Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
1905.12909	Deep multi-class learning from label proportions	We propose a learning algorithm capable of learning from label proportions instead of direct data labels. In this scenario, our data are arranged into various bags of a certain size, and only the proportions of each label within a given bag are known. This is a common situation in cases where per-data labeling is lengt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,931
2310.04701	Twin Graph-based Anomaly Detection via Attentive Multi-Modal Learning for Microservice System	Microservice architecture has sprung up over recent years for managing enterprise applications, due to its ability to independently deploy and scale services. Despite its benefits, ensuring the reliability and safety of a microservice system remains highly challenging. Existing anomaly detection algorithms based on a s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	397,776
2208.02194	Interpretable bilinear attention network with domain adaptation improves drug-target prediction	Predicting drug-target interaction is key for drug discovery. Recent deep learning-based methods show promising performance but two challenges remain: (i) how to explicitly model and learn local interactions between drugs and targets for better prediction and interpretation; (ii) how to generalize prediction performanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,404
2308.15560	WeatherBench 2: A benchmark for the next generation of data-driven global weather models	WeatherBench 2 is an update to the global, medium-range (1-14 day) weather forecasting benchmark proposed by Rasp et al. (2020), designed with the aim to accelerate progress in data-driven weather modeling. WeatherBench 2 consists of an open-source evaluation framework, publicly available training, ground truth and bas...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	388,721
0704.3241	Neighbor Discovery in Wireless Networks:A Multiuser-Detection Approach	We examine the problem of determining which nodes are neighbors of a given one in a wireless network. We consider an unsupervised network operating on a frequency-flat Gaussian channel, where $K+1$ nodes associate their identities to nonorthogonal signatures, transmitted at random times, synchronously, and independentl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89
cs/0205069	Machine Learning with Lexical Features: The Duluth Approach to Senseval-2	This paper describes the sixteen Duluth entries in the Senseval-2 comparative exercise among word sense disambiguation systems. There were eight pairs of Duluth systems entered in the Spanish and English lexical sample tasks. These are all based on standard machine learning algorithms that induce classifiers from sense...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,590
1908.10998	Focus-Enhanced Scene Text Recognition with Deformable Convolutions	Recently, scene text recognition methods based on deep learning have sprung up in computer vision area. The existing methods achieved great performances, but the recognition of irregular text is still challenging due to the various shapes and distorted patterns. Consider that at the time of reading words in the real wo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	143,262
2405.05709	On the Capacity of Correlated MIMO Phase-Noise Channels: An Electro-Optic Frequency Comb Example	The capacity of a discrete-time multiple-input-multiple-output channel with correlated phase noises is investigated. In particular, the electro-optic frequency comb system is considered, where the phase noise of each channel is a combination of two independent Wiener phase-noise sources. Capacity upper and lower bounds...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	453,025
2202.02758	3D Map Reconstruction of an Orchard using an Angle-Aware Covering Control Strategy	In the last years, unmanned aerial vehicles are becoming a reality in the context of precision agriculture, mainly for monitoring, patrolling and remote sensing tasks, but also for 3D map reconstruction. In this paper, we present an innovative approach where a fleet of unmanned aerial vehicles is exploited to perform r...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	278,933
2003.06190	WAC: A Corpus of Wikipedia Conversations for Online Abuse Detection	With the spread of online social networks, it is more and more difficult to monitor all the user-generated content. Automating the moderation process of the inappropriate exchange content on Internet has thus become a priority task. Methods have been proposed for this purpose, but it can be challenging to find a suitab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	168,052
1608.03832	On Minimal Accuracy Algorithm Selection in Computer Vision and Intelligent Systems	In this paper we discuss certain theoretical properties of algorithm selection approach to image processing and to intelligent system in general. We analyze the theoretical limits of algorithm selection with respect to the algorithm selection accuracy. We show the theoretical formulation of a crisp bound on the algorit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,736
2002.04397	Fake News Detection on News-Oriented Heterogeneous Information Networks through Hierarchical Graph Attention	The viral spread of fake news has caused great social harm, making fake news detection an urgent task. Current fake news detection methods rely heavily on text information by learning the extracted news content or writing style of internal knowledge. However, deliberate rumors can mask writing style, bypassing language...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	163,598
