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
1009.0921	An Efficient Retransmission Based on Network Coding with Unicast Flows	Recently, network coding technique has emerged as a promising approach that supports reliable transmission over wireless loss channels. In existing protocols where users have no interest in considering the encoded packets they had in coding or decoding operations, this rule is expensive and inef-ficient. This paper stu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	7,485
2306.08370	Object Detection in Hyperspectral Image via Unified Spectral-Spatial Feature Aggregation	Deep learning-based hyperspectral image (HSI) classification and object detection techniques have gained significant attention due to their vital role in image content analysis, interpretation, and wider HSI applications. However, current hyperspectral object detection approaches predominantly emphasize either spectral...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,393
2310.05341	From Question to Exploration: Test-Time Adaptation in Semantic Segmentation?	Test-time adaptation (TTA) aims to adapt a model, initially trained on training data, to test data with potential distribution shifts. Most existing TTA methods focus on classification problems. The pronounced success of classification might lead numerous newcomers and engineers to assume that classic TTA techniques ca...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	398,102
2104.06924	Evaluation of Unsupervised Entity and Event Salience Estimation	Salience Estimation aims to predict term importance in documents. Due to few existing human-annotated datasets and the subjective notion of salience, previous studies typically generate pseudo-ground truth for evaluation. However, our investigation reveals that the evaluation protocol proposed by prior work is difficul...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	230,233
1511.08310	Sic Transit Gloria Manuscriptum: Two Views of the Aggregate Fate of Ancient Papers	When PageRank began to be used for ranking in Web search, a concern soon arose that older pages have an inherent --- and potentially unfair --- advantage over emerging pages of high quality, because they have had more time to acquire hyperlink citations. Algorithms were then proposed to compensate for this effect. Curi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	49,522
2405.07666	New Solutions to Delsarte's Dual Linear Programs	Understanding the maximum size of a code with a given minimum distance is a major question in computer science and discrete mathematics. The most fruitful approach for finding asymptotic bounds on such codes is by using Delsarte's theory of association schemes. With this approach, Delsarte constructs a linear program s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	453,809
2408.00082	TASI Lectures on Physics for Machine Learning	These notes are based on lectures I gave at TASI 2024 on Physics for Machine Learning. The focus is on neural network theory, organized according to network expressivity, statistics, and dynamics. I present classic results such as the universal approximation theorem and neural network / Gaussian process correspondence,...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	477,697
2204.00720	Shared User Interfaces of Physiological Data: Systematic Review of Social Biofeedback Systems and Contexts in HCI	As an emerging interaction paradigm, physiological computing is increasingly being used to both measure and feed back information about our internal psychophysiological states. While most applications of physiological computing are designed for individual use, recent research has explored how biofeedback can be sociall...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	289,360
2203.03131	Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models	Recently the prompt-tuning paradigm has attracted significant attention. By only tuning continuous prompts with a frozen pre-trained language model (PLM), prompt-tuning takes a step towards deploying a shared frozen PLM to serve numerous downstream tasks. Although prompt-tuning shows good performance on certain natural...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	283,983
2502.04409	Learning low-dimensional representations of ensemble forecast fields using autoencoder-based methods	Large-scale numerical simulations often produce high-dimensional gridded data that is challenging to process for downstream applications. A prime example is numerical weather prediction, where atmospheric processes are modeled using discrete gridded representations of the physical variables and dynamics. Uncertainties ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,147
2010.00284	Bayesian Policy Search for Stochastic Domains	AI planning can be cast as inference in probabilistic models, and probabilistic programming was shown to be capable of policy search in partially observable domains. Prior work introduces policy search through Markov chain Monte Carlo in deterministic domains, as well as adapts black-box variational inference to stocha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,237
2205.05198	Reducing Activation Recomputation in Large Transformer Models	Training large transformer models is one of the most important computational challenges of modern AI. In this paper, we show how to significantly accelerate training of large transformer models by reducing activation recomputation. Activation recomputation is commonly used to work around memory capacity constraints. Ra...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	295,866
2009.06386	Moment-based Spectrum Sensing Under Generalized Noise Channels	A new spectrum sensing detector is proposed and analytically studied, when it operates under generalized noise channels. Particularly, the McLeish distribution is used to model the underlying noise, which is suitable for both non-Gaussian (impulsive) as well as classical Gaussian noise modeling. The introduced detector...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	195,623
