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
1811.12019	Large-Scale Distributed Second-Order Optimization Using Kronecker-Factored Approximate Curvature for Deep Convolutional Neural Networks	Large-scale distributed training of deep neural networks suffer from the generalization gap caused by the increase in the effective mini-batch size. Previous approaches try to solve this problem by varying the learning rate and batch size over epochs and layers, or some ad hoc modification of the batch normalization. W...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	114,914
2105.04817	Fibrational Initial Algebra-Final Coalgebra Coincidence over Initial Algebras: Turning Verification Witnesses Upside Down	The coincidence between initial algebras (IAs) and final coalgebras (FCs) is a phenomenon that underpins various important results in theoretical computer science. In this paper, we identify a general fibrational condition for the IA-FC coincidence, namely in the fiber over an initial algebra in the base category. Iden...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	234,627
2502.10443	One Class Restricted Kernel Machines	Restricted kernel machines (RKMs) have demonstrated a significant impact in enhancing generalization ability in the field of machine learning. Recent studies have introduced various methods within the RKM framework, combining kernel functions with the least squares support vector machine (LSSVM) in a manner similar to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	533,884
2501.06224	Detection, Retrieval, and Explanation Unified: A Violence Detection System Based on Knowledge Graphs and GAT	Recently, violence detection systems developed using unified multimodal models have achieved significant success and attracted widespread attention. However, most of these systems face two critical challenges: the lack of interpretability as black-box models and limited functionality, offering only classification or re...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	523,886
2312.12476	DSAF: A Dual-Stage Adaptive Framework for Numerical Weather Prediction Downscaling	While widely recognized as one of the most substantial weather forecasting methodologies, Numerical Weather Prediction (NWP) usually suffers from relatively coarse resolution and inevitable bias due to tempo-spatial discretization, physical parametrization process, and computation limitation. With the roaring growth of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,978
2404.11613	InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Prior	3D Gaussians have recently emerged as an efficient representation for novel view synthesis. This work studies its editability with a particular focus on the inpainting task, which aims to supplement an incomplete set of 3D Gaussians with additional points for visually harmonious rendering. Compared to 2D inpainting, th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	447,557
1812.10235	A Bi-model based RNN Semantic Frame Parsing Model for Intent Detection and Slot Filling	Intent detection and slot filling are two main tasks for building a spoken language understanding(SLU) system. Multiple deep learning based models have demonstrated good results on these tasks . The most effective algorithms are based on the structures of sequence to sequence models (or "encoder-decoder" models), and g...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	117,322
1802.00750	Optimal probabilistic polynomial time compression and the Slepian-Wolf theorem: tighter version and simple proofs	We give simplify the proofs of the 2 results in Marius Zimand's paper "Kolmogorov complexity version of Slepian-Wolf coding, proceedings of STOC 2017, p22--32". The first is a universal polynomial time compression algorithm: on input $\varepsilon > 0$, a number $k$ and a string $x$ it computes in polynomial time with p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89,464
2202.11838	Explanatory Paradigms in Neural Networks	In this article, we present a leap-forward expansion to the study of explainability in neural networks by considering explanations as answers to abstract reasoning-based questions. With $P$ as the prediction from a neural network, these questions are `Why P?', `What if not P?', and `Why P, rather than Q?' for a given c...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	282,017
1909.05159	On-line collision avoidance for collaborative robot manipulators by adjusting off-line generated paths: An industrial use case	Human-robot collision avoidance is a key in collaborative robotics and in the framework of Industry 4.0. It plays an important role for achieving safety criteria while having humans and machines working side-by-side in unstructured and time-varying environment. This study introduces the subject of manipulator's on-line...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	145,016
2307.02932	When No-Rejection Learning is Consistent for Regression with Rejection	Learning with rejection has been a prototypical model for studying the human-AI interaction on prediction tasks. Upon the arrival of a sample instance, the model first uses a rejector to decide whether to accept and use the AI predictor to make a prediction or reject and defer the sample to humans. Learning such a mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	377,869
2009.02285	Flow Field Reconstructions with GANs based on Radial Basis Functions	Nonlinear sparse data regression and generation have been a long-term challenge, to cite the flow field reconstruction as a typical example. The huge computational cost of computational fluid dynamics (CFD) makes it much expensive for large scale CFD data producing, which is the reason why we need some cheaper ways to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	194,509
