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
1404.0346	Scaling laws for molecular communication	In this paper, we investigate information-theoretic scaling laws, independent from communication strategies, for point-to-point molecular communication, where it sends/receives information-encoded molecules between nanomachines. Since the Shannon capacity for this is still an open problem, we first derive an asymptotic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	32,007
1912.05074	UNet++: Redesigning Skip Connections to Exploit Multiscale Features in Image Segmentation	The state-of-the-art models for medical image segmentation are variants of U-Net and fully convolutional networks (FCN). Despite their success, these models have two limitations: (1) their optimal depth is apriori unknown, requiring extensive architecture search or inefficient ensemble of models of varying depths; and ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	157,003
1904.11148	Divide and Conquer: A Deep CASA Approach to Talker-independent Monaural Speaker Separation	We address talker-independent monaural speaker separation from the perspectives of deep learning and computational auditory scene analysis (CASA). Specifically, we decompose the multi-speaker separation task into the stages of simultaneous grouping and sequential grouping. Simultaneous grouping is first performed in ea...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	128,798
1412.2455	Location Verification Systems for VANETs in Rician Fading Channels	In this work we propose and examine Location Verification Systems (LVSs) for Vehicular Ad Hoc Networks (VANETs) in the realistic setting of Rician fading channels. In our LVSs, a single authorized Base Station (BS) equipped with multiple antennas aims to detect a malicious vehicle that is spoofing its claimed location....	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	38,210
2108.13129	From General to Specific: Informative Scene Graph Generation via Balance Adjustment	The scene graph generation (SGG) task aims to detect visual relationship triplets, i.e., subject, predicate, object, in an image, providing a structural vision layout for scene understanding. However, current models are stuck in common predicates, e.g., "on" and "at", rather than informative ones, e.g., "standing on" a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,718
2305.18033	The ACROBAT 2022 Challenge: Automatic Registration Of Breast Cancer Tissue	The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for research and clinical applications. Advances in computing, deep learning, and availability of large WSI datasets have revolutionised WSI analysis. Therefore, the current state-of-the-art in WSI registration is unclear. To address ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	368,838
2111.06929	Hierarchical Bayesian Bandits	Meta-, multi-task, and federated learning can be all viewed as solving similar tasks, drawn from a distribution that reflects task similarities. We provide a unified view of all these problems, as learning to act in a hierarchical Bayesian bandit. We propose and analyze a natural hierarchical Thompson sampling algorith...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	266,220
1812.02814	Light Propagation Prediction through Multimode Optical Fibers with a Deep Neural Network	This work demonstrates a computational method for predicting the light propagation through a single multimode fiber using a deep neural network. The experiment for gathering training and testing data is performed with a digital micro-mirror device that enables the spatial light modulation. The modulated patterns on the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	115,855
2406.08649	MOTIVE: A Drug-Target Interaction Graph For Inductive Link Prediction	Drug-target interaction (DTI) prediction is crucial for identifying new therapeutics and detecting mechanisms of action. While structure-based methods accurately model physical interactions between a drug and its protein target, cell-based assays such as Cell Painting can better capture complex DTI interactions. This p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	463,566
1909.05578	Efficient and Robust Equilibrium Strategies of Utilities in Day-ahead Market with Load Uncertainty	We consider the scenario where $N$ utilities strategically bid for electricity in the day-ahead market and balance the mismatch between the committed supply and actual demand in the real-time market, with uncertainty in demand and local renewable generation in consideration. We model the interactions among utilities as...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	145,131
0804.3894	Unmanned Aerial Vehicle Instrumentation for Rapid Aerial Photo System	This research will proposed a new kind of relatively low cost autonomous UAV that will enable farmers to make just in time mosaics of aerial photo of their crop. These mosaics of aerial photo should be able to be produced with relatively low cost and within the 24 hours of acquisition constraint. The autonomous UAV wil...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	1,634
2412.02960	Semantic Segmentation Prior for Diffusion-Based Real-World Super-Resolution	Real-world image super-resolution (Real-ISR) has achieved a remarkable leap by leveraging large-scale text-to-image models, enabling realistic image restoration from given recognition textual prompts. However, these methods sometimes fail to recognize some salient objects, resulting in inaccurate semantic restoration i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	513,755
