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
2501.07721	LLMic: Romanian Foundation Language Model	Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks with commercial models leading the way. While open models usually operate at a smaller scale, they maintain competitiveness through specialization and fine-tuning. However, a significant challenge persists: op...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	524,480
2303.11944	Representational Tenets for Memory Athletics	We describe the current state of world-class memory competitions, including the methods used to prepare for and compete in memory competitions, based on the subjective report of World Memory Championship Grandmaster and co-author Nelson Dellis. We then explore the reported experiences through the lens of the Simulated,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	353,076
1810.12210	A Comparative Measurement Study of Deep Learning as a Service Framework	Big data powered Deep Learning (DL) and its applications have blossomed in recent years, fueled by three technological trends: a large amount of digitized data openly accessible, a growing number of DL software frameworks in open source and commercial markets, and a selection of affordable parallel computing hardware d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	111,718
2001.07612	Optimal Dispatch of Electrified Autonomous Mobility on Demand Vehicles during Power Outages	The era of fully autonomous, electrified taxi fleets is rapidly approaching, and with it the opportunity to innovate myriad on-demand services that extend beyond the realm of human mobility. This project envisions a future where autonomous plug-in electric vehicle (PEV) fleets can be dispatched as both a taxi service a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	161,081
1607.04942	Sparse Representation-Based Classification: Orthogonal Least Squares or Orthogonal Matching Pursuit?	Spare representation of signals has received significant attention in recent years. Based on these developments, a sparse representation-based classification (SRC) has been proposed for a variety of classification and related tasks, including face recognition. Recently, a class dependent variant of SRC was proposed to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	58,692
1901.10654	Domain Discrepancy Measure for Complex Models in Unsupervised Domain Adaptation	Appropriately evaluating the discrepancy between domains is essential for the success of unsupervised domain adaptation. In this paper, we first point out that existing discrepancy measures are less informative when complex models such as deep neural networks are used, in addition to the facts that they can be computat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,076
2211.17046	Rationale-Guided Few-Shot Classification to Detect Abusive Language	Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, models trained using these datasets do not perform well in cross-domain evaluation settings. To overcome this, a common strategy is to use a few...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	333,840
1711.05611	Interpreting Deep Visual Representations via Network Dissection	The success of recent deep convolutional neural networks (CNNs) depends on learning hidden representations that can summarize the important factors of variation behind the data. However, CNNs often criticized as being black boxes that lack interpretability, since they have millions of unexplained model parameters. In t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,607
2011.11247	Restricted Airspace Protection using Multi-UAV Spatio-TemporalMulti-Task Allocation	This paper addresses the problem of restricted airspace protection from invaders using the cooperative multi-UAV system. The objective is to detect and capture the invaders cooperatively by a team of homogeneous UAVs (called evaders)before invaders enter the restricted airspace. The problem of restricted airspace prote...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	207,772
1803.09467	A Switch to the Concern of User: Importance Coefficient in Utility Distribution and Message Importance Measure	This paper mainly focuses on the utilization frequency in receiving end of communication systems, which shows the inclination of the user about different symbols. When the average number of use is limited, a specific utility distribution is proposed on the best effort in term of fairness, which is also the closest one ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	93,500
1703.07839	Almost-global tracking for a rigid body with internal rotors	Almost-global orientation trajectory tracking for a rigid body with external actuation has been well studied in the literature, and in the geometric setting as well. The tracking control law relies on the fact that a rigid body is a simple mechanical system (SMS) on the $3-$dimensional group of special orthogonal matri...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	70,463
2401.09050	Consistent3D: Towards Consistent High-Fidelity Text-to-3D Generation with Deterministic Sampling Prior	Score distillation sampling (SDS) and its variants have greatly boosted the development of text-to-3D generation, but are vulnerable to geometry collapse and poor textures yet. To solve this issue, we first deeply analyze the SDS and find that its distillation sampling process indeed corresponds to the trajectory sampl...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	422,132
2310.19509	SparseByteNN: A Novel Mobile Inference Acceleration Framework Based on Fine-Grained Group Sparsity	To address the challenge of increasing network size, researchers have developed sparse models through network pruning. However, maintaining model accuracy while achieving significant speedups on general computing devices remains an open problem. In this paper, we present a novel mobile inference acceleration framework ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	404,015
