientific Dataset Recommendation from Natural Language Descriptions
Modern machine learning relies on datasets to develop and validate research ideas. Given the growth of publicly available data, finding the right dataset to use is increasingly difficult. Any research question imposes explicit and implicit constraints on how well a given dataset will enable researchers to answer this q...
http://arxiv.org/abs/2305.16636v2
cs.IR
new_dataset
0.99418
2305.16636
ParaAMR: A Large-Scale Syntactically Diverse Paraphrase Dataset by AMR Back-Translation
Paraphrase generation is a long-standing task in natural language processing (NLP). Supervised paraphrase generation models, which rely on human-annotated paraphrase pairs, are cost-inefficient and hard to scale up. On the other hand, automatically annotated paraphrase pairs (e.g., by machine back-translation), usually...
http://arxiv.org/abs/2305.16585v1
cs.CL
new_dataset
0.994407
2305.16585
CVB: A Video Dataset of Cattle Visual Behaviors
Existing image/video datasets for cattle behavior recognition are mostly small, lack well-defined labels, or are collected in unrealistic controlled environments. This limits the utility of machine learning (ML) models learned from them. Therefore, we introduce a new dataset, called Cattle Visual Behaviors (CVB), that ...
http://arxiv.org/abs/2305.16555v2
cs.CV
new_dataset
0.994576
2305.16555
AUC Optimization from Multiple Unlabeled Datasets
Weakly supervised learning aims to empower machine learning when the perfect supervision is unavailable, which has drawn great attention from researchers. Among various types of weak supervision, one of the most challenging cases is to learn from multiple unlabeled (U) datasets with only a little knowledge of the class...
http://arxiv.org/abs/2305.15776v3
cs.LG
not_new_dataset
0.992218
2305.15776
Towards Solving Cocktail-Party: The First Method to Build a Realistic Dataset with Ground Truths for Speech Separation
Speech separation is very important in real-world applications such as human-machine interaction, hearing aids devices, and automatic meeting transcription. In recent years, a significant improvement occurred towards the solution based on deep learning. In fact, much attention has been drawn to supervised learning meth...
http://arxiv.org/abs/2305.15758v1
cs.SD
new_dataset
0.99368
2305.15758
SciReviewGen: A Large-scale Dataset for Automatic Literature Review Generation
Automatic literature review generation is one of the most challenging tasks in natural language processing. Although large language models have tackled literature review generation, the absence of large-scale datasets has been a stumbling block to the progress. We release SciReviewGen, consisting of over 10,000 literat...
http://arxiv.org/abs/2305.15186v1
cs.CL
new_dataset
0.99438
2305.15186
Calc-X: Enriching Arithmetical Chain-of-Thoughts Datasets by Interaction with Symbolic Systems
This report overviews our ongoing work in enriching chain-of-thoughts datasets requiring arithmetical reasoning with the integration of non-parametric components, such as a calculator. We conduct an analysis of prominent relevant datasets such as GSM8K, Ape210K, AQuA-RAT, and MathQA and propose a machine-processable HT...
http://arxiv.org/abs/2305.15017v1
cs.LG
not_new_dataset
0.990214
2305.15017
Sāmayik: A Benchmark and Dataset for English-Sanskrit Translation
Sanskrit is a low-resource language with a rich heritage. Digitized Sanskrit corpora reflective of the contemporary usage of Sanskrit, specifically that too in prose, is heavily under-represented at present. Presently, no such English-Sanskrit parallel dataset is publicly available. We release a dataset, S\={a}mayik, o...
http://arxiv.org/abs/2305.14004v1
cs.CL
new_dataset
0.994475
2305.14004
BigVideo: A Large-scale Video Subtitle Translation Dataset for Multimodal Machine Translation
We present a large-scale video subtitle translation dataset, BigVideo, to facilitate the study of multi-modality machine translation. Compared with the widely used How2 and VaTeX datasets, BigVideo is more than 10 times larger, consisting of 4.5 million sentence pairs and 9,981 hours of videos. We also introduce two de...
http://arxiv.org/abs/2305.18326v3
cs.CV
new_dataset
0.994431
2305.18326
TeCS: A Dataset and Benchmark for Tense Consistency of Machine Translation
Tense inconsistency frequently occurs in machine translation. However, there are few criteria to assess the model's mastery of tense prediction from a linguistic perspective. In this paper, we present a parallel tense test set, containing French-English 552 utterances. We also introduce a corresponding benchmark, tense...
