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
2308.14486	Rebalancing Social Feed to Minimize Polarization and Disagreement	Social media have great potential for enabling public discourse on important societal issues. However, adverse effects, such as polarization and echo chambers, greatly impact the benefits of social media and call for algorithms that mitigate these effects. In this paper, we propose a novel problem formulation aimed at ...	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	false	388,349
2308.10724	Global visibility of publications through Digital Object Identifiers	This brief research report analyzes the availability of Digital Object Identifiers (DOIs) worldwide, highlighting the dominance of large publishing houses and the need for unique persistent identifiers to increase the visibility of publications from developing countries. The study reveals that a considerable amount of ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	386,858
2409.18572	Towards an active-learning approach to resource allocation for population-based damage prognosis	Damage prognosis is, arguably, one of the most difficult tasks of structural health monitoring (SHM). To address common problems of damage prognosis, a population-based SHM (PBSHM) approach is adopted in the current work. In this approach the prognosis problem is considered as an information-sharing problem where data ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	492,313
2212.11558	DaDe: Delay-adaptive Detector for Streaming Perception	Recognizing the surrounding environment at low latency is critical in autonomous driving. In real-time environment, surrounding environment changes when processing is over. Current detection models are incapable of dealing with changes in the environment that occur after processing. Streaming perception is proposed to ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	337,827
2402.17194	The Random Forest Model for Analyzing and Forecasting the US Stock Market in the Context of Smart Finance	The stock market is a crucial component of the financial market, playing a vital role in wealth accumulation for investors, financing costs for listed companies, and the stable development of the national macroeconomy. Significant fluctuations in the stock market can damage the interests of stock investors and cause an...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	432,882
2104.11892	A Survey of Modern Deep Learning based Object Detection Models	Object Detection is the task of classification and localization of objects in an image or video. It has gained prominence in recent years due to its widespread applications. This article surveys recent developments in deep learning based object detectors. Concise overview of benchmark datasets and evaluation metrics us...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	232,050
1910.00033	Hidden Trigger Backdoor Attacks	With the success of deep learning algorithms in various domains, studying adversarial attacks to secure deep models in real world applications has become an important research topic. Backdoor attacks are a form of adversarial attacks on deep networks where the attacker provides poisoned data to the victim to train the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	147,550
2202.13804	RestainNet: a self-supervised digital re-stainer for stain normalization	Color inconsistency is an inevitable challenge in computational pathology, which generally happens because of stain intensity variations or sections scanned by different scanners. It harms the pathological image analysis methods, especially the learning-based models. A series of approaches have been proposed for stain ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,753
2305.05915	A synchronization-capturing multi-scale solver to the noisy integrate-and-fire neuron networks	The noisy leaky integrate-and-fire (NLIF) model describes the voltage configurations of neuron networks with an interacting many-particles system at a microscopic level. When simulating neuron networks of large sizes, computing a coarse-grained mean-field Fokker-Planck equation solving the voltage densities of the netw...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	363,339
1711.03896	A Geometric Characterization of Observability in Inertial Parameter Identification	This paper presents an algorithm to geometrically characterize inertial parameter identifiability for an articulated robot. The geometric approach tests identifiability across the infinite space of configurations using only a finite set of conditions and without approximation. It can be applied to general open-chain ki...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	84,291
1202.3710	Strictly Proper Mechanisms with Cooperating Players	Prediction markets provide an efficient means to assess uncertain quantities from forecasters. Traditional and competitive strictly proper scoring rules have been shown to incentivize players to provide truthful probabilistic forecasts. However, we show that when those players can cooperate, these mechanisms can instea...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	14,382
1904.01301	Pragmatically Informative Text Generation	We improve the informativeness of models for conditional text generation using techniques from computational pragmatics. These techniques formulate language production as a game between speakers and listeners, in which a speaker should generate output text that a listener can use to correctly identify the original inpu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	126,108
1611.10094	The influence of the network topology on the agility of a supply chain	The right performance of a supply chain depends on the pattern of relationships among firms. Although there is not a general consensus among researchers yet, many studies point that scale-free topologies, where few highly related firms are combined with many low-related firms, assure the highest efficiency of a supply ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	64,772
