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
2011.10214	PIFE-PIC: Parallel Immersed-Finite-Element Particle-In-Cell For 3-D Kinetic Simulations of Plasma-Material Interactions	This paper presents a recently developed particle simulation code package PIFE-PIC, which is a novel three-dimensional (3-D) Parallel Immersed-Finite-Element (IFE) Particle-in-Cell (PIC) simulation model for particle simulations of plasma-material interactions. This framework is based on the recently developed non-homo...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	207,440
2403.18038	TGGLinesPlus: A robust topological graph-guided computer vision algorithm for line detection from images	Line detection is a classic and essential problem in image processing, computer vision and machine intelligence. Line detection has many important applications, including image vectorization (e.g., document recognition and art design), indoor mapping, and important societal challenges (e.g., sea ice fracture line extra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	441,733
1809.03577	Using Image Fairness Representations in Diversity-Based Re-ranking for Recommendations	The trade-off between relevance and fairness in personalized recommendations has been explored in recent works, with the goal of minimizing learned discrimination towards certain demographics while still producing relevant results. We present a fairness-aware variation of the Maximal Marginal Relevance (MMR) re-ranki...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	107,357
2104.08626	Mixed Gibbs Sampling Detector in High-Order Modulation Large-Scale MIMO Systems	A neighborhood restricted Mixed Gibbs Sampling (MGS) based approach is proposed for low-complexity high-order modulation large-scale Multiple-Input Multiple-Output (LS-MIMO) detection. The proposed LS-MIMO detector applies a neighborhood limitation (NL) on the noisy solution from the MGS at a distance d - thus, named d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	230,881
cs/0612019	On Finite Memory Universal Data Compression and Classification of Individual Sequences	Consider the case where consecutive blocks of N letters of a semi-infinite individual sequence X over a finite-alphabet are being compressed into binary sequences by some one-to-one mapping. No a-priori information about X is available at the encoder, which must therefore adopt a universal data-compression algorithm. I...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,939
1610.03705	Structure Properties of Koch Networks Based on Networks Dynamical Systems	We introduce an informative labeling algorithm for the vertices of a family of Koch networks. Each of the labels is consisted of two parts, the precise position and the time adding to Koch networks. The shortest path routing between any two vertices is determined only on the basis of their labels, and the routing is ca...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	62,287
1802.00167	Consensus-based Distributed Quickest Detection of Attacks with Unknown Parameters	Sequential attack detection in a distributed estimation system is considered, where each sensor successively produces one-bit quantized samples of a desired deterministic scalar parameter corrupted by additive noise. The unknown parameters in the pre-attack and post-attack models, namely the desired parameter to be est...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	89,360
1808.04126	Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering	The most approaches to Knowledge Base Question Answering are based on semantic parsing. In this paper, we address the problem of learning vector representations for complex semantic parses that consist of multiple entities and relations. Previous work largely focused on selecting the correct semantic relations for a qu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	105,072
2202.09481	TransDreamer: Reinforcement Learning with Transformer World Models	The Dreamer agent provides various benefits of Model-Based Reinforcement Learning (MBRL) such as sample efficiency, reusable knowledge, and safe planning. However, its world model and policy networks inherit the limitations of recurrent neural networks and thus an important question is how an MBRL framework can benefit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	281,209
2001.00391	Temporal-Spatial Neural Filter: Direction Informed End-to-End Multi-channel Target Speech Separation	Target speech separation refers to extracting the target speaker's speech from mixed signals. Despite the recent advances in deep learning based close-talk speech separation, the applications to real-world are still an open issue. Two main challenges are the complex acoustic environment and the real-time processing req...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,204
2201.13320	BEER: Fast $O(1/T)$ Rate for Decentralized Nonconvex Optimization with Communication Compression	Communication efficiency has been widely recognized as the bottleneck for large-scale decentralized machine learning applications in multi-agent or federated environments. To tackle the communication bottleneck, there have been many efforts to design communication-compressed algorithms for decentralized nonconvex optim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	277,948
2208.10099	Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect	Text-to-SQL has attracted attention from both the natural language processing and database communities because of its ability to convert the semantics in natural language into SQL queries and its practical application in building natural language interfaces to database systems. The major challenges in text-to-SQL lie i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	313,940