2310.09270	Retro-fallback: retrosynthetic planning in an uncertain world	Retrosynthesis is the task of planning a series of chemical reactions to create a desired molecule from simpler, buyable molecules. While previous works have proposed algorithms to find optimal solutions for a range of metrics (e.g. shortest, lowest-cost), these works generally overlook the fact that we have imperfect ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	399,716
2305.17147	Heterogeneous Value Alignment Evaluation for Large Language Models	The emergent capabilities of Large Language Models (LLMs) have made it crucial to align their values with those of humans. However, current methodologies typically attempt to assign value as an attribute to LLMs, yet lack attention to the ability to pursue value and the importance of transferring heterogeneous values i...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	368,431
1306.3610	Thresholds of Spatially Coupled Systems via Lyapunov's Method	The threshold, or saturation phenomenon of spatially coupled systems is revisited in the light of Lyapunov's theory of dynamical systems. It is shown that an application of Lyapunov's direct method can be used to quantitatively describe the threshold phenomenon, prove convergence, and compute threshold values. This pro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,226
2209.06862	Deep learning in a bilateral brain with hemispheric specialization	The brains of all bilaterally symmetric animals on Earth are divided into left and right hemispheres. The anatomy and functionality of the hemispheres have a large degree of overlap, but there are asymmetries, and they specialise in possesses different attributes. Other authors have used computational models to mimic h...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	317,531
2011.12775	Decentralized Control Barrier Functions for Coupled Multi-Agent Systems under Signal Temporal Logic Tasks	We study the problem of controlling multi-agent systems under a set of signal temporal logic tasks. Signal temporal logic is a formalism that is used to express time and space constraints for dynamical systems. Recent methods to solve the control synthesis problem for single-agent systems under signal temporal logic ta...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	208,267
2106.08056	Coupled Gradient Estimators for Discrete Latent Variables	Training models with discrete latent variables is challenging due to the high variance of unbiased gradient estimators. While low-variance reparameterization gradients of a continuous relaxation can provide an effective solution, a continuous relaxation is not always available or tractable. Dong et al. (2020) and Yin e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	241,170
1901.07683	Class Activation Map Generation by Representative Class Selection and Multi-Layer Feature Fusion	Existing method generates class activation map (CAM) by a set of fixed classes (i.e., using all the classes), while the discriminative cues between class pairs are not considered. Note that activation maps by considering different class pair are complementary, and therefore can provide more discriminative cues to overc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	119,271
2011.08511	Designing Cost- and Energy-Efficient Cell-Free Massive MIMO Network with Fiber and FSO Fronthaul Links	The emerging cell-free massive multiple-input multiple-output (CF-mMIMO) is a promising scheme to tackle the capacity crunch in wireless networks. Designing the optimal fronthaul network in the CF-mMIMIO is of utmost importance to deploy a cost- and energy-efficient network. In this paper, we present a framework to opt...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	206,899
2307.10714	Introducing Risk Shadowing For Decisive and Comfortable Behavior Planning	We consider the problem of group interactions in urban driving. State-of-the-art behavior planners for self-driving cars mostly consider each single agent-to-agent interaction separately in a cost function in order to find an optimal behavior for the ego agent, such as not colliding with any of the other agents. In thi...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	380,663
1901.04672	Integrating and querying similar tables from PDF documents using deep learning	Large amount of public data produced by enterprises are in semi-structured PDF form. Tabular data extraction from reports and other published data in PDF format is of interest for various data consolidation purposes such as analysing and aggregating financial reports of a company. Queries into the structured tabular da...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	118,641
2306.15348	PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation	Reliable LiDAR panoptic segmentation (LPS), including both semantic and instance segmentation, is vital for many robotic applications, such as autonomous driving. This work proposes a new LPS framework named PANet to eliminate the dependency on the offset branch and improve the performance on large objects, which are a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	375,994
1802.03675	Understanding Convolutional Networks with APPLE : Automatic Patch Pattern Labeling for Explanation	With the success of deep learning, recent efforts have been focused on analyzing how learned networks make their classifications. We are interested in analyzing the network output based on the network structure and information flow through the network layers. We contribute an algorithm for 1) analyzing a deep network t...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	90,037
1602.01792	Random Forest DBSCAN for USPTO Inventor Name Disambiguation	Name disambiguation and the subsequent name conflation are essential for the correct processing of person name queries in a digital library or other database. It distinguishes each unique person from all other records in the database. We study inventor name disambiguation for a patent database using methods and feature...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	51,747