2406.06932	Synthetic Face Ageing: Evaluation, Analysis and Facilitation of Age-Robust Facial Recognition Algorithms	The ability to accurately recognize an individual's face with respect to human aging factor holds significant importance for various private as well as government sectors such as customs and public security bureaus, passport office, and national database systems. Therefore, developing a robust age-invariant face recogn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	462,823
2402.04494	Amortized Planning with Large-Scale Transformers: A Case Study on Chess	This paper uses chess, a landmark planning problem in AI, to assess transformers' performance on a planning task where memorization is futile $\unicode{x2013}$ even at a large scale. To this end, we release ChessBench, a large-scale benchmark dataset of 10 million chess games with legal move and value annotations (15 b...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	427,474
1902.00819	Randomized Allocation with Nonparametric Estimation for Contextual Multi-Armed Bandits with Delayed Rewards	We study a multi-armed bandit problem with covariates in a setting where there is a possible delay in observing the rewards. Under some mild assumptions on the probability distributions for the delays and using an appropriate randomization to select the arms, the proposed strategy is shown to be strongly consistent.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,513
2105.07200	Multi-scale super-resolution generation of low-resolution scanned pathological images	Background. Digital pathology has aroused widespread interest in modern pathology. The key of digitalization is to scan the whole slide image (WSI) at high magnification. The lager the magnification is, the richer details WSI will provide, but the scanning time is longer and the file size of obtained is larger. Methods...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,357
2005.09787	Self-Updating Models with Error Remediation	Many environments currently employ machine learning models for data processing and analytics that were built using a limited number of training data points. Once deployed, the models are exposed to significant amounts of previously-unseen data, not all of which is representative of the original, limited training data. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,999
2307.07708	PSGformer: Enhancing 3D Point Cloud Instance Segmentation via Precise Semantic Guidance	Most existing 3D instance segmentation methods are derived from 3D semantic segmentation models. However, these indirect approaches suffer from certain limitations. They fail to fully leverage global and local semantic information for accurate prediction, which hampers the overall performance of the 3D instance segment...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	379,515
1208.0186	Opportunistic Forwarding with Partial Centrality	In opportunistic networks, the use of social metrics (e.g., degree, closeness and betweenness centrality) of human mobility network, has recently been shown to be an effective solution to improve the performance of opportunistic forwarding algorithms. Most of the current social-based forwarding schemes exploit some glo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	17,876
2006.04950	Machine Learning Systems for Intelligent Services in the IoT: A Survey	Machine learning (ML) technologies are emerging in the Internet of Things (IoT) to provision intelligent services. This survey moves beyond existing ML algorithms and cloud-driven design to investigate the less-explored systems, scaling and socio-technical aspects for consolidating ML and IoT. It covers the latest deve...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	180,871
2502.08284	Data Pricing for Graph Neural Networks without Pre-purchased Inspection	Machine learning (ML) models have become essential tools in various scenarios. Their effectiveness, however, hinges on a substantial volume of data for satisfactory performance. Model marketplaces have thus emerged as crucial platforms bridging model consumers seeking ML solutions and data owners possessing valuable da...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	532,963
2205.06986	Evaluating Membership Inference Through Adversarial Robustness	The usage of deep learning is being escalated in many applications. Due to its outstanding performance, it is being used in a variety of security and privacy-sensitive areas in addition to conventional applications. One of the key aspects of deep learning efficacy is to have abundant data. This trait leads to the usage...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	296,433
1908.02612	An End-to-End Text-independent Speaker Verification Framework with a Keyword Adversarial Network	This paper presents an end-to-end text-independent speaker verification framework by jointly considering the speaker embedding (SE) network and automatic speech recognition (ASR) network. The SE network learns to output an embedding vector which distinguishes the speaker characteristics of the input utterance, while th...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,047
cs/9707103	Defining Relative Likelihood in Partially-Ordered Preferential Structures	Starting with a likelihood or preference order on worlds, we extend it to a likelihood ordering on sets of worlds in a natural way, and examine the resulting logic. Lewis earlier considered such a notion of relative likelihood in the context of studying counterfactuals, but he assumed a total preference order on worlds...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	540,365
2401.00926	Accurate Leukocyte Detection Based on Deformable-DETR and Multi-Level Feature Fusion for Aiding Diagnosis of Blood Diseases	In standard hospital blood tests, the traditional process requires doctors to manually isolate leukocytes from microscopic images of patients' blood using microscopes. These isolated leukocytes are then categorized via automatic leukocyte classifiers to determine the proportion and volume of different types of leukocyt...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	419,160
