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
2406.15990	Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information	Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such as location, time, agent, and patient), lacking the ability to utilize document-level information. As a result, they struggle to capture lon...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	466,951
1405.7076	On minimal sets of graded attribute implications	We explore the structure of non-redundant and minimal sets consisting of graded if-then rules. The rules serve as graded attribute implications in object-attribute incidence data and as similarity-based functional dependencies in a similarity-based generalization of the relational model of data. Based on our observatio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	33,430
2408.09501	Beyond Local Views: Global State Inference with Diffusion Models for Cooperative Multi-Agent Reinforcement Learning	In partially observable multi-agent systems, agents typically only have access to local observations. This severely hinders their ability to make precise decisions, particularly during decentralized execution. To alleviate this problem and inspired by image outpainting, we propose State Inference with Diffusion Models ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	481,468
2004.03902	Deep daxes: Mutual exclusivity arises through both learning biases and pragmatic strategies in neural networks	Children's tendency to associate novel words with novel referents has been taken to reflect a bias toward mutual exclusivity. This tendency may be advantageous both as (1) an ad-hoc referent selection heuristic to single out referents lacking a label and as (2) an organizing principle of lexical acquisition. This paper...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	171,724
2203.02354	Benchmarking real-time algorithms for in-phase auditory stimulation of low amplitude slow waves with wearable EEG devices during sleep	Auditory stimulation of EEG slow waves (SW) during non-rapid eye movement (NREM) sleep has shown to improve cognitive function when it is delivered at the up-phase of SW. SW enhancement is particularly desirable in subjects with low-amplitude SW such as older adults or patients suffering from neurodegeneration such as ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,718
2002.02842	Assessing the Adversarial Robustness of Monte Carlo and Distillation Methods for Deep Bayesian Neural Network Classification	In this paper, we consider the problem of assessing the adversarial robustness of deep neural network models under both Markov chain Monte Carlo (MCMC) and Bayesian Dark Knowledge (BDK) inference approximations. We characterize the robustness of each method to two types of adversarial attacks: the fast gradient sign me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,048
2410.22482	Heterogeneous Team Coordination on Partially Observable Graphs with Realistic Communication	Team Coordination on Graphs with Risky Edges (\textsc{tcgre}) is a recently proposed problem, in which robots find paths to their goals while considering possible coordination to reduce overall team cost. However, \textsc{tcgre} assumes that the \emph{entire} environment is available to a \emph{homogeneous} robot team ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	503,647
2112.12792	Understanding and Measuring Robustness of Multimodal Learning	The modern digital world is increasingly becoming multimodal. Although multimodal learning has recently revolutionized the state-of-the-art performance in multimodal tasks, relatively little is known about the robustness of multimodal learning in an adversarial setting. In this paper, we introduce a comprehensive measu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	273,054
2007.00649	Group Ensemble: Learning an Ensemble of ConvNets in a single ConvNet	Ensemble learning is a general technique to improve accuracy in machine learning. However, the heavy computation of a ConvNets ensemble limits its usage in deep learning. In this paper, we present Group Ensemble Network (GENet), an architecture incorporating an ensemble of ConvNets in a single ConvNet. Through a shared...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	185,172
0909.5166	An Algorithm for Mining Multidimensional Fuzzy Association Rules	Multidimensional association rule mining searches for interesting relationship among the values from different dimensions or attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be pa...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	4,590
2007.02759	Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial	Intelligent reflecting surface (IRS) is an enabling technology to engineer the radio signal prorogation in wireless networks. By smartly tuning the signal reflection via a large number of low-cost passive reflecting elements, IRS is capable of dynamically altering wireless channels to enhance the communication performa...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	185,847
2311.04614	LuminanceL1Loss: A loss function which measures percieved brightness and colour differences	We introduce LuminanceL1Loss, a novel loss function designed to enhance the performance of image restoration tasks. We demonstrate its superiority over MSE when applied to the Retinexformer, BUIFD and DnCNN architectures. Our proposed LuminanceL1Loss leverages a unique approach by transforming images into grayscale and...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	406,294
2006.10976	Real-time Monitoring and Early Warning Analysis of Urban Railway Operation Based on Multi-parameter Vital Signs of Subway Drivers in Plateau Environment	In order to ensure the personal safety of the drivers and passengers of rail transit in plateau environment, the vital signs and train conditions of the drivers and passengers are taken as the research object, and the dynamic relationship between them is studied and analyzed. In this paper, subway drivers under normal ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	183,068