http://arxiv.org/abs/2305.13740v1
cs.CL
new_dataset
0.994371
2305.13740
Evaluating Model Performance in Medical Datasets Over Time
Machine learning (ML) models deployed in healthcare systems must face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in a time-agnostic manner, splitting datasets according to patients sampled randomly throughout the entire study time period. This w...
http://arxiv.org/abs/2305.13426v2
cs.LG
not_new_dataset
0.992188
2305.13426
Leveraging Human Feedback to Scale Educational Datasets: Combining Crowdworkers and Comparative Judgement
Machine Learning models have many potentially beneficial applications in education settings, but a key barrier to their development is securing enough data to train these models. Labelling educational data has traditionally relied on highly skilled raters using complex, multi-class rubrics, making the process expensive...
http://arxiv.org/abs/2305.12894v1
cs.CL
not_new_dataset
0.992043
2305.12894
Productive Crop Field Detection: A New Dataset and Deep Learning Benchmark Results
In precision agriculture, detecting productive crop fields is an essential practice that allows the farmer to evaluate operating performance separately and compare different seed varieties, pesticides, and fertilizers. However, manually identifying productive fields is often a time-consuming and error-prone task. Previ...
http://arxiv.org/abs/2305.11990v2
cs.CV
new_dataset
0.994537
2305.11990
MiraBest: A Dataset of Morphologically Classified Radio Galaxies for Machine Learning
The volume of data from current and future observatories has motivated the increased development and application of automated machine learning methodologies for astronomy. However, less attention has been given to the production of standardised datasets for assessing the performance of different machine learning algori...
http://arxiv.org/abs/2305.11108v1
astro-ph.IM
new_dataset
0.994551
2305.11108
Multi-CrossRE A Multi-Lingual Multi-Domain Dataset for Relation Extraction
Most research in Relation Extraction (RE) involves the English language, mainly due to the lack of multi-lingual resources. We propose Multi-CrossRE, the broadest multi-lingual dataset for RE, including 26 languages in addition to English, and covering six text domains. Multi-CrossRE is a machine translated version of ...
http://arxiv.org/abs/2305.10985v1
cs.CL
new_dataset
0.994547
2305.10985
Solar Active Region Magnetogram Image Dataset for Studies of Space Weather
In this dataset we provide a comprehensive collection of magnetograms (images quantifying the strength of the magnetic field) from the National Aeronautics and Space Administration's (NASA's) Solar Dynamics Observatory (SDO). The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Im...
http://arxiv.org/abs/2305.09492v2
astro-ph.SR
new_dataset
0.994557
2305.09492
Ship-D: Ship Hull Dataset for Design Optimization using Machine Learning
Machine learning has recently made significant strides in reducing design cycle time for complex products. Ship design, which currently involves years long cycles and small batch production, could greatly benefit from these advancements. By developing a machine learning tool for ship design that learns from the design ...
http://arxiv.org/abs/2305.08279v2
cs.LG
new_dataset
0.994549
2305.08279
Anomaly Detection Dataset for Industrial Control Systems
Over the past few decades, Industrial Control Systems (ICSs) have been targeted by cyberattacks and are becoming increasingly vulnerable as more ICSs are connected to the internet. Using Machine Learning (ML) for Intrusion Detection Systems (IDS) is a promising approach for ICS cyber protection, but the lack of suitabl...
http://arxiv.org/abs/2305.09678v1
cs.CR
new_dataset
0.994502
2305.09678
Collection Space Navigator: An Interactive Visualization Interface for Multidimensional Datasets
We introduce the Collection Space Navigator (CSN), a browser-based visualization tool to explore, research, and curate large collections of visual digital artifacts that are associated with multidimensional data, such as vector embeddings or tables of metadata. Media objects such as images are often encoded as numerica...
http://arxiv.org/abs/2305.06809v1
cs.CV
not_new_dataset
0.962312
2305.06809
BanglaBook: A Large-scale Bangla Dataset for Sentiment Analysis from Book Reviews
The analysis of consumer sentiment, as expressed through reviews, can provide a wealth of insight regarding the quality of a product. While the study of sentiment analysis has been widely explored in many popular languages, relatively less attention has been given to the Bangla language, mostly due to a lack of relevan...
http://arxiv.org/abs/2305.06595v3
cs.CL
new_dataset
0.994482
2305.06595
Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser
Spectral clustering is one of the most popular clustering algorithms that has stood the test of time. It is simple to describe, can be implemented using standard linear algebra, and often finds better clusters than traditional clustering algorithms like $k$-means and $k$-centers. The foundational algorithm for two-way ...