2412.09240	VLMs meet UDA: Boosting Transferability of Open Vocabulary Segmentation with Unsupervised Domain Adaptation	Segmentation models are typically constrained by the categories defined during training. To address this, researchers have explored two independent approaches: adapting Vision-Language Models (VLMs) and leveraging synthetic data. However, VLMs often struggle with granularity, failing to disentangle fine-grained concept...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	516,409
1210.2646	A General Methodology for the Determination of 2D Bodies Elastic Deformation Invariants. Application to the Automatic Identification of Parasites	A novel methodology is introduced here that exploits 2D images of arbitrary elastic body deformation instances, so as to quantify mechano-elastic characteristics that are deformation invariant. Determination of such characteristics allows for developing methods offering an image of the undeformed body. General assumpti...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	19,033
2403.16188	Cross-domain Multi-modal Few-shot Object Detection via Rich Text	Cross-modal feature extraction and integration have led to steady performance improvements in few-shot learning tasks due to generating richer features. However, existing multi-modal object detection (MM-OD) methods degrade when facing significant domain-shift and are sample insufficient. We hypothesize that rich text ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,917
1812.09809	Writer-Aware CNN for Parsimonious HMM-Based Offline Handwritten Chinese Text Recognition	Recently, the hybrid convolutional neural network hidden Markov model (CNN-HMM) has been introduced for offline handwritten Chinese text recognition (HCTR) and has achieved state-of-the-art performance. However, modeling each of the large vocabulary of Chinese characters with a uniform and fixed number of hidden states...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,235
2501.00289	Dual Diffusion for Unified Image Generation and Understanding	Diffusion models have gained tremendous success in text-to-image generation, yet still lag behind with visual understanding tasks, an area dominated by autoregressive vision-language models. We propose a large-scale and fully end-to-end diffusion model for multi-modal understanding and generation that significantly imp...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	521,608
2402.13108	On the Convergence of Gradient Descent for Large Learning Rates	A vast literature on convergence guarantees for gradient descent and derived methods exists at the moment. However, a simple practical situation remains unexplored: when a fixed step size is used, can we expect gradient descent to converge starting from any initialization? We provide fundamental impossibility results s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	431,116
1702.00716	Analysing Temporal Evolution of Interlingual Wikipedia Article Pairs	Wikipedia articles representing an entity or a topic in different language editions evolve independently within the scope of the language-specific user communities. This can lead to different points of views reflected in the articles, as well as complementary and inconsistent information. An analysis of how the informa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	67,695
1912.03366	Med2Meta: Learning Representations of Medical Concepts with Meta-Embeddings	Distributed representations of medical concepts have been used to support downstream clinical tasks recently. Electronic Health Records (EHR) capture different aspects of patients' hospital encounters and serve as a rich source for augmenting clinical decision making by learning robust medical concept embeddings. Howev...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	156,570
1709.01562	Optimizing for Measure of Performance in Max-Margin Parsing	Many statistical learning problems in the area of natural language processing including sequence tagging, sequence segmentation and syntactic parsing has been successfully approached by means of structured prediction methods. An appealing property of the corresponding discriminative learning algorithms is their ability...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	80,102
2308.05646	AST-MHSA : Code Summarization using Multi-Head Self-Attention	Code summarization aims to generate concise natural language descriptions for source code. The prevailing approaches adopt transformer-based encoder-decoder architectures, where the Abstract Syntax Tree (AST) of the source code is utilized for encoding structural information. However, ASTs are much longer than the corr...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	384,865
1804.05459	Comparative study of motion detection methods for video surveillance systems	The objective of this study is to compare several change detection methods for a mono static camera and identify the best method for different complex environments and backgrounds in indoor and outdoor scenes. To this end, we used the CDnet video dataset as a benchmark that consists of many challenging problems, rangin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,081
2405.13957	Exploring the Relationship Between Feature Attribution Methods and Model Performance	Machine learning and deep learning models are pivotal in educational contexts, particularly in predicting student success. Despite their widespread application, a significant gap persists in comprehending the factors influencing these models' predictions, especially in explainability within education. This work address...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,162
2107.02474	Viscos Flows: Variational Schur Conditional Sampling With Normalizing Flows	We present a method for conditional sampling for pre-trained normalizing flows when only part of an observation is available. We derive a lower bound to the conditioning variable log-probability using Schur complement properties in the spirit of Gaussian conditional sampling. Our derivation relies on partitioning flow'...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	244,839