2304.11015	DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction	There is currently a significant gap between the performance of fine-tuned models and prompting approaches using Large Language Models (LLMs) on the challenging task of text-to-SQL, as evaluated on datasets such as Spider. To improve the performance of LLMs in the reasoning process, we study how decomposing the task in...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	true	false	359,635
2112.12650	Distilling the Knowledge of Romanian BERTs Using Multiple Teachers	Running large-scale pre-trained language models in computationally constrained environments remains a challenging problem yet to be addressed, while transfer learning from these models has become prevalent in Natural Language Processing tasks. Several solutions, including knowledge distillation, network quantization, o...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	273,023
1706.08514	Well-supported phylogenies using largest subsets of core-genes by discrete particle swarm optimization	The number of complete chloroplastic genomes increases day after day, making it possible to rethink plants phylogeny at the biomolecular era. Given a set of close plants sharing in the order of one hundred of core chloroplastic genes, this article focuses on how to extract the largest subset of sequences in order to ob...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	76,004
1906.11521	Lattice-Based Unsupervised Test-Time Adaptation of Neural Network Acoustic Models	Acoustic model adaptation to unseen test recordings aims to reduce the mismatch between training and testing conditions. Most adaptation schemes for neural network models require the use of an initial one-best transcription for the test data, generated by an unadapted model, in order to estimate the adaptation transfor...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	136,687
2410.13899	Security of and by Generative AI platforms	This whitepaper highlights the dual importance of securing generative AI (genAI) platforms and leveraging genAI for cybersecurity. As genAI technologies proliferate, their misuse poses significant risks, including data breaches, model tampering, and malicious content generation. Securing these platforms is critical to ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	499,764
1902.01718	End-to-End Open-Domain Question Answering with BERTserini	We demonstrate an end-to-end question answering system that integrates BERT with the open-source Anserini information retrieval toolkit. In contrast to most question answering and reading comprehension models today, which operate over small amounts of input text, our system integrates best practices from IR with a BERT...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	120,717
2108.06890	GC-TTS: Few-shot Speaker Adaptation with Geometric Constraints	Few-shot speaker adaptation is a specific Text-to-Speech (TTS) system that aims to reproduce a novel speaker's voice with a few training data. While numerous attempts have been made to the few-shot speaker adaptation system, there is still a gap in terms of speaker similarity to the target speaker depending on the amou...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,765
1812.04951	The FLUXCOM ensemble of global land-atmosphere energy fluxes	Although a key driver of Earth's climate system, global land-atmosphere energy fluxes are poorly constrained. Here we use machine learning to merge energy flux measurements from FLUXNET eddy covariance towers with remote sensing and meteorological data to estimate net radiation, latent and sensible heat and their uncer...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	116,322
2110.05283	Phase Collapse in Neural Networks	Deep convolutional classifiers linearly separate image classes and improve accuracy as depth increases. They progressively reduce the spatial dimension whereas the number of channels grows with depth. Spatial variability is therefore transformed into variability along channels. A fundamental challenge is to understand ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,227
2306.09490	Attention-based Open RAN Slice Management using Deep Reinforcement Learning	As emerging networks such as Open Radio Access Networks (O-RAN) and 5G continue to grow, the demand for various services with different requirements is increasing. Network slicing has emerged as a potential solution to address the different service requirements. However, managing network slices while maintaining qualit...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	373,853
2106.08122	Sequence-Level Training for Non-Autoregressive Neural Machine Translation	In recent years, Neural Machine Translation (NMT) has achieved notable results in various translation tasks. However, the word-by-word generation manner determined by the autoregressive mechanism leads to high translation latency of the NMT and restricts its low-latency applications. Non-Autoregressive Neural Machine T...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	241,192
2010.13418	Residual Recurrent CRNN for End-to-End Optical Music Recognition on Monophonic Scores	One of the challenges of the Optical Music Recognition task is to transcript the symbols of the camera-captured images into digital music notations. Previous end-to-end model which was developed as a Convolutional Recurrent Neural Network does not explore sufficient contextual information from full scales and there is ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	203,125