2009.10263	Semantic Workflows and Machine Learning for the Assessment of Carbon Storage by Urban Trees	Climate science is critical for understanding both the causes and consequences of changes in global temperatures and has become imperative for decisive policy-making. However, climate science studies commonly require addressing complex interoperability issues between data, software, and experimental approaches from mul...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	196,846
1908.11047	Shallow Syntax in Deep Water	Shallow syntax provides an approximation of phrase-syntactic structure of sentences; it can be produced with high accuracy, and is computationally cheap to obtain. We investigate the role of shallow syntax-aware representations for NLP tasks using two techniques. First, we enhance the ELMo architecture to allow pretrai...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	143,279
2207.01204	Adversarial Pairwise Reverse Attention for Camera Performance Imbalance in Person Re-identification: New Dataset and Metrics	Existing evaluation metrics for Person Re-Identification (Person ReID) models focus on system-wide performance. However, our studies reveal weaknesses due to the uneven data distributions among cameras and different camera properties that expose the ReID system to exploitation. In this work, we raise the long-ignored R...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	306,081
2105.01757	A Survey on End-User Robot Programming	As robots interact with a broader range of end-users, end-user robot programming has helped democratize robot programming by empowering end-users who may not have experience in robot programming to customize robots to meet their individual contextual needs. This article surveys work on end-user robot programming, with ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	233,612
2310.07131	Echocardiography video synthesis from end diastolic semantic map via diffusion model	Denoising Diffusion Probabilistic Models (DDPMs) have demonstrated significant achievements in various image and video generation tasks, including the domain of medical imaging. However, generating echocardiography videos based on semantic anatomical information remains an unexplored area of research. This is mostly du...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,834
2408.16287	Measuring the Accuracy of Automatic Speech Recognition Solutions	For d/Deaf and hard of hearing (DHH) people, captioning is an essential accessibility tool. Significant developments in artificial intelligence (AI) mean that Automatic Speech Recognition (ASR) is now a part of many popular applications. This makes creating captions easy and broadly available - but transcription needs ...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	484,273
2104.09708	Distributed nonlinear model predictive control of an autonomous tractor-trailer system	This paper addresses the trajectory tracking problem of an autonomous tractor-trailer system by using a fast distributed nonlinear model predictive control algorithm in combination with nonlinear moving horizon estimation for the state and parameter estimation in which constraints on the inputs and the states can be in...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	231,324
2112.05253	MAGMA -- Multimodal Augmentation of Generative Models through Adapter-based Finetuning	Large-scale pretraining is fast becoming the norm in Vision-Language (VL) modeling. However, prevailing VL approaches are limited by the requirement for labeled data and the use of complex multi-step pretraining objectives. We present MAGMA - a simple method for augmenting generative language models with additional mod...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	270,784
1806.05754	Quantized State Hybrid Automata for Cyber-Physical Systems	Cyber-physical systems involve a network of discrete controllers that control physical processes. Examples range from autonomous cars to implantable medical devices, which are highly safety critical. Hybrid Automata (HA) based formal approach is gaining momentum for the specification and validation of CPS. HA combines ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	100,546
1204.3748	Statistical Multiresolution Estimation for Variational Imaging: With an Application in Poisson-Biophotonics	In this paper we present a spatially-adaptive method for image reconstruction that is based on the concept of statistical multiresolution estimation as introduced in [Frick K, Marnitz P, and Munk A. "Statistical multiresolution Dantzig estimation in imaging: Fundamental concepts and algorithmic framework". Electron. J....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	15,534
2308.04837	A New Family of Perfect Polyphase Sequences with Low Cross-Correlation	Spread spectrum multiple access systems demand minimum possible cross-correlation between the sequences within a set of sequences having good auto-correlation properties. Through a connection between generalised Frank sequences and Florentine arrays, we present a family of perfect sequences with low cross-correlation h...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	384,583
2501.15871	Transient Finite Element Simulation of Accelerator Magnets Using Thermal Thin Shell Approximation	Thermal transient responses of superconducting magnets can be simulated using the finite element (FE) method. Some accelerator magnets use cables whose electric insulation is significantly thinner than the bare electric conductor. The FE discretisation of such geometries with high-quality meshes leads to many degrees o...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	527,741
