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
2306.08242	Quantum interactive proofs using quantum energy teleportation	We present a simple quantum interactive proof (QIP) protocol using the quantum state teleportation (QST) and quantum energy teleportation (QET) protocols. QET is a technique that allows a receiver at a distance to extract the local energy by local operations and classical communication (LOCC), using the energy injected...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	373,337
2202.11961	"Is not the truth the truth?": Analyzing the Impact of User Validations for Bus In/Out Detection in Smartphone-based Surveys	Passenger flow allows the study of users' behavior through the public network and assists in designing new facilities and services. This flow is observed through interactions between passengers and infrastructure. For this task, Bluetooth technology and smartphones represent the ideal solution. The latter component all...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	282,068
2110.07305	DI-AA: An Interpretable White-box Attack for Fooling Deep Neural Networks	White-box Adversarial Example (AE) attacks towards Deep Neural Networks (DNNs) have a more powerful destructive capacity than black-box AE attacks in the fields of AE strategies. However, almost all the white-box approaches lack interpretation from the point of view of DNNs. That is, adversaries did not investigate the...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	260,933
2310.19630	Convolutional Neural Networks for Automatic Detection of Intact Adenovirus from TEM Imaging with Debris, Broken and Artefacts Particles	Regular monitoring of the primary particles and purity profiles of a drug product during development and manufacturing processes is essential for manufacturers to avoid product variability and contamination. Transmission electron microscopy (TEM) imaging helps manufacturers predict how changes affect particle character...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	404,062
1704.08821	Active Collaborative Ensemble Tracking	A discriminative ensemble tracker employs multiple classifiers, each of which casts a vote on all of the obtained samples. The votes are then aggregated in an attempt to localize the target object. Such method relies on collective competence and the diversity of the ensemble to approach the target/non-target classifica...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,577
2303.04328	The Novel Adaptive Fractional Order Gradient Decent Algorithms Design via Robust Control	The vanilla fractional order gradient descent may oscillatively converge to a region around the global minimum instead of converging to the exact minimum point, or even diverge, in the case where the objective function is strongly convex. To address this problem, a novel adaptive fractional order gradient descent (AFOG...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,041
2107.03574	On the 4-Adic Complexity of Quaternary Sequences with Ideal Autocorrelation	In this paper, we determine the 4-adic complexity of the balanced quaternary sequences of period $2p$ and $2(2^n-1)$ with ideal autocorrelation defined by Kim et al. (ISIT, pp. 282-285, 2009) and Jang et al. (ISIT, pp. 278-281, 2009), respectively. Our results show that the 4-adic complexity of the quaternary sequences...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	245,191
2501.01424	Object-level Visual Prompts for Compositional Image Generation	We introduce a method for composing object-level visual prompts within a text-to-image diffusion model. Our approach addresses the task of generating semantically coherent compositions across diverse scenes and styles, similar to the versatility and expressiveness offered by text prompts. A key challenge in this task i...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	522,058
1604.07547	Towards Miss Universe Automatic Prediction: The Evening Gown Competition	Can we predict the winner of Miss Universe after watching how they stride down the catwalk during the evening gown competition? Fashion gurus say they can! In our work, we study this question from the perspective of computer vision. In particular, we want to understand whether existing computer vision approaches can be...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	true	55,107
2408.15865	microYOLO: Towards Single-Shot Object Detection on Microcontrollers	This work-in-progress paper presents results on the feasibility of single-shot object detection on microcontrollers using YOLO. Single-shot object detectors like YOLO are widely used, however due to their complexity mainly on larger GPU-based platforms. We present microYOLO, which can be used on Cortex-M based microcon...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	484,103
2402.03792	No-Regret Reinforcement Learning in Smooth MDPs	Obtaining no-regret guarantees for reinforcement learning (RL) in the case of problems with continuous state and/or action spaces is still one of the major open challenges in the field. Recently, a variety of solutions have been proposed, but besides very specific settings, the general problem remains unsolved. In this...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	427,195
2005.08341	Impact of multiple modalities on emotion recognition: investigation into 3d facial landmarks, action units, and physiological data	To fully understand the complexities of human emotion, the integration of multiple physical features from different modalities can be advantageous. Considering this, we present an analysis of 3D facial data, action units, and physiological data as it relates to their impact on emotion recognition. We analyze each modal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	177,586