2408.08345	5%>100%: Breaking Performance Shackles of Full Fine-Tuning on Visual Recognition Tasks	Pre-training & fine-tuning can enhance the transferring efficiency and performance in visual tasks. Recent delta-tuning methods provide more options for visual classification tasks. Despite their success, existing visual delta-tuning art fails to exceed the upper limit of full fine-tuning on challenging tasks like obje...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,965
2404.03392	Boosting Unsupervised Segmentation Learning	We present two practical improvement techniques for unsupervised segmentation learning. These techniques address limitations in the resolution and accuracy of predicted segmentation maps of recent state-of-the-art methods. Firstly, we leverage image post-processing techniques such as guided filtering to refine the outp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,237
2406.00047	A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Electronic Schrodinger Equation	A central problem in quantum mechanics involves solving the Electronic Schrodinger Equation for a molecule or material. The Variational Monte Carlo approach to this problem approximates a particular variational objective via sampling, and then optimizes this approximated objective over a chosen parameterized family of ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	459,684
1212.4210	From compression to compressed sensing	Can compression algorithms be employed for recovering signals from their underdetermined set of linear measurements? Addressing this question is the first step towards applying compression algorithms for compressed sensing (CS). In this paper, we consider a family of compression algorithms $\mathcal{C}_r$, parametrized...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	20,458
1812.09832	Texture Deformation Based Generative Adversarial Networks for Face Editing	Despite the significant success in image-to-image translation and latent representation based facial attribute editing and expression synthesis, the existing approaches still have limitations in the sharpness of details, distinct image translation and identity preservation. To address these issues, we propose a Texture...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,238
2202.10201	OG-SGG: Ontology-Guided Scene Graph Generation. A Case Study in Transfer Learning for Telepresence Robotics	Scene graph generation from images is a task of great interest to applications such as robotics, because graphs are the main way to represent knowledge about the world and regulate human-robot interactions in tasks such as Visual Question Answering (VQA). Unfortunately, its corresponding area of machine learning is sti...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	281,454
2401.01495	A Two-Stage Multimodal Emotion Recognition Model Based on Graph Contrastive Learning	In terms of human-computer interaction, it is becoming more and more important to correctly understand the user's emotional state in a conversation, so the task of multimodal emotion recognition (MER) started to receive more attention. However, existing emotion classification methods usually perform classification only...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	419,377
2110.01968	Missing $g$-mass: Investigating the Missing Parts of Distributions	Estimating the underlying distribution from \textit{iid} samples is a classical and important problem in statistics. When the alphabet size is large compared to number of samples, a portion of the distribution is highly likely to be unobserved or sparsely observed. The missing mass, defined as the sum of probabilities ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	258,961
2012.15480	Likelihood Ratio Exponential Families	The exponential family is well known in machine learning and statistical physics as the maximum entropy distribution subject to a set of observed constraints, while the geometric mixture path is common in MCMC methods such as annealed importance sampling. Linking these two ideas, recent work has interpreted the geometr...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	213,804
1908.10063	FinBERT: Financial Sentiment Analysis with Pre-trained Language Models	Financial sentiment analysis is a challenging task due to the specialized language and lack of labeled data in that domain. General-purpose models are not effective enough because of the specialized language used in a financial context. We hypothesize that pre-trained language models can help with this problem because ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	143,015
2303.08359	Haptics-Enabled Forceps with Multi-Modal Force Sensing: Towards Task-Autonomous Surgery	Many robotic surgical systems have been developed with micro-sized forceps for tissue manipulation. However, these systems often lack force sensing at the tool side and the manipulation forces are roughly estimated and controlled relying on the surgeon's visual perception. To address this challenge, we present a vision...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	351,613
2111.00309	TargetUM: Targeted High-Utility Itemset Querying	Traditional high-utility itemset mining (HUIM) aims to determine all high-utility itemsets (HUIs) that satisfy the minimum utility threshold (\textit{minUtil}) in transaction databases. However, in most applications, not all HUIs are interesting because only specific parts are required. Thus, targeted mining based on u...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	264,175