2109.04778	Improving Multilingual Translation by Representation and Gradient Regularization	Multilingual Neural Machine Translation (NMT) enables one model to serve all translation directions, including ones that are unseen during training, i.e. zero-shot translation. Despite being theoretically attractive, current models often produce low quality translations -- commonly failing to even produce outputs in th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	254,536
2009.07432	Surgical Video Motion Magnification with Suppression of Instrument Artefacts	Video motion magnification could directly highlight subsurface blood vessels in endoscopic video in order to prevent inadvertent damage and bleeding. Applying motion filters to the full surgical image is however sensitive to residual motion from the surgical instruments and can impede practical application due to aberr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	195,921
1507.08429	Multilinear Map Layer: Prediction Regularization by Structural Constraint	In this paper we propose and study a technique to impose structural constraints on the output of a neural network, which can reduce amount of computation and number of parameters besides improving prediction accuracy when the output is known to approximately conform to the low-rankness prior. The technique proceeds by ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,567
2102.11638	Enhancing Data-Free Adversarial Distillation with Activation Regularization and Virtual Interpolation	Knowledge distillation refers to a technique of transferring the knowledge from a large learned model or an ensemble of learned models to a small model. This method relies on access to the original training set, which might not always be available. A possible solution is a data-free adversarial distillation framework, ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	221,485
2304.05646	Breaking Modality Disparity: Harmonized Representation for Infrared and Visible Image Registration	Since the differences in viewing range, resolution and relative position, the multi-modality sensing module composed of infrared and visible cameras needs to be registered so as to have more accurate scene perception. In practice, manual calibration-based registration is the most widely used process, and it is regularl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,703
2403.20216	Distributed agency in second language learning and teaching through generative AI	Generative AI offers significant opportunities for language learning. Tools like ChatGPT can provide informal second language practice through chats in written or voice forms, with the learner specifying through prompts conversational parameters such as proficiency level, language register, and discussion topics. AI ca...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	442,665
1907.10209	Mixed-Supervised Dual-Network for Medical Image Segmentation	Deep learning based medical image segmentation models usually require large datasets with high-quality dense segmentations to train, which are very time-consuming and expensive to prepare. One way to tackle this challenge is by using the mixed-supervised learning framework, in which only a part of data is densely annot...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	139,559
2408.05398	PersonViT: Large-scale Self-supervised Vision Transformer for Person Re-Identification	Person Re-Identification (ReID) aims to retrieve relevant individuals in non-overlapping camera images and has a wide range of applications in the field of public safety. In recent years, with the development of Vision Transformer (ViT) and self-supervised learning techniques, the performance of person ReID based on se...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,764
2405.05549	Intelligent Reflecting Surface Aided AirComp: Multi-Timescale Design and Performance Analysis	The integration of intelligent reflecting surface (IRS) into over-the-air computation (AirComp) is an effective solution for reducing the computational mean squared error (MSE) via its high passive beamforming gain. Prior works on IRS aided AirComp generally rely on the full instantaneous channel state information (I-C...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	452,962
2401.10843	Training a General Spiking Neural Network with Improved Efficiency and Minimum Latency	Spiking Neural Networks (SNNs) that operate in an event-driven manner and employ binary spike representation have recently emerged as promising candidates for energy-efficient computing. However, a cost bottleneck arises in obtaining high-performance SNNs: training a SNN model requires a large number of time steps in a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	422,793
2010.02616	On the Interplay Between Fine-tuning and Sentence-level Probing for Linguistic Knowledge in Pre-trained Transformers	Fine-tuning pre-trained contextualized embedding models has become an integral part of the NLP pipeline. At the same time, probing has emerged as a way to investigate the linguistic knowledge captured by pre-trained models. Very little is, however, understood about how fine-tuning affects the representations of pre-tra...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	199,105
1811.12127	Scaling up Probabilistic Inference in Linear and Non-Linear Hybrid Domains by Leveraging Knowledge Compilation	Weighted model integration (WMI) extends weighted model counting (WMC) in providing a computational abstraction for probabilistic inference in mixed discrete-continuous domains. WMC has emerged as an assembly language for state-of-the-art reasoning in Bayesian networks, factor graphs, probabilistic programs and probabi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	114,938