2206.02345	Anomaly Detection with Test Time Augmentation and Consistency Evaluation	Deep neural networks are known to be vulnerable to unseen data: they may wrongly assign high confidence stcores to out-distribuion samples. Recent works try to solve the problem using representation learning methods and specific metrics. In this paper, we propose a simple, yet effective post-hoc anomaly detection algor...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	300,856
2405.13005	Understanding Sarcoidosis Using Large Language Models and Social Media Data	Sarcoidosis is a rare inflammatory disease characterized by the formation of granulomas in various organs. The disease presents diagnostic and treatment challenges due to its diverse manifestations and unpredictable nature. In this study, we employed a Large Language Model (LLM) to analyze sarcoidosis-related discussio...	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	455,738
2405.08597	Risks and Opportunities of Open-Source Generative AI	Applications of Generative AI (Gen AI) are expected to revolutionize a number of different areas, ranging from science & medicine to education. The potential for these seismic changes has triggered a lively debate about the potential risks of the technology, and resulted in calls for tighter regulation, in particular f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	454,151
2307.09437	Grounded Object Centric Learning	The extraction of modular object-centric representations for downstream tasks is an emerging area of research. Learning grounded representations of objects that are guaranteed to be stable and invariant promises robust performance across different tasks and environments. Slot Attention (SA) learns object-centric repres...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	380,172
2008.00816	Evolving Multi-Resolution Pooling CNN for Monaural Singing Voice Separation	Monaural Singing Voice Separation (MSVS) is a challenging task and has been studied for decades. Deep neural networks (DNNs) are the current state-of-the-art methods for MSVS. However, the existing DNNs are often designed manually, which is time-consuming and error-prone. In addition, the network architectures are usua...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,121
1711.06606	Unsupervised Reverse Domain Adaptation for Synthetic Medical Images via Adversarial Training	To realize the full potential of deep learning for medical imaging, large annotated datasets are required for training. Such datasets are difficult to acquire because labeled medical images are not usually available due to privacy issues, lack of experts available for annotation, underrepresentation of rare conditions ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,811
2203.15052	Learning Minimum-Time Flight in Cluttered Environments	We tackle the problem of minimum-time flight for a quadrotor through a sequence of waypoints in the presence of obstacles while exploiting the full quadrotor dynamics. Early works relied on simplified dynamics or polynomial trajectory representations that did not exploit the full actuator potential of the quadrotor, an...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	288,213
2009.11180	AI and Legal Argumentation: Aligning the Autonomous Levels of AI Legal Reasoning	Legal argumentation is a vital cornerstone of justice, underpinning an adversarial form of law, and extensive research has attempted to augment or undertake legal argumentation via the use of computer-based automation including Artificial Intelligence (AI). AI advances in Natural Language Processing (NLP) and Machine L...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	197,097
2302.01486	Xtal2DoS: Attention-based Crystal to Sequence Learning for Density of States Prediction	Modern machine learning techniques have been extensively applied to materials science, especially for property prediction tasks. A majority of these methods address scalar property predictions, while more challenging spectral properties remain less emphasized. We formulate a crystal-to-sequence learning task and propos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	343,615
2107.11359	Rethinking Hard-Parameter Sharing in Multi-Domain Learning	Hard parameter sharing in multi-domain learning (MDL) allows domains to share some of the model parameters to reduce storage cost while improving prediction accuracy. One common sharing practice is to share the bottom layers of a deep neural network among domains while using separate top layers for each domain. In this...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	247,572
1809.10610	Counterfactual Fairness in Text Classification through Robustness	In this paper, we study counterfactual fairness in text classification, which asks the question: How would the prediction change if the sensitive attribute referenced in the example were different? Toxicity classifiers demonstrate a counterfactual fairness issue by predicting that "Some people are gay" is toxic while "...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	108,944
1903.00780	Fairness in Recommendation Ranking through Pairwise Comparisons	Recommender systems are one of the most pervasive applications of machine learning in industry, with many services using them to match users to products or information. As such it is important to ask: what are the possible fairness risks, how can we quantify them, and how should we address them? In this paper we offer ...	false	false	false	false	true	true	true	false	false	false	false	false	false	true	false	false	false	false	123,099
2003.01871	Semantic sensor fusion: from camera to sparse lidar information	To navigate through urban roads, an automated vehicle must be able to perceive and recognize objects in a three-dimensional environment. A high-level contextual understanding of the surroundings is necessary to plan and execute accurate driving maneuvers. This paper presents an approach to fuse different sensory inform...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	166,782
