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
2409.13442	Automatic Classification of White Blood Cell Images using Convolutional Neural Network	Human immune system contains white blood cells (WBC) that are good indicator of many diseases like bacterial infections, AIDS, cancer, spleen, etc. White blood cells have been sub classified into four types: monocytes, lymphocytes, eosinophils and neutrophils on the basis of their nucleus, shape and cytoplasm. Traditio...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	489,994
2412.05719	Finite Element Neural Network Interpolation. Part I: Interpretable and Adaptive Discretization for Solving PDEs	We present the Finite Element Neural Network Interpolation (FENNI) framework, a sparse neural network architecture extending previous work on Embedded Finite Element Neural Networks (EFENN) introduced with the Hierarchical Deep-learning Neural Networks (HiDeNN). Due to their mesh-based structure, EFENN requires signifi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	514,942
2410.19944	A Multimodal Approach For Endoscopic VCE Image Classification Using BiomedCLIP-PubMedBERT	This Paper presents an advanced approach for fine-tuning BiomedCLIP PubMedBERT, a multimodal model, to classify abnormalities in Video Capsule Endoscopy (VCE) frames, aiming to enhance diagnostic efficiency in gastrointestinal healthcare. By integrating the PubMedBERT language model with a Vision Transformer (ViT) to p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	502,580
2103.15631	On data-driven stabilization of systems with quadratic nonlinearities	In this paper, we directly design a state feedback controller that stabilizes a class of uncertain nonlinear systems solely based on input-state data collected from a finite-length experiment. Necessary and sufficient conditions are derived to guarantee that the system is absolutely stabilizable and a controller is des...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	227,293
2401.15071	From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities	Multi-modal Large Language Models (MLLMs) have shown impressive abilities in generating reasonable responses with respect to multi-modal contents. However, there is still a wide gap between the performance of recent MLLM-based applications and the expectation of the broad public, even though the most powerful OpenAI's ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,310
2410.07673	Multimodal Clickbait Detection by De-confounding Biases Using Causal Representation Inference	This paper focuses on detecting clickbait posts on the Web. These posts often use eye-catching disinformation in mixed modalities to mislead users to click for profit. That affects the user experience and thus would be blocked by content provider. To escape detection, malicious creators use tricks to add some irrelevan...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	496,740
2405.12800	Deep Reinforcement Learning for Time-Critical Wilderness Search And Rescue Using Drones	Traditional search and rescue methods in wilderness areas can be time-consuming and have limited coverage. Drones offer a faster and more flexible solution, but optimizing their search paths is crucial. This paper explores the use of deep reinforcement learning to create efficient search missions for drones in wilderne...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	455,660
2009.06914	The impact of social influence in Australian real-estate: market forecasting with a spatial agent-based model	Housing markets are inherently spatial, yet many existing models fail to capture this spatial dimension. Here we introduce a new graph-based approach for incorporating a spatial component in a large-scale urban housing agent-based model (ABM). The model explicitly captures several social and economic factors that influ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	195,790
1612.02903	Facial Expression Recognition using Convolutional Neural Networks: State of the Art	The ability to recognize facial expressions automatically enables novel applications in human-computer interaction and other areas. Consequently, there has been active research in this field, with several recent works utilizing Convolutional Neural Networks (CNNs) for feature extraction and inference. These works diffe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,301
2306.02689	Equity-Transformer: Solving NP-hard Min-Max Routing Problems as Sequential Generation with Equity Context	Min-max routing problems aim to minimize the maximum tour length among multiple agents by having agents conduct tasks in a cooperative manner. These problems include impactful real-world applications but are known as NP-hard. Existing methods are facing challenges, particularly in large-scale problems that require the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,013
1806.05173	A Unified Framework for Generalizable Style Transfer: Style and Content Separation	Image style transfer has drawn broad attention in recent years. However, most existing methods aim to explicitly model the transformation between different styles, and the learned model is thus not generalizable to new styles. We here propose a unified style transfer framework for both character typeface transfer and n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	100,407
2207.01294	A New Index for Clustering Evaluation Based on Density Estimation	A new index for internal evaluation of clustering is introduced. The index is defined as a mixture of two sub-indices. The first sub-index $ I_a $ is called the Ambiguous Index; the second sub-index $ I_s $ is called the Similarity Index. Calculation of the two sub-indices is based on density estimation to each cluster...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	306,119