2206.02536	The impact of spatio-temporal travel distance on epidemics using an interpretable attention-based sequence-to-sequence model	Amidst the COVID-19 pandemic, travel restrictions have emerged as crucial interventions for mitigating the spread of the virus. In this study, we enhance the predictive capabilities of our model, Sequence-to-Sequence Epidemic Attention Network (S2SEA-Net), by incorporating an attention module, allowing us to assess the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	300,931
2407.16388	Anwendung von Causal-Discovery-Algorithmen zur Root-Cause-Analyse in der Fahrzeugmontage	Root Cause Analysis (RCA) is a quality management method that aims to systematically investigate and identify the cause-and-effect relationships of problems and their underlying causes. Traditional methods are based on the analysis of problems by subject matter experts. In modern production processes, large amounts of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	475,584
2404.00358	Spread Your Wings: A Radial Strip Transformer for Image Deblurring	Exploring motion information is important for the motion deblurring task. Recent the window-based transformer approaches have achieved decent performance in image deblurring. Note that the motion causing blurry results is usually composed of translation and rotation movements and the window-shift operation in the Carte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,882
1604.07928	Distributed Flexible Nonlinear Tensor Factorization	Tensor factorization is a powerful tool to analyse multi-way data. Compared with traditional multi-linear methods, nonlinear tensor factorization models are capable of capturing more complex relationships in the data. However, they are computationally expensive and may suffer severe learning bias in case of extreme dat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	55,147
2312.09773	In vivo learning-based control of microbial populations density in bioreactors	A key problem toward the use of microorganisms as bio-factories is reaching and maintaining cellular communities at a desired density and composition so that they can efficiently convert their biomass into useful compounds. Promising technological platforms for the real time, scalable control of cellular density are bi...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	415,872
2105.00146	EntrapNet: a Blockchain-Based Verification Protocol for Trustless Computing	In this paper, we propose a blockchain-based computing verification protocol, called EntrapNet, for distributed shared computing networks, an emerging underlying network for many internet of things (IoT) applications. EntrapNet borrows the idea from the practice of entrapment in criminal law to reduce the possibility o...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	233,103
2110.08619	SAGAN: Adversarial Spatial-asymmetric Attention for Noisy Nona-Bayer Reconstruction	Nona-Bayer colour filter array (CFA) pattern is considered one of the most viable alternatives to traditional Bayer patterns. Despite the substantial advantages, such non-Bayer CFA patterns are susceptible to produce visual artefacts while reconstructing RGB images from noisy sensor data. This study addresses the chall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	261,486
1808.01363	GeneSys: Enabling Continuous Learning through Neural Network Evolution in Hardware	Modern deep learning systems rely on (a) a hand-tuned neural network topology, (b) massive amounts of labeled training data, and (c) extensive training over large-scale compute resources to build a system that can perform efficient image classification or speech recognition. Unfortunately, we are still far away from im...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	104,555
1907.00294	Generative Mask Pyramid Network for CT/CBCT Metal Artifact Reduction with Joint Projection-Sinogram Correction	A conventional approach to computed tomography (CT) or cone beam CT (CBCT) metal artifact reduction is to replace the X-ray projection data within the metal trace with synthesized data. However, existing projection or sinogram completion methods cannot always produce anatomically consistent information to fill the meta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,998
1401.2184	Variations on Memetic Algorithms for Graph Coloring Problems	Graph vertex coloring with a given number of colors is a well-known and much-studied NP-complete problem.The most effective methods to solve this problem are proved to be hybrid algorithms such as memetic algorithms or quantum annealing. Those hybrid algorithms use a powerful local search inside a population-based algo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	29,725
2302.08664	Socialz: Multi-Feature Social Fuzz Testing	Online social networks have become an integral aspect of our daily lives and play a crucial role in shaping our relationships with others. However, bugs and glitches, even minor ones, can cause anything from frustrating problems to serious data leaks that can have farreaching impacts on millions of users. To mitigate t...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	346,130
2502.08365	Towards Principled Multi-Agent Task Agnostic Exploration	In reinforcement learning, we typically refer to task-agnostic exploration when we aim to explore the environment without access to the task specification a priori. In a single-agent setting the problem has been extensively studied and mostly understood. A popular approach cast the task-agnostic objective as maximizing...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,994