http://arxiv.org/abs/2305.06541v1
cs.LG
not_new_dataset
0.992087
2305.06541
WikiSQE: A Large-Scale Dataset for Sentence Quality Estimation in Wikipedia
Wikipedia can be edited by anyone and thus contains various quality sentences. Therefore, Wikipedia includes some poor-quality edits, which are often marked up by other editors. While editors' reviews enhance the credibility of Wikipedia, it is hard to check all edited text. Assisting in this process is very important,...
http://arxiv.org/abs/2305.05928v1
cs.CL
new_dataset
0.994403
2305.05928
Augmented Datasheets for Speech Datasets and Ethical Decision-Making
Speech datasets are crucial for training Speech Language Technologies (SLT); however, the lack of diversity of the underlying training data can lead to serious limitations in building equitable and robust SLT products, especially along dimensions of language, accent, dialect, variety, and speech impairment - and the in...
http://arxiv.org/abs/2305.04672v1
cs.CY
not_new_dataset
0.98482
2305.04672
MultiTACRED: A Multilingual Version of the TAC Relation Extraction Dataset
Relation extraction (RE) is a fundamental task in information extraction, whose extension to multilingual settings has been hindered by the lack of supervised resources comparable in size to large English datasets such as TACRED (Zhang et al., 2017). To address this gap, we introduce the MultiTACRED dataset, covering 1...
http://arxiv.org/abs/2305.04582v2
cs.CL
new_dataset
0.994431
2305.04582
Scaling Graph-Based ANNS Algorithms to Billion-Size Datasets: A Comparative Analysis
Algorithms for approximate nearest-neighbor search (ANNS) have been the topic of significant recent interest in the research community. However, evaluations of such algorithms are usually restricted to a small number of datasets with millions or tens of millions of points, whereas real-world applications require algori...
http://arxiv.org/abs/2305.04359v1
cs.IR
not_new_dataset
0.991472
2305.04359
Considerations for Ethical Speech Recognition Datasets
Speech AI Technologies are largely trained on publicly available datasets or by the massive web-crawling of speech. In both cases, data acquisition focuses on minimizing collection effort, without necessarily taking the data subjects' protection or user needs into consideration. This results to models that are not robu...
http://arxiv.org/abs/2305.02081v1
cs.CY
not_new_dataset
0.99218
2305.02081
SAMRS: Scaling-up Remote Sensing Segmentation Dataset with Segment Anything Model
The success of the Segment Anything Model (SAM) demonstrates the significance of data-centric machine learning. However, due to the difficulties and high costs associated with annotating Remote Sensing (RS) images, a large amount of valuable RS data remains unlabeled, particularly at the pixel level. In this study, we ...
http://arxiv.org/abs/2305.02034v2
cs.CV
new_dataset
0.994428
2305.02034
A Survey on Dataset Distillation: Approaches, Applications and Future Directions
Dataset distillation is attracting more attention in machine learning as training sets continue to grow and the cost of training state-of-the-art models becomes increasingly high. By synthesizing datasets with high information density, dataset distillation offers a range of potential applications, including support for...
http://arxiv.org/abs/2305.01975v3
cs.LG
not_new_dataset
0.992036
2305.01975
NorQuAD: Norwegian Question Answering Dataset
In this paper we present NorQuAD: the first Norwegian question answering dataset for machine reading comprehension. The dataset consists of 4,752 manually created question-answer pairs. We here detail the data collection procedure and present statistics of the dataset. We also benchmark several multilingual and Norwegi...
http://arxiv.org/abs/2305.01957v1
cs.CL
new_dataset
0.99436
2305.01957
HTPS: Heterogeneous Transferring Prediction System for Healthcare Datasets
Medical internet of things leads to revolutionary improvements in medical services, also known as smart healthcare. With the big healthcare data, data mining and machine learning can assist wellness management and intelligent diagnosis, and achieve the P4-medicine. However, healthcare data has high sparsity and heterog...
http://arxiv.org/abs/2305.01252v1
cs.LG
not_new_dataset
0.991726
2305.01252
S2abEL: A Dataset for Entity Linking from Scientific Tables
Entity linking (EL) is the task of linking a textual mention to its corresponding entry in a knowledge base, and is critical for many knowledge-intensive NLP applications. When applied to tables in scientific papers, EL is a step toward large-scale scientific knowledge bases that could enable advanced scientific questi...