2202.12451	Human-Centered Concept Explanations for Neural Networks	Understanding complex machine learning models such as deep neural networks with explanations is crucial in various applications. Many explanations stem from the model perspective, and may not necessarily effectively communicate why the model is making its predictions at the right level of abstraction. For example, prov...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	282,247
2309.05780	LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images	The retina is the only part of the human body in which blood vessels can be accessed non-invasively using imaging techniques such as digital fundus images (DFI). The spatial distribution of the retinal microvasculature may change with cardiovascular diseases and thus the eyes may be regarded as a window to our hearts. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,182
2206.07534	Optimal Synthesis of LTI Koopman Models for Nonlinear Systems with Inputs	A popular technique used to obtain linear representations of nonlinear systems is the so-called Koopman approach, where the nonlinear dynamics are lifted to a (possibly infinite dimensional) linear space through nonlinear functions called observables. In the lifted space, the dynamics are linear and represented by a so...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	302,775
2010.13018	Adversarial Robust Low Rank Matrix Estimation: Compressed Sensing and Matrix Completion	We consider robust low rank matrix estimation as a trace regression when outputs are contaminated by adversaries. The adversaries are allowed to add arbitrary values to arbitrary outputs. Such values can depend on any samples. We deal with matrix compressed sensing, including lasso as a partial problem, and matrix comp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,967
1704.04860	Caching Policy Optimization for D2D Communications by Learning User Preference	Cache-enabled device-to-device (D2D) communications can boost network throughput. By pre-downloading contents to local caches of users, the content requested by a user can be transmitted via D2D links by other users in proximity. Prior works optimize the caching policy at users with the knowledge of content popularity,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,907
1911.10298	CoverNet: Multimodal Behavior Prediction using Trajectory Sets	We present CoverNet, a new method for multimodal, probabilistic trajectory prediction for urban driving. Previous work has employed a variety of methods, including multimodal regression, occupancy maps, and 1-step stochastic policies. We instead frame the trajectory prediction problem as classification over a diverse s...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	154,782
2404.13679	GScream: Learning 3D Geometry and Feature Consistent Gaussian Splatting for Object Removal	This paper tackles the intricate challenge of object removal to update the radiance field using the 3D Gaussian Splatting. The main challenges of this task lie in the preservation of geometric consistency and the maintenance of texture coherence in the presence of the substantial discrete nature of Gaussian primitives....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,396
2004.14584	Out-of-the-box channel pruned networks	In the last decade convolutional neural networks have become gargantuan. Pre-trained models, when used as initializers are able to fine-tune ever larger networks on small datasets. Consequently, not all the convolutional features that these fine-tuned models detect are requisite for the end-task. Several works of chann...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	174,944
2106.14184	Memory Guided Road Detection	In self driving car applications, there is a requirement to predict the location of the lane given an input RGB front facing image. In this paper, we propose an architecture that allows us to increase the speed and robustness of road detection without a large hit in accuracy by introducing an underlying shared feature ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	243,322
2305.10434	Learning the Visualness of Text Using Large Vision-Language Models	Visual text evokes an image in a person's mind, while non-visual text fails to do so. A method to automatically detect visualness in text will enable text-to-image retrieval and generation models to augment text with relevant images. This is particularly challenging with long-form text as text-to-image generation and r...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	365,060
1404.3026	On the Ground Validation of Online Diagnosis with Twitter and Medical Records	Social media has been considered as a data source for tracking disease. However, most analyses are based on models that prioritize strong correlation with population-level disease rates over determining whether or not specific individual users are actually sick. Taking a different approach, we develop a novel system fo...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	32,265
2202.09374	Explaining, Evaluating and Enhancing Neural Networks' Learned Representations	Most efforts in interpretability in deep learning have focused on (1) extracting explanations of a specific downstream task in relation to the input features and (2) imposing constraints on the model, often at the expense of predictive performance. New advances in (unsupervised) representation learning and transfer lea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,173