2405.19285	MASSIVE Multilingual Abstract Meaning Representation: A Dataset and Baselines for Hallucination Detection	Abstract Meaning Representation (AMR) is a semantic formalism that captures the core meaning of an utterance. There has been substantial work developing AMR corpora in English and more recently across languages, though the limited size of existing datasets and the cost of collecting more annotations are prohibitive. Wi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	458,825
2410.14475	Enhancing Cryptocurrency Market Forecasting: Advanced Machine Learning Techniques and Industrial Engineering Contributions	Cryptocurrencies, as decentralized digital assets, have experienced rapid growth and adoption, with over 23,000 cryptocurrencies and a market capitalization nearing \$1.1 trillion (about \$3,400 per person in the US) as of 2023. This dynamic market presents significant opportunities and risks, highlighting the need for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	500,038
2310.01202	Unified Uncertainty Calibration	To build robust, fair, and safe AI systems, we would like our classifiers to say ``I don't know'' when facing test examples that are difficult or fall outside of the training classes.The ubiquitous strategy to predict under uncertainty is the simplistic \emph{reject-or-classify} rule: abstain from prediction if epistem...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	396,319
2203.07302	Mixed Evidence for Gestalt Grouping in Deep Neural Networks	Gestalt psychologists have identified a range of conditions in which humans organize elements of a scene into a group or whole, and perceptual grouping principles play an essential role in scene perception and object identification. Recently, Deep Neural Networks (DNNs) trained on natural images (ImageNet) have been pr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	285,389
2006.07119	Learning Diverse Representations for Fast Adaptation to Distribution Shift	The i.i.d. assumption is a useful idealization that underpins many successful approaches to supervised machine learning. However, its violation can lead to models that learn to exploit spurious correlations in the training data, rendering them vulnerable to adversarial interventions, undermining their reliability, and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,695
2005.03228	Collective Loss Function for Positive and Unlabeled Learning	People learn to discriminate between classes without explicit exposure to negative examples. On the contrary, traditional machine learning algorithms often rely on negative examples, otherwise the model would be prone to collapse and always-true predictions. Therefore, it is crucial to design the learning objective whi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	176,096
2111.05825	A Two-Stage Approach towards Generalization in Knowledge Base Question Answering	Most existing approaches for Knowledge Base Question Answering (KBQA) focus on a specific underlying knowledge base either because of inherent assumptions in the approach, or because evaluating it on a different knowledge base requires non-trivial changes. However, many popular knowledge bases share similarities in the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	265,891
2211.02432	RCDPT: Radar-Camera fusion Dense Prediction Transformer	Recently, transformer networks have outperformed traditional deep neural networks in natural language processing and show a large potential in many computer vision tasks compared to convolutional backbones. In the original transformer, readout tokens are used as designated vectors for aggregating information from other...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	328,580
2406.17420	Real-Time Remote Control via VR over Limited Wireless Connectivity	This work introduces a solution to enhance human-robot interaction over limited wireless connectivity. The goal is toenable remote control of a robot through a virtual reality (VR)interface, ensuring a smooth transition to autonomous mode in the event of connectivity loss. The VR interface provides accessto a dynamic 3...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	467,565
2112.07334	OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval	Articulated objects are pervasive in daily life. However, due to the intrinsic high-DoF structure, the joint states of the articulated objects are hard to be estimated. To model articulated objects, two kinds of shape deformations namely the geometric and the pose deformation should be considered. In this work, we pres...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	271,449
2308.09934	Joint User Association and Transmission Scheduling in Integrated mmWave Access and Terahertz Backhaul Networks	Terahertz wireless backhaul is expected to meet the high-speed backhaul requirements of future ultra-dense networks using millimeter-wave (mmWave) base stations (BSs). In order to achieve higher network capacity with limited resources and meet the quality of service (QoS) requirements of more users in the integrated mm...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	386,492
1803.05942	Adaptive Tube-based Nonlinear MPC for Ecological Autonomous Cruise Control of Plug-in Hybrid Electric Vehicles	This paper proposes an adaptive tube-based nonlinear model predictive control (AT-NMPC) approach to the design of autonomous cruise control (ACC) systems. The proposed method utilizes two separate models to define the constrained receding horizon optimal control problem. A fixed nominal model is used to handle the prob...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	92,739
1603.08262	Towards Machine Intelligence	There exists a theory of a single general-purpose learning algorithm which could explain the principles of its operation. This theory assumes that the brain has some initial rough architecture, a small library of simple innate circuits which are prewired at birth and proposes that all significant mental algorithms can ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	53,756