2202.12183	Large-scale Stochastic Optimization of NDCG Surrogates for Deep Learning with Provable Convergence	NDCG, namely Normalized Discounted Cumulative Gain, is a widely used ranking metric in information retrieval and machine learning. However, efficient and provable stochastic methods for maximizing NDCG are still lacking, especially for deep models. In this paper, we propose a principled approach to optimize NDCG and it...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	282,140
2403.00994	Leveraging Prompt-Based Large Language Models: Predicting Pandemic Health Decisions and Outcomes Through Social Media Language	We introduce a multi-step reasoning framework using prompt-based LLMs to examine the relationship between social media language patterns and trends in national health outcomes. Grounded in fuzzy-trace theory, which emphasizes the importance of gists of causal coherence in effective health communication, we introduce Ro...	true	false	false	true	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,219
2408.13100	Complete Autonomous Robotic Nasopharyngeal Swab System with Evaluation on a Stochastically Moving Phantom Head	The application of autonomous robotics to close-contact healthcare tasks has a clear role for the future due to its potential to reduce infection risks to staff and improve clinical efficiency. Nasopharyngeal (NP) swab sample collection for diagnosing upper-respiratory illnesses is one type of close contact task that i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	483,007
1611.05190	Driving CDCL Search	The CDCL algorithm is the leading solution adopted by state-of-the-art solvers for SAT, SMT, ASP, and others. Experiments show that the performance of CDCL solvers can be significantly boosted by embedding domain-specific heuristics, especially on large real-world problems. However, a proper integration of such criteri...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	63,972
1806.08468	Personalized Thread Recommendation for MOOC Discussion Forums	Social learning, i.e., students learning from each other through social interactions, has the potential to significantly scale up instruction in online education. In many cases, such as in massive open online courses (MOOCs), social learning is facilitated through discussion forums hosted by course providers. In this p...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	101,158
2405.04028	Masked Graph Transformer for Large-Scale Recommendation	Graph Transformers have garnered significant attention for learning graph-structured data, thanks to their superb ability to capture long-range dependencies among nodes. However, the quadratic space and time complexity hinders the scalability of Graph Transformers, particularly for large-scale recommendation. Here we p...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	452,413
2002.03374	Communication Efficient Secret Sharing in the Presence of Malicious Adversary	Consider the communication efficient secret sharing problem. A dealer wants to share a secret with $n$ parties such that any $k\leq n$ parties can reconstruct the secret and any $z<k$ parties eavesdropping on their shares obtain no information about the secret. In addition, a legitimate user contacting any $d$, $k\leq ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	163,244
2211.09847	CoLI-Machine Learning Approaches for Code-mixed Language Identification at the Word Level in Kannada-English Texts	The task of automatically identifying a language used in a given text is called Language Identification (LI). India is a multilingual country and many Indians especially youths are comfortable with Hindi and English, in addition to their local languages. Hence, they often use more than one language to post their commen...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	331,119
2009.06899	Co-evolution of Functional Brain Network at Multiple Scales during Early Infancy	The human brains are organized into hierarchically modular networks facilitating efficient and stable information processing and supporting diverse cognitive processes during the course of development. While the remarkable reconfiguration of functional brain network has been firmly established in early life, all these ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	195,784
2107.03380	RRL: Resnet as representation for Reinforcement Learning	The ability to autonomously learn behaviors via direct interactions in uninstrumented environments can lead to generalist robots capable of enhancing productivity or providing care in unstructured settings like homes. Such uninstrumented settings warrant operations only using the robot's proprioceptive sensor such as o...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	245,144
2209.03300	Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising	Position emission tomography (PET) is widely used in clinics and research due to its quantitative merits and high sensitivity, but suffers from low signal-to-noise ratio (SNR). Recently convolutional neural networks (CNNs) have been widely used to improve PET image quality. Though successful and efficient in local feat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	316,463
2301.06620	Does Spending More Always Ensure Higher Cooperation? An Analysis of Institutional Incentives on Heterogeneous Networks	Humans have developed considerable machinery used at scale to create policies and to distribute incentives, yet we are forever seeking ways in which to improve upon these, our institutions. Especially when funding is limited, it is imperative to optimise spending without sacrificing positive outcomes, a challenge which...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	340,686
2404.14811	FLARE: A New Federated Learning Framework with Adjustable Learning Rates over Resource-Constrained Wireless Networks	Wireless federated learning (WFL) suffers from heterogeneity prevailing in the data distributions, computing powers, and channel conditions of participating devices. This paper presents a new Federated Learning with Adjusted leaRning ratE (FLARE) framework to mitigate the impact of the heterogeneity. The key idea is to...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,828