2305.12073	GELU Activation Function in Deep Learning: A Comprehensive Mathematical Analysis and Performance	Selecting the most suitable activation function is a critical factor in the effectiveness of deep learning models, as it influences their learning capacity, stability, and computational efficiency. In recent years, the Gaussian Error Linear Unit (GELU) activation function has emerged as a dominant method, surpassing tr...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	365,821
2111.01203	One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search	Convolutional neural networks (CNNs) are used in numerous real-world applications such as vision-based autonomous driving and video content analysis. To run CNN inference on various target devices, hardware-aware neural architecture search (NAS) is crucial. A key requirement of efficient hardware-aware NAS is the fast ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	264,480
2101.00036	KART: Parameterization of Privacy Leakage Scenarios from Pre-trained Language Models	For the safe sharing pre-trained language models, no guidelines exist at present owing to the difficulty in estimating the upper bound of the risk of privacy leakage. One problem is that previous studies have assessed the risk for different real-world privacy leakage scenarios and attack methods, which reduces the port...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,942
1404.1872	Int\'egration des donn\'ees d'un lexique syntaxique dans un analyseur syntaxique probabiliste	This article reports the evaluation of the integration of data from a syntactic-semantic lexicon, the Lexicon-Grammar of French, into a syntactic parser. We show that by changing the set of labels for verbs and predicational nouns, we can improve the performance on French of a non-lexicalized probabilistic parser.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	32,154
2112.12321	Physics Constrained Flow Neural Network for Short-Timescale Predictions in Data Communications Networks	Machine learning is gaining growing momentum in various recent models for the dynamic analysis of information flows in data communications networks. These preliminary models often rely on off-the-shelf learning models to predict from historical statistics while disregarding the physics governing the generating behavior...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	272,933
1805.10611	Robust Hypothesis Testing Using Wasserstein Uncertainty Sets	We develop a novel computationally efficient and general framework for robust hypothesis testing. The new framework features a new way to construct uncertainty sets under the null and the alternative distributions, which are sets centered around the empirical distribution defined via Wasserstein metric, thus our approa...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	98,723
2310.16295	Instance-wise Linearization of Neural Network for Model Interpretation	Neural network have achieved remarkable successes in many scientific fields. However, the interpretability of the neural network model is still a major bottlenecks to deploy such technique into our daily life. The challenge can dive into the non-linear behavior of the neural network, which rises a critical question tha...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	402,662
1306.1511	SPATA: A Seeding and Patching Algorithm for Hybrid Transcriptome Assembly	Transcriptome assembly from RNA-Seq reads is an active area of bioinformatics research. The ever-declining cost and the increasing depth of RNA-Seq have provided unprecedented opportunities to better identify expressed transcripts. However, the nonlinear transcript structures and the ultra-high throughput of RNA-Seq re...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	25,053
1608.01059	Analyzing Linear Dynamical Systems: From Modeling to Coding and Learning	Encoding time-series with Linear Dynamical Systems (LDSs) leads to rich models with applications ranging from dynamical texture recognition to video segmentation to name a few. In this paper, we propose to represent LDSs with infinite-dimensional subspaces and derive an analytic solution to obtain stable LDSs. We then ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,379
2111.11112	Data Sensing and Offloading in Edge Computing Networks: TDMA or NOMA?	With the development of Internet-of-Things (IoT), we witness the explosive growth in the number of devices with sensing, computing, and communication capabilities, along with a large amount of raw data generated at the network edge. Mobile (multi-access) edge computing (MEC), acquiring and processing data at network ed...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	267,552
2301.13848	Benchmarking Large Language Models for News Summarization	Large language models (LLMs) have shown promise for automatic summarization but the reasons behind their successes are poorly understood. By conducting a human evaluation on ten LLMs across different pretraining methods, prompts, and model scales, we make two important observations. First, we find instruction tuning, a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	343,054
2408.07726	Graph neural network surrogate for strategic transport planning	As the complexities of urban environments continue to grow, the modelling of transportation systems become increasingly challenging. This paper explores the application of advanced Graph Neural Network (GNN) architectures as surrogate models for strategic transport planning. Building upon a prior work that laid the fou...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	480,703
2409.13513	Efficient and Discriminative Image Feature Extraction for Universal Image Retrieval	Current image retrieval systems often face domain specificity and generalization issues. This study aims to overcome these limitations by developing a computationally efficient training framework for a universal feature extractor that provides strong semantic image representations across various domains. To this end, w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	490,025