2308.00407	Coded Modulation Schemes for Voronoi Constellations	Multidimensional Voronoi constellations (VCs) are shown to be more power-efficient than quadrature amplitude modulation (QAM) formats given the same uncoded bit error rate, and also have higher achievable information rates. However, a coded modulation scheme to sustain these gains after forward error correction (FEC) c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	382,932
2308.15366	AnomalyGPT: Detecting Industrial Anomalies Using Large Vision-Language Models	Large Vision-Language Models (LVLMs) such as MiniGPT-4 and LLaVA have demonstrated the capability of understanding images and achieved remarkable performance in various visual tasks. Despite their strong abilities in recognizing common objects due to extensive training datasets, they lack specific domain knowledge and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,659
2311.15209	See and Think: Embodied Agent in Virtual Environment	Large language models (LLMs) have achieved impressive pro-gress on several open-world tasks. Recently, using LLMs to build embodied agents has been a hotspot. This paper proposes STEVE, a comprehensive and visionary embodied agent in the Minecraft virtual environment. STEVE comprises three key components: vision percep...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	410,422
2110.00736	Stanford Pupper: A Low-Cost Agile Quadruped Robot for Benchmarking and Education	We present Stanford Pupper, an easily-replicated open source quadruped robot designed specifically as a benchmark platform for legged robotics research. The robot features torque-controllable brushless motors with high specific power that enable testing of impedance and torque-based machine learning and optimization co...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	258,512
2204.05258	Multi-view graph structure learning using subspace merging on Grassmann manifold	Many successful learning algorithms have been recently developed to represent graph-structured data. For example, Graph Neural Networks (GNNs) have achieved considerable successes in various tasks such as node classification, graph classification, and link prediction. However, these methods are highly dependent on the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,977
2203.01236	Convolutional neural networks as an alternative to Bayesian retrievals	Exoplanet observations are currently analysed with Bayesian retrieval techniques. Due to the computational load of the models used, a compromise is needed between model complexity and computing time. Analysis of data from future facilities, will need more complex models which will increase the computational load of ret...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	283,306
1808.09829	MACNet: Multi-scale Atrous Convolution Networks for Food Places Classification in Egocentric Photo-streams	First-person (wearable) camera continually captures unscripted interactions of the camera user with objects, people, and scenes reflecting his personal and relational tendencies. One of the preferences of people is their interaction with food events. The regulation of food intake and its duration has a great importance...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	106,276
2405.05989	Clustering-based Multitasking Deep Neural Network for Solar Photovoltaics Power Generation Prediction	The increasing installation of Photovoltaics (PV) cells leads to more generation of renewable energy sources (RES), but results in increased uncertainties of energy scheduling. Predicting PV power generation is important for energy management and dispatch optimization in smart grid. However, the PV power generation dat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	453,137
2404.04736	ProtoAL: Interpretable Deep Active Learning with prototypes for medical imaging	The adoption of Deep Learning algorithms in the medical imaging field is a prominent area of research, with high potential for advancing AI-based Computer-aided diagnosis (AI-CAD) solutions. However, current solutions face challenges due to a lack of interpretability features and high data demands, prompting recent eff...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	444,776
1912.00863	Independent language modeling architecture for end-to-end ASR	The attention-based end-to-end (E2E) automatic speech recognition (ASR) architecture allows for joint optimization of acoustic and language models within a single network. However, in a vanilla E2E ASR architecture, the decoder sub-network (subnet), which incorporates the role of the language model (LM), is conditioned...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	155,916
2312.09674	Optimal Regret Bounds for Collaborative Learning in Bandits	We consider regret minimization in a general collaborative multi-agent multi-armed bandit model, in which each agent faces a finite set of arms and may communicate with other agents through a central controller. The optimal arm for each agent in this model is the arm with the largest expected mixed reward, where the mi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	415,838
2112.10525	Certified Federated Adversarial Training	In federated learning (FL), robust aggregation schemes have been developed to protect against malicious clients. Many robust aggregation schemes rely on certain numbers of benign clients being present in a quorum of workers. This can be hard to guarantee when clients can join at will, or join based on factors such as i...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	272,460