2207.04136	CompoSuite: A Compositional Reinforcement Learning Benchmark	We present CompoSuite, an open-source simulated robotic manipulation benchmark for compositional multi-task reinforcement learning (RL). Each CompoSuite task requires a particular robot arm to manipulate one individual object to achieve a task objective while avoiding an obstacle. This compositional definition of the t...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	307,086
2208.02369	Deep VULMAN: A Deep Reinforcement Learning-Enabled Cyber Vulnerability Management Framework	Cyber vulnerability management is a critical function of a cybersecurity operations center (CSOC) that helps protect organizations against cyber-attacks on their computer and network systems. Adversaries hold an asymmetric advantage over the CSOC, as the number of deficiencies in these systems is increasing at a signif...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	true	false	false	311,442
1805.05370	AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library	This paper describes our winning contribution to SemEval 2018 Task 4: Character Identification on Multiparty Dialogues. It is a simple, standard model with one key innovation, an entity library. Our results show that this innovation greatly facilitates the identification of infrequent characters. Because of the generic...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	97,406
2211.10439	BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision	We present a novel bird's-eye-view (BEV) detector with perspective supervision, which converges faster and better suits modern image backbones. Existing state-of-the-art BEV detectors are often tied to certain depth pre-trained backbones like VoVNet, hindering the synergy between booming image backbones and BEV detecto...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,310
2410.01537	Attention layers provably solve single-location regression	Attention-based models, such as Transformer, excel across various tasks but lack a comprehensive theoretical understanding, especially regarding token-wise sparsity and internal linear representations. To address this gap, we introduce the single-location regression task, where only one token in a sequence determines t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,814
2306.05582	A newborn embodied Turing test for view-invariant object recognition	Recent progress in artificial intelligence has renewed interest in building machines that learn like animals. Almost all of the work comparing learning across biological and artificial systems comes from studies where animals and machines received different training data, obscuring whether differences between animals a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	372,251
1312.6199	Intriguing properties of neural networks	Deep neural networks are highly expressive models that have recently achieved state of the art performance on speech and visual recognition tasks. While their expressiveness is the reason they succeed, it also causes them to learn uninterpretable solutions that could have counter-intuitive properties. In this paper we ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	29,345
2408.14173	BackFlip: The Impact of Local and Global Data Augmentations on Artistic Image Aesthetic Assessment	Assessing the aesthetic quality of artistic images presents unique challenges due to the subjective nature of aesthetics and the complex visual characteristics inherent to artworks. Basic data augmentation techniques commonly applied to natural images in computer vision may not be suitable for art images in aesthetic e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	483,442
2412.15536	The Impact of Cut Layer Selection in Split Federated Learning	Split Federated Learning (SFL) is a distributed machine learning paradigm that combines federated learning and split learning. In SFL, a neural network is partitioned at a cut layer, with the initial layers deployed on clients and remaining layers on a training server. There are two main variants of SFL: SFL-V1 where t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	519,163
2411.03279	Oblivious Defense in ML Models: Backdoor Removal without Detection	As society grows more reliant on machine learning, ensuring the security of machine learning systems against sophisticated attacks becomes a pressing concern. A recent result of Goldwasser, Kim, Vaikuntanathan, and Zamir (2022) shows that an adversary can plant undetectable backdoors in machine learning models, allowin...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	505,838
1806.03364	Kronecker weights for instability analysis of Markov jump linear systems	In this paper, we analyze the instability of continuous-time Markov jump linear systems. Although there exist several effective criteria for the stability of Markov jump linear systems, there is a lack of methodologies for verifying their instability. In this paper, we present a novel criterion for the exponential mean...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	99,977
2303.07240	PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents	Foundation models trained on large-scale dataset gain a recent surge in CV and NLP. In contrast, development in biomedical domain lags far behind due to data scarcity. To address this issue, we build and release PMC-OA, a biomedical dataset with 1.6M image-caption pairs collected from PubMedCentral's OpenAccess subset,...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	true	351,181
2206.09529	Temporal Link Prediction via Adjusted Sigmoid Function and 2-Simplex Sructure	Temporal network link prediction is an important task in the field of network science, and has a wide range of applications in practical scenarios. Revealing the evolutionary mechanism of the network is essential for link prediction, and how to effectively utilize the historical information for temporal links and effic...	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	303,602