1703.03717	Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations	Neural networks are among the most accurate supervised learning methods in use today, but their opacity makes them difficult to trust in critical applications, especially when conditions in training differ from those in test. Recent work on explanations for black-box models has produced tools (e.g. LIME) to show the im...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	69,771
2207.00781	Analysis of Age of Information in Dual Updating Systems	We study the average Age of Information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. Although the double queue parallel transmission is instrumental in reducing AoI, the out of order of data arrivals also imposes a significant challenge to the performance ana...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	305,892
2303.01130	Distillation from Heterogeneous Models for Top-K Recommendation	Recent recommender systems have shown remarkable performance by using an ensemble of heterogeneous models. However, it is exceedingly costly because it requires resources and inference latency proportional to the number of models, which remains the bottleneck for production. Our work aims to transfer the ensemble knowl...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	348,840
1903.07902	A Comparative Study for Unsupervised Network Representation Learning	There has been appreciable progress in unsupervised network representation learning (UNRL) approaches over graphs recently with flexible random-walk approaches, new optimization objectives and deep architectures. However, there is no common ground for systematic comparison of embeddings to understand their behavior for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,731
2212.02978	Muscles in Action	Human motion is created by, and constrained by, our muscles. We take a first step at building computer vision methods that represent the internal muscle activity that causes motion. We present a new dataset, Muscles in Action (MIA), to learn to incorporate muscle activity into human motion representations. The dataset ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,954
1611.08222	On Stochastic Sensor Network Scheduling for Multiple Processes	We consider the problem of multiple sensor scheduling for remote state estimation of multiple process over a shared link. In this problem, a set of sensors monitor mutually independent dynamical systems in parallel but only one sensor can access the shared channel at each time to transmit the data packet to the estimat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	64,466
2108.01291	A Non-uniform Sampling Approach for Fast and Efficient Path Planning	In this paper, we develop a non-uniform sampling approach for fast and efficient path planning of autonomous vehicles. The approach uses a novel non-uniform partitioning scheme that divides the area into obstacle-free convex cells. The partitioning results in large cells in obstacle-free areas and small cells in obstac...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	248,985
2403.03444	Uncertainty quantification for deeponets with ensemble kalman inversion	In recent years, operator learning, particularly the DeepONet, has received much attention for efficiently learning complex mappings between input and output functions across diverse fields. However, in practical scenarios with limited and noisy data, accessing the uncertainty in DeepONet predictions becomes essential,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	435,193
1512.02819	Reduced Complexity Detection for Network-Coded Slotted ALOHA using Sphere Decoding	Network-coded slotted ALOHA (NCSA) is a re- finement to the classic slotted ALOHA protocol which im- proves throughput by enabling multiple source transmissions per ALOHA slot using physical-layer network coding (PNC). The receiver detects the network-coded combination of bits during every slot and recovers information...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,971
2301.11284	BillionCOV: An Enriched Billion-scale Collection of COVID-19 tweets for Efficient Hydration	The COVID-19 pandemic introduced new norms such as social distancing, face masks, quarantine, lockdowns, travel restrictions, work/study from home, and business closures, to name a few. The pandemic's seriousness made people vocal on social media, especially on microblogs such as Twitter. Researchers have been collecti...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	342,077
1711.06968	Intelligent Word Embeddings of Free-Text Radiology Reports	Radiology reports are a rich resource for advancing deep learning applications in medicine by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the ambiguity and subtlety of natural language. We propose a hybrid stra...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	84,892
cs/0607090	Neural Networks with Complex and Quaternion Inputs	This article investigates Kak neural networks, which can be instantaneously trained, for complex and quaternion inputs. The performance of the basic algorithm has been analyzed and shown how it provides a plausible model of human perception and understanding of images. The motivation for studying quaternion inputs is t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	539,599
2409.10737	AutoSafeCoder: A Multi-Agent Framework for Securing LLM Code Generation through Static Analysis and Fuzz Testing	Recent advancements in automatic code generation using large language models (LLMs) have brought us closer to fully automated secure software development. However, existing approaches often rely on a single agent for code generation, which struggles to produce secure, vulnerability-free code. Traditional program synthe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	488,865