2302.06039	Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection	Unsupervised Domain Adaptive Object Detection (UDA-OD) uses unlabelled data to improve the reliability of robotic vision systems in open-world environments. Previous approaches to UDA-OD based on self-training have been effective in overcoming changes in the general appearance of images. However, shifts in a robot's de...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	345,266
1805.01369	Framewise approach in multimodal emotion recognition in OMG challenge	In this report we described our approach achieves $53\%$ of unweighted accuracy over $7$ emotions and $0.05$ and $0.09$ mean squared errors for arousal and valence in OMG emotion recognition challenge. Our results were obtained with ensemble of single modality models trained on voice and face data from video separately...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	96,646
2103.04941	InFillmore: Frame-Guided Language Generation with Bidirectional Context	We propose a structured extension to bidirectional-context conditional language generation, or "infilling," inspired by Frame Semantic theory (Fillmore, 1976). Guidance is provided through two approaches: (1) model fine-tuning, conditioning directly on observed symbolic frames, and (2) a novel extension to disjunctive ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	223,810
2502.13954	Latent Distribution Decoupling: A Probabilistic Framework for Uncertainty-Aware Multimodal Emotion Recognition	Multimodal multi-label emotion recognition (MMER) aims to identify the concurrent presence of multiple emotions in multimodal data. Existing studies primarily focus on improving fusion strategies and modeling modality-to-label dependencies. However, they often overlook the impact of \textbf{aleatoric uncertainty}, whic...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	535,590
1803.03503	Construction of neural networks for realization of localized deep learning	The subject of deep learning has recently attracted users of machine learning from various disciplines, including: medical diagnosis and bioinformatics, financial market analysis and online advertisement, speech and handwriting recognition, computer vision and natural language processing, time series forecasting, and s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	92,263
2311.18200	INarIG: Iterative Non-autoregressive Instruct Generation Model For Word-Level Auto Completion	Computer-aided translation (CAT) aims to enhance human translation efficiency and is still important in scenarios where machine translation cannot meet quality requirements. One fundamental task within this field is Word-Level Auto Completion (WLAC). WLAC predicts a target word given a source sentence, translation cont...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	411,597
2411.18630	Volume Rendering of Human Hand Anatomy	We study the design of transfer functions for volumetric rendering of magnetic resonance imaging (MRI) datasets of human hands. Human hands are anatomically complex, containing various organs within a limited space, which presents challenges for volumetric rendering. We focus on hand musculoskeletal organs because they...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	511,937
2403.11590	HSEmotion Team at the 6th ABAW Competition: Facial Expressions, Valence-Arousal and Emotion Intensity Prediction	This article presents our results for the sixth Affective Behavior Analysis in-the-wild (ABAW) competition. To improve the trustworthiness of facial analysis, we study the possibility of using pre-trained deep models that extract reliable emotional features without the need to fine-tune the neural networks for a downst...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,774
2502.13825	Mixup Regularization: A Probabilistic Perspective	In recent years, mixup regularization has gained popularity as an effective way to improve the generalization performance of deep learning models by training on convex combinations of training data. While many mixup variants have been explored, the proper adoption of the technique to conditional density estimation and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	535,534
1910.09358	A Decision-Theoretic Approach for Model Interpretability in Bayesian Framework	A salient approach to interpretable machine learning is to restrict modeling to simple models. In the Bayesian framework, this can be pursued by restricting the model structure and prior to favor interpretable models. Fundamentally, however, interpretability is about users' preferences, not the data generation mechanis...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	150,168
2310.15670	Leveraging Vision-Centric Multi-Modal Expertise for 3D Object Detection	Current research is primarily dedicated to advancing the accuracy of camera-only 3D object detectors (apprentice) through the knowledge transferred from LiDAR- or multi-modal-based counterparts (expert). However, the presence of the domain gap between LiDAR and camera features, coupled with the inherent incompatibility...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	402,400
1910.07521	End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation	Kidney tumor segmentation emerges as a new frontier of computer vision in medical imaging. This is partly due to its challenging manual annotation and great medical impact. Within the scope of the Kidney Tumor Segmentation Challenge 2019, that is aiming at combined kidney and tumor segmentation, this work proposes a no...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,646