2305.11908	Sequential Best-Arm Identification with Application to Brain-Computer Interface	A brain-computer interface (BCI) is a technology that enables direct communication between the brain and an external device or computer system. It allows individuals to interact with the device using only their thoughts, and holds immense potential for a wide range of applications in medicine, rehabilitation, and human...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,750
1702.04711	Quantized Compressed Sensing for Partial Random Circulant Matrices	We provide the first analysis of a non-trivial quantization scheme for compressed sensing measurements arising from structured measurements. Specifically, our analysis studies compressed sensing matrices consisting of rows selected at random, without replacement, from a circulant matrix generated by a random subgaussia...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,304
1602.02066	Distributed Fictitious Play for Optimal Behavior of Multi-Agent Systems with Incomplete Information	A multi-agent system operates in an uncertain environment about which agents have different and time varying beliefs that, as time progresses, converge to a common belief. A global utility function that depends on the realized state of the environment and actions of all the agents determines the system's optimal behavi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	51,786
2402.04686	The Influence of Autofocus Lenses in the Camera Calibration Process	Camera calibration is a crucial step in robotics and computer vision. Accurate camera parameters are necessary to achieve robust applications. Nowadays, camera calibration process consists of adjusting a set of data to a pin-hole model, assuming that with a reprojection error close to cero, camera parameters are correc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	427,557
2207.11838	SAVCHOI: Detecting Suspicious Activities using Dense Video Captioning with Human Object Interactions	Detecting suspicious activities in surveillance videos is a longstanding problem in real-time surveillance that leads to difficulties in detecting crimes. Hence, we propose a novel approach for detecting and summarizing suspicious activities in surveillance videos. We have also created ground truth summaries for the UC...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	309,799
2409.02747	Tractable Offline Learning of Regular Decision Processes	This work studies offline Reinforcement Learning (RL) in a class of non-Markovian environments called Regular Decision Processes (RDPs). In RDPs, the unknown dependency of future observations and rewards from the past interactions can be captured by some hidden finite-state automaton. For this reason, many RDP algorith...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	485,825
1705.06401	Towards Robotically Supported Decommissioning of Nuclear Sites	This paper overviews certain radiation detection, perception, and planning challenges for nuclearized robotics that aim to support the waste management and decommissioning mission. To enable the autonomous monitoring, inspection and multi-modal characterization of nuclear sites, we discuss important problems relevant t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	73,631
2404.02043	Cross-lingual Text Classification Transfer: The Case of Ukrainian	Despite the extensive amount of labeled datasets in the NLP text classification field, the persistent imbalance in data availability across various languages remains evident. To support further fair development of NLP models, exploring the possibilities of effective knowledge transfer to new languages is crucial. Ukrai...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	443,697
2408.07522	Optimising MFCC parameters for the automatic detection of respiratory diseases	Voice signals originating from the respiratory tract are utilized as valuable acoustic biomarkers for the diagnosis and assessment of respiratory diseases. Among the employed acoustic features, Mel Frequency Cepstral Coefficients (MFCC) is widely used for automatic analysis, with MFCC extraction commonly relying on def...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	480,620
2102.04321	Monte Carlo Rollout Policy for Recommendation Systems with Dynamic User Behavior	We model online recommendation systems using the hidden Markov multi-state restless multi-armed bandit problem. To solve this we present Monte Carlo rollout policy. We illustrate numerically that Monte Carlo rollout policy performs better than myopic policy for arbitrary transition dynamics with no specific structure. ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	219,073
2407.17946	Quantum-Inspired Evolutionary Algorithms for Feature Subset Selection: A Comprehensive Survey	The clever hybridization of quantum computing concepts and evolutionary algorithms (EAs) resulted in a new field called quantum-inspired evolutionary algorithms (QIEAs). Unlike traditional EAs, QIEAs employ quantum bits to adopt a probabilistic representation of the state of a feature in a given solution. This unpreced...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	476,186
2011.12430	SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition	We tackle the problem of place recognition from point cloud data and introduce a self-attention and orientation encoding network (SOE-Net) that fully explores the relationship between points and incorporates long-range context into point-wise local descriptors. Local information of each point from eight orientations is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	208,150
1904.12654	The Mutex Watershed and its Objective: Efficient, Parameter-Free Graph Partitioning	Image partitioning, or segmentation without semantics, is the task of decomposing an image into distinct segments, or equivalently to detect closed contours. Most prior work either requires seeds, one per segment; or a threshold; or formulates the task as multicut / correlation clustering, an NP-hard problem. Here, we ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	129,188