2405.17240	Content-Style Decoupling for Unsupervised Makeup Transfer without Generating Pseudo Ground Truth	The absence of real targets to guide the model training is one of the main problems with the makeup transfer task. Most existing methods tackle this problem by synthesizing pseudo ground truths (PGTs). However, the generated PGTs are often sub-optimal and their imprecision will eventually lead to performance degradatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	457,820
1908.07968	Assessing the Impact of a User-Item Collaborative Attack on Class of Users	Collaborative Filtering (CF) models lie at the core of most recommendation systems due to their state-of-the-art accuracy. They are commonly adopted in e-commerce and online services for their impact on sales volume and/or diversity, and their impact on companies' outcome. However, CF models are only as good as the int...	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	142,429
1909.12127	Intensity-Free Learning of Temporal Point Processes	Temporal point processes are the dominant paradigm for modeling sequences of events happening at irregular intervals. The standard way of learning in such models is by estimating the conditional intensity function. However, parameterizing the intensity function usually incurs several trade-offs. We show how to overcome...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	147,032
2110.02153	Inference and De-Noising of Non-Gaussian Particle Distribution Functions: A Generative Modeling Approach	The particle-in-cell numerical method of plasma physics balances a trade-off between computational cost and intrinsic noise. Inference on data produced by these simulations generally consists of binning the data to recover the particle distribution function, from which physical processes may be investigated. In additio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,021
2311.06292	Towards a data-driven debt collection strategy based on an advanced machine learning framework	The European debt purchase market as measured by the total book value of purchased debt approached 25bn euros in 2020 and it was growing at double-digit rates. This is an example of how big the debt collection and debt purchase industry has grown and the important impact it has in the financial sector. However, in orde...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,884
2501.05109	EquiBoost: An Equivariant Boosting Approach to Molecular Conformation Generation	Molecular conformation generation plays key roles in computational drug design. Recently developed deep learning methods, particularly diffusion models have reached competitive performance over traditional cheminformatical approaches. However, these methods are often time-consuming or require extra support from traditi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,472
1811.08306	Study of Multi-Step Knowledge-Aided Iterative Nested MUSIC for Direction Finding	In this work, we propose a subspace-based algorithm for direction-of-arrival (DOA) estimation applied to the signals impinging on a two-level nested array, referred to as multi-step knowledge-aided iterative nested MUSIC method (MS-KAI-Nested-MUSIC), which significantly improves the accuracy of the original Nested-MUSI...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	114,010
2209.01121	Back-to-Bones: Rediscovering the Role of Backbones in Domain Generalization	Domain Generalization (DG) studies the capability of a deep learning model to generalize to out-of-training distributions. In the last decade, literature has been massively filled with training methodologies that claim to obtain more abstract and robust data representations to tackle domain shifts. Recent research has ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	315,783
2308.08538	Proprioceptive Learning with Soft Polyhedral Networks	Proprioception is the "sixth sense" that detects limb postures with motor neurons. It requires a natural integration between the musculoskeletal systems and sensory receptors, which is challenging among modern robots that aim for lightweight, adaptive, and sensitive designs at a low cost. Here, we present the Soft Poly...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	385,944
2111.05940	A Novel Corpus of Discourse Structure in Humans and Computers	We present a novel corpus of 445 human- and computer-generated documents, comprising about 27,000 clauses, annotated for semantic clause types and coherence relations that allow for nuanced comparison of artificial and natural discourse modes. The corpus covers both formal and informal discourse, and contains documents...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	265,919
2202.01551	Isometries and MacWilliams Extension Property for Weighted Poset Metric	Let $\mathbf{H}$ be the cartesian product of a family of left modules over a ring $S$, indexed by a finite set $\Omega$. We are concerned with the $(\mathbf{P},\omega)$-weight on $\mathbf{H}$, where $\mathbf{P}=(\Omega,\preccurlyeq_{\mathbf{P}})$ is a poset and $\omega:\Omega\longrightarrow\mathbb{R}^{+}$ is a weight f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	278,518
1906.11437	Hard Pixel Mining for Depth Privileged Semantic Segmentation	Semantic segmentation has achieved remarkable progress but remains challenging due to the complex scene, object occlusion, and so on. Some research works have attempted to use extra information such as a depth map to help RGB based semantic segmentation because the depth map could provide complementary geometric cues. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	136,668
1911.10088	Optimizing Data Usage via Differentiable Rewards	To acquire a new skill, humans learn better and faster if a tutor, based on their current knowledge level, informs them of how much attention they should pay to particular content or practice problems. Similarly, a machine learning model could potentially be trained better with a scorer that "adapts" to its current lea...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	154,721