1807.05670	Wireless Powered Communication Networks: TDD or FDD?	In this paper, we compare two common modes of duplexing in wireless powered communication networks (WPCN); namely TDD and FDD. So far, TDD has been the most widely used duplexing technique due to its simplicity. Yet, TDD does not allow the energy transmitter to function continuously, which means to deliver the same amo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	102,974
2102.01503	A Survey On (Stochastic Fractal Search) Algorithm	Evolutionary Algorithms are naturally inspired approximation optimisation algorithms that usually interfere with science problems when common mathematical methods are unable to provide a good solution or finding the exact solution requires an unreasonable amount of time using traditional exhaustive search algorithms. T...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	218,134
2406.12277	What Matters in Memorizing and Recalling Facts? Multifaceted Benchmarks for Knowledge Probing in Language Models	Language models often struggle with handling factual knowledge, exhibiting factual hallucination issue. This makes it vital to evaluate the models' ability to recall its parametric knowledge about facts. In this study, we introduce a knowledge probing benchmark, BELIEF(ICL), to evaluate the knowledge recall ability of ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	465,317
2212.04567	Enhanced prediction accuracy with uncertainty quantification in monitoring CO2 sequestration using convolutional neural networks	Monitoring changes inside a reservoir in real time is crucial for the success of CO2 injection and long-term storage. Machine learning (ML) is well-suited for real-time CO2 monitoring because of its computational efficiency. However, most existing applications of ML yield only one prediction (i.e., the expectation) for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	335,484
1908.10122	Heuristic design of fuzzy inference systems: A review of three decades of research	This paper provides an in-depth review of the optimal design of type-1 and type-2 fuzzy inference systems (FIS) using five well known computational frameworks: genetic-fuzzy systems (GFS), neuro-fuzzy systems (NFS), hierarchical fuzzy systems (HFS), evolving fuzzy systems (EFS), and multi-objective fuzzy systems (MFS),...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	143,026
1501.07439	The Arbitrarily Varying Wiretap Channel - Secret Randomness, Stability and Super-Activation	We define the common randomness assisted capacity of an arbitrarily varying channel (AVWC) when the Eavesdropper is kept ignorant about the common randomness. We prove a multi-letter capacity formula for this model. We prove that, if enough common randomness is used, the capacity formula can be given a single-shot form...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,711
2008.01332	Real-Time Cleaning and Refinement of Facial Animation Signals	With the increasing demand for real-time animated 3D content in the entertainment industry and beyond, performance-based animation has garnered interest among both academic and industrial communities. While recent solutions for motion-capture animation have achieved impressive results, handmade post-processing is often...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	190,279
2412.14020	Landscape of AI safety concerns -- A methodology to support safety assurance for AI-based autonomous systems	Artificial Intelligence (AI) has emerged as a key technology, driving advancements across a range of applications. Its integration into modern autonomous systems requires assuring safety. However, the challenge of assuring safety in systems that incorporate AI components is substantial. The lack of concrete specificati...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	518,545
2407.20741	Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditions	"AI for Science" aims to solve fundamental scientific problems using AI techniques. As most physical phenomena can be described as Partial Differential Equations (PDEs) , approximating their solutions using neural networks has evolved as a central component of scientific-ML. Physics-Informed Neural Networks (PINNs) is ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	477,272
1202.0296	Error Performance of Multidimensional Lattice Constellations-Part I: A Parallelotope Geometry Based Approach for the AWGN Channel	Multidimensional lattice constellations which present signal space diversity (SSD) have been extensively studied for single-antenna transmission over fading channels, with focus on their optimal design for achieving high diversity gain. In this two-part series of papers we present a novel combinatorial geometrical appr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,060
1910.01849	Randomized Shortest Paths with Net Flows and Capacity Constraints	This work extends the randomized shortest paths (RSP) model by investigating the net flow RSP and adding capacity constraints on edge flows. The standard RSP is a model of movement, or spread, through a network interpolating between a random-walk and a shortest-path behavior [30, 42, 49]. The framework assumes a unit f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,056
2410.12586	How to Make LLMs Forget: On Reversing In-Context Knowledge Edits	In-context knowledge editing (IKE) enables efficient modification of large language model (LLM) outputs without parameter changes and at zero-cost. However, it can be misused to manipulate responses opaquely, e.g., insert misinformation or offensive content. Such malicious interventions could be incorporated into high-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	499,097