2302.00482	Improving and generalizing flow-based generative models with minibatch optimal transport	Continuous normalizing flows (CNFs) are an attractive generative modeling technique, but they have been held back by limitations in their simulation-based maximum likelihood training. We introduce the generalized conditional flow matching (CFM) technique, a family of simulation-free training objectives for CNFs. CFM fe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,227
2411.08509	Sum Rate Maximization for Movable Antenna-Aided Downlink RSMA Systems	Rate splitting multiple access (RSMA) is regarded as a crucial and powerful physical layer (PHY) paradigm for next-generation communication systems. Particularly, users employ successive interference cancellation (SIC) to decode part of the interference while treating the remainder as noise. However, conventional RSMA ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	507,914
2204.05905	Few-shot Forgery Detection via Guided Adversarial Interpolation	The increase in face manipulation models has led to a critical issue in society - the synthesis of realistic visual media. With the emergence of new forgery approaches at an unprecedented rate, existing forgery detection methods suffer from significant performance drops when applied to unseen novel forgery approaches. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	291,180
2101.11885	Causality and independence in perfectly adapted dynamical systems	Perfect adaptation in a dynamical system is the phenomenon that one or more variables have an initial transient response to a persistent change in an external stimulus but revert to their original value as the system converges to equilibrium. With the help of the causal ordering algorithm, one can construct graphical r...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	217,418
1601.04071	Hidden geometric correlations in real multiplex networks	Real networks often form interacting parts of larger and more complex systems. Examples can be found in different domains, ranging from the Internet to structural and functional brain networks. Here, we show that these multiplex systems are not random combinations of single network layers. Instead, they are organized i...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	50,975
2311.13015	Fast and Interpretable Mortality Risk Scores for Critical Care Patients	Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these two categories by building on modern interpretable ML te...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	409,587
2312.02153	Aligning and Prompting Everything All at Once for Universal Visual Perception	Vision foundation models have been explored recently to build general-purpose vision systems. However, predominant paradigms, driven by casting instance-level tasks as an object-word alignment, bring heavy cross-modality interaction, which is not effective in prompting object detection and visual grounding. Another lin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,720
2207.00221	VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations	Vision-Language Pretraining (VLP) models have recently successfully facilitated many cross-modal downstream tasks. Most existing works evaluated their systems by comparing the fine-tuned downstream task performance. However, only average downstream task accuracy provides little information about the pros and cons of ea...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	305,687
2203.13607	Fast and computationally efficient generative adversarial network algorithm for unmanned aerial vehicle-based network coverage optimization	The challenge of dynamic traffic demand in mobile networks is tackled by moving cells based on unmanned aerial vehicles. Considering the tremendous potential of unmanned aerial vehicles in the future, we propose a new heuristic algorithm for coverage optimization. The proposed algorithm is implemented based on a condit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	287,695
2109.10521	Incorporating Data Uncertainty in Object Tracking Algorithms	Methodologies for incorporating the uncertainties characteristic of data-driven object detectors into object tracking algorithms are explored. Object tracking methods rely on measurement error models, typically in the form of measurement noise, false positive rates, and missed detection rates. Each of these quantities,...	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	256,653
2008.05742	SkeletonNet: A Topology-Preserving Solution for Learning Mesh Reconstruction of Object Surfaces from RGB Images	This paper focuses on the challenging task of learning 3D object surface reconstructions from RGB images. Existingmethods achieve varying degrees of success by using different surface representations. However, they all have their own drawbacks,and cannot properly reconstruct the surface shapes of complex topologies, ar...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,599
2303.05308	SpyroPose: SE(3) Pyramids for Object Pose Distribution Estimation	Object pose estimation is a core computer vision problem and often an essential component in robotics. Pose estimation is usually approached by seeking the single best estimate of an object's pose, but this approach is ill-suited for tasks involving visual ambiguity. In such cases it is desirable to estimate the uncert...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	350,417