2210.13695	Structure-based Drug Design with Equivariant Diffusion Models	Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage structural data of drugs in complex with their protein targets to propose new drug candidates. These approaches typically place one at...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,264
1912.11032	Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning	Learning robotic manipulation tasks using reinforcement learning with sparse rewards is currently impractical due to the outrageous data requirements. Many practical tasks require manipulation of multiple objects, and the complexity of such tasks increases with the number of objects. Learning from a curriculum of incre...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	158,466
2410.17032	Insights on Disagreement Patterns in Multimodal Safety Perception across Diverse Rater Groups	AI systems crucially rely on human ratings, but these ratings are often aggregated, obscuring the inherent diversity of perspectives in real-world phenomenon. This is particularly concerning when evaluating the safety of generative AI, where perceptions and associated harms can vary significantly across socio-cultural ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	501,288
2404.15028	PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts	In this paper, we present PRISM, a Promptable and Robust Interactive Segmentation Model, aiming for precise segmentation of 3D medical images. PRISM accepts various visual inputs, including points, boxes, and scribbles as sparse prompts, as well as masks as dense prompts. Specifically, PRISM is designed with four princ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,920
2306.11025	Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting	This paper presents a novel study on harnessing Large Language Models' (LLMs) outstanding knowledge and reasoning abilities for explainable financial time series forecasting. The application of machine learning models to financial time series comes with several challenges, including the difficulty in cross-sequence rea...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	374,452
2111.12115	Algorithmic Fairness in Face Morphing Attack Detection	Face morphing attacks can compromise Face Recognition System (FRS) by exploiting their vulnerability. Face Morphing Attack Detection (MAD) techniques have been developed in recent past to deter such attacks and mitigate risks from morphing attacks. MAD algorithms, as any other algorithms should treat the images of subj...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,867
2208.02578	N-best Response-based Analysis of Contradiction-awareness in Neural Response Generation Models	Avoiding the generation of responses that contradict the preceding context is a significant challenge in dialogue response generation. One feasible method is post-processing, such as filtering out contradicting responses from a resulting n-best response list. In this scenario, the quality of the n-best list considerabl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	311,509
2312.13494	Visual Tomography: Physically Faithful Volumetric Models of Partially Translucent Objects	When created faithfully from real-world data, Digital 3D representations of objects can be useful for human or computer-assisted analysis. Such models can also serve for generating training data for machine learning approaches in settings where data is difficult to obtain or where too few training data exists, e.g. by ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,326
2109.08994	ReaSCAN: Compositional Reasoning in Language Grounding	The ability to compositionally map language to referents, relations, and actions is an essential component of language understanding. The recent gSCAN dataset (Ruis et al. 2020, NeurIPS) is an inspiring attempt to assess the capacity of models to learn this kind of grounding in scenarios involving navigational instruct...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	256,108
2111.05672	Automatically detecting data drift in machine learning classifiers	Classifiers and other statistics-based machine learning (ML) techniques generalize, or learn, based on various statistical properties of the training data. The assumption underlying statistical ML resulting in theoretical or empirical performance guarantees is that the distribution of the training data is representativ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	265,853
2210.03379	Geomagnetic Survey Interpolation with the Machine Learning Approach	This paper portrays the method of UAV magnetometry survey data interpolation. The method accommodates the fact that this kind of data has a spatial distribution of the samples along a series of straight lines (similar to maritime tacks), which is a prominent characteristic of many kinds of UAV surveys. The interpolatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	322,011
2110.04094	Privacy-Aware Communication Over a Wiretap Channel with Generative Networks	We study privacy-aware communication over a wiretap channel using end-to-end learning. Alice wants to transmit a source signal to Bob over a binary symmetric channel, while passive eavesdropper Eve tries to infer some sensitive attribute of Alice's source based on its overheard signal. Since we usually do not have acce...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	259,757
2405.00982	On the Evaluation of Machine-Generated Reports	Large Language Models (LLMs) have enabled new ways to satisfy information needs. Although great strides have been made in applying them to settings like document ranking and short-form text generation, they still struggle to compose complete, accurate, and verifiable long-form reports. Reports with these qualities are ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	451,164