2407.16884	Cluster Model for parsimonious selection of variables and enhancing Students Employability Prediction	Educational Data Mining (EDM) is a promising field, where data mining is widely used for predicting students performance. One of the most prevalent and recent challenge that higher education faces today is making students skillfully employable. Institutions possess large volume of data; still they are unable to reveal ...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	475,759
2212.05153	Algorithmic progress in computer vision	We investigate algorithmic progress in image classification on ImageNet, perhaps the most well-known test bed for computer vision. We estimate a model, informed by work on neural scaling laws, and infer a decomposition of progress into the scaling of compute, data, and algorithms. Using Shapley values to attribute perf...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	335,689
1403.3109	Sparse Recovery with Linear and Nonlinear Observations: Dependent and Noisy Data	We formulate sparse support recovery as a salient set identification problem and use information-theoretic analyses to characterize the recovery performance and sample complexity. We consider a very general model where we are not restricted to linear models or specific distributions. We state non-asymptotic bounds on r...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	31,541
1504.05651	Distinguishing Cause from Effect Based on Exogeneity	Recent developments in structural equation modeling have produced several methods that can usually distinguish cause from effect in the two-variable case. For that purpose, however, one has to impose substantial structural constraints or smoothness assumptions on the functional causal models. In this paper, we consider...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	42,299
2103.14930	Hyperbolic Geometry is Not Necessary: Lightweight Euclidean-Based Models for Low-Dimensional Knowledge Graph Embeddings	Recent knowledge graph embedding (KGE) models based on hyperbolic geometry have shown great potential in a low-dimensional embedding space. However, the necessity of hyperbolic space in KGE is still questionable, because the calculation based on hyperbolic geometry is much more complicated than Euclidean operations. In...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	227,021
1903.04473	The Past and the Present of the Color Checker Dataset Misuse	The pipelines of digital cameras contain a part for computational color constancy, which aims to remove the influence of the illumination on the scene colors. One of the best known and most widely used benchmark datasets for this problem is the Color Checker dataset. However, due to the improper handling of the black l...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,980
1810.05724	Unpaired High-Resolution and Scalable Style Transfer Using Generative Adversarial Networks	Neural networks have proven their capabilities by outperforming many other approaches on regression or classification tasks on various kinds of data. Other astonishing results have been achieved using neural nets as data generators, especially in settings of generative adversarial networks (GANs). One special applicati...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	110,290
1812.04315	Faster-than-fast NMF using random projections and Nesterov iterations	Random projections have been recently implemented in Nonnegative Matrix Factorization (NMF) to speed-up the NMF computations, with a negligible loss of performance. In this paper, we investigate the effects of such projections when the NMF technique uses the fast Nesterov gradient descent (NeNMF). We experimentally sho...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	116,189
2205.15891	One Policy is Enough: Parallel Exploration with a Single Policy is Near-Optimal for Reward-Free Reinforcement Learning	Although parallelism has been extensively used in reinforcement learning (RL), the quantitative effects of parallel exploration are not well understood theoretically. We study the benefits of simple parallel exploration for reward-free RL in linear Markov decision processes (MDPs) and two-player zero-sum Markov games (...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	299,907
2102.04456	Common Spatial Generative Adversarial Networks based EEG Data Augmentation for Cross-Subject Brain-Computer Interface	The cross-subject application of EEG-based brain-computer interface (BCI) has always been limited by large individual difference and complex characteristics that are difficult to perceive. Therefore, it takes a long time to collect the training data of each user for calibration. Even transfer learning method pre-traini...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,123
2307.09931	DISA: DIfferentiable Similarity Approximation for Universal Multimodal Registration	Multimodal image registration is a challenging but essential step for numerous image-guided procedures. Most registration algorithms rely on the computation of complex, frequently non-differentiable similarity metrics to deal with the appearance discrepancy of anatomical structures between imaging modalities. Recent Ma...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	380,355
1202.3767	Distributed Anytime MAP Inference	We present a distributed anytime algorithm for performing MAP inference in graphical models. The problem is formulated as a linear programming relaxation over the edges of a graph. The resulting program has a constraint structure that allows application of the Dantzig-Wolfe decomposition principle. Subprograms are defi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	14,439