2312.17263	TACIT: A Target-Agnostic Feature Disentanglement Framework for Cross-Domain Text Classification	Cross-domain text classification aims to transfer models from label-rich source domains to label-poor target domains, giving it a wide range of practical applications. Many approaches promote cross-domain generalization by capturing domain-invariant features. However, these methods rely on unlabeled samples provided by...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	418,680
1610.06809	The Anatomy of Brexit Debate on Facebook	Nowadays users get informed and shape their opinion through social media. However, the disintermediated access to contents does not guarantee quality of information. Selective exposure and confirmation bias, indeed, have been shown to play a pivotal role in content consumption and information spreading. Users tend to s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	62,699
1807.03234	Bayesian Sequential Joint Detection and Estimation	Joint detection and estimation refers to deciding between two or more hypotheses and, depending on the test outcome, simultaneously estimating the unknown parameters of the underlying distribution. This problem is investigated in a sequential framework under mild assumptions on the underlying random process. We formula...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	102,478
1503.07706	Pain Intensity Estimation by a Self--Taught Selection of Histograms of Topographical Features	Pain assessment through observational pain scales is necessary for special categories of patients such as neonates, patients with dementia, critically ill patients, etc. The recently introduced Prkachin-Solomon score allows pain assessment directly from facial images opening the path for multiple assistive applications...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	41,505
2303.06799	Gaussian Process on the Product of Directional Manifolds	We present a principled study on defining Gaussian processes (GPs) with inputs on the product of directional manifolds. A circular kernel is first presented according to the von Mises distribution. Based thereon, the hypertoroidal von Mises (HvM) kernel is proposed to establish GPs on hypertori with consideration of co...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,988
2204.07120	Exploring Dual Encoder Architectures for Question Answering	Dual encoders have been used for question-answering (QA) and information retrieval (IR) tasks with good results. Previous research focuses on two major types of dual encoders, Siamese Dual Encoder (SDE), with parameters shared across two encoders, and Asymmetric Dual Encoder (ADE), with two distinctly parameterized enc...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	291,568
2408.17169	Secure Transmission in Cell-Free Massive MIMO under Active Eavesdropping	We study secure communications in cell-free massive multiple-input multiple-output (CF-mMIMO) systems with multi-antenna access points (APs) and protective partial zero-forcing (PPZF) precoding. In particular, we consider an active eavesdropping attack, where an eavesdropper contaminates the uplink channel estimation p...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	484,607
2310.17974	FaultSeg Swin-UNETR: Transformer-Based Self-Supervised Pretraining Model for Fault Recognition	This paper introduces an approach to enhance seismic fault recognition through self-supervised pretraining. Seismic fault interpretation holds great significance in the fields of geophysics and geology. However, conventional methods for seismic fault recognition encounter various issues, including dependence on data qu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	403,359
2406.20095	LLaRA: Supercharging Robot Learning Data for Vision-Language Policy	Vision Language Models (VLMs) have recently been leveraged to generate robotic actions, forming Vision-Language-Action (VLA) models. However, directly adapting a pretrained VLM for robotic control remains challenging, particularly when constrained by a limited number of robot demonstrations. In this work, we introduce ...	false	false	false	false	true	false	true	true	true	false	false	true	false	false	false	false	false	false	468,668
2105.15101	Anchor Nodes Positioning for Self-localization in Wireless Sensor Networks using Belief Propagation and Evolutionary Algorithms	Locating each node in a wireless sensor network is essential for starting the monitoring job and sending information about the area. One method that has been used in hard and inaccessible environments is randomly scattering each node in the area. In order to reduce the cost of using GPS at each node, some nodes should ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	237,919
2102.03012	A Serverless Cloud-Fog Platform for DNN-Based Video Analytics with Incremental Learning	DNN-based video analytics have empowered many new applications (e.g., automated retail). Meanwhile, the proliferation of fog devices provides developers with more design options to improve performance and save cost. To the best of our knowledge, this paper presents the first serverless system that takes full advantage ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	218,599
2409.19007	Rephrase and Contrast: Fine-Tuning Language Models for Enhanced Understanding of Communication and Computer Networks	Large language models (LLMs) are being widely researched across various disciplines, with significant recent efforts focusing on adapting LLMs for understanding of how communication networks operate. However, over-reliance on prompting techniques hinders the full exploitation of the generalization ability of these mode...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	492,503