2106.08706	Silent Speech and Emotion Recognition from Vocal Tract Shape Dynamics in Real-Time MRI	Speech sounds of spoken language are obtained by varying configuration of the articulators surrounding the vocal tract. They contain abundant information that can be utilized to better understand the underlying mechanism of human speech production. We propose a novel deep neural network-based learning framework that un...	true	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	241,393
0911.3823	Google matrix and Ulam networks of intermittency maps	We study the properties of the Google matrix of an Ulam network generated by intermittency maps. This network is created by the Ulam method which gives a matrix approximant for the Perron-Frobenius operator of dynamical map. The spectral properties of eigenvalues and eigenvectors of this matrix are analyzed. We show th...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	4,981
1905.01995	Using Context Information to Enhance Simple Question Answering	With the rapid development of knowledge bases(KBs),question answering(QA)based on KBs has become a hot research issue. In this paper,we propose two frameworks(i.e.,pipeline framework,an end-to-end framework)to focus answering single-relation factoid question. In both of two frameworks,we study the effect of context inf...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	129,875
1910.12362	Distance approximation using Isolation Forests	This work briefly explores the possibility of approximating spatial distance (alternatively, similarity) between data points using the Isolation Forest method envisioned for outlier detection. The logic is similar to that of isolation: the more similar or closer two points are, the more random splits it will take to se...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	151,059
2411.04693	Electromagnetic Scattering Kernel Guided Reciprocal Point Learning for SAR Open-Set Recognition	The limitations of existing Synthetic Aperture Radar (SAR) Automatic Target Recognition (ATR) methods lie in their confinement by the closed-environment assumption, hindering their effective and robust handling of unknown target categories in open environments. Open Set Recognition (OSR), a pivotal facet for algorithmi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	506,374
2108.09141	Reinforcement Learning to Optimize Lifetime Value in Cold-Start Recommendation	Recommender system plays a crucial role in modern E-commerce platform. Due to the lack of historical interactions between users and items, cold-start recommendation is a challenging problem. In order to alleviate the cold-start issue, most existing methods introduce content and contextual information as the auxiliary i...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	251,512
2410.19595	Mask-Weighted Spatial Likelihood Coding for Speaker-Independent Joint Localization and Mask Estimation	Due to their robustness and flexibility, neural-driven beamformers are a popular choice for speech separation in challenging environments with a varying amount of simultaneous speakers alongside noise and reverberation. Time-frequency masks and relative directions of the speakers regarding a fixed spatial grid can be u...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	502,380
2003.13551	European Language Grid: An Overview	With 24 official EU and many additional languages, multilingualism in Europe and an inclusive Digital Single Market can only be enabled through Language Technologies (LTs). European LT business is dominated by hundreds of SMEs and a few large players. Many are world-class, with technologies that outperform the global p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	170,239
2103.16050	Progressive Domain Expansion Network for Single Domain Generalization	Single domain generalization is a challenging case of model generalization, where the models are trained on a single domain and tested on other unseen domains. A promising solution is to learn cross-domain invariant representations by expanding the coverage of the training domain. These methods have limited generalizat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,435
cs/0611069	Scaling Construction Grammar up to Production Systems: the SCIM	While a great effort has concerned the development of fully integrated modular understanding systems, few researches have focused on the problem of unifying existing linguistic formalisms with cognitive processing models. The Situated Constructional Interpretation Model is one of these attempts. In this model, the noti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	539,876
2209.14849	Federated Stain Normalization for Computational Pathology	Although deep federated learning has received much attention in recent years, progress has been made mainly in the context of natural images and barely for computational pathology. However, deep federated learning is an opportunity to create datasets that reflect the data diversity of many laboratories. Further, the ef...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,371
2305.02506	String Diagrams with Factorized Densities	A growing body of research on probabilistic programs and causal models has highlighted the need to reason compositionally about model classes that extend directed graphical models. Both probabilistic programs and causal models define a joint probability density over a set of random variables, and exhibit sparse structu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	362,062
2202.06373	Scheduling Techniques for Liver Segmentation: ReduceLRonPlateau Vs OneCycleLR	Machine learning and computer vision techniques have influenced many fields including the biomedical one. The aim of this paper is to investigate the important concept of schedulers in manipulating the learning rate (LR), for the liver segmentation task, throughout the training process, focusing on the newly devised On...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	280,198