2202.03695	Network Comparison Study of Deep Activation Feature Discriminability with Novel Objects	Feature extraction has always been a critical component of the computer vision field. More recently, state-of-the-art computer visions algorithms have incorporated Deep Neural Networks (DNN) in feature extracting roles, creating Deep Convolutional Activation Features (DeCAF). The transferability of DNN knowledge domain...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,309
2312.03475	Molecule Joint Auto-Encoding: Trajectory Pretraining with 2D and 3D Diffusion	Recently, artificial intelligence for drug discovery has raised increasing interest in both machine learning and chemistry domains. The fundamental building block for drug discovery is molecule geometry and thus, the molecule's geometrical representation is the main bottleneck to better utilize machine learning techniq...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	413,270
2401.12801	Deep Learning-based Target-To-User Association in Integrated Sensing and Communication Systems	In Integrated Sensing and Communication (ISAC) systems, matching the radar targets with communication user equipments (UEs) is functional to several communication tasks, such as proactive handover and beam prediction. In this paper, we consider a radar-assisted communication system where a base station (BS) is equipped...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	423,501
2107.13751	The Cross-Lingual Arabic Information REtrieval (CLAIRE) System	Despite advances in neural machine translation, cross-lingual retrieval tasks in which queries and documents live in different natural language spaces remain challenging. Although neural translation models may provide an intuitive approach to tackle the cross-lingual problem, their resource-consuming training and advan...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	248,292
2403.02573	Learning-augmented Online Minimization of Age of Information and Transmission Costs	We consider a discrete-time system where a resource-constrained source (e.g., a small sensor) transmits its time-sensitive data to a destination over a time-varying wireless channel. Each transmission incurs a fixed transmission cost (e.g., energy cost), and no transmission results in a staleness cost represented by th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,848
2305.01090	Autoencoders for discovering manifold dimension and coordinates in data from complex dynamical systems	While many phenomena in physics and engineering are formally high-dimensional, their long-time dynamics often live on a lower-dimensional manifold. The present work introduces an autoencoder framework that combines implicit regularization with internal linear layers and $L_2$ regularization (weight decay) to automatica...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,548
0909.4830	Super-wavelets versus poly-Bergman spaces	Motivated by potential applications in multiplexing and by recent results on Gabor analysis with Hermite windows due to Gr\"{o}chenig and Lyubarskii, we investigate vector-valued wavelet transforms and vector-valued wavelet frames, which constitute special cases of super-wavelets, with a particular attention to the cas...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,576
2403.02683	Learning to Defer to a Population: A Meta-Learning Approach	The learning to defer (L2D) framework allows autonomous systems to be safe and robust by allocating difficult decisions to a human expert. All existing work on L2D assumes that each expert is well-identified, and if any expert were to change, the system should be re-trained. In this work, we alleviate this constraint, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	434,895
2302.14334	Design of an Adaptive Lightweight LiDAR to Decouple Robot-Camera Geometry	A fundamental challenge in robot perception is the coupling of the sensor pose and robot pose. This has led to research in active vision where robot pose is changed to reorient the sensor to areas of interest for perception. Further, egomotion such as jitter, and external effects such as wind and others affect percepti...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	348,249
2202.05568	On change of measure inequalities for $f$-divergences	We propose new change of measure inequalities based on $f$-divergences (of which the Kullback-Leibler divergence is a particular case). Our strategy relies on combining the Legendre transform of $f$-divergences and the Young-Fenchel inequality. By exploiting these new change of measure inequalities, we derive new PAC-B...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	279,916
2501.19095	PathE: Leveraging Entity-Agnostic Paths for Parameter-Efficient Knowledge Graph Embeddings	Knowledge Graphs (KGs) store human knowledge in the form of entities (nodes) and relations, and are used extensively in various applications. KG embeddings are an effective approach to addressing tasks like knowledge discovery, link prediction, and reasoning. This is often done by allocating and learning embedding tabl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	529,010
1510.03608	Deep convolutional neural networks for pedestrian detection	Pedestrian detection is a popular research topic due to its paramount importance for a number of applications, especially in the fields of automotive, surveillance and robotics. Despite the significant improvements, pedestrian detection is still an open challenge that calls for more and more accurate algorithms. In the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	47,850
2412.07977	Thinking Fast and Laterally: Multi-Agentic Approach for Reasoning about Uncertain Emerging Events	This paper introduces lateral thinking to implement System-2 reasoning capabilities in AI systems, focusing on anticipatory and causal reasoning under uncertainty. We present a framework for systematic generation and modeling of lateral thinking queries and evaluation datasets. We introduce Streaming Agentic Lateral Th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	515,882