2109.10642	Decentralized Learning of Tree-Structured Gaussian Graphical Models from Noisy Data	This paper studies the decentralized learning of tree-structured Gaussian graphical models (GGMs) from noisy data. In decentralized learning, data set is distributed across different machines (sensors), and GGMs are widely used to model complex networks such as gene regulatory networks and social networks. The proposed...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	256,695
1701.04931	Characterizing Linguistic Attributes for Automatic Classification of Intent Based Racist/Radicalized Posts on Tumblr Micro-Blogging Website	Research shows that many like-minded people use popular microblogging websites for posting hateful speech against various religions and race. Automatic identification of racist and hate promoting posts is required for building social media intelligence and security informatics based solutions. However, just keyword spo...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	66,912
1701.07254	Cascaded Incremental Nonlinear Dynamic Inversion Control for MAV Disturbance Rejection	Micro Aerial Vehicles (MAVs) are limited in their operation outdoors near obstacles by their ability to withstand wind gusts. Currently widespread position control methods such as Proportional Integral Derivative control do not perform well under the influence of gusts. Incremental Nonlinear Dynamic Inversion (INDI) is...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	67,260
0905.3769	Multiset Ordering Constraints	We identify a new and important global (or non-binary) constraint. This constraint ensures that the values taken by two vectors of variables, when viewed as multisets, are ordered. This constraint is useful for a number of different applications including breaking symmetry and fuzzy constraint satisfaction. We propose ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	3,754
2306.02586	Internet of Things Meets Robotics: A Survey of Cloud-based Robots	This work presents a survey of existing literature on the fusion of the Internet of Things (IoT) with robotics and explores the integration of these technologies for the development of the Internet of Robotics Things (IoRT). The survey focuses on the applications of IoRT in healthcare and agriculture, while also addres...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	370,965
2401.11333	Error bounds of constant gain least-mean-squares algorithms	Constant gain least-mean-squares (LMS) algorithms have a wide range of applications in trajectory tracking problems, but the formal convergence of LMS in mean square is not yet fully established. This work provides an upper bound on the constant gain that guarantees a bounded mean-squared error of LMS for a general des...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	422,955
2005.08224	#Coronavirus or #Chinesevirus?!: Understanding the negative sentiment reflected in Tweets with racist hashtags across the development of COVID-19	Situated in the global outbreak of COVID-19, our study enriches the discussion concerning the emergent racism and xenophobia on social media. With big data extracted from Twitter, we focus on the analysis of negative sentiment reflected in tweets marked with racist hashtags, as racism and xenophobia are more likely to ...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	177,558
2409.00159	LLMs hallucinate graphs too: a structural perspective	It is known that LLMs do hallucinate, that is, they return incorrect information as facts. In this paper, we introduce the possibility to study these hallucinations under a structured form: graphs. Hallucinations in this context are incorrect outputs when prompted for well known graphs from the literature (e.g. Karate ...	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	484,814
2006.01402	A Smart Background Scheduler for Storage Systems	In today's enterprise storage systems, supported data services such as snapshot delete or drive rebuild can cause tremendous performance interference if executed inline along with heavy foreground IO, often leading to missing SLOs (Service Level Objectives). Typical storage system applications such as web or VDI (Virtu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	179,761
2209.07754	On the Robustness of Graph Neural Diffusion to Topology Perturbations	Neural diffusion on graphs is a novel class of graph neural networks that has attracted increasing attention recently. The capability of graph neural partial differential equations (PDEs) in addressing common hurdles of graph neural networks (GNNs), such as the problems of over-smoothing and bottlenecks, has been inves...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	317,875
1909.02214	Auxiliary Learning for Deep Multi-task Learning	Multi-task learning (MTL) is an efficient solution to solve multiple tasks simultaneously in order to get better speed and performance than handling each single-task in turn. The most current methods can be categorized as either: (i) hard parameter sharing where a subset of the parameters is shared among tasks while ot...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	144,129
1711.09670	Improving OCR Accuracy on Early Printed Books by utilizing Cross Fold Training and Voting	In this paper we introduce a method that significantly reduces the character error rates for OCR text obtained from OCRopus models trained on early printed books. The method uses a combination of cross fold training and confidence based voting. After allocating the available ground truth in different subsets several tr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,457
1304.0419	Top-K Product Design Based on Collaborative Tagging Data	The widespread use and popularity of collaborative content sites (e.g., IMDB, Amazon, Yelp, etc.) has created rich resources for users to consult in order to make purchasing decisions on various products such as movies, e-commerce products, restaurants, etc. Products with desirable tags (e.g., modern, reliable, etc.) h...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	true	23,387