2302.10359	Replicable Clustering	We design replicable algorithms in the context of statistical clustering under the recently introduced notion of replicability from Impagliazzo et al. [2022]. According to this definition, a clustering algorithm is replicable if, with high probability, its output induces the exact same partition of the sample space aft...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	346,774
2208.11203	Graph Neural Networks and Representation Embedding for Table Extraction in PDF Documents	Tables are widely used in several types of documents since they can bring important information in a structured way. In scientific papers, tables can sum up novel discoveries and summarize experimental results, making the research comparable and easily understandable by scholars. Several methods perform table analysis ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	314,340
2405.19221	Domain adaptation in small-scale and heterogeneous biological datasets	Machine learning techniques are steadily becoming more important in modern biology, and are used to build predictive models, discover patterns, and investigate biological problems. However, models trained on one dataset are often not generalizable to other datasets from different cohorts or laboratories, due to differe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,796
2203.06873	TSR-DSAW: Table Structure Recognition via Deep Spatial Association of Words	Existing methods for Table Structure Recognition (TSR) from camera-captured or scanned documents perform poorly on complex tables consisting of nested rows / columns, multi-line texts and missing cell data. This is because current data-driven methods work by simply training deep models on large volumes of data and fail...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,250
2406.05409	Natural Language-Oriented Programming (NLOP): Towards Democratizing Software Creation	As generative Artificial Intelligence (AI) technologies evolve, they offer unprecedented potential to automate and enhance various tasks, including coding. Natural Language-Oriented Programming (NLOP), a vision introduced in this paper, harnesses this potential by allowing developers to articulate software requirements...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	462,121
2401.06771	Curiosity as a Self-Supervised Method to Improve Exploration in De novo Drug Design	In recent years, deep learning has demonstrated promising results in de novo drug design. However, the proposed techniques still lack an efficient exploration of the large chemical space. Most of these methods explore a small fragment of the chemical space of known drugs, if the desired molecules were not found, the pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	421,270
1904.04792	Quizbowl: The Case for Incremental Question Answering	Scholastic trivia competitions test knowledge and intelligence through mastery of question answering. Modern question answering benchmarks are one variant of the Turing test. Specifically, answering a set of questions as well as a human is a minimum bar towards demonstrating human-like intelligence. This paper makes th...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	127,128
1812.01672	Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning	On-device CNN inference for real-time computer vision applications can result in computational demands that far exceed the energy budgets of mobile devices. This paper proposes FixyNN, a co-designed hardware accelerator platform which splits a CNN model into two parts: a set of layers that are fixed in the hardware pla...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	115,573
2110.08583	ASR4REAL: An extended benchmark for speech models	Popular ASR benchmarks such as Librispeech and Switchboard are limited in the diversity of settings and speakers they represent. We introduce a set of benchmarks matching real-life conditions, aimed at spotting possible biases and weaknesses in models. We have found out that even though recent models do not seem to exh...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	261,471
2108.11996	Drop-DTW: Aligning Common Signal Between Sequences While Dropping Outliers	In this work, we consider the problem of sequence-to-sequence alignment for signals containing outliers. Assuming the absence of outliers, the standard Dynamic Time Warping (DTW) algorithm efficiently computes the optimal alignment between two (generally) variable-length sequences. While DTW is robust to temporal shift...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,361
2502.08092	GCoT: Chain-of-Thought Prompt Learning for Graphs	Chain-of-thought (CoT) prompting has achieved remarkable success in natural language processing (NLP). However, its vast potential remains largely unexplored for graphs. This raises an interesting question: How can we design CoT prompting for graphs to guide graph models to learn step by step? On one hand, unlike natur...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	532,886
2203.05657	Anonymous Hyperlocal Communities: What do they talk about?	In this paper, we study what users talk about in a plethora of independent hyperlocal and anonymous online communities in a single country: Saudi Arabia (KSA). We base this perspective on performing a content classification of the Jodel network in the KSA. To do so, we first contribute a content classification schema t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	284,866