http://arxiv.org/abs/2305.00366v1
cs.CL
new_dataset
0.99456
2305.00366
A CSI Dataset for Wireless Human Sensing on 80 MHz Wi-Fi Channels
In the last years, several machine learning-based techniques have been proposed to monitor human movements from Wi-Fi channel readings. However, the development of domain-adaptive algorithms that robustly work across different environments is still an open problem, whose solution requires large datasets characterized b...
http://arxiv.org/abs/2305.03170v1
eess.SP
new_dataset
0.994552
2305.03170
HeySQuAD: A Spoken Question Answering Dataset
Human-spoken questions are critical to evaluating the performance of spoken question answering (SQA) systems that serve several real-world use cases including digital assistants. We present a new large-scale community-shared SQA dataset, HeySQuAD that consists of 76k human-spoken questions and 97k machine-generated que...
http://arxiv.org/abs/2304.13689v1
cs.CL
new_dataset
0.994506
2304.13689
On the redundancy in large material datasets: efficient and robust learning with less data
Extensive efforts to gather materials data have largely overlooked potential data redundancy. In this study, we present evidence of a significant degree of redundancy across multiple large datasets for various material properties, by revealing that up to 95 % of data can be safely removed from machine learning training...
http://arxiv.org/abs/2304.13076v2
cond-mat.mtrl-sci
not_new_dataset
0.99217
2304.13076
Scalable Bilevel Optimization for Generating Maximally Representative OPF Datasets
New generations of power systems, containing high shares of renewable energy resources, require improved data-driven tools which can swiftly adapt to changes in system operation. Many of these tools, such as ones using machine learning, rely on high-quality training datasets to construct probabilistic models. Such mode...
http://arxiv.org/abs/2304.10912v1
eess.SY
not_new_dataset
0.991748
2304.10912
Application of quantum-inspired generative models to small molecular datasets
Quantum and quantum-inspired machine learning has emerged as a promising and challenging research field due to the increased popularity of quantum computing, especially with near-term devices. Theoretical contributions point toward generative modeling as a promising direction to realize the first examples of real-world...
http://arxiv.org/abs/2304.10867v1
quant-ph
not_new_dataset
0.991291
2304.10867
HabitatDyn Dataset: Dynamic Object Detection to Kinematics Estimation
The advancement of computer vision and machine learning has made datasets a crucial element for further research and applications. However, the creation and development of robots with advanced recognition capabilities are hindered by the lack of appropriate datasets. Existing image or video processing datasets are unab...
http://arxiv.org/abs/2304.10854v1
cs.CV
new_dataset
0.994464
2304.10854
The Dataset Multiplicity Problem: How Unreliable Data Impacts Predictions
We introduce dataset multiplicity, a way to study how inaccuracies, uncertainty, and social bias in training datasets impact test-time predictions. The dataset multiplicity framework asks a counterfactual question of what the set of resultant models (and associated test-time predictions) would be if we could somehow ac...
http://arxiv.org/abs/2304.10655v1
cs.LG
not_new_dataset
0.992135
2304.10655
Is augmentation effective to improve prediction in imbalanced text datasets?
Imbalanced datasets present a significant challenge for machine learning models, often leading to biased predictions. To address this issue, data augmentation techniques are widely used in natural language processing (NLP) to generate new samples for the minority class. However, in this paper, we challenge the common a...
http://arxiv.org/abs/2304.10283v1
cs.CL
not_new_dataset
0.991772
2304.10283
HandCT: hands-on computational dataset for X-Ray Computed Tomography and Machine-Learning
Machine-learning methods rely on sufficiently large dataset to learn data distributions. They are widely used in research in X-Ray Computed Tomography, from low-dose scan denoising to optimisation of the reconstruction process. The lack of datasets prevents the scalability of these methods to realistic 3D problems. We ...
http://arxiv.org/abs/2304.14412v1
eess.IV
new_dataset
0.994517
2304.14412
Robust Educational Dialogue Act Classifiers with Low-Resource and Imbalanced Datasets
Dialogue acts (DAs) can represent conversational actions of tutors or students that take place during tutoring dialogues. Automating the identification of DAs in tutoring dialogues is significant to the design of dialogue-based intelligent tutoring systems. Many prior studies employ machine learning models to classify ...