2007.15850	Resist : Reconstruction of irises from templates	Iris recognition systems transform an iris image into a feature vector. The seminal pipeline segments an image into iris and non-iris pixels, normalizes this region into a fixed-dimension rectangle, and extracts features which are stored and called a template (Daugman, 2009). This template is stored on a system. A futu...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	189,784
2101.11560	Wisdom of the Contexts: Active Ensemble Learning for Contextual Anomaly Detection	In contextual anomaly detection, an object is only considered anomalous within a specific context. Most existing methods for CAD use a single context based on a set of user-specified contextual features. However, identifying the right context can be very challenging in practice, especially in datasets, with a large num...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	217,322
1606.09560	Neural Network-based Word Alignment through Score Aggregation	We present a simple neural network for word alignment that builds source and target word window representations to compute alignment scores for sentence pairs. To enable unsupervised training, we use an aggregation operation that summarizes the alignment scores for a given target word. A soft-margin objective increases...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	58,005
2405.00973	Active Cell Balancing for Extended Operational Time of Lithium-Ion Battery Systems in Energy Storage Applications	Cell inconsistency within a lithium-ion battery system poses a significant challenge in maximizing the system operational time. This study presents an optimization-driven active balancing method to minimize the effects of cell inconsistency on the system operational time while simultaneously satisfying the system outpu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	451,157
2302.04453	Data Quality-aware Mixed-precision Quantization via Hybrid Reinforcement Learning	Mixed-precision quantization mostly predetermines the model bit-width settings before actual training due to the non-differential bit-width sampling process, obtaining sub-optimal performance. Worse still, the conventional static quality-consistent training setting, i.e., all data is assumed to be of the same quality a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	344,710
2308.12960	Towards Realistic Zero-Shot Classification via Self Structural Semantic Alignment	Large-scale pre-trained Vision Language Models (VLMs) have proven effective for zero-shot classification. Despite the success, most traditional VLMs-based methods are restricted by the assumption of partial source supervision or ideal vocabularies, which rarely satisfy the open-world scenario. In this paper, we aim at ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,732
2410.11718	Converging to a Lingua Franca: Evolution of Linguistic Regions and Semantics Alignment in Multilingual Large Language Models	Large language models (LLMs) have demonstrated remarkable performance, particularly in multilingual contexts. While recent studies suggest that LLMs can transfer skills learned in one language to others, the internal mechanisms behind this ability remain unclear. We observed that the neuron activation patterns of LLMs ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	498,685
2305.04114	Memory CODA: introducing memory effects in the Continuous Opinions and Discrete Actions model	The Continuous Opinions and Discrete Actions (CODA) model has been widely used to study the emergence of extremism in social networks. However, this standard model has been shown to generate unrealistic extreme opinions due to the reinforcement among agents. To address this issue, this paper introduces memory effects i...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	362,644
2007.09371	Tighter Generalization Bounds for Iterative Differentially Private Learning Algorithms	This paper studies the relationship between generalization and privacy preservation in iterative learning algorithms by two sequential steps. We first establish an alignment between generalization and privacy preservation for any learning algorithm. We prove that $(\varepsilon, \delta)$-differential privacy implies an ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	187,921
2207.01233	Domain Adaptive Nuclei Instance Segmentation and Classification via Category-aware Feature Alignment and Pseudo-labelling	Unsupervised domain adaptation (UDA) methods have been broadly utilized to improve the models' adaptation ability in general computer vision. However, different from the natural images, there exist huge semantic gaps for the nuclei from different categories in histopathology images. It is still under-explored how could...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,094
2212.13876	xFBD: Focused Building Damage Dataset and Analysis	The xView2 competition and xBD dataset spurred significant advancements in overhead building damage detection, but the competition's pixel level scoring can lead to reduced solution performance in areas with tight clusters of buildings or uninformative context. We seek to advance automatic building damage assessment fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	338,416
2411.08583	An Empirical Examination of the Evaluative AI Framework	This study empirically examines the "Evaluative AI" framework, which aims to enhance the decision-making process for AI users by transitioning from a recommendation-based approach to a hypothesis-driven one. Rather than offering direct recommendations, this framework presents users pro and con evidence for hypotheses t...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	507,942