1703.02638	Constellation Queries over Big Data	A geometrical pattern is a set of points with all pairwise distances (or, more generally, relative distances) specified. Finding matches to such patterns has applications to spatial data in seismic, astronomical, and transportation contexts. For example, a particularly interesting geometric pattern in astronomy is the ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	69,592
2002.07016	Meta-learning Extractors for Music Source Separation	We propose a hierarchical meta-learning-inspired model for music source separation (Meta-TasNet) in which a generator model is used to predict the weights of individual extractor models. This enables efficient parameter-sharing, while still allowing for instrument-specific parameterization. Meta-TasNet is shown to be m...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,357
2303.17921	IC-FPS: Instance-Centroid Faster Point Sampling Module for 3D Point-base Object Detection	3D object detection is one of the most important tasks in autonomous driving and robotics. Our research focuses on tackling low efficiency issue of point-based methods on large-scale point clouds. Existing point-based methods adopt farthest point sampling (FPS) strategy for downsampling, which is computationally expens...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,394
2205.08363	REAL ML: Recognizing, Exploring, and Articulating Limitations of Machine Learning Research	Transparency around limitations can improve the scientific rigor of research, help ensure appropriate interpretation of research findings, and make research claims more credible. Despite these benefits, the machine learning (ML) research community lacks well-developed norms around disclosing and discussing limitations....	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	296,906
2211.11035	Heterogenous Ensemble of Models for Molecular Property Prediction	Previous works have demonstrated the importance of considering different modalities on molecules, each of which provide a varied granularity of information for downstream property prediction tasks. Our method combines variants of the recent TransformerM architecture with Transformer, GNN, and ResNet backbone architectu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,550
2103.11027	Relational Operations in FOLE	This paper discusses relational operations in the first-order logical environment {FOLE}. Here we demonstrate how FOLE expresses the relational operations of database theory in a clear and implementable representation. An analysis of the representation of database tables/relations in FOLE reveals a principled way to ex...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	225,640
2303.07223	PromptFusion: Decoupling Stability and Plasticity for Continual Learning	Current research on continual learning mainly focuses on relieving catastrophic forgetting, and most of their success is at the cost of limiting the performance of newly incoming tasks. Such a trade-off is referred to as the stability-plasticity dilemma and is a more general and challenging problem for continual learni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,175
2312.11521	Large Language Models are Complex Table Parsers	With the Generative Pre-trained Transformer 3.5 (GPT-3.5) exhibiting remarkable reasoning and comprehension abilities in Natural Language Processing (NLP), most Question Answering (QA) research has primarily centered around general QA tasks based on GPT, neglecting the specific challenges posed by Complex Table QA. In ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	416,606
2303.16024	Egocentric Auditory Attention Localization in Conversations	In a noisy conversation environment such as a dinner party, people often exhibit selective auditory attention, or the ability to focus on a particular speaker while tuning out others. Recognizing who somebody is listening to in a conversation is essential for developing technologies that can understand social behavior ...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,710
2303.14703	Exploring the Interplay Between Colorectal Cancer Subtypes Genomic Variants and Cellular Morphology: A Deep-Learning Approach	Molecular subtypes of colorectal cancer (CRC) significantly influence treatment decisions. While convolutional neural networks (CNNs) have recently been introduced for automated CRC subtype identification using H&E stained histopathological images, the correlation between CRC subtype genomic variants and their correspo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,210
2010.08705	DEAL: Difficulty-aware Active Learning for Semantic Segmentation	Active learning aims to address the paucity of labeled data by finding the most informative samples. However, when applying to semantic segmentation, existing methods ignore the segmentation difficulty of different semantic areas, which leads to poor performance on those hard semantic areas such as tiny or slender obje...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	201,271
2203.00513	A comparative study of several parameterizations for speaker recognition	This paper presents an exhaustive study about the robustness of several parameterizations, in speaker verification and identification tasks. We have studied several mismatch conditions: different recording sessions, microphones, and different languages (it has been obtained from a bilingual set of speakers). This study...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,029
1301.3791	XORing Elephants: Novel Erasure Codes for Big Data	Distributed storage systems for large clusters typically use replication to provide reliability. Recently, erasure codes have been used to reduce the large storage overhead of three-replicated systems. Reed-Solomon codes are the standard design choice and their high repair cost is often considered an unavoidable price ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	21,142