http://arxiv.org/abs/2304.07499v1
cs.CL
not_new_dataset
0.992221
2304.07499
Vax-Culture: A Dataset for Studying Vaccine Discourse on Twitter
Vaccine hesitancy continues to be a main challenge for public health officials during the COVID-19 pandemic. As this hesitancy undermines vaccine campaigns, many researchers have sought to identify its root causes, finding that the increasing volume of anti-vaccine misinformation on social media platforms is a key elem...
http://arxiv.org/abs/2304.06858v3
cs.SI
new_dataset
0.994557
2304.06858
ASL Citizen: A Community-Sourced Dataset for Advancing Isolated Sign Language Recognition
Sign languages are used as a primary language by approximately 70 million D/deaf people world-wide. However, most communication technologies operate in spoken and written languages, creating inequities in access. To help tackle this problem, we release ASL Citizen, the first crowdsourced Isolated Sign Language Recognit...
http://arxiv.org/abs/2304.05934v2
cs.CV
new_dataset
0.994518
2304.05934
A Multi-Institutional Open-Source Benchmark Dataset for Breast Cancer Clinical Decision Support using Synthetic Correlated Diffusion Imaging Data
Recently, a new form of magnetic resonance imaging (MRI) called synthetic correlated diffusion (CDI$^s$) imaging was introduced and showed considerable promise for clinical decision support for cancers such as prostate cancer when compared to current gold-standard MRI techniques. However, the efficacy for CDI$^s$ for o...
http://arxiv.org/abs/2304.05623v1
eess.IV
new_dataset
0.994491
2304.05623
NutritionVerse-3D: A 3D Food Model Dataset for Nutritional Intake Estimation
77% of adults over 50 want to age in place today, presenting a major challenge to ensuring adequate nutritional intake. It has been reported that one in four older adults that are 65 years or older are malnourished and given the direct link between malnutrition and decreased quality of life, there have been numerous st...
http://arxiv.org/abs/2304.05619v1
cs.CV
new_dataset
0.994549
2304.05619
Multimodal Brain-Computer Interface for In-Vehicle Driver Cognitive Load Measurement: Dataset and Baselines
Through this paper, we introduce a novel driver cognitive load assessment dataset, CL-Drive, which contains Electroencephalogram (EEG) signals along with other physiological signals such as Electrocardiography (ECG) and Electrodermal Activity (EDA) as well as eye tracking data. The data was collected from 21 subjects w...
http://arxiv.org/abs/2304.04273v1
cs.LG
new_dataset
0.99446
2304.04273
The Saudi Privacy Policy Dataset
This paper introduces the Saudi Privacy Policy Dataset, a diverse compilation of Arabic privacy policies from various sectors in Saudi Arabia, annotated according to the 10 principles of the Personal Data Protection Law (PDPL); the PDPL was established to be compatible with General Data Protection Regulation (GDPR); on...
http://arxiv.org/abs/2304.02757v1
cs.CL
new_dataset
0.994539
2304.02757
Statistics of extreme events in coarse-scale climate simulations via machine learning correction operators trained on nudged datasets
This work presents a systematic framework for improving the predictions of statistical quantities for turbulent systems, with a focus on correcting climate simulations obtained by coarse-scale models. While high resolution simulations or reanalysis data are available, they cannot be directly used as training datasets t...
http://arxiv.org/abs/2304.02117v1
physics.ao-ph
not_new_dataset
0.992065
2304.02117
Distance-based Analysis of Machine Learning Prediction Reliability for Datasets in Materials Science and Other Fields
Despite successful use in a wide variety of disciplines for data analysis and prediction, machine learning (ML) methods suffer from a lack of understanding of the reliability of predictions due to the lack of transparency and black-box nature of ML models. In materials science and other fields, typical ML model results...
http://arxiv.org/abs/2304.01146v1
cond-mat.mtrl-sci
not_new_dataset
0.992094
2304.01146
LAHM : Large Annotated Dataset for Multi-Domain and Multilingual Hate Speech Identification
Current research on hate speech analysis is typically oriented towards monolingual and single classification tasks. In this paper, we present a new multilingual hate speech analysis dataset for English, Hindi, Arabic, French, German and Spanish languages for multiple domains across hate speech - Abuse, Racism, Sexism, ...
http://arxiv.org/abs/2304.00913v1
cs.CL
new_dataset
0.994545
2304.00913
PEOPL: Characterizing Privately Encoded Open Datasets with Public Labels
Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique for this still-open problem is to train models on the encoded data. Our approach, called Privately Encoded Open Datasets with Public Labels...
http://arxiv.org/abs/2304.00047v1
cs.LG
not_new_dataset
0.992232
2304.00047