2409.10803	Quantum Machine Learning for Semiconductor Fabrication: Modeling GaN HEMT Contact Process	This paper pioneers the use of quantum machine learning (QML) for modeling the Ohmic contact process in GaN high-electron-mobility transistors (HEMTs) for the first time. Utilizing data from 159 devices and variational auto-encoder-based augmentation, we developed a quantum kernel-based regressor (QKR) with a 2-level Z...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	488,886
2405.11284	The Logic of Counterfactuals and the Epistemology of Causal Inference	The 2021 Nobel Prize in Economics recognizes a type of causal model known as the Rubin causal model, or potential outcome framework, which deserves far more attention from philosophers than it currently receives. To spark philosophers' interest, I develop a dialectic connecting the Rubin causal model to the Lewis-Staln...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	455,077
2403.15709	Contact-aware Human Motion Generation from Textual Descriptions	This paper addresses the problem of generating 3D interactive human motion from text. Given a textual description depicting the actions of different body parts in contact with static objects, we synthesize sequences of 3D body poses that are visually natural and physically plausible. Yet, this task poses a significant ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	440,708
2410.22244	Abrupt Learning in Transformers: A Case Study on Matrix Completion	Recent analysis on the training dynamics of Transformers has unveiled an interesting characteristic: the training loss plateaus for a significant number of training steps, and then suddenly (and sharply) drops to near--optimal values. To understand this phenomenon in depth, we formulate the low-rank matrix completion p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	503,555
2204.00391	Automatic Biomedical Term Clustering by Learning Fine-grained Term Representations	Term clustering is important in biomedical knowledge graph construction. Using similarities between terms embedding is helpful for term clustering. State-of-the-art term embeddings leverage pretrained language models to encode terms, and use synonyms and relation knowledge from knowledge graphs to guide contrastive lea...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,242
2410.10995	Watching the Watchers: Exposing Gender Disparities in Machine Translation Quality Estimation	The automatic assessment of translation quality has recently become crucial across several stages of the translation pipeline, from data curation to training and decoding. Although quality estimation (QE) metrics have been optimized to align with human judgments, no attention has been given to these metrics' potential ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	498,333
2212.02304	Matching DNN Compression and Cooperative Training with Resources and Data Availability	To make machine learning (ML) sustainable and apt to run on the diverse devices where relevant data is, it is essential to compress ML models as needed, while still meeting the required learning quality and time performance. However, how much and when an ML model should be compressed, and {\em where} its training shoul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	334,754
2007.00601	Emergence of polarized ideological opinions in multidimensional topic spaces	Opinion polarization is on the rise, causing concerns for the openness of public debates. Additionally, extreme opinions on different topics often show significant correlations. The dynamics leading to these polarized ideological opinions pose a challenge: How can such correlations emerge, without assuming them a prior...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	185,161
1905.09712	Accelerating DNN Training in Wireless Federated Edge Learning Systems	Training task in classical machine learning models, such as deep neural networks, is generally implemented at a remote cloud center for centralized learning, which is typically time-consuming and resource-hungry. It also incurs serious privacy issue and long communication latency since a large amount of data are transm...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,811
2410.08319	MELO: An Evaluation Benchmark for Multilingual Entity Linking of Occupations	We present the Multilingual Entity Linking of Occupations (MELO) Benchmark, a new collection of 48 datasets for evaluating the linking of entity mentions in 21 languages to the ESCO Occupations multilingual taxonomy. MELO was built using high-quality, pre-existent human annotations. We conduct experiments with simple l...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	497,055
1903.10673	Probabilistic Dense Reconstruction from a Moving Camera	This paper presents a probabilistic approach for online dense reconstruction using a single monocular camera moving through the environment. Compared to spatial stereo, depth estimation from motion stereo is challenging due to insufficient parallaxes, visual scale changes, pose errors, etc. We utilize both the spatial ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	125,335
2501.00015	Energy-Efficient Sampling Using Stochastic Magnetic Tunnel Junctions	(Pseudo)random sampling, a costly yet widely used method in (probabilistic) machine learning and Markov Chain Monte Carlo algorithms, remains unfeasible on a truly large scale due to unmet computational requirements. We introduce an energy-efficient algorithm for uniform Float16 sampling, utilizing a room-temperature s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	521,490
2412.16177	Mining Math Conjectures from LLMs: A Pruning Approach	We present a novel approach to generating mathematical conjectures using Large Language Models (LLMs). Focusing on the solubilizer, a relatively recent construct in group theory, we demonstrate how LLMs such as ChatGPT, Gemini, and Claude can be leveraged to generate conjectures. These conjectures are pruned by allowin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	519,391