2312.01575	A Challenging Multimodal Video Summary: Simultaneously Extracting and Generating Keyframe-Caption Pairs from Video	This paper proposes a practical multimodal video summarization task setting and a dataset to train and evaluate the task. The target task involves summarizing a given video into a predefined number of keyframe-caption pairs and displaying them in a listable format to grasp the video content quickly. This task aims to e...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	412,498
2501.01859	Deposition Rates in Thermal Laser Epitaxy: Simulation and Experiment	The modeling of deposition rates in Thermal Laser Epitaxy (TLE) is essential for the accurate prediction of the evaporation process and for improved dynamic process control. We demonstrate excellent agreement between experimental data and a model based on a finite element simulation that describes the temperature distr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	522,244
cs/0610128	Hierarchical Bin Buffering: Online Local Moments for Dynamic External Memory Arrays	Local moments are used for local regression, to compute statistical measures such as sums, averages, and standard deviations, and to approximate probability distributions. We consider the case where the data source is a very large I/O array of size n and we want to compute the first N local moments, for some constant N...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	539,812
2303.06833	Transformer-based Planning for Symbolic Regression	Symbolic regression (SR) is a challenging task in machine learning that involves finding a mathematical expression for a function based on its values. Recent advancements in SR have demonstrated the effectiveness of pre-trained transformer-based models in generating equations as sequences, leveraging large-scale pre-tr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	351,005
1607.04311	Defensive Distillation is Not Robust to Adversarial Examples	We show that defensive distillation is not secure: it is no more resistant to targeted misclassification attacks than unprotected neural networks.	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	58,596
2403.03053	Neural Codebook Design for Network Beam Management	Obtaining accurate and timely channel state information (CSI) is a fundamental challenge for large antenna systems. Mobile systems like 5G use a beam management framework that joins the initial access, beamforming, CSI acquisition, and data transmission. The design of codebooks for these stages, however, is challenging...	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	false	true	435,048
2109.13963	Smart at what cost? Characterising Mobile Deep Neural Networks in the wild	With smartphones' omnipresence in people's pockets, Machine Learning (ML) on mobile is gaining traction as devices become more powerful. With applications ranging from visual filters to voice assistants, intelligence on mobile comes in many forms and facets. However, Deep Neural Network (DNN) inference remains a comput...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	257,802
2502.06853	Native Fortran Implementation of TensorFlow-Trained Deep and Bayesian Neural Networks	Over the past decade, the investigation of machine learning (ML) within the field of nuclear engineering has grown significantly. With many approaches reaching maturity, the next phase of investigation will determine the feasibility and usefulness of ML model implementation in a production setting. Several of the codes...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,295
1712.09677	Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods	In this paper we study several classes of stochastic optimization algorithms enriched with heavy ball momentum. Among the methods studied are: stochastic gradient descent, stochastic Newton, stochastic proximal point and stochastic dual subspace ascent. This is the first time momentum variants of several of these metho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	87,388
1907.00377	FVA: Modeling Perceived Friendliness of Virtual Agents Using Movement Characteristics	We present a new approach for improving the friendliness and warmth of a virtual agent in an AR environment by generating appropriate movement characteristics. Our algorithm is based on a novel data-driven friendliness model that is computed using a user-study and psychological characteristics. We use our model to cont...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	137,023
1506.02465	ASlib: A Benchmark Library for Algorithm Selection	The task of algorithm selection involves choosing an algorithm from a set of algorithms on a per-instance basis in order to exploit the varying performance of algorithms over a set of instances. The algorithm selection problem is attracting increasing attention from researchers and practitioners in AI. Years of fruitfu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	43,925
2308.10146	OCHID-Fi: Occlusion-Robust Hand Pose Estimation in 3D via RF-Vision	Hand Pose Estimation (HPE) is crucial to many applications, but conventional cameras-based CM-HPE methods are completely subject to Line-of-Sight (LoS), as cameras cannot capture occluded objects. In this paper, we propose to exploit Radio-Frequency-Vision (RF-vision) capable of bypassing obstacles for achieving occlud...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	386,594
2212.05652	PyPop7: A Pure-Python Library for Population-Based Black-Box Optimization	In this paper, we present an open-source pure-Python library called PyPop7 for black-box optimization (BBO). As population-based methods (e.g., evolutionary algorithms, swarm intelligence, and pattern search) become increasingly popular for BBO, the design goal of PyPop7 is to provide a unified API and elegant implemen...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	335,842