2406.11767	Stein Variational Ergodic Search	Exploration requires that robots reason about numerous ways to cover a space in response to dynamically changing conditions. However, in continuous domains there are potentially infinitely many options for robots to explore which can prove computationally challenging. How then should a robot efficiently optimize and ch...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	465,044
2305.18358	DataChat: Prototyping a Conversational Agent for Dataset Search and Visualization	Data users need relevant context and research expertise to effectively search for and identify relevant datasets. Leading data providers, such as the Inter-university Consortium for Political and Social Research (ICPSR), offer standardized metadata and search tools to support data search. Metadata standards emphasize t...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	368,982
2107.00184	Bilinear Scoring Function Search for Knowledge Graph Learning	Learning embeddings for entities and relations in knowledge graph (KG) have benefited many downstream tasks. In recent years, scoring functions, the crux of KG learning, have been human-designed to measure the plausibility of triples and capture different kinds of relations in KGs. However, as relations exhibit intrica...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	244,066
1603.06743	Localized Lasso for High-Dimensional Regression	We introduce the localized Lasso, which is suited for learning models that are both interpretable and have a high predictive power in problems with high dimensionality $d$ and small sample size $n$. More specifically, we consider a function defined by local sparse models, one at each data point. We introduce sample-wis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	53,535
2205.05429	Learning a Better Control Barrier Function	Control barrier functions (CBFs) are widely used in safety-critical controllers. However, constructing a valid CBF is challenging, especially under nonlinear or non-convex constraints and for high relative degree systems. Meanwhile, finding a conservative CBF that only recovers a portion of the true safe set is usually...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	295,927
2005.10149	Discriminative Dictionary Design for Action Classification in Still Images and Videos	In this paper, we address the problem of action recognition from still images and videos. Traditional local features such as SIFT, STIP etc. invariably pose two potential problems: 1) they are not evenly distributed in different entities of a given category and 2) many of such features are not exclusive of the visual c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,104
2501.14704	Stroke classification using Virtual Hybrid Edge Detection from in silico electrical impedance tomography data	Electrical impedance tomography (EIT) is a non-invasive imaging method for recovering the internal conductivity of a physical body from electric boundary measurements. EIT combined with machine learning has shown promise for the classification of strokes. However, most previous works have used raw EIT voltage data as n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	527,223
2108.02452	VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild	We present VoxelTrack for multi-person 3D pose estimation and tracking from a few cameras which are separated by wide baselines. It employs a multi-branch network to jointly estimate 3D poses and re-identification (Re-ID) features for all people in the environment. In contrast to previous efforts which require to estab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,333
2502.11877	JoLT: Joint Probabilistic Predictions on Tabular Data Using LLMs	We introduce a simple method for probabilistic predictions on tabular data based on Large Language Models (LLMs) called JoLT (Joint LLM Process for Tabular data). JoLT uses the in-context learning capabilities of LLMs to define joint distributions over tabular data conditioned on user-specified side information about t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,581
1503.00040	Efficient Upsampling of Natural Images	We propose a novel method of efficient upsampling of a single natural image. Current methods for image upsampling tend to produce high-resolution images with either blurry salient edges, or loss of fine textural detail, or spurious noise artifacts. In our method, we mitigate these effects by modeling the input image ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	40,653
1701.06717	Lower Bounds on the Complexity of Solving Two Classes of Non-cooperative Games	This paper studies the complexity of solving two classes of non-cooperative games in a distributed manner in which the players communicate with a set of system nodes over noisy communication channels. The complexity of solving each game class is defined as the minimum number of iterations required to find a Nash equili...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,186
2307.02009	Using Data Augmentations and VTLN to Reduce Bias in Dutch End-to-End Speech Recognition Systems	Speech technology has improved greatly for norm speakers, i.e., adult native speakers of a language without speech impediments or strong accents. However, non-norm or diverse speaker groups show a distinct performance gap with norm speakers, which we refer to as bias. In this work, we aim to reduce bias against differe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	377,551
2205.02764	Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing	The Metaverse is a virtual environment where users are represented by avatars to navigate a virtual world, which has strong links with the physical one. State-of-the-art Metaverse architectures rely on a cloud-based approach for avatar physics emulation and graphics rendering computation. Such centralized design is unf...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	true	295,052