2310.08754	Tokenizer Choice For LLM Training: Negligible or Crucial?	The recent success of Large Language Models (LLMs) has been predominantly driven by curating the training dataset composition, scaling of model architectures and dataset sizes and advancements in pretraining objectives, leaving tokenizer influence as a blind spot. Shedding light on this underexplored area, we conduct a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	399,515
1712.10061	The Age of Information in Multihop Networks	Information updates in multihop networks such as Internet of Things (IoT) and intelligent transportation systems have received significant recent attention. In this paper, we minimize the age of a single information flow in interference-free multihop networks. When preemption is allowed and the packet transmission time...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	87,442
2203.04452	Cooperative Trajectory Planning in Uncertain Environments with Monte Carlo Tree Search and Risk Metrics	Automated vehicles require the ability to cooperate with humans for smooth integration into today's traffic. While the concept of cooperation is well known, developing a robust and efficient cooperative trajectory planning method is still a challenge. One aspect of this challenge is the uncertainty surrounding the stat...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	284,477
2311.17287	Utilizing Model Residuals to Identify Rental Properties of Interest: The Price Anomaly Score (PAS) and Its Application to Real-time Data in Manhattan	Understanding whether a property is priced fairly hinders buyers and sellers since they usually do not have an objective viewpoint of the price distribution for the overall market of their interest. Drawing from data collected of all possible available properties for rent in Manhattan as of September 2023, this paper a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	411,237
2202.03944	Detecting Anomalies within Time Series using Local Neural Transformations	We develop a new method to detect anomalies within time series, which is essential in many application domains, reaching from self-driving cars, finance, and marketing to medical diagnosis and epidemiology. The method is based on self-supervised deep learning that has played a key role in facilitating deep anomaly dete...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	279,397
2212.03189	Towards Energy Efficient Mobile Eye Tracking for AR Glasses through Optical Sensor Technology	After the introduction of smartphones and smartwatches, AR glasses are considered the next breakthrough in the field of wearables. While the transition from smartphones to smartwatches was based mainly on established display technologies, the display technology of AR glasses presents a technological challenge. Many dis...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,024
1909.06044	Say What I Want: Towards the Dark Side of Neural Dialogue Models	Neural dialogue models have been widely adopted in various chatbot applications because of their good performance in simulating and generalizing human conversations. However, there exists a dark side of these models -- due to the vulnerability of neural networks, a neural dialogue model can be manipulated by users to s...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	145,279
2201.08387	Understanding and Detecting Hateful Content using Contrastive Learning	The spread of hate speech and hateful imagery on the Web is a significant problem that needs to be mitigated to improve our Web experience. This work contributes to research efforts to detect and understand hateful content on the Web by undertaking a multimodal analysis of Antisemitism and Islamophobia on 4chan's /pol/...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	276,324
1805.01222	audEERING's approach to the One-Minute-Gradual Emotion Challenge	This paper describes audEERING's submissions as well as additional evaluations for the One-Minute-Gradual (OMG) emotion recognition challenge. We provide the results for audio and video processing on subject (in)dependent evaluations. On the provided Development set, we achieved 0.343 Concordance Correlation Coefficien...	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	96,616
cs/0601073	A Theory of Routing for Large-Scale Wireless Ad-Hoc Networks	In this work we develop a new theory to analyse the process of routing in large-scale ad-hoc wireless networks. We use a path integral formulation to examine the properties of the paths generated by different routing strategies in these kinds of networks. Using this theoretical framework, we calculate the statistical d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	539,210
2404.10664	Assessing The Impact of CNN Auto Encoder-Based Image Denoising on Image Classification Tasks	Images captured from the real world are often affected by different types of noise, which can significantly impact the performance of Computer Vision systems and the quality of visual data. This study presents a novel approach for defect detection in casting product noisy images, specifically focusing on submersible pu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	447,192
2312.16629	Autonomous Docking Method via Non-linear Model Predictive Control	This paper presents a proposed method of autonomous control for docking tasks of a single-seat personal mobility vehicle. We proposed a non-linear model predictive control (NMPC) based visual servoing to achieves the desired autonomous docking task. The proposed method is implemented on a four-wheel electric wheelchair...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	418,462