1603.07475	Fine-scale Surface Normal Estimation using a Single NIR Image	We present surface normal estimation using a single near infrared (NIR) image. We are focusing on fine-scale surface geometry captured with an uncalibrated light source. To tackle this ill-posed problem, we adopt a generative adversarial network which is effective in recovering a sharp output, which is also essential f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	53,634
2411.17720	MAS-Attention: Memory-Aware Stream Processing for Attention Acceleration on Resource-Constrained Edge Devices	The advent of foundation models have revolutionized various fields, enabling unprecedented task accuracy and flexibility in computational linguistics, computer vision and other domains. Attention mechanism has become an essential component of foundation models, due to their superb capability of capturing correlations i...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	511,566
2102.09954	A bi-level encoding scheme for the clustered shortest-path tree problem in multifactorial optimization	The Clustered Shortest-Path Tree Problem (CluSPT) plays an important role in various types of optimization problems in real-life. Recently, some Multifactorial Evolutionary Algorithm (MFEA) have been introduced to deal with the CluSPT, however these researches still have some shortcomings such as evolution operators on...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	220,935
1902.05880	Robot Co-design: Beyond the Monotone Case	Recent advances in 3D printing and manufacturing of miniaturized robotic hardware and computing are paving the way to build inexpensive and disposable robots. This will have a large impact on several applications including scientific discovery (e.g., hurricane monitoring), search-and-rescue (e.g., operation in confined...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	121,635
2410.03190	Tuning Timestep-Distilled Diffusion Model Using Pairwise Sample Optimization	Recent advancements in timestep-distilled diffusion models have enabled high-quality image generation that rivals non-distilled multi-step models, but with significantly fewer inference steps. While such models are attractive for applications due to the low inference cost and latency, fine-tuning them with a naive diff...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	494,670
2211.15144	Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes	The potential of offline reinforcement learning (RL) is that high-capacity models trained on large, heterogeneous datasets can lead to agents that generalize broadly, analogously to similar advances in vision and NLP. However, recent works argue that offline RL methods encounter unique challenges to scaling up model ca...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,134
2112.07209	ACE-BERT: Adversarial Cross-modal Enhanced BERT for E-commerce Retrieval	Nowadays on E-commerce platforms, products are presented to the customers with multiple modalities. These multiple modalities are significant for a retrieval system while providing attracted products for customers. Therefore, how to take into account those multiple modalities simultaneously to boost the retrieval perfo...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	271,409
2005.12841	Applying Evolutionary Metaheuristics for Parameter Estimation of Individual-Based Models	Individual-based models are complex and they have usually an elevated number of input parameters which must be tuned for reproducing the observed population data or the experimental results as accurately as possible. Thus, one of the weakest points of this modelling approach lies on the fact that rarely the modeler has...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	178,838
2306.05791	Enabling Robot Manipulation of Soft and Rigid Objects with Vision-based Tactile Sensors	Endowing robots with tactile capabilities opens up new possibilities for their interaction with the environment, including the ability to handle fragile and/or soft objects. In this work, we equip the robot gripper with low-cost vision-based tactile sensors and propose a manipulation algorithm that adapts to both rigid...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	372,339
1904.08303	Usage of Decision Support Systems for Conflicts Modelling during Information Operations Recognition	Application of decision support systems for conflict modeling in information operations recognition is presented. An information operation is considered as a complex weakly structured system. The model of conflict between two subjects is proposed based on the second-order rank reflexive model. The method is described f...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	128,023
2006.11280	Self-PU: Self Boosted and Calibrated Positive-Unlabeled Training	Many real-world applications have to tackle the Positive-Unlabeled (PU) learning problem, i.e., learning binary classifiers from a large amount of unlabeled data and a few labeled positive examples. While current state-of-the-art methods employ importance reweighting to design various risk estimators, they ignored the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,163
2208.06187	Stabilizer quantum codes defined by trace-depending polynomials	Quantum error-correcting codes with good parameters can be constructed by evaluating polynomials at the roots of the polynomial trace. In this paper, we propose to evaluate polynomials at the roots of trace-depending polynomials (given by a constant plus the trace of a polynomial) and show that this procedure gives ris...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	312,636