2302.10179	A Dynamic Feedforward Control Strategy for Energy-efficient Building System Operation	The development of current building energy system operation has benefited from: 1. Informational support from the optimal design through simulation or first-principles models; 2. System load and energy prediction through machine learning (ML). Through the literature review, we note that in current control strategies an...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	346,699
2406.09617	Multimodal Large Language Models with Fusion Low Rank Adaptation for Device Directed Speech Detection	Although Large Language Models (LLMs) have shown promise for human-like conversations, they are primarily pre-trained on text data. Incorporating audio or video improves performance, but collecting large-scale multimodal data and pre-training multimodal LLMs is challenging. To this end, we propose a Fusion Low Rank Ada...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	464,008
2211.05543	Vis2Mus: Exploring Multimodal Representation Mapping for Controllable Music Generation	In this study, we explore the representation mapping from the domain of visual arts to the domain of music, with which we can use visual arts as an effective handle to control music generation. Unlike most studies in multimodal representation learning that are purely data-driven, we adopt an analysis-by-synthesis appro...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	329,588
1904.05417	Unsupervised Deep Learning Algorithm for PDE-based Forward and Inverse Problems	We propose a neural network-based algorithm for solving forward and inverse problems for partial differential equations in unsupervised fashion. The solution is approximated by a deep neural network which is the minimizer of a cost function, and satisfies the PDE, boundary conditions, and additional regularizations. Th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,309
2206.13752	Sub-Block Rearranged Staircase Codes for Optical Transport Networks	We propose a new family of spatially coupled product codes, called sub-block rearranged staircase (SR-staircase) codes. Each SR-staircase code block is constructed by encoding rearranged preceding code blocks and new information blocks, where the rearrangement involves sub-blocks decomposition and transposition. The pr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	305,073
cmp-lg/9604005	Better Language Models with Model Merging	This paper investigates model merging, a technique for deriving Markov models from text or speech corpora. Models are derived by starting with a large and specific model and by successively combining states to build smaller and more general models. We present methods to reduce the time complexity of the algorithm and r...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,507
2103.16629	Learning Lipschitz Feedback Policies from Expert Demonstrations: Closed-Loop Guarantees, Generalization and Robustness	In this work, we propose a framework to learn feedback control policies with guarantees on closed-loop generalization and adversarial robustness. These policies are learned directly from expert demonstrations, contained in a dataset of state-control input pairs, without any prior knowledge of the task and system model....	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	227,645
2305.17148	Differentially Private Low-dimensional Synthetic Data from High-dimensional Datasets	Differentially private synthetic data provide a powerful mechanism to enable data analysis while protecting sensitive information about individuals. However, when the data lie in a high-dimensional space, the accuracy of the synthetic data suffers from the curse of dimensionality. In this paper, we propose a differenti...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	368,432
1504.03878	Optimization results for a generalized coupon collector problem	We study in this paper a generalized coupon collector problem, which consists in analyzing the time needed to collect a given number of distinct coupons that are drawn from a set of coupons with an arbitrary probability distribution. We suppose that a special coupon called the null coupon can be drawn but never belongs...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	42,078
2402.09338	Neural Networks Asymptotic Behaviours for the Resolution of Inverse Problems	This paper presents a study of the effectiveness of Neural Network (NN) techniques for deconvolution inverse problems relevant for applications in Quantum Field Theory, but also in more general contexts. We consider NN's asymptotic limits, corresponding to Gaussian Processes (GPs), where non-linearities in the paramete...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	429,474
1803.07512	Fusion of stereo and still monocular depth estimates in a self-supervised learning context	We study how autonomous robots can learn by themselves to improve their depth estimation capability. In particular, we investigate a self-supervised learning setup in which stereo vision depth estimates serve as targets for a convolutional neural network (CNN) that transforms a single still image to a dense depth map. ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	93,070
1809.10272	Multi-variate correlation and mixtures of product measures	Total correlation (`TC') and dual total correlation (`DTC') are two classical ways to quantify the correlation among an $n$-tuple of random variables. They both reduce to mutual information when $n=2$. The first part of this paper sets up the theory of TC and DTC for general random variables, not necessarily finite-v...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	108,872
2405.14176	Certified Robustness against Sparse Adversarial Perturbations via Data Localization	Recent work in adversarial robustness suggests that natural data distributions are localized, i.e., they place high probability in small volume regions of the input space, and that this property can be utilized for designing classifiers with improved robustness guarantees for $\ell_2$-bounded perturbations. Yet, it is ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	456,292