2106.06362	Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing	Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behaviour, (dis)similarity or complementarity. We propose a simple method to derive 2D representation from detection scores produced by an arbitrar...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	240,461
2205.12749	A Human-Centric Assessment Framework for AI	With the rise of AI systems in real-world applications comes the need for reliable and trustworthy AI. An essential aspect of this are explainable AI systems. However, there is no agreed standard on how explainable AI systems should be assessed. Inspired by the Turing test, we introduce a human-centric assessment frame...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	298,698
2310.08308	Multicriteria Optimization of Lower Limb Exoskeleton Mechanism	Typical leg exoskeletons employ open-loop kinematic chains with motors placed directly on movable joints; while this design offers flexibility, it leads to increased costs and heightened control complexity due to the high number of degrees of freedom. The use of heavy servo-motors to handle torque in active joints resu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	399,344
2412.00261	Attribute-Enhanced Similarity Ranking for Sparse Link Prediction	Link prediction is a fundamental problem in graph data. In its most realistic setting, the problem consists of predicting missing or future links between random pairs of nodes from the set of disconnected pairs. Graph Neural Networks (GNNs) have become the predominant framework for link prediction. GNN-based methods tr...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	512,577
2102.07033	PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them	Open-domain Question Answering models which directly leverage question-answer (QA) pairs, such as closed-book QA (CBQA) models and QA-pair retrievers, show promise in terms of speed and memory compared to conventional models which retrieve and read from text corpora. QA-pair retrievers also offer interpretable answers,...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	219,962
2407.15286	Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis	Large Language Models (LLMs) are capable of producing content that perpetuates stereotypes, discrimination, and toxicity. The recently proposed moral self-correction is a computationally efficient method for reducing harmful content in the responses of LLMs. However, the process of how injecting self-correction instruc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	475,115
2412.05753	Can OpenAI o1 outperform humans in higher-order cognitive thinking?	This study evaluates the performance of OpenAI's o1-preview model in higher-order cognitive domains, including critical thinking, systematic thinking, computational thinking, data literacy, creative thinking, logical reasoning, and scientific reasoning. Using established benchmarks, we compared the o1-preview models's ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	514,958
2001.02496	Architecting Safe Automated Driving with Legacy Platforms	Modern vehicles have electrical architectures whose complexity grows year after year due to feature growth corresponding to customer expectations. The latest of the expectations, automation of the dynamic driving task however, is poised to bring about some of the largest changes seen so far. In one fell swoop, not only...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	159,750
2211.15656	SuperFusion: Multilevel LiDAR-Camera Fusion for Long-Range HD Map Generation	High-definition (HD) semantic map generation of the environment is an essential component of autonomous driving. Existing methods have achieved good performance in this task by fusing different sensor modalities, such as LiDAR and camera. However, current works are based on raw data or network feature-level fusion and ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	333,348
0705.2272	Quantization Bounds on Grassmann Manifolds of Arbitrary Dimensions and MIMO Communications with Feedback	This paper considers the quantization problem on the Grassmann manifold with dimension n and p. The unique contribution is the derivation of a closed-form formula for the volume of a metric ball in the Grassmann manifold when the radius is sufficiently small. This volume formula holds for Grassmann manifolds with arbit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	250
2209.03190	Efficient Implementation of Non-linear Flow Law Using Neural Network into the Abaqus Explicit FEM code	Machine learning techniques are increasingly used to predict material behavior in scientific applications and offer a significant advantage over conventional numerical methods. In this work, an Artificial Neural Network (ANN) model is used in a finite element formulation to define the flow law of a metallic material as...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	316,436
2109.14860	Physics and Equality Constrained Artificial Neural Networks: Application to Forward and Inverse Problems with Multi-fidelity Data Fusion	Physics-informed neural networks (PINNs) have been proposed to learn the solution of partial differential equations (PDE). In PINNs, the residual form of the PDE of interest and its boundary conditions are lumped into a composite objective function as soft penalties. Here, we show that this specific way of formulating ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	258,094
2011.11266	Federated learning with class imbalance reduction	Federated learning (FL) is a promising technique that enables a large amount of edge computing devices to collaboratively train a global learning model. Due to privacy concerns, the raw data on devices could not be available for centralized server. Constrained by the spectrum limitation and computation capacity, only a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	207,782