2006.01644	Learning Efficient Representations of Mouse Movements to Predict User Attention	Tracking mouse cursor movements can be used to predict user attention on heterogeneous page layouts like SERPs. So far, previous work has relied heavily on handcrafted features, which is a time-consuming approach that often requires domain expertise. We investigate different representations of mouse cursor movements, i...	true	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	179,830
1901.10469	Automated Prototype for Asteroids Detection	Near Earth Asteroids (NEAs) are discovered daily, mainly by few major surveys, nevertheless many of them remain unobserved for years, even decades. Even so, there is room for new discoveries, including those submitted by smaller projects and amateur astronomers. Besides the well-known surveys that have their own automa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	120,029
1903.06708	Live Reconstruction of Large-Scale Dynamic Outdoor Worlds	Standard 3D reconstruction pipelines assume stationary world, therefore suffer from `ghost artifacts' whenever dynamic objects are present in the scene. Recent approaches has started tackling this issue, however, they typically either only discard dynamic information, represent it using bounding boxes or per-frame dept...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	124,447
2204.10979	Smoothed Online Combinatorial Optimization Using Imperfect Predictions	Smoothed online combinatorial optimization considers a learner who repeatedly chooses a combinatorial decision to minimize an unknown changing cost function with a penalty on switching decisions in consecutive rounds. We study smoothed online combinatorial optimization problems when an imperfect predictive model is ava...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	292,985
1707.08279	A General and Yet Efficient Scheme for Sub-Nyquist Radar Processing	We study the target parameter estimation for sub-Nyquist pulse-Doppler radar. Several past works have addressed this problem but either have low estimation accuracy for off-grid targets, take large computation load, or lack versatility for analog-to-information conversion (AIC) systems. To overcome these difficulties, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	77,794
2108.13382	Exploring Multi-Tasking Learning in Document Attribute Classification	In this work, we adhere to explore a Multi-Tasking learning (MTL) based network to perform document attribute classification such as the font type, font size, font emphasis and scanning resolution classification of a document image. To accomplish these tasks, we operate on either segmented word level or on uniformed si...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,791
1711.02549	Remote Sensing Image Fusion Based on Two-stream Fusion Network	Remote sensing image fusion (also known as pan-sharpening) aims at generating high resolution multi-spectral (MS) image from inputs of a high spatial resolution single band panchromatic (PAN) image and a low spatial resolution multi-spectral image. Inspired by the astounding achievements of convolutional neural network...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,080
2311.07888	RoboSense At Edge: Detecting Slip, Crumple and Shape of the Object in Robotic Hand for Teleoprations	Slip and crumple detection is essential for performing robust manipulation tasks with a robotic hand (RH) like remote surgery. It has been one of the challenging problems in the robotics manipulation community. In this work, we propose a technique based on machine learning (ML) based techniques to detect the slip, and ...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	407,507
2407.05557	$R^2$-Guard: Robust Reasoning Enabled LLM Guardrail via Knowledge-Enhanced Logical Reasoning	As LLMs become increasingly prevalent across various applications, it is critical to establish safety guardrails to moderate input/output content of LLMs. Existing guardrail models treat various safety categories independently and fail to explicitly capture the intercorrelations among them. This has led to limitations ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	471,027
2407.04638	Semi-Supervised Segmentation via Embedding Matching	Deep convolutional neural networks are widely used in medical image segmentation but require many labeled images for training. Annotating three-dimensional medical images is a time-consuming and costly process. To overcome this limitation, we propose a novel semi-supervised segmentation method that leverages mostly unl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,641
2007.00622	A Multi-spectral Dataset for Evaluating Motion Estimation Systems	Visible images have been widely used for motion estimation. Thermal images, in contrast, are more challenging to be used in motion estimation since they typically have lower resolution, less texture, and more noise. In this paper, a novel dataset for evaluating the performance of multi-spectral motion estimation system...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	185,165
1703.05671	Upper bounds for the Holevo quantity and their use	We present a family of easily computable upper bounds for the Holevo quantity of ensemble of quantum states depending on a reference state as a free parameter. These upper bounds are obtained by combining probabilistic and metric characteristics of the ensemble. We show that appropriate choice of the reference state gi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	70,119
2312.08650	PhyOT: Physics-informed object tracking in surveillance cameras	While deep learning has been very successful in computer vision, real world operating conditions such as lighting variation, background clutter, or occlusion hinder its accuracy across several tasks. Prior work has shown that hybrid models -- combining neural networks and heuristics/algorithms -- can outperform vanilla...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,384