0708.3613	Kinematics and Workspace Analysis of a Three-Axis Parallel Manipulator: the Orthoglide	The paper addresses kinematic and geometrical aspects of the Orthoglide, a three-DOF parallel mechanism. This machine consists of three fixed linear joints, which are mounted orthogonally, three identical legs and a mobile platform, which moves in the Cartesian x-y-z space with fixed orientation. New solutions to solve...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	599
2205.02949	Over-The-Air Federated Learning under Byzantine Attacks	Federated learning (FL) is a promising solution to enable many AI applications, where sensitive datasets from distributed clients are needed for collaboratively training a global model. FL allows the clients to participate in the training phase, governed by a central server, without sharing their local data. One of the...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	295,120
2206.14164	Visualizing and Alleviating the Effect of Radial Distortion on Camera Calibration Using Principal Lines	Preparing appropriate images for camera calibration is crucial to obtain accurate results. In this paper, new suggestions for preparing such data to alleviate the adverse effect of radial distortion for a calibration procedure using principal lines are developed through the investigations of: (i) identifying directions...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	305,194
2305.14918	Incremental Dense Reconstruction from Monocular Video with Guided Sparse Feature Volume Fusion	Incrementally recovering 3D dense structures from monocular videos is of paramount importance since it enables various robotics and AR applications. Feature volumes have recently been shown to enable efficient and accurate incremental dense reconstruction without the need to first estimate depth, but they are not able ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	367,334
2305.08735	The Non-Strict Projection Lemma	The projection lemma (often also referred to as the elimination lemma) is one of the most powerful and useful tools in the context of linear matrix inequalities for system analysis and control. In its traditional formulation, the projection lemma only applies to strict inequalities, however, in many applications we nat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	364,385
1910.07428	Gaze Gestures and Their Applications in human-computer interaction with a head-mounted display	A head-mounted display (HMD) is a portable and interactive display device. With the development of 5G technology, it may become a general-purpose computing platform in the future. Human-computer interaction (HCI) technology for HMDs has also been of significant interest in recent years. In addition to tracking gestures...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	149,607
2210.13668	ConnectedUNets++: Mass Segmentation from Whole Mammographic Images	Deep learning has made a breakthrough in medical image segmentation in recent years due to its ability to extract high-level features without the need for prior knowledge. In this context, U-Net is one of the most advanced medical image segmentation models, with promising results in mammography. Despite its excellent o...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	326,252
2308.15493	Unidentifiability of System Dynamics: Conditions and Controller Design	How to make a dynamic system unidentifiable is an important but still open issue. It not only requires that the parameters of the systems but also the equivalent systems cannot be identified by any identification approaches. Thus, it is a much more challenging problem than the existing analysis of parameter identifiabi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	388,703
1605.06827	Complementary Dual Subfield Linear Codes Over Finite Fields	Two families of complementary codes over finite fields $\mathbb{F}_q$ are studied, where $q=r^2$ is square: i) Hermitian complementary dual linear codes, and ii) trace Hermitian complementary dual subfield linear codes. Necessary and sufficient conditions for a linear code (resp., a subfield linear code) to be Hermitia...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,195
2407.03115	$L_p$-norm Distortion-Efficient Adversarial Attack	Adversarial examples have shown a powerful ability to make a well-trained model misclassified. Current mainstream adversarial attack methods only consider one of the distortions among $L_0$-norm, $L_2$-norm, and $L_\infty$-norm. $L_0$-norm based methods cause large modification on a single pixel, resulting in naked-eye...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,028
1511.06292	Foveation-based Mechanisms Alleviate Adversarial Examples	We show that adversarial examples, i.e., the visually imperceptible perturbations that result in Convolutional Neural Networks (CNNs) fail, can be alleviated with a mechanism based on foveations---applying the CNN in different image regions. To see this, first, we report results in ImageNet that lead to a revision of t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	49,190
2407.00956	A Closer Look at Deep Learning Methods on Tabular Datasets	Tabular data is prevalent across diverse domains in machine learning. While classical methods like tree-based models have long been effective, Deep Neural Network (DNN)-based methods have recently demonstrated promising performance. However, the diverse characteristics of methods and the inherent heterogeneity of tabul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	469,082
1203.6130	Spectral dimensionality reduction for HMMs	Hidden Markov Models (HMMs) can be accurately approximated using co-occurrence frequencies of pairs and triples of observations by using a fast spectral method in contrast to the usual slow methods like EM or Gibbs sampling. We provide a new spectral method which significantly reduces the number of model parameters tha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	15,151