1907.07675	Distributed vibration sensing based on forward transmission and coherent detection	A novel ultra-long distributed vibration sensing (DVS) system using forward transmission and coherent detection is proposed and experimentally demonstrated. In the proposed scheme, a pair of multi-span optical fibers are deployed for sensing, and a loop-back configuration is used by connecting the two fibers at the far...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	138,937
2208.11671	Interpreting Song Lyrics with an Audio-Informed Pre-trained Language Model	Lyric interpretations can help people understand songs and their lyrics quickly, and can also make it easier to manage, retrieve and discover songs efficiently from the growing mass of music archives. In this paper we propose BART-fusion, a novel model for generating lyric interpretations from lyrics and music audio th...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	314,512
2409.11308	SpMis: An Investigation of Synthetic Spoken Misinformation Detection	In recent years, speech generation technology has advanced rapidly, fueled by generative models and large-scale training techniques. While these developments have enabled the production of high-quality synthetic speech, they have also raised concerns about the misuse of this technology, particularly for generating synt...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,101
2305.05461	What is the best recipe for character-level encoder-only modelling?	This paper aims to benchmark recent progress in language understanding models that output contextualised representations at the character level. Many such modelling architectures and methods to train those architectures have been proposed, but it is currently unclear what the relative contributions of the architecture ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	363,158
2312.05756	A quantitative fusion strategy of stock picking and timing based on Particle Swarm Optimized-Back Propagation Neural Network and Multivariate Gaussian-Hidden Markov Model	In recent years, machine learning (ML) has brought effective approaches and novel techniques to economic decision, investment forecasting, and risk management, etc., coping the variable and intricate nature of economic and financial environments. For the investment in stock market, this research introduces a pioneering...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	414,221
1501.01294	Design and simulation of a hybrid controller for a multi-input multi-output magnetic suspension system	In this paper we present a Fuzzy Logic control approach designed to stabilize a multi-input multi-output magnetic suspension system. The system has four cubic floaters and four actuators that apply magnetic forces on the floaters, the suspension is performed by changing the voltages applied on the actuators, hence chan...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	39,068
1810.04534	Random matrix-improved estimation of covariance matrix distances	Given two sets $x_1^{(1)},\ldots,x_{n_1}^{(1)}$ and $x_1^{(2)},\ldots,x_{n_2}^{(2)}\in\mathbb{R}^p$ (or $\mathbb{C}^p$) of random vectors with zero mean and positive definite covariance matrices $C_1$ and $C_2\in\mathbb{R}^{p\times p}$ (or $\mathbb{C}^{p\times p}$), respectively, this article provides novel estimators ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,064
2403.02504	A Tutorial on the Pretrain-Finetune Paradigm for Natural Language Processing	Given that natural language serves as the primary conduit for expressing thoughts and emotions, text analysis has become a key technique in psychological research. It enables the extraction of valuable insights from natural language, facilitating endeavors like personality traits assessment, mental health monitoring, a...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,824
0707.3461	Lattices for Distributed Source Coding: Jointly Gaussian Sources and Reconstruction of a Linear Function	Consider a pair of correlated Gaussian sources (X1,X2). Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear combination of X1 and X2 to within a mean-square distortion of D. We obtain an inne...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	473
1605.07362	On Edge Caching in the Presence of Malicious Users	In this paper we investigate the problem of optimal cache placement in the presence of malicious mobile users in heterogeneous networks, where small-cell base stations are equipped with caches in order to reduce the overall backhaul load. In particular the malicious users aim at maximizing the congestion of files at th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	56,287
2401.05857	Secure Dynamic Event-triggered Consensus Under Asynchronous Denial of Service	This article proposes a secure implementation for consensus using a dynamic event-triggered (DET) communication scheme in high-order nonlinear multi-agent systems (MAS) under asynchronous (distributed) denial of service (DoS) attacks. By introducing a linear auxiliary trajectory of the system, the DET data transmission...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	420,936
2111.05476	Learning to Disentangle Scenes for Person Re-identification	There are many challenging problems in the person re-identification (ReID) task, such as the occlusion and scale variation. Existing works usually tried to solve them by employing a one-branch network. This one-branch network needs to be robust to various challenging problems, which makes this network overburdened. Thi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	265,804