2005.03180	Model Reduction and Neural Networks for Parametric PDEs	We develop a general framework for data-driven approximation of input-output maps between infinite-dimensional spaces. The proposed approach is motivated by the recent successes of neural networks and deep learning, in combination with ideas from model reduction. This combination results in a neural network approximati...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	176,072
1309.0781	An Exploratory Data Survey of Drug Name Incidence and Prevalence From the FDA's Adverse Event Reporting System, 2004 to 2012Q2	Drug Names, Population Level Surveillance and the FDA's Adverse Event Reporting System: An Exploratory Data Survey of Drug Name Incidence and Prevalence, 2004-2012Q2 Purpose: To count and monitor the drug names reported in the publicly available version of the Federal Adverse Event Reporting System (FAERS) from 2004 to...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	26,806
2405.01761	Multivariate Bayesian Last Layer for Regression: Uncertainty Quantification and Disentanglement	We present new Bayesian Last Layer models in the setting of multivariate regression under heteroscedastic noise, and propose an optimization algorithm for parameter learning. Bayesian Last Layer combines Bayesian modelling of the predictive distribution with neural networks for parameterization of the prior, and has th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,495
1910.01588	Probabilistic Robust Small-Signal Stability Framework using Gaussian Process Learning	While most power system small-signal stability assessments rely on the reduced Jacobian, which depends non-linearly on the states, uncertain operating points introduce nontrivial hurdles in certifying the system's stability. In this paper, a novel probabilistic robust small-signal stability (PRS) framework is developed...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	147,977
2008.06319	OR-Gym: A Reinforcement Learning Library for Operations Research Problems	Reinforcement learning (RL) has been widely applied to game-playing and surpassed the best human-level performance in many domains, yet there are few use-cases in industrial or commercial settings. We introduce OR-Gym, an open-source library for developing reinforcement learning algorithms to address operations researc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	191,775
1103.1255	A General Framework for Representing, Reasoning and Querying with Annotated Semantic Web Data	We describe a generic framework for representing and reasoning with annotated Semantic Web data, a task becoming more important with the recent increased amount of inconsistent and non-reliable meta-data on the web. We formalise the annotated language, the corresponding deductive system and address the query answering ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	9,503
1703.02223	Opinion diversity and community formation in adaptive networks	It is interesting and of significant importance to investigate how network structures co-evolve with opinions. The existing models of such co-evolution typically lead to the final states where network nodes either reach a global consensus or break into separated communities, each of which holding its own community cons...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	69,519
1811.04076	AttS2S-VC: Sequence-to-Sequence Voice Conversion with Attention and Context Preservation Mechanisms	This paper describes a method based on a sequence-to-sequence learning (Seq2Seq) with attention and context preservation mechanism for voice conversion (VC) tasks. Seq2Seq has been outstanding at numerous tasks involving sequence modeling such as speech synthesis and recognition, machine translation, and image captioni...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,990
2210.03120	GBSVM: Granular-ball Support Vector Machine	GBSVM (Granular-ball Support Vector Machine) is a significant attempt to construct a classifier using the coarse-to-fine granularity of a granular-ball as input, rather than a single data point. It is the first classifier whose input contains no points. However, the existing model has some errors, and its dual model ha...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	321,909
2312.16599	Relationship between auditory and semantic entrainment using Deep Neural Networks (DNN)	The tendency of people to engage in similar, matching, or synchronized behaviour when interacting is known as entrainment. Many studies examined linguistic (syntactic and lexical structures) and paralinguistic (pitch, intensity) entrainment, but less attention was given to finding the relationship between them. In this...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	418,443
2112.00202	3DVNet: Multi-View Depth Prediction and Volumetric Refinement	We present 3DVNet, a novel multi-view stereo (MVS) depth-prediction method that combines the advantages of previous depth-based and volumetric MVS approaches. Our key idea is the use of a 3D scene-modeling network that iteratively updates a set of coarse depth predictions, resulting in highly accurate predictions which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,054
1903.01454	Making the Dynamic Time Warping Distance Warping-Invariant	The literature postulates that the dynamic time warping (dtw) distance can cope with temporal variations but stores and processes time series in a form as if the dtw-distance cannot cope with such variations. To address this inconsistency, we first show that the dtw-distance is not warping-invariant. The lack of warpin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,257