1108.0027	Revisiting Degree Distribution Models for Social Graph Analysis	Degree distribution models are incredibly important tools for analyzing and understanding the structure and formation of social networks, and can help guide the design of efficient graph algorithms. In particular, the Power-law degree distribution has long been used to model the structure of online social networks, and...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	11,516
2205.06631	A Polar Subcode Approach to Belief Propagation List Decoding	Permutation decoding gained recent interest as it can exploit the symmetries of a code in a parallel fashion. Moreover, it has been shown that by viewing permuted polar codes as polar subcodes, the set of usable permutations in permutation decoding can be increased. We extend this idea to pre-transformed polar codes, s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	296,303
2409.17754	Byzantine-Robust Aggregation for Securing Decentralized Federated Learning	Federated Learning (FL) emerges as a distributed machine learning approach that addresses privacy concerns by training AI models locally on devices. Decentralized Federated Learning (DFL) extends the FL paradigm by eliminating the central server, thereby enhancing scalability and robustness through the avoidance of a s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	491,966
2004.02589	Software Defect Prediction Based On Deep Learning Models: Performance Study	In recent years, defect prediction, one of the major software engineering problems, has been in the focus of researchers since it has a pivotal role in estimating software errors and faulty modules. Researchers with the goal of improving prediction accuracy have developed many models for software defect prediction. How...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	171,277
2502.08636	PulseCheck457: A Diagnostic Benchmark for 6D Spatial Reasoning of Large Multimodal Models	Although large multimodal models (LMMs) have demonstrated remarkable capabilities in visual scene interpretation and reasoning, their capacity for complex and precise 3-dimensional spatial reasoning remains uncertain. Existing benchmarks focus predominantly on 2D spatial understanding and lack a framework to comprehens...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	533,090
1902.00746	On the bias, risk and consistency of sample means in multi-armed bandits	The sample mean is among the most well studied estimators in statistics, having many desirable properties such as unbiasedness and consistency. However, when analyzing data collected using a multi-armed bandit (MAB) experiment, the sample mean is biased and much remains to be understood about its properties. For exampl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	120,494
2410.09588	A Game-Theoretic Perspective for Efficient Modern Random Access	Modern random access mechanisms combine packet repetitions with multi-user detection mechanisms at the receiver to maximize the throughput and reliability in massive Internet of Things (IoT) scenarios. However, optimizing the access policy, which selects the number of repetitions, is a complicated problem, and failing ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	497,666
2004.10360	Breaking Down Memory Walls: Adaptive Memory Management in LSM-based Storage Systems (Extended Version)	Log-Structured Merge-trees (LSM-trees) have been widely used in modern NoSQL systems. Due to their out-of-place update design, LSM-trees have introduced memory walls among the memory components of multiple LSM-trees and between the write memory and the buffer cache. Optimal memory allocation among these regions is non-...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	173,615
2311.16673	Large Language Models Meet Computer Vision: A Brief Survey	Recently, the intersection of Large Language Models (LLMs) and Computer Vision (CV) has emerged as a pivotal area of research, driving significant advancements in the field of Artificial Intelligence (AI). As transformers have become the backbone of many state-of-the-art models in both Natural Language Processing (NLP)...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	411,012
2311.01073	Fourier Analysis of Signals on Directed Acyclic Graphs (DAG) Using Graph Zero-Padding	Directed acyclic graphs (DAGs) are used for modeling causal relationships, dependencies, and flows in various systems. However, spectral analysis becomes impractical in this setting because the eigendecomposition of the adjacency matrix yields all eigenvalues equal to zero. This inherent property of DAGs results in an ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	404,911
2202.02686	PuzzleBots: Physical Coupling of Robot Swarms	Robot swarms have been shown to improve the ability of individual robots by inter-robot collaboration. In this paper, we present the PuzzleBots - a low-cost robotic swarm system where robots can physically couple with each other to form functional structures with minimum energy consumption while maintaining individual ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	278,910
1604.06635	Bridging LSTM Architecture and the Neural Dynamics during Reading	Recently, the long short-term memory neural network (LSTM) has attracted wide interest due to its success in many tasks. LSTM architecture consists of a memory cell and three gates, which looks similar to the neuronal networks in the brain. However, there still lacks the evidence of the cognitive plausibility of LSTM a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	54,970
2110.10136	Activation Landscapes as a Topological Summary of Neural Network Performance	We use topological data analysis (TDA) to study how data transforms as it passes through successive layers of a deep neural network (DNN). We compute the persistent homology of the activation data for each layer of the network and summarize this information using persistence landscapes. The resulting feature map provid...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,048