2011.02151	Simulation of Human and Artificial Emotion (SHArE)	The framework for Simulation of Human and Artificial Emotion (SHArE) describes the architecture of emotion in terms of parameters transferable between psychology, neuroscience, and artificial intelligence. These parameters can be defined as abstract concepts or granularized down to the voltage levels of individual neur...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	204,840
2402.05122	History of generative Artificial Intelligence (AI) chatbots: past, present, and future development	This research provides an in-depth comprehensive review of the progress of chatbot technology over time, from the initial basic systems relying on rules to today's advanced conversational bots powered by artificial intelligence. Spanning many decades, the paper explores the major milestones, innovations, and paradigm s...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	427,731
2210.17395	User Manual of Automatic Data Curation Tool(ADCT): A bulk data curator software in Library and Information Science	In library and information science, document storage and user-specific document retrieval are the main aspects of digital library services. To preserve the cultural heritage, documents, and literature, we need a common platform where all types of documents are available in a specific format. Our proposed software tool,...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	327,668
2010.07259	Privacy-Preserving Object Detection & Localization Using Distributed Machine Learning: A Case Study of Infant Eyeblink Conditioning	Distributed machine learning is becoming a popular model-training method due to privacy, computational scalability, and bandwidth capacities. In this work, we explore scalable distributed-training versions of two algorithms commonly used in object detection. A novel distributed training algorithm using Mean Weight Matr...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	200,755
2409.02564	Learnable Wireless Digital Twins: Reconstructing Electromagnetic Field with Neural Representations	Fully harvesting the gain of multiple-input and multiple-output (MIMO) requires accurate channel information. However, conventional channel acquisition methods mainly rely on pilot training signals, resulting in significant training overheads (time, energy, spectrum). Digital twin-aided communications have been propose...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	485,750
2006.09738	LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB	While short range 3D pedestrian detection is sufficient for emergency breaking, long range detections are required for smooth breaking and gaining trust in autonomous vehicles. The current state-of-the-art on the KITTI benchmark performs suboptimal in detecting the position of pedestrians at long range. Thus, we propos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	182,642
2011.11205	A Geometrically Exact Continuum Framework for Light-Matter Interaction in Photo-Active Polymers I. Variational Setting	Molecular photo-switches as, e.g., azobenzene molecules allow, when embedded into a polymeric matrix, for photo-active polymer compounds responding mechanically when exposed to light of certain wavelength. Photo-mechanics, i.e. light-matter interaction in photo-active polymers holds great promise for, e.g., remote and ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	207,759
2111.02357	Multivariate feature ranking of gene expression data	Gene expression datasets are usually of high dimensionality and therefore require efficient and effective methods for identifying the relative importance of their attributes. Due to the huge size of the search space of the possible solutions, the attribute subset evaluation feature selection methods tend to be not appl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	264,847
2103.05154	Explanations in Autonomous Driving: A Survey	The automotive industry has witnessed an increasing level of development in the past decades; from manufacturing manually operated vehicles to manufacturing vehicles with a high level of automation. With the recent developments in Artificial Intelligence (AI), automotive companies now employ blackbox AI models to enabl...	true	false	false	false	true	false	true	true	false	false	false	false	false	true	false	false	false	false	223,884
2206.05498	A Review of Causality for Learning Algorithms in Medical Image Analysis	Medical image analysis is a vibrant research area that offers doctors and medical practitioners invaluable insight and the ability to accurately diagnose and monitor disease. Machine learning provides an additional boost for this area. However, machine learning for medical image analysis is particularly vulnerable to n...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	302,027
1206.3002	Study of the Importance of Adequacy to Robot Verbal and Non Verbal Communication in Human-Robot interaction	The Robadom project aims at creating a homecare robot that help and assist people in their daily life, either in doing task for the human or in managing day organization. A robot could have this kind of role only if it is accepted by humans. Before thinking about the robot appearance, we decided to evaluate the importa...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	16,471
2104.01742	Explainability-aided Domain Generalization for Image Classification	Traditionally, for most machine learning settings, gaining some degree of explainability that tries to give users more insights into how and why the network arrives at its predictions, restricts the underlying model and hinders performance to a certain degree. For example, decision trees are thought of as being more ex...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	228,458