1907.08591	Zermelo's problem: Optimal point-to-point navigation in 2D turbulent flows using Reinforcement Learning	To find the path that minimizes the time to navigate between two given points in a fluid flow is known as Zermelo's problem. Here, we investigate it by using a Reinforcement Learning (RL) approach for the case of a vessel which has a slip velocity with fixed intensity, Vs , but variable direction and navigating in a 2D...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	139,140
2303.17898	Information-Theoretic Study of Time-Domain Energy-Saving Techniques in Radio Access	Reduction of wireless network energy consumption is becoming increasingly important to reduce environmental footprint and operational costs. A key concept to achieve it is the use of lean transmission techniques that dynamically (de)activate hardware resources as a function of the load. In this paper, we propose a pion...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	355,384
1709.01467	Subspace Segmentation by Successive Approximations: A Method for Low-Rank and High-Rank Data with Missing Entries	We propose a method to reconstruct and cluster incomplete high-dimensional data lying in a union of low-dimensional subspaces. Exploring the sparse representation model, we jointly estimate the missing data while imposing the intrinsic subspace structure. Since we have a non-convex problem, we propose an iterative meth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	80,086
2105.08058	A parameter refinement method for Ptychography based on Deep Learning concepts	X-ray Ptychography is an advanced computational microscopy technique which is delivering exceptionally detailed quantitative imaging of biological and nanotechnology specimens. However coarse parametrisation in propagation distance, position errors and partial coherence frequently menaces the experiment viability. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	235,642
1608.03961	Reed-Solomon and Concatenated Codes with Applications in Space Communication	In this paper we provide a detailed description of Reed-Solomon (RS) codes, the most important algorithms for decoding them, and their use in concatenated coding systems for space applications. In the current literature there is scattered information regarding the bit-level implementation of such codes for either space...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	59,751
1012.0356	The Past and the Future in the Present	We show how the shared information between the past and future---the excess entropy---derives from the components of directional information stored in the present---the predictive and retrodictive causal states. A detailed proof allows us to highlight a number of the subtle problems in estimation and analysis that impe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,391
2502.11268	Improved Unbiased Watermark for Large Language Models	As artificial intelligence surpasses human capabilities in text generation, the necessity to authenticate the origins of AI-generated content has become paramount. Unbiased watermarks offer a powerful solution by embedding statistical signals into language model-generated text without distorting the quality. In this pa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	534,279
2406.09657	ScaLES: Scalable Latent Exploration Score for Pre-Trained Generative Networks	We develop Scalable Latent Exploration Score (ScaLES) to mitigate over-exploration in Latent Space Optimization (LSO), a popular method for solving black-box discrete optimization problems. LSO utilizes continuous optimization within the latent space of a Variational Autoencoder (VAE) and is known to be susceptible to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	464,027
2408.11438	A Benchmark for AI-based Weather Data Assimilation	Recent advancements in Artificial Intelligence (AI) have led to the development of several Large Weather Models (LWMs) that rival State-Of-The-Art (SOTA) Numerical Weather Prediction (NWP) systems. Until now, these models have still relied on traditional NWP-generated analysis fields as input and are far from autonomou...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	482,293
2402.12649	Bias in Language Models: Beyond Trick Tests and Toward RUTEd Evaluation	Standard benchmarks of bias and fairness in large language models (LLMs) measure the association between social attributes implied in user prompts and short LLM responses. In the commonly studied domain of gender-occupation bias, we test whether these benchmarks are robust to lengthening the LLM responses as a measure ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	430,927
0910.2066	A Lossless Fuzzy Binary AND/OR Compressor	In this report, a new fuzzy 2bit-AND parallel-to-OR, or simply, a fuzzy binary AND/OR (FBAR) text data compression model as an algorithm is suggested for bettering spatial locality limits on nodes during database transactions. The current model incorporates a four-layer application technique: string-to-AND/OR pairwise ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,713
1802.10204	Improved Explainability of Capsule Networks: Relevance Path by Agreement	Recent advancements in signal processing and machine learning domains have resulted in an extensive surge of interest in deep learning models due to their unprecedented performance and high accuracy for different and challenging problems of significant engineering importance. However, when such deep learning architectu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	91,478
1711.08992	Self-Supervised Vision-Based Detection of the Active Speaker as Support for Socially-Aware Language Acquisition	This paper presents a self-supervised method for visual detection of the active speaker in a multi-person spoken interaction scenario. Active speaker detection is a fundamental prerequisite for any artificial cognitive system attempting to acquire language in social settings. The proposed method is intended to compleme...	true	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	85,302