2206.00582	The elements of flexibility for task-performing systems	What makes living systems flexible so that they can react quickly and adapt easily to changing environments? This question has not only engaged biologists for decades but is also of great interest to computer scientists and engineers who seek inspiration from nature to increase the flexibility of task-performing system...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	300,178
1007.1708	A Study on the Effectiveness of Different Patch Size and Shape for Eyes and Mouth Detection	Template matching is one of the simplest methods used for eyes and mouth detection. However, it can be modified and extended to become a powerful tool. Since the patch itself plays a significant role in optimizing detection performance, a study on the influence of patch size and shape is carried out. The optimum patch ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	7,032
2206.02134	Toward Sustainable Transportation: Accelerating Vehicle Electrification with Dynamic Charging Deployment	Electric vehicles (EVs) are being actively adopted as a solution to sustainable transportation. However, a bottleneck remains with charging, where two of the main problems are the long charging time and the range anxiety of EV drivers. In this research, we investigate the deployment of dynamic charging systems, i.e., e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	300,763
2309.11814	Micromechanics-Informed Parametric Deep Material Network for Physics Behavior Prediction of Heterogeneous Materials with a Varying Morphology	Deep Material Network (DMN) has recently emerged as a data-driven surrogate model for heterogeneous materials. Given a particular microstructural morphology, the effective linear and nonlinear behaviors can be successfully approximated by such physics-based neural-network like architecture. In this work, a novel microm...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	393,545
2306.07962	Parting with Misconceptions about Learning-based Vehicle Motion Planning	The release of nuPlan marks a new era in vehicle motion planning research, offering the first large-scale real-world dataset and evaluation schemes requiring both precise short-term planning and long-horizon ego-forecasting. Existing systems struggle to simultaneously meet both requirements. Indeed, we find that these ...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	373,221
2205.04819	Massive Enhanced Extracted Email Features Tailored for Cosine Distance	In this paper, the process of converting the Enron email dataset (the version cited in the preprint) to thousands of features per email for a selected set of 2400 labelled emails is explained and evaluated. The final features are tailored for Cosine distance so that the Cosine distance invertly reflect the number of to...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	295,761
1805.10396	An Improved Phrase-based Approach to Annotating and Summarizing Student Course Responses	Teaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged to summarize the student feedback, submitted immediately after each lecture, but it is left to be discovered what makes a good ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,662
2412.04069	ProtDAT: A Unified Framework for Protein Sequence Design from Any Protein Text Description	Protein design has become a critical method in advancing significant potential for various applications such as drug development and enzyme engineering. However, protein design methods utilizing large language models with solely pretraining and fine-tuning struggle to capture relationships in multi-modal protein data. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	514,242
1008.4941	Pairwise Optimal Discrete Coverage Control for Gossiping Robots	We propose distributed algorithms to automatically deploy a group of robotic agents and provide coverage of a discretized environment represented by a graph. The classic Lloyd approach to coverage optimization involves separate centering and partitioning steps and converges to the set of centroidal Voronoi partitions. ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	7,399
2405.02024	Analyzing Narrative Processing in Large Language Models (LLMs): Using GPT4 to test BERT	The ability to transmit and receive complex information via language is unique to humans and is the basis of traditions, culture and versatile social interactions. Through the disruptive introduction of transformer based large language models (LLMs) humans are not the only entity to "understand" and produce language an...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	451,598
2006.10829	Matrix Completion with Quantified Uncertainty through Low Rank Gaussian Copula	Modern large scale datasets are often plagued with missing entries. For tabular data with missing values, a flurry of imputation algorithms solve for a complete matrix which minimizes some penalized reconstruction error. However, almost none of them can estimate the uncertainty of its imputations. This paper proposes a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,011
2308.15055	Taxonomic Loss for Morphological Glossing of Low-Resource Languages	Morpheme glossing is a critical task in automated language documentation and can benefit other downstream applications greatly. While state-of-the-art glossing systems perform very well for languages with large amounts of existing data, it is more difficult to create useful models for low-resource languages. In this pa...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	388,550