2303.04384	SEMv2: Table Separation Line Detection Based on Instance Segmentation	Table structure recognition is an indispensable element for enabling machines to comprehend tables. Its primary purpose is to identify the internal structure of a table. Nevertheless, due to the complexity and diversity of their structure and style, it is highly challenging to parse the tabular data into a structured f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,068
1703.07909	Data Driven Exploratory Attacks on Black Box Classifiers in Adversarial Domains	While modern day web applications aim to create impact at the civilization level, they have become vulnerable to adversarial activity, where the next cyber-attack can take any shape and can originate from anywhere. The increasing scale and sophistication of attacks, has prompted the need for a data driven solution, wit...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	70,474
2202.12226	Probing BERT's priors with serial reproduction chains	Sampling is a promising bottom-up method for exposing what generative models have learned about language, but it remains unclear how to generate representative samples from popular masked language models (MLMs) like BERT. The MLM objective yields a dependency network with no guarantee of consistent conditional distribu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	282,152
2312.04874	Interpretable Underwater Diver Gesture Recognition	In recent years, usage and applications of Autonomous Underwater Vehicles has grown rapidly. Interaction of divers with the AUVs remains an integral part of the usage of AUVs for various applications and makes building robust and efficient underwater gesture recognition systems extremely important. In this paper, we pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,867
1706.00842	Neural Network-Based Automatic Liver Tumor Segmentation With Random Forest-Based Candidate Filtering	We present a fully automatic method employing convolutional neural networks based on the 2D U-net architecture and random forest classifier to solve the automatic liver lesion segmentation problem of the ISBI 2017 Liver Tumor Segmentation Challenge (LiTS). In order to constrain the ROI in which the tumors could be loca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,694
2110.03680	Burst Image Restoration and Enhancement	Modern handheld devices can acquire burst image sequence in a quick succession. However, the individual acquired frames suffer from multiple degradations and are misaligned due to camera shake and object motions. The goal of Burst Image Restoration is to effectively combine complimentary cues across multiple burst fram...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	259,590
1704.04912	Pseudorehearsal in actor-critic agents	Catastrophic forgetting has a serious impact in reinforcement learning, as the data distribution is generally sparse and non-stationary over time. The purpose of this study is to investigate whether pseudorehearsal can increase performance of an actor-critic agent with neural-network based policy selection and function...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	71,916
2411.00270	Unsupervised Feature Selection Algorithm Based on Graph Filtering and Self-representation	Aiming at the problem that existing methods could not fully capture the intrinsic structure of data without considering the higher-order neighborhood information of the data, we proposed an unsupervised feature selection algorithm based on graph filtering and self-representation. Firstly,a higher-order graph filter was...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,515
2406.15955	Beyond the Doors of Perception: Vision Transformers Represent Relations Between Objects	Though vision transformers (ViTs) have achieved state-of-the-art performance in a variety of settings, they exhibit surprising failures when performing tasks involving visual relations. This begs the question: how do ViTs attempt to perform tasks that require computing visual relations between objects? Prior efforts to...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	466,933
1910.00370	Sub-Architecture Ensemble Pruning in Neural Architecture Search	Neural architecture search (NAS) is gaining more and more attention in recent years due to its flexibility and remarkable capability to reduce the burden of neural network design. To achieve better performance, however, the searching process usually costs massive computations that might not be affordable for researcher...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	147,646
2311.10236	Latent Feature-based Data Splits to Improve Generalisation Evaluation: A Hate Speech Detection Case Study	With the ever-growing presence of social media platforms comes the increased spread of harmful content and the need for robust hate speech detection systems. Such systems easily overfit to specific targets and keywords, and evaluating them without considering distribution shifts that might occur between train and test ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	408,456
1804.07612	Revisiting Small Batch Training for Deep Neural Networks	Modern deep neural network training is typically based on mini-batch stochastic gradient optimization. While the use of large mini-batches increases the available computational parallelism, small batch training has been shown to provide improved generalization performance and allows a significantly smaller memory footp...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	95,558
2406.09411	MuirBench: A Comprehensive Benchmark for Robust Multi-image Understanding	We introduce MuirBench, a comprehensive benchmark that focuses on robust multi-image understanding capabilities of multimodal LLMs. MuirBench consists of 12 diverse multi-image tasks (e.g., scene understanding, ordering) that involve 10 categories of multi-image relations (e.g., multiview, temporal relations). Comprisi...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	463,930