0911.4521	On the equivalence between minimal sufficient statistics, minimal typical models and initial segments of the Halting sequence	It is shown that the length of the algorithmic minimal sufficient statistic of a binary string x, either in a representation of a finite set, computable semimeasure, or a computable function, has a length larger than the computational depth of x, and can solve the Halting problem for all programs with length shorter th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	5,007
2301.08141	Self-supervised Learning for Segmentation and Quantification of Dopamine Neurons in Parkinson's Disease	Parkinson's Disease (PD) is the second most common neurodegenerative disease in humans. PD is characterized by the gradual loss of dopaminergic neurons in the Substantia Nigra (SN). Counting the number of dopaminergic neurons in the SN is one of the most important indexes in evaluating drug efficacy in PD animal models...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	341,111
1909.06500	Adversarial Attack on Skeleton-based Human Action Recognition	Deep learning models achieve impressive performance for skeleton-based human action recognition. However, the robustness of these models to adversarial attacks remains largely unexplored due to their complex spatio-temporal nature that must represent sparse and discrete skeleton joints. This work presents the first adv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	145,390
2411.10960	Beamforming Design and Multi-User Scheduling in Transmissive RIS Enabled Distributed Cooperative ISAC Networks with RSMA	In this paper, we propose a novel transmissive reconfigurable intelligent surface (TRIS) transceiver-empowered distributed cooperative integrated sensing and communication (ISAC) network to enhance coverage as well as to enhance wireless environment understanding. Based on the network requirements, the users are catego...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	508,873
1911.03749	A Characterization of All Passivizing Input-Output Transformations of a Passive-Short System	Passivity theory is one of the cornerstones of control theory, as it allows one to prove stability of a large-scale system while treating each component separately. In practice, many systems are not passive, and must be passivized in order to be included in the framework of passivity theory. Input-output transformation...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	152,744
1503.06242	Modeling and Analysis of Energy Efficiency and Interference for Cellular Relay Deployment	By relying on a wireless backhaul link, relay stations enhance the performance of cellular networks at low infrastructure cost, but at the same time, they can aggravate the interference issue. In this paper, we analyze for several relay coding schemes the maximum energy gain provided by a relay, taking into account the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,319
1407.7590	Feedback through Overhearing	In this paper we examine the value of feedback that comes from overhearing, without dedicated feedback resources. We focus on a simple model for this purpose: a deterministic two-hop interference channel, where feedback comes from overhearing the forward-links. A new aspect brought by this setup is the dual-role of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,964
2402.03522	Influencer Identification on Link Predicted Graphs	How would admissions look like in a it university program for influencers? In the realm of social network analysis, influence maximization and link prediction stand out as pivotal challenges. Influence maximization focuses on identifying a set of key nodes to maximize information dissemination, while link prediction ai...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	427,050
2309.07293	GAN-based Algorithm for Efficient Image Inpainting	Global pandemic due to the spread of COVID-19 has post challenges in a new dimension on facial recognition, where people start to wear masks. Under such condition, the authors consider utilizing machine learning in image inpainting to tackle the problem, by complete the possible face that is originally covered in mask....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,727
2408.13566	Control-Informed Reinforcement Learning for Chemical Processes	This work proposes a control-informed reinforcement learning (CIRL) framework that integrates proportional-integral-derivative (PID) control components into the architecture of deep reinforcement learning (RL) policies. The proposed approach augments deep RL agents with a PID controller layer, incorporating prior knowl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	483,193
2304.08847	BadVFL: Backdoor Attacks in Vertical Federated Learning	Federated learning (FL) enables multiple parties to collaboratively train a machine learning model without sharing their data; rather, they train their own model locally and send updates to a central server for aggregation. Depending on how the data is distributed among the participants, FL can be classified into Horiz...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	358,842
2211.04449	Fairness-aware Regression Robust to Adversarial Attacks	In this paper, we take a first step towards answering the question of how to design fair machine learning algorithms that are robust to adversarial attacks. Using a minimax framework, we aim to design an adversarially robust fair regression model that achieves optimal performance in the presence of an attacker who is a...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	329,250

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