2305.19066	Nested Diffusion Processes for Anytime Image Generation	Diffusion models are the current state-of-the-art in image generation, synthesizing high-quality images by breaking down the generation process into many fine-grained denoising steps. Despite their good performance, diffusion models are computationally expensive, requiring many neural function evaluations (NFEs). In th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	369,360
1612.00628	Overloaded Multiuser MISO Transmission with Imperfect CSIT	A required feature for the next generation of wireless communication networks will be the capability to serve simultaneously a large number of devices with heterogeneous CSIT qualities and demands. In this paper, we consider the overloaded MISO BC with two groups of CSIT qualities. We propose a transmission scheme wher...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,925
2108.04899	Analysis of ODE2VAE with Examples	Deep generative models aim to learn underlying distributions that generate the observed data. Given the fact that the generative distribution may be complex and intractable, deep latent variable models use probabilistic frameworks to learn more expressive joint probability distributions over the data and their low-dime...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,144
2407.07521	CHILLI: A data context-aware perturbation method for XAI	The trustworthiness of Machine Learning (ML) models can be difficult to assess, but is critical in high-risk or ethically sensitive applications. Many models are treated as a `black-box' where the reasoning or criteria for a final decision is opaque to the user. To address this, some existing Explainable AI (XAI) appro...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	471,797
2005.00088	Domain Siamese CNNs for Sparse Multispectral Disparity Estimation	Multispectral disparity estimation is a difficult task for many reasons: it has all the same challenges as traditional visible-visible disparity estimation (occlusions, repetitive patterns, textureless surfaces), in addition of having very few common visual information between images (e.g. color information vs. thermal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	175,121
2003.04335	Congestion-aware Routing and Rebalancing of Autonomous Mobility-on-Demand Systems in Mixed Traffic	This paper studies congestion-aware route-planning policies for Autonomous Mobility-on-Demand (AMoD) systems, whereby a fleet of autonomous vehicles provides on-demand mobility under mixed traffic conditions. Specifically, we first devise a network flow model to optimize the AMoD routing and rebalancing strategies in a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	167,527
1001.4419	A Framework to Manage the Complex Organisation of Collaborating: Its Application to Autonomous Systems	In this paper we present an analysis of the complexities of large group collaboration and its application to develop detailed requirements for collaboration schema for Autonomous Systems (AS). These requirements flow from our development of a framework for collaboration that provides a basis for designing, supporting a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	5,520
2412.03391	Risk-aware Classification via Uncertainty Quantification	Autonomous and semi-autonomous systems are using deep learning models to improve decision-making. However, deep classifiers can be overly confident in their incorrect predictions, a major issue especially in safety-critical domains. The present study introduces three foundational desiderata for developing real-world ri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	513,942
2411.12792	CLIC: Contrastive Learning Framework for Unsupervised Image Complexity Representation	As an essential visual attribute, image complexity affects human image comprehension and directly influences the performance of computer vision tasks. However, accurately assessing and quantifying image complexity faces significant challenges. Previous works needed more generalization capabilities and well-labeled data...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,551
2405.11461	DocReLM: Mastering Document Retrieval with Language Model	With over 200 million published academic documents and millions of new documents being written each year, academic researchers face the challenge of searching for information within this vast corpus. However, existing retrieval systems struggle to understand the semantics and domain knowledge present in academic papers...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	455,150
2002.03229	Supervised Quantile Normalization for Low-rank Matrix Approximation	Low rank matrix factorization is a fundamental building block in machine learning, used for instance to summarize gene expression profile data or word-document counts. To be robust to outliers and differences in scale across features, a matrix factorization step is usually preceded by ad-hoc feature normalization steps...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	163,187
2403.09536	Mixed Algorithm of SINDy and HAVOK for Measure-Based Analysis of Power System with Inverter-based Resources	Artificial intelligence and machine learning is enhancing electric grids by offering data analysis tools that can be used to operate the power grid more reliably. However, the complex nonlinear dynamics, particularly when coupled with multi-scale interactions among Inverter-based renewable energy Resources, calls for e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	437,805