2102.07945	Local Hyper-Flow Diffusion	Recently, hypergraphs have attracted a lot of attention due to their ability to capture complex relations among entities. The insurgence of hypergraphs has resulted in data of increasing size and complexity that exhibit interesting small-scale and local structure, e.g., small-scale communities and localized node-rankin...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	220,283
2403.16124	Enhancing Visual Continual Learning with Language-Guided Supervision	Continual learning (CL) aims to empower models to learn new tasks without forgetting previously acquired knowledge. Most prior works concentrate on the techniques of architectures, replay data, regularization, \etc. However, the category name of each class is largely neglected. Existing methods commonly utilize the one...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	440,880
2004.09316	Degree-targeted cascades in modular, degree-heterogeneous networks	The dynamics of cascading activation, such as rapid changes in public opinion and the outbreak of disease epidemics, have a crucial dependence on the connectivity patterns among the agents. We study cascading dynamics in modular, degree-heterogeneous networks, and consider the impact of intra-module seeding strategy on...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	173,311
2112.07239	Compensating trajectory bias for unsupervised patient stratification using adversarial recurrent neural networks	Electronic healthcare records are an important source of information which can be used in patient stratification to discover novel disease phenotypes. However, they can be challenging to work with as data is often sparse and irregularly sampled. One approach to solve these limitations is learning dense embeddings that ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,421
2205.04992	KeypointNeRF: Generalizing Image-based Volumetric Avatars using Relative Spatial Encoding of Keypoints	Image-based volumetric humans using pixel-aligned features promise generalization to unseen poses and identities. Prior work leverages global spatial encodings and multi-view geometric consistency to reduce spatial ambiguity. However, global encodings often suffer from overfitting to the distribution of the training da...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	295,809
quant-ph/0610200	Quantum List Decoding of Classical Block Codes of Polynomially Small Rate from Quantumly Corrupted Codewords	Given a classical error-correcting block code, the task of quantum list decoding is to produce from any quantumly corrupted codeword a short list containing all messages whose codewords exhibit high "presence" in the quantumly corrupted codeword. Efficient quantum list decoders have been used to prove a quantum hardcor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	540,905
2112.03364	Scalable Geometric Deep Learning on Molecular Graphs	Deep learning in molecular and materials sciences is limited by the lack of integration between applied science, artificial intelligence, and high-performance computing. Bottlenecks with respect to the amount of training data, the size and complexity of model architectures, and the scale of the compute infrastructure a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,170
2308.00911	Optimal Sensor Deception to Deviate from an Allowed Itinerary	In this work, we study a class of deception planning problems in which an agent aims to alter a security monitoring system's sensor readings so as to disguise its adversarial itinerary as an allowed itinerary in the environment. The adversarial itinerary set and allowed itinerary set are captured by regular languages. ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	383,071
1810.00360	Improving Bag-of-Visual-Words Towards Effective Facial Expressive Image Classification	Bag-of-Visual-Words (BoVW) approach has been widely used in the recent years for image classification purposes. However, the limitations regarding optimal feature selection, clustering technique, the lack of spatial organization of the data and the weighting of visual words are crucial. These factors affect the stabili...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	109,162
2309.09582	Fabricator: An Open Source Toolkit for Generating Labeled Training Data with Teacher LLMs	Most NLP tasks are modeled as supervised learning and thus require labeled training data to train effective models. However, manually producing such data at sufficient quality and quantity is known to be costly and time-intensive. Current research addresses this bottleneck by exploring a novel paradigm called zero-shot...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	392,670
2303.04381	Automatically Auditing Large Language Models via Discrete Optimization	Auditing large language models for unexpected behaviors is critical to preempt catastrophic deployments, yet remains challenging. In this work, we cast auditing as an optimization problem, where we automatically search for input-output pairs that match a desired target behavior. For example, we might aim to find a non-...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	350,067
2312.13528	DyBluRF: Dynamic Deblurring Neural Radiance Fields for Blurry Monocular Video	Neural Radiance Fields (NeRF), initially developed for static scenes, have inspired many video novel view synthesis techniques. However, the challenge for video view synthesis arises from motion blur, a consequence of object or camera movement during exposure, which hinders the precise synthesis of sharp spatio-tempora...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,339