1603.01882	Composing inference algorithms as program transformations	Probabilistic inference procedures are usually coded painstakingly from scratch, for each target model and each inference algorithm. We reduce this effort by generating inference procedures from models automatically. We make this code generation modular by decomposing inference algorithms into reusable program-to-progr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	52,949
2410.12216	Learning Differentiable Tensegrity Dynamics using Graph Neural Networks	Tensegrity robots are composed of rigid struts and flexible cables. They constitute an emerging class of hybrid rigid-soft robotic systems and are promising systems for a wide array of applications, ranging from locomotion to assembly. They are difficult to control and model accurately, however, due to their compliance...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	498,909
1812.06298	Residual Policy Learning	We present Residual Policy Learning (RPL): a simple method for improving nondifferentiable policies using model-free deep reinforcement learning. RPL thrives in complex robotic manipulation tasks where good but imperfect controllers are available. In these tasks, reinforcement learning from scratch remains data-ineffic...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	116,582
1911.01509	Understanding racial bias in health using the Medical Expenditure Panel Survey data	Over the years, several studies have demonstrated that there exist significant disparities in health indicators in the United States population across various groups. Healthcare expense is used as a proxy for health in algorithms that drive healthcare systems and this exacerbates the existing bias. In this work, we foc...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	152,117
1812.00888	A Consolidated Approach to Convolutional Neural Networks and the Kolmogorov Complexity	The ability to precisely quantify similarity between various entities has been a fundamental complication in various problem spaces specifically in the classification of cellular images. Contemporary similarity measures applied in the domain of image processing proposed by the scientific community are mainly pursued in...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	115,375
2312.11723	Improving Uniquely Decodable Codes in Binary Adder Channels	We present a general method to modify existing uniquely decodable codes in the $T$-user binary adder channel. If at least one of the original constituent codes does not have average weight exactly half of the dimension, then our method produces a new set of constituent codes in a higher dimension, with a strictly highe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	416,690
2310.08571	Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders	Machine Learning as a Service (MLaaS) APIs provide ready-to-use and high-utility encoders that generate vector representations for given inputs. Since these encoders are very costly to train, they become lucrative targets for model stealing attacks during which an adversary leverages query access to the API to replicat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	399,437
1604.03222	Fuzzy Logic Trajectory Tracking Controller for a Tanker	This paper proposes a fuzzy logic controller for design of autopilot of a ship. Triangular membership functions have been use for fuzzification and the centroid method for defuzzification. A nonlinear mathematical model of an oil tanker has been considered whose parameters vary with the depth of water. The performance ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	54,460
2308.09267	GraphReason: Enhancing Reasoning Capabilities of Large Language Models through A Graph-Based Verification Approach	Large Language Models (LLMs) have showcased impressive reasoning capabilities, particularly when guided by specifically designed prompts in complex reasoning tasks such as math word problems. These models typically solve tasks using a chain-of-thought approach, which not only bolsters their reasoning abilities but also...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	386,213
2103.07925	An SPH framework for fluid-solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions	The present work proposes an approach for fluid-solid and contact interaction problems including thermo-mechanical coupling and reversible phase transitions. The solid field is assumed to consist of several arbitrarily-shaped, undeformable but mobile rigid bodies, that are evolved in time individually and allowed to ge...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	224,737
2302.00242	The Parametric Stability of Well-separated Spherical Gaussian Mixtures	We quantify the parameter stability of a spherical Gaussian Mixture Model (sGMM) under small perturbations in distribution space. Namely, we derive the first explicit bound to show that for a mixture of spherical Gaussian $P$ (sGMM) in a pre-defined model class, all other sGMM close to $P$ in this model class in total ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,154
2208.00313	Untargeted Region of Interest Selection for GC-MS Data using a Pseudo F-Ratio Moving Window ($\psi$FRMV)	There are many challenges associated with analysing gas chromatography - mass spectrometry (GC-MS) data. Many of these challenges stem from the fact that electron ionisation can make it difficult to recover molecular information due to the high degree of fragmentation with concomitant loss of molecular ion signal. With...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,809