1303.5751	Algorithms for Irrelevance-Based Partial MAPs	Irrelevance-based partial MAPs are useful constructs for domain-independent explanation using belief networks. We look at two definitions for such partial MAPs, and prove important properties that are useful in designing algorithms for computing them effectively. We make use of these properties in modifying our standar...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,199
2104.11977	On the stability of deep convolutional neural networks under irregular or random deformations	The problem of robustness under location deformations for deep convolutional neural networks (DCNNs) is of great theoretical and practical interest. This issue has been studied in pioneering works, especially for scattering-type architectures, for deformation vector fields $\tau(x)$ with some regularity - at least $C^1...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	232,076
2110.15326	GOMP-FIT: Grasp-Optimized Motion Planning for Fast Inertial Transport	High-speed motions in pick-and-place operations are critical to making robots cost-effective in many automation scenarios, from warehouses and manufacturing to hospitals and homes. However, motions can be too fast -- such as when the object being transported has an open-top, is fragile, or both. One way to avoid spills...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	263,844
2008.03496	Human Robot Collaborative Assembly Planning: An Answer Set Programming Approach	For planning an assembly of a product from a given set of parts, robots necessitate certain cognitive skills: high-level planning is needed to decide the order of actuation actions, while geometric reasoning is needed to check the feasibility of these actions. For collaborative assembly tasks with humans, robots requir...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	true	190,920
2204.01618	Deep-Ensemble-Based Uncertainty Quantification in Spatiotemporal Graph Neural Networks for Traffic Forecasting	Deep-learning-based data-driven forecasting methods have produced impressive results for traffic forecasting. A major limitation of these methods, however, is that they provide forecasts without estimates of uncertainty, which are critical for real-time deployments. We focus on a diffusion convolutional recurrent neura...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	289,662
1007.0528	Binary Independent Component Analysis with OR Mixtures	Independent component analysis (ICA) is a computational method for separating a multivariate signal into subcomponents assuming the mutual statistical independence of the non-Gaussian source signals. The classical Independent Components Analysis (ICA) framework usually assumes linear combinations of independent sources...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	6,968
2202.01385	Technical Report: A Hierarchical Deliberative-Reactive System Architecture for Task and Motion Planning in Partially Known Environments	We describe a task and motion planning architecture for highly dynamic systems that combines a domain-independent sampling-based deliberative planning algorithm with a global reactive planner. We leverage the recent development of a reactive, vector field planner that provides guarantees of reachability to large region...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	278,466
2501.02968	FlipedRAG: Black-Box Opinion Manipulation Attacks to Retrieval-Augmented Generation of Large Language Models	Retrieval-Augmented Generation (RAG) addresses hallucination and real-time constraints by dynamically retrieving relevant information from a knowledge database to supplement the LLMs' input. When presented with a query, RAG selects the most semantically similar texts from its knowledge bases and uses them as context fo...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	522,710
2105.07911	SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising	In text-to-SQL task, seq-to-seq models often lead to sub-optimal performance due to limitations in their architecture. In this paper, we present a simple yet effective approach that adapts transformer-based seq-to-seq model to robust text-to-SQL generation. Instead of inducing constraint to decoder or reformat the task...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	235,595
1706.10036	Providing Effective Real-time Feedback in Simulation-based Surgical Training	Virtual reality simulation is becoming popular as a training platform in surgical education. However, one important aspect of simulation-based surgical training that has not received much attention is the provision of automated real-time performance feedback to support the learning process. Performance feedback is acti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	76,240
2402.01536	Homogenization Effects of Large Language Models on Human Creative Ideation	Large language models (LLMs) are now being used in a wide variety of contexts, including as creativity support tools (CSTs) intended to help their users come up with new ideas. But do LLMs actually support user creativity? We hypothesized that the use of an LLM as a CST might make the LLM's users feel more creative, an...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	426,070
2103.04023	PISE: Person Image Synthesis and Editing with Decoupled GAN	Person image synthesis, e.g., pose transfer, is a challenging problem due to large variation and occlusion. Existing methods have difficulties predicting reasonable invisible regions and fail to decouple the shape and style of clothing, which limits their applications on person image editing. In this paper, we propose ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	223,492