2309.08302	T-UDA: Temporal Unsupervised Domain Adaptation in Sequential Point Clouds	Deep perception models have to reliably cope with an open-world setting of domain shifts induced by different geographic regions, sensor properties, mounting positions, and several other reasons. Since covering all domains with annotated data is technically intractable due to the endless possible variations, researcher...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	392,118
2407.10828	Towards Enhanced Classification of Abnormal Lung sound in Multi-breath: A Light Weight Multi-label and Multi-head Attention Classification Method	This study aims to develop an auxiliary diagnostic system for classifying abnormal lung respiratory sounds, enhancing the accuracy of automatic abnormal breath sound classification through an innovative multi-label learning approach and multi-head attention mechanism. Addressing the issue of class imbalance and lack of...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	473,146
1507.03698	Lifting GIS Maps into Strong Geometric Context for Scene Understanding	Contextual information can have a substantial impact on the performance of visual tasks such as semantic segmentation, object detection, and geometric estimation. Data stored in Geographic Information Systems (GIS) offers a rich source of contextual information that has been largely untapped by computer vision. We prop...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,095
2401.03588	Gate--Level Statistical Timing Analysis: Exact Solutions, Approximations and Algorithms	In this paper, the Statistical Static Timing Analysis (SSTA) is considered within the block--based approach. The statistical model of the logic gate delay propagation is systematically studied and the exact analytical solution is obtained, which is strongly non-Gaussian. The procedure of handling such (non-Gaussian) di...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	420,162
2410.22134	ProMoE: Fast MoE-based LLM Serving using Proactive Caching	The promising applications of large language models are often limited by the constrained GPU memory capacity available on edge devices. Mixture-of-Experts (MoE) models help address this issue by activating only a subset of the model's parameters during computation. This approach allows the unused parameters to be offlo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	503,516
2409.00851	Dissecting Temporal Understanding in Text-to-Audio Retrieval	Recent advancements in machine learning have fueled research on multimodal tasks, such as for instance text-to-video and text-to-audio retrieval. These tasks require models to understand the semantic content of video and audio data, including objects, and characters. The models also need to learn spatial arrangements a...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	485,097
2408.08925	Retail-GPT: leveraging Retrieval Augmented Generation (RAG) for building E-commerce Chat Assistants	This work presents Retail-GPT, an open-source RAG-based chatbot designed to enhance user engagement in retail e-commerce by guiding users through product recommendations and assisting with cart operations. The system is cross-platform and adaptable to various e-commerce domains, avoiding reliance on specific chat appli...	true	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	481,215
2404.00390	Learning truly monotone operators with applications to nonlinear inverse problems	This article introduces a novel approach to learning monotone neural networks through a newly defined penalization loss. The proposed method is particularly effective in solving classes of variational problems, specifically monotone inclusion problems, commonly encountered in image processing tasks. The Forward-Backwar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	442,899
2501.13397	ExLM: Rethinking the Impact of [MASK] Tokens in Masked Language Models	Masked Language Models (MLMs) have achieved remarkable success in many self-supervised representation learning tasks. MLMs are trained by randomly masking portions of the input sequences with [MASK] tokens and learning to reconstruct the original content based on the remaining context. This paper explores the impact of...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	526,670
2404.05183	Progressive Alignment with VLM-LLM Feature to Augment Defect Classification for the ASE Dataset	Traditional defect classification approaches are facing with two barriers. (1) Insufficient training data and unstable data quality. Collecting sufficient defective sample is expensive and time-costing, consequently leading to dataset variance. It introduces the difficulty on recognition and learning. (2) Over-dependen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	444,972
2003.06068	Snapshot Samplings of the Bitcoin Transaction Network and Analysis of Cryptocurrency Growth	The purpose of this work was to perform a network analysis on the rapidly growing bitcoin transaction network. Using a web-socket API, we collected data on all transactions occurring during a six hour window. Sender and receiver addresses as well as the amount of bitcoin exchanged were record. Graphs were generated, us...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	168,017
1707.03350	MovePattern: Interactive Framework to Provide Scalable Visualization of Movement Patterns	The rapid growth of movement data sources such as GPS traces, traffic networks and social media have provided analysts with the opportunity to explore collective patterns of geographical movements in a nearly real-time fashion. A fast and interactive visualization framework can help analysts to understand these massive...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	true	76,848
2502.13407	JL1-CD: A New Benchmark for Remote Sensing Change Detection and a Robust Multi-Teacher Knowledge Distillation Framework	Deep learning has achieved significant success in the field of remote sensing image change detection (CD), yet two major challenges remain: the scarcity of sub-meter, all-inclusive open-source CD datasets, and the difficulty of achieving consistent and satisfactory detection results across images with varying change ar...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	535,352