2007.07743	Finding Non-Uniform Quantization Schemes using Multi-Task Gaussian Processes	We propose a novel method for neural network quantization that casts the neural architecture search problem as one of hyperparameter search to find non-uniform bit distributions throughout the layers of a CNN. We perform the search assuming a Multi-Task Gaussian Processes prior, which splits the problem to multiple tas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,426
1903.07309	Bilateral Cyclic Constraint and Adaptive Regularization for Unsupervised Monocular Depth Prediction	Supervised learning methods to infer (hypothesize) depth of a scene from a single image require costly per-pixel ground-truth. We follow a geometric approach that exploits abundant stereo imagery to learn a model to hypothesize scene structure without direct supervision. Although we train a network with stereo pairs, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	124,590
1401.3168	On the Design of Relay--Assisted Primary--Secondary Networks	The use of $N$ cognitive relays to assist primary and secondary transmissions in a time-slotted cognitive setting with one primary user (PU) and one secondary user (SU) is investigated. An overlapped spectrum sensing strategy is proposed for channel sensing, where the SU senses the channel for $\tau$ seconds from the b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	29,814
2009.09595	RL STaR Platform: Reinforcement Learning for Simulation based Training of Robots	Reinforcement learning (RL) is a promising field to enhance robotic autonomy and decision making capabilities for space robotics, something which is challenging with traditional techniques due to stochasticity and uncertainty within the environment. RL can be used to enable lunar cave exploration with infrequent human ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	196,633
2312.16079	Coexistence assessment and interference mitigation for 5G and Fixed Satellite Stations in C-band in India	In this paper, we present the findings of a study conducted to assess the coexistence of Fifth Generation (5G) wireless networks and Fixed Satellite Station (FSS) receivers in the C-Band (3300-4200 MHz) in India. Through simulations, we evaluate the coexistence feasibility and calculate the minimum separation distances...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	418,257
2402.09897	COVIDHealth: A Benchmark Twitter Dataset and Machine Learning based Web Application for Classifying COVID-19 Discussions	The COVID-19 pandemic has had adverse effects on both physical and mental health. During this pandemic, numerous studies have focused on gaining insights into health-related perspectives from social media. In this study, our primary objective is to develop a machine learning-based web application for automatically clas...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,724
1911.03391	Single-shot 3D multi-person pose estimation in complex images	In this paper, we propose a new single shot method for multi-person 3D human pose estimation in complex images. The model jointly learns to locate the human joints in the image, to estimate their 3D coordinates and to group these predictions into full human skeletons. The proposed method deals with a variable number of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	152,639
0812.3648	A New Method for Knowledge Representation in Expert System's (XMLKR)	Knowledge representation it is an essential section of a Expert Systems, Because in this section we have a framework to establish an expert system then we can modeling and use by this to design an expert system. Many method it is exist for knowledge representation but each method have problems, in this paper we introdu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	2,827
2207.01193	A Customized Text Sanitization Mechanism with Differential Privacy	As privacy issues are receiving increasing attention within the Natural Language Processing (NLP) community, numerous methods have been proposed to sanitize texts subject to differential privacy. However, the state-of-the-art text sanitization mechanisms based on metric local differential privacy (MLDP) do not apply to...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	306,075
2103.03385	Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy data	This paper presents a machine learning framework (GP-NODE) for Bayesian systems identification from partial, noisy and irregular observations of nonlinear dynamical systems. The proposed method takes advantage of recent developments in differentiable programming to propagate gradient information through ordinary differ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	223,248
2106.00072	Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data	Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease. Understanding the spatio-temporal dynamic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	237,969
2308.14683	Fine-Tuning Llama 2 Large Language Models for Detecting Online Sexual Predatory Chats and Abusive Texts	Detecting online sexual predatory behaviours and abusive language on social media platforms has become a critical area of research due to the growing concerns about online safety, especially for vulnerable populations such as children and adolescents. Researchers have been exploring various techniques and approaches to...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	388,418
2408.10378	Finite-time input-to-state stability for infinite-dimensional systems	In this paper, we extend the notion of finite-time input-to-state stability (FTISS) for finite-dimensional systems to infinite-dimensional systems. More specifically, we first prove an FTISS Lyapunov theorem for a class of infinite-dimensional systems, namely, the existence of an FTISS Lyapunov functional (FTISS-LF) im...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	481,825