2410.01857	Learning the Optimal Path and DNN Partition for Collaborative Edge Inference	Recent advancements in Deep Neural Networks (DNNs) have catalyzed the development of numerous intelligent mobile applications and services. However, they also introduce significant computational challenges for resource-constrained mobile devices. To address this, collaborative edge inference has been proposed. This met...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	493,992
1612.09506	Smart Content Recognition from Images Using a Mixture of Convolutional Neural Networks	With rapid development of the Internet, web contents become huge. Most of the websites are publicly available, and anyone can access the contents from anywhere such as workplace, home and even schools. Nevertheless, not all the web contents are appropriate for all users, especially children. An example of these content...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	66,197
1605.07891	Query Expansion with Locally-Trained Word Embeddings	Continuous space word embeddings have received a great deal of attention in the natural language processing and machine learning communities for their ability to model term similarity and other relationships. We study the use of term relatedness in the context of query expansion for ad hoc information retrieval. We dem...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	56,358
cs/0412060	Monotonicity Results for Coherent MIMO Rician Channels	The dependence of the Gaussian input information rate on the line-of-sight (LOS) matrix in multiple-input multiple-output coherent Rician fading channels is explored. It is proved that the outage probability and the mutual information induced by a multivariate circularly symmetric Gaussian input with any covariance mat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,441
1207.2734	Information-bit error rate and false positives in an MDS code	In this paper, a refinement of the weight distribution in an MDS code is computed. Concretely, the number of codewords with a fixed amount of nonzero bits in both information and redundancy parts is obtained. This refinement improves the theoretical approximation of the information-bit and -symbol error rate, in terms ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,413
1903.05202	Continual Learning in Practice	This paper describes a reference architecture for self-maintaining systems that can learn continually, as data arrives. In environments where data evolves, we need architectures that manage Machine Learning (ML) models in production, adapt to shifting data distributions, cope with outliers, retrain when necessary, and ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	124,116
1304.0740	O(logT) Projections for Stochastic Optimization of Smooth and Strongly Convex Functions	Traditional algorithms for stochastic optimization require projecting the solution at each iteration into a given domain to ensure its feasibility. When facing complex domains, such as positive semi-definite cones, the projection operation can be expensive, leading to a high computational cost per iteration. In this pa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	23,408
2401.14277	An Instance-Based Approach to the Trace Reconstruction Problem	In the trace reconstruction problem, one observes the output of passing a binary string $s \in \{0,1\}^n$ through a deletion channel $T$ times and wishes to recover $s$ from the resulting $T$ "traces." Most of the literature has focused on characterizing the hardness of this problem in terms of the number of traces $T$...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	424,032
2310.20210	UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer	Underwater images often exhibit poor quality, distorted color balance and low contrast due to the complex and intricate interplay of light, water, and objects. Despite the significant contributions of previous underwater enhancement techniques, there exist several problems that demand further improvement: (i) The curre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	404,303
1609.09619	Big Data analytics. Three use cases with R, Python and Spark	Management and analysis of big data are systematically associated with a data distributed architecture in the Hadoop and now Spark frameworks. This article offers an introduction for statisticians to these technologies by comparing the performance obtained by the direct use of three reference environments: R, Python Sc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	61,753
1709.07322	Playing for Benchmarks	We present a benchmark suite for visual perception. The benchmark is based on more than 250K high-resolution video frames, all annotated with ground-truth data for both low-level and high-level vision tasks, including optical flow, semantic instance segmentation, object detection and tracking, object-level 3D scene lay...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	81,257
2303.13797	Personalizing Task-oriented Dialog Systems via Zero-shot Generalizable Reward Function	Task-oriented dialog systems enable users to accomplish tasks using natural language. State-of-the-art systems respond to users in the same way regardless of their personalities, although personalizing dialogues can lead to higher levels of adoption and better user experiences. Building personalized dialog systems is a...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	353,827
2211.11160	Unsupervised Explanation Generation via Correct Instantiations	While large pre-trained language models (PLM) have shown their great skills at solving discriminative tasks, a significant gap remains when compared with humans for explanation-related tasks. Among them, explaining the reason why a statement is wrong (e.g., against commonsense) is incredibly challenging. The major diff...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	331,607