2407.06109	PerLDiff: Controllable Street View Synthesis Using Perspective-Layout Diffusion Models	Controllable generation is considered a potentially vital approach to address the challenge of annotating 3D data, and the precision of such controllable generation becomes particularly imperative in the context of data production for autonomous driving. Existing methods focus on the integration of diverse generative i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,256
2405.05049	Seeds of Stereotypes: A Large-Scale Textual Analysis of Race and Gender Associations with Diseases in Online Sources	Background Advancements in Large Language Models (LLMs) hold transformative potential in healthcare, however, recent work has raised concern about the tendency of these models to produce outputs that display racial or gender biases. Although training data is a likely source of such biases, exploration of disease and de...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	452,776
1805.06660	Single Shot Active Learning using Pseudo Annotators	Standard myopic active learning assumes that human annotations are always obtainable whenever new samples are selected. This, however, is unrealistic in many real-world applications where human experts are not readily available at all times. In this paper, we consider the single shot setting: all the required samples s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	97,661
2006.08052	Autofocused oracles for model-based design	Data-driven design is making headway into a number of application areas, including protein, small-molecule, and materials engineering. The design goal is to construct an object with desired properties, such as a protein that binds to a therapeutic target, or a superconducting material with a higher critical temperature...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,051
2011.13284	A question-answering system for aircraft pilots' documentation	The aerospace industry relies on massive collections of complex and technical documents covering system descriptions, manuals or procedures. This paper presents a question answering (QA) system that would help aircraft pilots access information in this documentation by naturally interacting with the system and asking q...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	208,432
2412.15386	Systematic Evaluation of Long-Context LLMs on Financial Concepts	Long-context large language models (LC LLMs) promise to increase reliability of LLMs in real-world tasks requiring processing and understanding of long input documents. However, this ability of LC LLMs to reliably utilize their growing context windows remains under investigation. In this work, we evaluate the performan...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	519,089
2409.13305	Model Predictive Control For Multiple Castaway Tracking with an Autonomous Aerial Agent	Over the past few years, a plethora of advancements in Unmanned Areal Vehicle (UAV) technology has paved the way for UAV-based search and rescue operations with transformative impact to the outcome of critical life-saving missions. This paper dives into the challenging task of multiple castaway tracking using an autono...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	489,934
2404.06220	Zero-Shot Relational Learning for Multimodal Knowledge Graphs	Relational learning is an essential task in the domain of knowledge representation, particularly in knowledge graph completion (KGC). While relational learning in traditional single-modal settings has been extensively studied, exploring it within a multimodal KGC context presents distinct challenges and opportunities. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	445,377
2109.04200	Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation	With the prevalence of social media, there has recently been a proliferation of recommenders that shift their focus from individual modeling to group recommendation. Since the group preference is a mixture of various predilections from group members, the fundamental challenge of group recommendation is to model the cor...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	254,311
1609.05043	Linear representations of convolutional codes over rings	In this paper we extend the relation between convolutional codes and linear systems over finite fields to certain commutative rings through first order representations . We introduce the definition of rings with representations as those for which these representations always exist, and we show that finite products of f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	61,063
1910.04210	Perturbation Sensitivity Analysis to Detect Unintended Model Biases	Data-driven statistical Natural Language Processing (NLP) techniques leverage large amounts of language data to build models that can understand language. However, most language data reflect the public discourse at the time the data was produced, and hence NLP models are susceptible to learning incidental associations ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	148,702
2306.04849	ScaleDet: A Scalable Multi-Dataset Object Detector	Multi-dataset training provides a viable solution for exploiting heterogeneous large-scale datasets without extra annotation cost. In this work, we propose a scalable multi-dataset detector (ScaleDet) that can scale up its generalization across datasets when increasing the number of training datasets. Unlike existing m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	371,931
1501.03569	On the Capacity of Symmetric Gaussian Interference Channels with Feedback	In this paper, we propose a new coding scheme for symmetric Gaussian interference channels with feedback based on the ideas of time-varying coding schemes. The proposed scheme improves the Suh-Tse and Kramer inner bounds of the channel capacity for the cases of weak and not very strong interference. This improvement is...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,279

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