2304.03752	V3Det: Vast Vocabulary Visual Detection Dataset	Recent advances in detecting arbitrary objects in the real world are trained and evaluated on object detection datasets with a relatively restricted vocabulary. To facilitate the development of more general visual object detection, we propose V3Det, a vast vocabulary visual detection dataset with precisely annotated bo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,930
2101.07983	Cell image segmentation by Feature Random Enhancement Module	It is important to extract good features using an encoder to realize semantic segmentation with high accuracy. Although loss function is optimized in training deep neural network, far layers from the layers for computing loss function are difficult to train. Skip connection is effective for this problem but there are s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,194
2111.11718	StrokeNet: Stroke Assisted and Hierarchical Graph Reasoning Networks	Scene text detection is still a challenging task, as there may be extremely small or low-resolution strokes, and close or arbitrary-shaped texts. In this paper, StrokeNet is proposed to effectively detect the texts by capturing the fine-grained strokes, and infer structural relations between the hierarchical representa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,751
2104.06644	Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little	A possible explanation for the impressive performance of masked language model (MLM) pre-training is that such models have learned to represent the syntactic structures prevalent in classical NLP pipelines. In this paper, we propose a different explanation: MLMs succeed on downstream tasks almost entirely due to their ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	230,144
2211.08976	Generating Stable and Collision-Free Policies through Lyapunov Function Learning	The need for rapid and reliable robot deployment is on the rise. Imitation Learning (IL) has become popular for producing motion planning policies from a set of demonstrations. However, many methods in IL are not guaranteed to produce stable policies. The generated policy may not converge to the robot target, reducing ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	330,828
2305.01604	The Training Process of Many Deep Networks Explores the Same Low-Dimensional Manifold	We develop information-geometric techniques to analyze the trajectories of the predictions of deep networks during training. By examining the underlying high-dimensional probabilistic models, we reveal that the training process explores an effectively low-dimensional manifold. Networks with a wide range of architecture...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,732
2309.03199	Matcha-TTS: A fast TTS architecture with conditional flow matching	We introduce Matcha-TTS, a new encoder-decoder architecture for speedy TTS acoustic modelling, trained using optimal-transport conditional flow matching (OT-CFM). This yields an ODE-based decoder capable of high output quality in fewer synthesis steps than models trained using score matching. Careful design choices add...	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,300
1810.03966	Adaptive Image Stream Classification via Convolutional Neural Network with Intrinsic Similarity Metrics	When performing data classification over a stream of continuously occurring instances, a key challenge is to develop an open-world classifier that anticipates instances from an unknown class. Studies addressing this problem, typically called novel class detection, have considered classification methods that reactively ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	109,920
2011.03330	Safe trajectory of a piece moved by a robot	In this work, we propose a mathematical model for a physical problem based on the movement of a metal piece held by a robot. Using the principles of Kirchoff plate theory, a set of equations determining stresses and deformations caused during the motion, have been provided. We also discuss possible numerical treatment ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	205,214
2102.13472	A Quantitative Metric for Privacy Leakage in Federated Learning	In the federated learning system, parameter gradients are shared among participants and the central modulator, while the original data never leave their protected source domain. However, the gradient itself might carry enough information for precise inference of the original data. By reporting their parameter gradients...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	222,071
0705.1345	Degree Optimization and Stability Condition for the Min-Sum Decoder	The min-sum (MS) algorithm is arguably the second most fundamental algorithm in the realm of message passing due to its optimality (for a tree code) with respect to the {\em block error} probability \cite{Wiberg}. There also seems to be a fundamental relationship of MS decoding with the linear programming decoder \cite...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	209
1807.05933	Visual Graphs from Motion (VGfM): Scene understanding with object geometry reasoning	Recent approaches on visual scene understanding attempt to build a scene graph -- a computational representation of objects and their pairwise relationships. Such rich semantic representation is very appealing, yet difficult to obtain from a single image, especially when considering complex spatial arrangements in the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	103,021
2211.02753	The Tensor Data Platform: Towards an AI-centric Database System	Database engines have historically absorbed many of the innovations in data processing, adding features to process graph data, XML, object oriented, and text among many others. In this paper, we make the case that it is time to do the same for AI -- but with a twist! While existing approaches have tried to achieve this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	328,684