1904.01866	A Comprehensive Overhaul of Feature Distillation	We investigate the design aspects of feature distillation methods achieving network compression and propose a novel feature distillation method in which the distillation loss is designed to make a synergy among various aspects: teacher transform, student transform, distillation feature position and distance function. O...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	126,270
2402.01485	Di-NeRF: Distributed NeRF for Collaborative Learning with Relative Pose Refinement	Collaborative mapping of unknown environments can be done faster and more robustly than a single robot. However, a collaborative approach requires a distributed paradigm to be scalable and deal with communication issues. This work presents a fully distributed algorithm enabling a group of robots to collectively optimiz...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	426,044
2409.02406	Hadamard Row-Wise Generation Algorithm	In this paper, we introduce an efficient algorithm for generating specific Hadamard rows, addressing the memory demands of pre-computing the entire matrix. Leveraging Sylvester's recursive construction, our method generates the required $i$-th row on demand, significantly reducing computational resources. The algorithm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	485,687
0808.1508	Comparison between CPBPV, ESC/Java, CBMC, Blast, EUREKA and Why for Bounded Program Verification	This report describes experimental results for a set of benchmarks on program verification. It compares the capabilities of CPBVP "Constraint Programming framework for Bounded Program Verification" [4] with the following frameworks: ESC/Java, CBMC, Blast, EUREKA and Why.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	2,187
cmp-lg/9608009	Centering theory and the Italian pronominal system	In this paper, I give an account of some phenomena of pronominalization in Italian in terms of centering theory. After a general introduction to the Italian pronominal system, I will review centering, and then show how the original rules have to be extended or modified. Finally, I will show that centering does not acco...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,644
2302.04928	Regularization for Strategy Exploration in Empirical Game-Theoretic Analysis	In iterative approaches to empirical game-theoretic analysis (EGTA), the strategy space is expanded incrementally based on analysis of intermediate game models. A common approach to strategy exploration, represented by the double oracle algorithm, is to add strategies that best-respond to a current equilibrium. This ap...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	344,866
2210.11164	Graph Neural Networks with Trainable Adjacency Matrices for Fault Diagnosis on Multivariate Sensor Data	Timely detected anomalies in the chemical technological processes, as well as the earliest detection of the cause of the fault, significantly reduce the production cost in the industrial factories. Data on the state of the technological process and the operation of production equipment are received by a large number of...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	325,203
2207.11222	Forest and Water Bodies Segmentation Through Satellite Images Using U-Net	Global environment monitoring is a task that requires additional attention in the contemporary rapid climate change environment. This includes monitoring the rate of deforestation and areas affected by flooding. Satellite imaging has greatly helped monitor the earth, and deep learning techniques have helped to automate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,550
2405.16893	Cross Far- and Near-Field Channel Measurement and Modeling in Extremely Large-scale Antenna Array (ELAA) Systems	Technologies like ultra-massive multiple-input-multiple-output (UM-MIMO) and reconfigurable intelligent surfaces (RISs) are of special interest to meet the key performance indicators of future wireless systems including ubiquitous connectivity and lightning-fast data rates. One of their common features, the extremely l...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	457,666
2401.15291	Improved Construction of Robust Gray Code	A robust Gray code, formally introduced by (Lolck and Pagh, SODA 2024), is a Gray code that additionally has the property that, given a noisy version of the encoding of an integer $j$, it is possible to reconstruct $\hat{j}$ so that $\|j - \hat{j}\|$ is small with high probability. That work presented a transformation th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	424,390
2402.07496	Understanding Deep Learning defenses Against Adversarial Examples Through Visualizations for Dynamic Risk Assessment	In recent years, Deep Neural Network models have been developed in different fields, where they have brought many advances. However, they have also started to be used in tasks where risk is critical. A misdiagnosis of these models can lead to serious accidents or even death. This concern has led to an interest among re...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	428,745
2203.13472	Facial Expression Recognition with Swin Transformer	The task of recognizing human facial expressions plays a vital role in various human-related systems, including health care and medical fields. With the recent success of deep learning and the accessibility of a large amount of annotated data, facial expression recognition research has been mature enough to be utilized...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	287,644
2111.10210	The Application of Zig-Zag Sampler in Sequential Markov Chain Monte Carlo	Particle filtering methods are widely applied in sequential state estimation within nonlinear non-Gaussian state space model. However, the traditional particle filtering methods suffer the weight degeneracy in the high-dimensional state space model. Currently, there are many methods to improve the performance of partic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	267,247