2005.02767	Maximum Likelihood Methods for Inverse Learning of Optimal Controllers	This paper presents a framework for inverse learning of objective functions for constrained optimal control problems, which is based on the Karush-Kuhn-Tucker (KKT) conditions. We discuss three variants corresponding to different model assumptions and computational complexities. The first method uses a convex relaxatio...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	175,966
1809.04467	Multi range Real-time depth inference from a monocular stabilized footage using a Fully Convolutional Neural Network	Using a neural network architecture for depth map inference from monocular stabilized videos with application to UAV videos in rigid scenes, we propose a multi-range architecture for unconstrained UAV flight, leveraging flight data from sensors to make accurate depth maps for uncluttered outdoor environment. We try our...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	107,576
1303.0793	Reasoning about Strategies under Partial Observability and Fairness Constraints	A number of extensions exist for Alternating-time Temporal Logic; some of these mix strategies and partial observability but, to the best of our knowledge, no work provides a unified framework for strategies, partial observability and fairness constraints. In this paper we propose ATLK^F_po, a logic mixing strategies u...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	22,625
2410.08114	Parameter-Efficient Fine-Tuning in Spectral Domain for Point Cloud Learning	Recently, leveraging pre-training techniques to enhance point cloud models has become a hot research topic. However, existing approaches typically require full fine-tuning of pre-trained models to achieve satisfied performance on downstream tasks, accompanying storage-intensive and computationally demanding. To address...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,957
2305.13582	Translation and Fusion Improves Zero-shot Cross-lingual Information Extraction	Large language models (LLMs) combined with instruction tuning have shown significant progress in information extraction (IE) tasks, exhibiting strong generalization capabilities to unseen datasets by following annotation guidelines. However, their applicability to low-resource languages remains limited due to lack of b...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	366,563
1812.04599	Adversarial Framing for Image and Video Classification	Neural networks are prone to adversarial attacks. In general, such attacks deteriorate the quality of the input by either slightly modifying most of its pixels, or by occluding it with a patch. In this paper, we propose a method that keeps the image unchanged and only adds an adversarial framing on the border of the im...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	116,242
1908.07985	MobiSR: Efficient On-Device Super-Resolution through Heterogeneous Mobile Processors	In recent years, convolutional networks have demonstrated unprecedented performance in the image restoration task of super-resolution (SR). SR entails the upscaling of a single low-resolution image in order to meet application-specific image quality demands and plays a key role in mobile devices. To comply with privacy...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	142,432
1309.6871	Bounded Approximate Symbolic Dynamic Programming for Hybrid MDPs	Recent advances in symbolic dynamic programming (SDP) combined with the extended algebraic decision diagram (XADD) data structure have provided exact solutions for mixed discrete and continuous (hybrid) MDPs with piecewise linear dynamics and continuous actions. Since XADD-based exact solutions may grow intractably lar...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	27,328
2409.01690	Taming CLIP for Fine-grained and Structured Visual Understanding of Museum Exhibits	CLIP is a powerful and widely used tool for understanding images in the context of natural language descriptions to perform nuanced tasks. However, it does not offer application-specific fine-grained and structured understanding, due to its generic nature. In this work, we aim to adapt CLIP for fine-grained and structu...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	485,442
1411.3698	Minimal Realization Problems for Hidden Markov Models	Consider a stationary discrete random process with alphabet size d, which is assumed to be the output process of an unknown stationary Hidden Markov Model (HMM). Given the joint probabilities of finite length strings of the process, we are interested in finding a finite state generative model to describe the entire pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	37,525
2308.16139	MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision	Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from numerous shape-related publi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	388,909
2204.09108	Sintel: A Machine Learning Framework to Extract Insights from Signals	The detection of anomalies in time series data is a critical task with many monitoring applications. Existing systems often fail to encompass an end-to-end detection process, to facilitate comparative analysis of various anomaly detection methods, or to incorporate human knowledge to refine output. This precludes curre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	292,317
1709.00257	Recovery analysis for weighted mixed $\ell_2/\ell_p$ minimization with $0<p\leq 1$	We study the recovery conditions of weighted mixed $\ell_2/\ell_p\,(0<p\leq 1)$ minimization for block sparse signal reconstruction from compressed measurements when partial block support information is available. We show that the block $p$-restricted isometry property (RIP) can ensure the robust recovery. Moreover, we...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	79,874