2101.08540	Activity Graph Transformer for Temporal Action Localization	We introduce Activity Graph Transformer, an end-to-end learnable model for temporal action localization, that receives a video as input and directly predicts a set of action instances that appear in the video. Detecting and localizing action instances in untrimmed videos requires reasoning over multiple action instance...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	216,351
2012.03460	Reprogramming Language Models for Molecular Representation Learning	Recent advancements in transfer learning have made it a promising approach for domain adaptation via transfer of learned representations. This is especially when relevant when alternate tasks have limited samples of well-defined and labeled data, which is common in the molecule data domain. This makes transfer learning...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	210,126
2411.05735	Aioli: A Unified Optimization Framework for Language Model Data Mixing	Language model performance depends on identifying the optimal mixture of data groups to train on (e.g., law, code, math). Prior work has proposed a diverse set of methods to efficiently learn mixture proportions, ranging from fitting regression models over training runs to dynamically updating proportions throughout tr...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	506,767
2308.06834	Diagnostic Reasoning Prompts Reveal the Potential for Large Language Model Interpretability in Medicine	One of the major barriers to using large language models (LLMs) in medicine is the perception they use uninterpretable methods to make clinical decisions that are inherently different from the cognitive processes of clinicians. In this manuscript we develop novel diagnostic reasoning prompts to study whether LLMs can p...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	385,289
2304.02451	Adaptive Data Augmentation for Contrastive Learning	In computer vision, contrastive learning is the most advanced unsupervised learning framework. Yet most previous methods simply apply fixed composition of data augmentations to improve data efficiency, which ignores the changes in their optimal settings over training. Thus, the pre-determined parameters of augmentation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,440
2301.01319	The ReSWARM Microgravity Flight Experiments: Planning, Control, and Model Estimation for On-Orbit Close Proximity Operations	On-orbit close proximity operations involve robotic spacecraft maneuvering and making decisions for a growing number of mission scenarios demanding autonomy, including on-orbit assembly, repair, and astronaut assistance. Of these scenarios, on-orbit assembly is an enabling technology that will allow large space structu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	339,205
2309.09875	RaLF: Flow-based Global and Metric Radar Localization in LiDAR Maps	Localization is paramount for autonomous robots. While camera and LiDAR-based approaches have been extensively investigated, they are affected by adverse illumination and weather conditions. Therefore, radar sensors have recently gained attention due to their intrinsic robustness to such conditions. In this paper, we p...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	392,776
2409.14673	Instruction Tuning Vs. In-Context Learning: Revisiting Large Language Models in Few-Shot Computational Social Science	Real-world applications of large language models (LLMs) in computational social science (CSS) tasks primarily depend on the effectiveness of instruction tuning (IT) or in-context learning (ICL). While IT has shown highly effective at fine-tuning LLMs for various tasks, ICL offers a rapid alternative for task adaptation...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	490,576
2009.08198	Multi-objective dynamic programming with limited precision	This paper addresses the problem of approximating the set of all solutions for Multi-objective Markov Decision Processes. We show that in the vast majority of interesting cases, the number of solutions is exponential or even infinite. In order to overcome this difficulty we propose to approximate the set of all solutio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,164
1902.09191	Improving Neural Response Diversity with Frequency-Aware Cross-Entropy Loss	Sequence-to-Sequence (Seq2Seq) models have achieved encouraging performance on the dialogue response generation task. However, existing Seq2Seq-based response generation methods suffer from a low-diversity problem: they frequently generate generic responses, which make the conversation less interesting. In this paper, ...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	122,366
2410.03959	Grounding Language in Multi-Perspective Referential Communication	We introduce a task and dataset for referring expression generation and comprehension in multi-agent embodied environments. In this task, two agents in a shared scene must take into account one another's visual perspective, which may be different from their own, to both produce and understand references to objects in a...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	495,062
1906.05959	Early Detection of Long Term Evaluation Criteria in Online Controlled Experiments	A common dilemma encountered by many upon implementing an optimization method or experiment, whether it be a reinforcement learning algorithm, or A/B testing, is deciding on what metric to optimize for. Very often short-term metrics, which are easier to measure are chosen over long term metrics which have undesirable t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	135,174