1012.2621	Throughput and Latency of Acyclic Erasure Networks with Feedback in a Finite Buffer Regime	The exact Markov modeling analysis of erasure networks with finite buffers is an extremely hard problem due to the large number of states in the system. In such networks, packets are lost due to either link erasures or blocking by the full buffers. In this paper, we propose a novel method that iteratively estimates the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,512
2109.13527	Concept-Aware Denoising Graph Neural Network for Micro-Video Recommendation	Recently, micro-video sharing platforms such as Kuaishou and Tiktok have become a major source of information for people's lives. Thanks to the large traffic volume, short video lifespan and streaming fashion of these services, it has become more and more pressing to improve the existing recommender systems to accommod...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	257,665
1001.1133	Multi-cell MIMO Downlink with Fairness Criteria: the Large System Limit	We consider the downlink of a cellular network with multiple cells and multi-antenna base stations including arbitrary inter-cell cooperation, realistic distance-dependent pathloss and general "fairness" requirements. Beyond Monte Carlo simulation, no efficient computation method to evaluate the ergodic throughput of s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,287
2307.05898	Rectifying Noisy Labels with Sequential Prior: Multi-Scale Temporal Feature Affinity Learning for Robust Video Segmentation	Noisy label problems are inevitably in existence within medical image segmentation causing severe performance degradation. Previous segmentation methods for noisy label problems only utilize a single image while the potential of leveraging the correlation between images has been overlooked. Especially for video segment...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	378,892
2206.05278	Dual-Branch Squeeze-Fusion-Excitation Module for Cross-Modality Registration of Cardiac SPECT and CT	Single-photon emission computed tomography (SPECT) is a widely applied imaging approach for diagnosis of coronary artery diseases. Attenuation maps (u-maps) derived from computed tomography (CT) are utilized for attenuation correction (AC) to improve diagnostic accuracy of cardiac SPECT. However, SPECT and CT are obtai...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	301,953
2310.17315	Nabra: Syrian Arabic Dialects with Morphological Annotations	This paper presents Nabra, a corpora of Syrian Arabic dialects with morphological annotations. A team of Syrian natives collected more than 6K sentences containing about 60K words from several sources including social media posts, scripts of movies and series, lyrics of songs and local proverbs to build Nabra. Nabra co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,081
1710.02543	Socially Compliant Navigation through Raw Depth Inputs with Generative Adversarial Imitation Learning	We present an approach for mobile robots to learn to navigate in dynamic environments with pedestrians via raw depth inputs, in a socially compliant manner. To achieve this, we adopt a generative adversarial imitation learning (GAIL) strategy, which improves upon a pre-trained behavior cloning policy. Our approach over...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	82,180
2308.08493	Time Travel in LLMs: Tracing Data Contamination in Large Language Models	Data contamination, i.e., the presence of test data from downstream tasks in the training data of large language models (LLMs), is a potential major issue in measuring LLMs' real effectiveness on other tasks. We propose a straightforward yet effective method for identifying data contamination within LLMs. At its core, ...	false	false	false	false	true	false	true	false	true	false	false	false	true	false	false	false	false	false	385,925
2202.12515	Faithful learning with sure data for lung nodule diagnosis	Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two generalizability issues in clinical practice. First, benign-malignant discrimination is often assessed by human observers without pathologic dia...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	282,272
2411.13820	InstCache: A Predictive Cache for LLM Serving	Large language models are revolutionizing every aspect of human life. However, the unprecedented power comes at the cost of significant computing intensity, suggesting long latency and large energy footprint. Key-Value Cache and Semantic Cache have been proposed as a solution to the above problem, but both suffer from ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	509,930
2305.15072	PathAsst: A Generative Foundation AI Assistant Towards Artificial General Intelligence of Pathology	As advances in large language models (LLMs) and multimodal techniques continue to mature, the development of general-purpose multimodal large language models (MLLMs) has surged, offering significant applications in interpreting natural images. However, the field of pathology has largely remained untapped, particularly ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	367,436
2202.13840	Text Smoothing: Enhance Various Data Augmentation Methods on Text Classification Tasks	Before entering the neural network, a token is generally converted to the corresponding one-hot representation, which is a discrete distribution of the vocabulary. Smoothed representation is the probability of candidate tokens obtained from a pre-trained masked language model, which can be seen as a more informative su...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	282,762

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