2306.04374	Label Aware Speech Representation Learning For Language Identification	Speech representation learning approaches for non-semantic tasks such as language recognition have either explored supervised embedding extraction methods using a classifier model or self-supervised representation learning approaches using raw data. In this paper, we propose a novel framework of combining self-supervis...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	371,721
1710.00341	Fully Automated Fact Checking Using External Sources	Given the constantly growing proliferation of false claims online in recent years, there has been also a growing research interest in automatically distinguishing false rumors from factually true claims. Here, we propose a general-purpose framework for fully-automatic fact checking using external sources, tapping the p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	81,848
2305.02626	"Oops, Did I Just Say That?" Testing and Repairing Unethical Suggestions of Large Language Models with Suggest-Critique-Reflect Process	As the popularity of large language models (LLMs) soars across various applications, ensuring their alignment with human values has become a paramount concern. In particular, given that LLMs have great potential to serve as general-purpose AI assistants in daily life, their subtly unethical suggestions become a serious...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	362,114
1210.2019	On the relation of nonanticipative rate distortion function and filtering theory	In this paper the relation between nonanticipative rate distortion function (RDF) and Bayesian filtering theory is investigated using the topology of weak convergence of probability measures on Polish spaces. The relation is established via an optimization on the space of conditional distributions of the so-called dire...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	18,982
2406.06729	Synthetic Query Generation using Large Language Models for Virtual Assistants	Virtual Assistants (VAs) are important Information Retrieval platforms that help users accomplish various tasks through spoken commands. The speech recognition system (speech-to-text) uses query priors, trained solely on text, to distinguish between phonetically confusing alternatives. Hence, the generation of syntheti...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	462,745
2412.07009	LUIEO: A Lightweight Model for Integrating Underwater Image Enhancement and Object Detection	Underwater optical images inevitably suffer from various degradation factors such as blurring, low contrast, and color distortion, which hinder the accuracy of object detection tasks. Due to the lack of paired underwater/clean images, most research methods adopt a strategy of first enhancing and then detecting, resulti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	515,470
2410.24019	Speech is More Than Words: Do Speech-to-Text Translation Systems Leverage Prosody?	The prosody of a spoken utterance, including features like stress, intonation and rhythm, can significantly affect the underlying semantics, and as a consequence can also affect its textual translation. Nevertheless, prosody is rarely studied within the context of speech-to-text translation (S2TT) systems. In particula...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	504,292
2412.15294	A Universal Model for Human Mobility Prediction	Predicting human mobility is crucial for urban planning, traffic control, and emergency response. Mobility behaviors can be categorized into individual and collective, and these behaviors are recorded by diverse mobility data, such as individual trajectory and crowd flow. As different modalities of mobility data, indiv...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	519,047
1712.04487	Topological mixture estimation	Density functions that represent sample data are often multimodal, i.e. they exhibit more than one maximum. Typically this behavior is taken to indicate that the underlying data deserves a more detailed representation as a mixture of densities with individually simpler structure. The usual specification of a component ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	86,613
1905.03042	Rumour Detection via News Propagation Dynamics and User Representation Learning	Rumours have existed for a long time and have been known for serious consequences. The rapid growth of social media platforms has multiplied the negative impact of rumours; it thus becomes important to early detect them. Many methods have been introduced to detect rumours using the content or the social context of news...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	130,117
2011.07961	An Empirical Investigation of Contextualized Number Prediction	We conduct a large scale empirical investigation of contextualized number prediction in running text. Specifically, we consider two tasks: (1)masked number prediction-predicting a missing numerical value within a sentence, and (2)numerical anomaly detection-detecting an errorful numeric value within a sentence. We expe...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	206,725
1211.2155	Improved Modeling of the Correlation Between Continuous-Valued Sources in LDPC-Based DSC	Accurate modeling of the correlation between the sources plays a crucial role in the efficiency of distributed source coding (DSC) systems. This correlation is commonly modeled in the binary domain by using a single binary symmetric channel (BSC), both for binary and continuous-valued sources. We show that "one" BSC ca...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	19,654

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