2304.13778	Security Constrained Optimal Power Shutoff	Electric grid faults are increasingly the source of ignition for major wildfires. To reduce the likelihood of such ignitions in high risk situations, utilities use pre-emptive deenergization of power lines, commonly referred to as Public Safety Power Shut-offs (PSPS). Besides raising challenging trade-offs between powe...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	360,701
2311.18608	Contrastive Denoising Score for Text-guided Latent Diffusion Image Editing	With the remarkable advent of text-to-image diffusion models, image editing methods have become more diverse and continue to evolve. A promising recent approach in this realm is Delta Denoising Score (DDS) - an image editing technique based on Score Distillation Sampling (SDS) framework that leverages the rich generati...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	411,742
2201.13073	Learning Representations of Entities and Relations	Encoding facts as representations of entities and binary relationships between them, as learned by knowledge graph representation models, is useful for various tasks, including predicting new facts, question answering, fact checking and information retrieval. The focus of this thesis is on (i) improving knowledge graph...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	277,876
1704.05119	Exploring Sparsity in Recurrent Neural Networks	Recurrent Neural Networks (RNN) are widely used to solve a variety of problems and as the quantity of data and the amount of available compute have increased, so have model sizes. The number of parameters in recent state-of-the-art networks makes them hard to deploy, especially on mobile phones and embedded devices. Th...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	71,939
2211.04987	Interpretable Deep Reinforcement Learning for Green Security Games with Real-Time Information	Green Security Games with real-time information (GSG-I) add the real-time information about the agents' movement to the typical GSG formulation. Prior works on GSG-I have used deep reinforcement learning (DRL) to learn the best policy for the agent in such an environment without any need to store the huge number of sta...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	329,408
2110.15801	Application of the Multi-label Residual Convolutional Neural Network text classifier using Content-Based Routing process	In this article, we will present an NLP application in text classifying process using the content-based router. The ultimate goal throughout this article is to predict the event described by a legal ad from the plain text of the ad. This problem is purely a supervised problem that will involve the use of NLP techniques...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	264,012
1203.0146	Relevant Sampling of Band-limited Functions	We study the random sampling of band-limited functions of several variables. If a bandlimited function with bandwidth one has its essential support on a cube of volume $R^d$, then $\cO (R^d \log R^d)$ random samples suffice to approximate the function up to a given error with high probability.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,677
math/0702804	The Loss Rank Principle for Model Selection	We introduce a new principle for model selection in regression and classification. Many regression models are controlled by some smoothness or flexibility or complexity parameter c, e.g. the number of neighbors to be averaged over in k nearest neighbor (kNN) regression or the polynomial degree in regression with polyno...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	540,744
1908.08289	Trajectory Space Factorization for Deep Video-Based 3D Human Pose Estimation	Existing deep learning approaches on 3d human pose estimation for videos are either based on Recurrent or Convolutional Neural Networks (RNNs or CNNs). However, RNN-based frameworks can only tackle sequences with limited frames because sequential models are sensitive to bad frames and tend to drift over long sequences....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	142,513
1509.08368	Limits of Friendship Networks in Predicting Epidemic Risk	The spread of an infection on a real-world social network is determined by the interplay of two processes: the dynamics of the network, whose structure changes over time according to the encounters between individuals, and the dynamics on the network, whose nodes can infect each other after an encounter. Physical encou...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	47,361
1502.03322	Boost Phrase-level Polarity Labelling with Review-level Sentiment Classification	Sentiment analysis on user reviews helps to keep track of user reactions towards products, and make advices to users about what to buy. State-of-the-art review-level sentiment classification techniques could give pretty good precisions of above 90%. However, current phrase-level sentiment analysis approaches might only...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	40,136
2502.04126	RC Measurement Uncertainty Estimation Method for Directive Antennas and Turntable Stirring	This paper investigates measurement uncertainty in a Reverberation Chamber (RC) within the lower FR2 bands (24.25-29.5 GHz). The study focuses on the impact of several factors contributing to RC measurement uncertainty, including finite sample size, polarization imbalance, and spatial non-uniformity. A series of 24 mea...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	530,992
1611.07596	Fast Fourier Color Constancy	We present Fast Fourier Color Constancy (FFCC), a color constancy algorithm which solves illuminant estimation by reducing it to a spatial localization task on a torus. By operating in the frequency domain, FFCC produces lower error rates than the previous state-of-the-art by 13-20% while being 250-3000 times faster. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	64,373

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.