1607.07295	Learning Aligned Cross-Modal Representations from Weakly Aligned Data	People can recognize scenes across many different modalities beyond natural images. In this paper, we investigate how to learn cross-modal scene representations that transfer across modalities. To study this problem, we introduce a new cross-modal scene dataset. While convolutional neural networks can categorize cross-...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,003
2008.01679	Applying Incremental Deep Neural Networks-based Posture Recognition Model for Injury Risk Assessment in Construction	Monitoring awkward postures is a proactive prevention for Musculoskeletal Disorders (MSDs)in construction. Machine Learning (ML) models have shown promising results for posture recognition from Wearable Sensors. However, further investigations are needed concerning: i) Incremental Learning (IL), where trained models ad...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	190,408
2203.13551	Feature extraction using Spectral Clustering for Gene Function Prediction using Hierarchical Multi-label Classification	Gene annotation addresses the problem of predicting unknown associations between gene and functions (e.g., biological processes) of a specific organism. Despite recent advances, the cost and time demanded by annotation procedures that rely largely on in vivo biological experiments remain prohibitively high. This paper ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,674
2007.09699	Improving the HardNet Descriptor	In the thesis we consider the problem of local feature descriptor learning for wide baseline stereo focusing on the HardNet descriptor, which is close to state-of-the-art. AMOS Patches dataset is introduced, which improves robustness to illumination and appearance changes. It is based on registered images from selected...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	188,044
2110.05983	Network-Aware Flexibility Requests for Distribution-Level Flexibility Markets	This paper proposes a method to design network-aware flexibility requests for local flexibility markets. These markets are becoming increasingly important for distribution system operators (DSOs) to ensure grid safety while minimizing costs and public opposition to new network investments. Despite extended recent liter...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	260,464
1904.03275	Robust Subspace Recovery with Adversarial Outliers	We study the problem of robust subspace recovery (RSR) in the presence of adversarial outliers. That is, we seek a subspace that contains a large portion of a dataset when some fraction of the data points are arbitrarily corrupted. We first examine a theoretical estimator that is intractable to calculate and use it to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,658
2404.00890	Development of Musculoskeletal Legs with Planar Interskeletal Structures to Realize Human Comparable Moving Function	Musculoskeletal humanoids have been developed by imitating humans and expected to perform natural and dynamic motions as well as humans. To achieve desired motions stably in current musculoskeletal humanoids is not easy because they cannot maintain the sufficient moment arm of muscles in various postures. In this resea...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	443,150
2105.09188	High-Resolution Photorealistic Image Translation in Real-Time: A Laplacian Pyramid Translation Network	Existing image-to-image translation (I2IT) methods are either constrained to low-resolution images or long inference time due to their heavy computational burden on the convolution of high-resolution feature maps. In this paper, we focus on speeding-up the high-resolution photorealistic I2IT tasks based on closed-form ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,997
1810.05250	Measuring Sample Path Causal Influences with Relative Entropy	We present a sample path dependent measure of causal influence between time series. The proposed causal measure is a random sequence, a realization of which enables identification of specific patterns that give rise to high levels of causal influence. We show that these patterns cannot be identified by existing measure...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	110,192
1708.00672	Action recognition by learning pose representations	Pose detection is one of the fundamental steps for the recognition of human actions. In this paper we propose a novel trainable detector for recognizing human poses based on the analysis of the skeleton. The main idea is that a skeleton pose can be described by the spatial arrangements of its joints. Starting from this...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,254
cs/0005027	A Bayesian Reflection on Surfaces	The topic of this paper is a novel Bayesian continuous-basis field representation and inference framework. Within this paper several problems are solved: The maximally informative inference of continuous-basis fields, that is where the basis for the field is itself a continuous object and not representable in a finite ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	537,111
1909.04485	VACL: Variance-Aware Cross-Layer Regularization for Pruning Deep Residual Networks	Improving weight sparsity is a common strategy for producing light-weight deep neural networks. However, pruning models with residual learning is more challenging. In this paper, we introduce Variance-Aware Cross-Layer (VACL), a novel approach to address this problem. VACL consists of two parts, a Cross-Layer grouping ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	144,815
2409.14526	What Are They Doing? Joint Audio-Speech Co-Reasoning	In audio and speech processing, tasks usually focus on either the audio or speech modality, even when both sounds and human speech are present in the same audio clip. Recent Auditory Large Language Models (ALLMs) have made it possible to process audio and speech simultaneously within a single model, leading to further ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	490,507