2208.10250	Multi-Task Learning for Depression Detection in Dialogs	Depression is a serious mental illness that impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work examines depression signals in dialogs, a less studied setting that suffers from data sparsity. We hypothesize that depression and emotion can i...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	313,987
1809.03479	Relay-Aided Secure Broadcasting for Visible Light Communications	A visible light communication broadcast channel is considered, in which a transmitter luminaire communicates with two legitimate receivers in the presence of an external eavesdropper. A number of trusted cooperative half-duplex relay luminaires are deployed to aid with securing the transmitted data. Transmitters are eq...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	107,337
1611.07599	Efficient Delivery Policy to Minimize User Traffic Consumption in Guaranteed Advertising	In this work, we study the guaranteed delivery model which is widely used in online display advertising. In the guaranteed delivery scenario, ad exposures (which are also called impressions in some works) to users are guaranteed by contracts signed in advance between advertisers and publishers. A crucial problem for th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	64,374
1907.08556	D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction	Spatio-temporal (ST) data for urban applications, such as taxi demand, traffic flow, regional rainfall is inherently stochastic and unpredictable. Recently, deep learning based ST prediction models are proposed to learn the ST characteristics of data. However, it is still very challenging (1) to adequately learn the co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,134
1705.08931	Proximity Variational Inference	Variational inference is a powerful approach for approximate posterior inference. However, it is sensitive to initialization and can be subject to poor local optima. In this paper, we develop proximity variational inference (PVI). PVI is a new method for optimizing the variational objective that constrains subsequent i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,110
2405.20053	Would I Lie To You? Inference Time Alignment of Language Models using Direct Preference Heads	Pre-trained Language Models (LMs) exhibit strong zero-shot and in-context learning capabilities; however, their behaviors are often difficult to control. By utilizing Reinforcement Learning from Human Feedback (RLHF), it is possible to fine-tune unsupervised LMs to follow instructions and produce outputs that reflect h...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	459,176
2502.11437	Learning Dexterous Bimanual Catch Skills through Adversarial-Cooperative Heterogeneous-Agent Reinforcement Learning	Robotic catching has traditionally focused on single-handed systems, which are limited in their ability to handle larger or more complex objects. In contrast, bimanual catching offers significant potential for improved dexterity and object handling but introduces new challenges in coordination and control. In this pape...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	534,366
2407.12655	Optimal Control for Clutched-Elastic Robots: A Contact-Implicit Approach	Intrinsically elastic robots surpass their rigid counterparts in a range of different characteristics. By temporarily storing potential energy and subsequently converting it to kinetic energy, elastic robots are capable of highly dynamic motions even with limited motor power. However, the time-dependency of this energy...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	474,020
1909.12375	On the Importance of Subword Information for Morphological Tasks in Truly Low-Resource Languages	Recent work has validated the importance of subword information for word representation learning. Since subwords increase parameter sharing ability in neural models, their value should be even more pronounced in low-data regimes. In this work, we therefore provide a comprehensive analysis focused on the usefulness of s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	147,109
1812.06544	Towards Robust Human Activity Recognition from RGB Video Stream with Limited Labeled Data	Human activity recognition based on video streams has received numerous attentions in recent years. Due to lack of depth information, RGB video based activity recognition performs poorly compared to RGB-D video based solutions. On the other hand, acquiring depth information, inertia etc. is costly and requires special ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	116,636
1703.09393	Mixture of Counting CNNs: Adaptive Integration of CNNs Specialized to Specific Appearance for Crowd Counting	This paper proposes a crowd counting method. Crowd counting is difficult because of large appearance changes of a target which caused by density and scale changes. Conventional crowd counting methods generally utilize one predictor (e,g., regression and multi-class classifier). However, such only one predictor can not ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,743
2202.12634	Deep Dirichlet uncertainty for unsupervised out-of-distribution detection of eye fundus photographs in glaucoma screening	The development of automatic tools for early glaucoma diagnosis with color fundus photographs can significantly reduce the impact of this disease. However, current state-of-the-art solutions are not robust to real-world scenarios, providing over-confident predictions for out-of-distribution cases. With this in mind, we...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	282,315

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.