2201.06696	ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues	Object proposal generation is an important and fundamental task in computer vision. In this paper, we propose ProposalCLIP, a method towards unsupervised open-category object proposal generation. Unlike previous works which require a large number of bounding box annotations and/or can only generate proposals for limite...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	275,796
2204.13751	BEINIT: Avoiding Barren Plateaus in Variational Quantum Algorithms	Barren plateaus are a notorious problem in the optimization of variational quantum algorithms and pose a critical obstacle in the quest for more efficient quantum machine learning algorithms. Many potential reasons for barren plateaus have been identified but few solutions have been proposed to avoid them in practice. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	293,925
2305.17826	NOTABLE: Transferable Backdoor Attacks Against Prompt-based NLP Models	Prompt-based learning is vulnerable to backdoor attacks. Existing backdoor attacks against prompt-based models consider injecting backdoors into the entire embedding layers or word embedding vectors. Such attacks can be easily affected by retraining on downstream tasks and with different prompting strategies, limiting ...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	368,760
1707.02459	Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping	The state-of-the-art named entity recognition (NER) systems are statistical machine learning models that have strong generalization capability (i.e., can recognize unseen entities that do not appear in training data) based on lexical and contextual information. However, such a model could still make mistakes if its fea...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	76,709
1112.0038	Information Theoretic Authentication and Secrecy Codes in the Splitting Model	In the splitting model, information theoretic authentication codes allow non-deterministic encoding, that is, several messages can be used to communicate a particular plaintext. Certain applications require that the aspect of secrecy should hold simultaneously. Ogata-Kurosawa-Stinson-Saido (2004) have constructed optim...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	13,261
2205.11081	BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating Low-Resource Natural Language Generation in Bangla	This work presents BanglaNLG, a comprehensive benchmark for evaluating natural language generation (NLG) models in Bangla, a widely spoken yet low-resource language. We aggregate six challenging conditional text generation tasks under the BanglaNLG benchmark, introducing a new dataset on dialogue generation in the proc...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	297,986
1912.02927	Smart Cloud: Scalable Cloud Robotic Architecture for Web-powered Multi-Robot Applications	Robots have inherently limited onboard processing, storage, and power capabilities. Cloud computing resources have the potential to provide significant advantages for robots in many applications. However, to make use of these resources, frameworks must be developed that facilitate robot interactions with cloud services...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	true	156,470
1907.05446	General Evaluation for Instruction Conditioned Navigation using Dynamic Time Warping	In instruction conditioned navigation, agents interpret natural language and their surroundings to navigate through an environment. Datasets for studying this task typically contain pairs of these instructions and reference trajectories. Yet, most evaluation metrics used thus far fail to properly account for the latter...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	138,368
2204.13548	Tragedy Plus Time: Capturing Unintended Human Activities from Weakly-labeled Videos	In videos that contain actions performed unintentionally, agents do not achieve their desired goals. In such videos, it is challenging for computer vision systems to understand high-level concepts such as goal-directed behavior, an ability present in humans from a very early age. Inculcating this ability in artificiall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	293,851
2406.15504	Multi-View Empowered Structural Graph Wordification for Language Models	Significant efforts have been dedicated to integrating the powerful Large Language Models (LLMs) with diverse modalities, particularly focusing on the fusion of language, vision and audio data. However, the graph-structured data, which is inherently rich in structural and domain-specific knowledge, has not yet been gra...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	466,755
2007.00740	Build2Vec: Building Representation in Vector Space	In this paper, we represent a methodology of a graph embeddings algorithm that is used to transform labeled property graphs obtained from a Building Information Model (BIM). Industrial Foundation Classes (IFC) is a standard schema for BIM, which is utilized to convert the building data into a graph representation. We u...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	185,194
1807.00942	Stochastic Layer-Wise Precision in Deep Neural Networks	Low precision weights, activations, and gradients have been proposed as a way to improve the computational efficiency and memory footprint of deep neural networks. Recently, low precision networks have even shown to be more robust to adversarial attacks. However, typical implementations of low precision DNNs use unifor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	101,948

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