2008.03215	Autonomous Six-Degree-of-Freedom Spacecraft Docking Maneuvers via Reinforcement Learning	A policy for six-degree-of-freedom docking maneuvers is developed through reinforcement learning and implemented as a feedback control law. Reinforcement learning provides a potential framework for robust, autonomous maneuvers in uncertain environments with low on-board computational cost. Specifically, proximal policy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	190,839
2104.09190	Credibility Analysis in Social Big Data	The concept of social trust has attracted an attention of information processors/data scientists and information consumers / business firms. One of the main reasons for acquiring the value of SBD is to provide frameworks and methodologies using which the credibility of online social services users can be evaluated. The...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	231,144
1912.12817	An End-to-End Joint Learning Scheme of Image Compression and Quality Enhancement with Improved Entropy Minimization	Recently, learned image compression methods have been actively studied. Among them, entropy-minimization based approaches have achieved superior results compared to conventional image codecs such as BPG and JPEG2000. However, the quality enhancement and rate-minimization are conflictively coupled in the process of imag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,937
2302.10511	MVFusion: Multi-View 3D Object Detection with Semantic-aligned Radar and Camera Fusion	Multi-view radar-camera fused 3D object detection provides a farther detection range and more helpful features for autonomous driving, especially under adverse weather. The current radar-camera fusion methods deliver kinds of designs to fuse radar information with camera data. However, these fusion approaches usually a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	346,839
2501.04304	DGQ: Distribution-Aware Group Quantization for Text-to-Image Diffusion Models	Despite the widespread use of text-to-image diffusion models across various tasks, their computational and memory demands limit practical applications. To mitigate this issue, quantization of diffusion models has been explored. It reduces memory usage and computational costs by compressing weights and activations into ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	523,174
1209.0061	Compensation of IQ-Imbalance and Phase Noise in MIMO-OFDM Systems	The degrading effect of RF impairments on the performance of wireless communication systems is more pronounced in MIMO-OFDM transmission. Two of the most common impairments that significantly limit the performance of MIMO-OFDM transceivers are IQ-imbalance and phase noise. Low-complexity estimation and compensation tec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,340
1612.02493	Research on the Multiple Feature Fusion Image Retrieval Algorithm based on Texture Feature and Rough Set Theory	Recently, we have witnessed the explosive growth of images with complex information and content. In order to effectively and precisely retrieve desired images from a large-scale image database with low time-consuming, we propose the multiple feature fusion image retrieval algorithm based on the texture feature and roug...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,234
2109.07760	Learning Observation-Based Certifiable Safe Policy for Decentralized Multi-Robot Navigation	Safety is of great importance in multi-robot navigation problems. In this paper, we propose a control barrier function (CBF) based optimizer that ensures robot safety with both high probability and flexibility, using only sensor measurement. The optimizer takes action commands from the policy network as initial values ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	255,644
2402.17403	Sora Generates Videos with Stunning Geometrical Consistency	The recently developed Sora model [1] has exhibited remarkable capabilities in video generation, sparking intense discussions regarding its ability to simulate real-world phenomena. Despite its growing popularity, there is a lack of established metrics to evaluate its fidelity to real-world physics quantitatively. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,973
2202.02085	SignSGD: Fault-Tolerance to Blind and Byzantine Adversaries	Distributed learning has become a necessity for training ever-growing models by sharing calculation among several devices. However, some of the devices can be faulty, deliberately or not, preventing the proper convergence. As a matter of fact, the baseline distributed SGD algorithm does not converge in the presence of ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,692
2412.07031	Large Language Models: An Applied Econometric Framework	How can we use the novel capacities of large language models (LLMs) in empirical research? And how can we do so while accounting for their limitations, which are themselves only poorly understood? We develop an econometric framework to answer this question that distinguishes between two types of empirical tasks. Using ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	515,481
2102.13064	LES: Locally Exploitative Sampling for Robot Path Planning	Sampling-based algorithms solve the path planning problem by generating random samples in the search-space and incrementally growing a connectivity graph or a tree. Conventionally, the sampling strategy used in these algorithms is biased towards exploration to acquire information about the search-space. In contrast, th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	221,935

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