2212.13221	A Combined Synchronization Index for Grassroots Activism on Social Media	Social media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided by inorganic synchronization, which arise from bot actors. It is thus important ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	338,250
2309.05192	Towards Viewpoint Robustness in Bird's Eye View Segmentation	Autonomous vehicles (AV) require that neural networks used for perception be robust to different viewpoints if they are to be deployed across many types of vehicles without the repeated cost of data collection and labeling for each. AV companies typically focus on collecting data from diverse scenarios and locations, b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,992
2110.14709	Sharp-GAN: Sharpness Loss Regularized GAN for Histopathology Image Synthesis	Existing deep learning-based approaches for histopathology image analysis require large annotated training sets to achieve good performance; but annotating histopathology images is slow and resource-intensive. Conditional generative adversarial networks have been applied to generate synthetic histopathology images to a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	263,606
2209.06264	High-resolution semantically-consistent image-to-image translation	Deep learning has become one of remote sensing scientists' most efficient computer vision tools in recent years. However, the lack of training labels for the remote sensing datasets means that scientists need to solve the domain adaptation problem to narrow the discrepancy between satellite image datasets. As a result,...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	317,336
cs/0305027	Managing Inconsistent Intelligence	In this paper we demonstrate that it is possible to manage intelligence in constant time as a pre-process to information fusion through a series of processes dealing with issues such as clustering reports, ranking reports with respect to importance, extraction of prototypes from clusters and immediate classification of...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	537,843
2107.12589	Cross-modal Consensus Network for Weakly Supervised Temporal Action Localization	Weakly supervised temporal action localization (WS-TAL) is a challenging task that aims to localize action instances in the given video with video-level categorical supervision. Both appearance and motion features are used in previous works, while they do not utilize them in a proper way but apply simple concatenation ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,941
2311.15439	Efficient Encoding of Graphics Primitives with Simplex-based Structures	Grid-based structures are commonly used to encode explicit features for graphics primitives such as images, signed distance functions (SDF), and neural radiance fields (NeRF) due to their simple implementation. However, in $n$-dimensional space, calculating the value of a sampled point requires interpolating the values...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,513
1704.06825	Deep Learning for Medical Image Processing: Overview, Challenges and Future	Healthcare sector is totally different from other industry. It is on high priority sector and people expect highest level of care and services regardless of cost. It did not achieve social expectation even though it consume huge percentage of budget. Mostly the interpretations of medical data is being done by medical e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	72,227
1106.1803	Improving the Efficiency of Inductive Logic Programming Through the Use of Query Packs	Inductive logic programming, or relational learning, is a powerful paradigm for machine learning or data mining. However, in order for ILP to become practically useful, the efficiency of ILP systems must improve substantially. To this end, the notion of a query pack is introduced: it structures sets of similar queries....	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,785
2104.01857	Fast Channel Estimation in the Transformed Spatial Domain for Analog Millimeter Wave Systems	Fast channel estimation in millimeter-wave (mmWave) systems is a fundamental enabler of high-gain beamforming, which boosts coverage and capacity. The channel estimation stage typically involves an initial beam training process where a subset of the possible beam directions at the transmitter and receiver is scanned al...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	228,506
2106.01560	CitationIE: Leveraging the Citation Graph for Scientific Information Extraction	Automatically extracting key information from scientific documents has the potential to help scientists work more efficiently and accelerate the pace of scientific progress. Prior work has considered extracting document-level entity clusters and relations end-to-end from raw scientific text, which can improve literatur...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	238,540
1809.05454	Lower Bounds on the Redundancy of Huffman Codes with Known and Unknown Probabilities	In this paper we provide a method to obtain tight lower bounds on the minimum redundancy achievable by a Huffman code when the probability distribution underlying an alphabet is only partially known. In particular, we address the case where the occurrence probabilities are unknown for some of the symbols in an alphabet...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	107,792
0804.2057	Comparing and Combining Methods for Automatic Query Expansion	Query expansion is a well known method to improve the performance of information retrieval systems. In this work we have tested different approaches to extract the candidate query terms from the top ranked documents returned by the first-pass retrieval. One of them is the cooccurrence approach, based on measures of c...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	1,577

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