1901.01985	Combining Unsupervised and Supervised Learning for Asset Class Failure Prediction in Power Systems	In power systems, an asset class is a group of power equipment that has the same function and shares similar electrical or mechanical characteristics. Predicting failures for different asset classes is critical for electric utilities towards developing cost-effective asset management strategies. Previously, physical ag...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,094
2011.09270	Respiratory Distress Detection from Telephone Speech using Acoustic and Prosodic Features	With the widespread use of telemedicine services, automatic assessment of health conditions via telephone speech can significantly impact public health. This work summarizes our preliminary findings on automatic detection of respiratory distress using well-known acoustic and prosodic features. Speech samples are collec...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	207,139
1605.01435	A Fast Lightweight Time-Series Store for IoT Data	With the advent of the Internet-of-Things (IoT), handling large volumes of time-series data has become a growing concern. Data, generated from millions of Internet-connected sensors, will drive new IoT applications and services. A key requirement is the ability to aggregate, preprocess, index, store and analyze data wi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	55,480
2303.16956	FeDiSa: A Semi-asynchronous Federated Learning Framework for Power System Fault and Cyberattack Discrimination	With growing security and privacy concerns in the Smart Grid domain, intrusion detection on critical energy infrastructure has become a high priority in recent years. To remedy the challenges of privacy preservation and decentralized power zones with strategic data owners, Federated Learning (FL) has contemporarily sur...	false	false	false	false	false	false	true	false	false	false	true	false	true	false	false	false	false	true	355,054
0812.1557	To Cooperate, or Not to Cooperate in Imperfectly-Known Fading Channels	In this paper, communication over imperfectly-known fading channels with different degrees of cooperation is studied. The three-node relay channel is considered. It is assumed that communication starts with the network training phase in which the receivers estimate the fading coefficients of their respective channels. ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,763
1602.01569	Unraveling the Rank-One Solution Mystery of Robust MISO Downlink Transmit Optimization: A Verifiable Sufficient Condition via a New Duality Result	This paper concentrates on a robust transmit optimization problem for the multiuser multi-input single-output (MISO) downlink scenario and under inaccurate channel state information (CSI). This robust problem deals with a general-rank transmit covariance design, and it follows a safe rate-constrained formulation under ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,717
2301.03047	Large-scale Global Low-rank Optimization for Computational Compressed Imaging	Computational reconstruction plays a vital role in computer vision and computational photography. Most of the conventional optimization and deep learning techniques explore local information for reconstruction. Recently, nonlocal low-rank (NLR) reconstruction has achieved remarkable success in improving accuracy and ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	339,679
2404.05187	LGSDF: Continual Global Learning of Signed Distance Fields Aided by Local Updating	Implicit reconstruction of ESDF (Euclidean Signed Distance Field) involves training a neural network to regress the signed distance from any point to the nearest obstacle, which has the advantages of lightweight storage and continuous querying. However, existing algorithms usually rely on conflicting raw observations a...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	true	444,975
2412.09424	Slope Considered Online Nonlinear Trajectory Planning with Differential Energy Model for Autonomous Driving	Achieving energy-efficient trajectory planning for autonomous driving remains a challenge due to the limitations of model-agnostic approaches. This study addresses this gap by introducing an online nonlinear programming trajectory optimization framework that integrates a differentiable energy model into autonomous syst...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	516,479
2206.11752	CLAMP: Prompt-based Contrastive Learning for Connecting Language and Animal Pose	Animal pose estimation is challenging for existing image-based methods because of limited training data and large intra- and inter-species variances. Motivated by the progress of visual-language research, we propose that pre-trained language models (e.g., CLIP) can facilitate animal pose estimation by providing rich pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,359
2205.08675	Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation	We introduce a novel setup for low-resource task-oriented semantic parsing which incorporates several constraints that may arise in real-world scenarios: (1) lack of similar datasets/models from a related domain, (2) inability to sample useful logical forms directly from a grammar, and (3) privacy requirements for unla...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	297,016
2207.01230	Intelligent Reflecting Surface Enabled Multi-Target Sensing	Besides improving communication performance, intelligent reflecting surfaces (IRSs) are also promising enablers for achieving larger sensing coverage and enhanced sensing quality. Nevertheless, in the absence of a direct path between the base station (BS) and the targets, multi-target sensing is generally very difficul...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	306,093
1703.01135	Deep Learning with Domain Adaptation for Accelerated Projection-Reconstruction MR	Purpose: The radial k-space trajectory is a well-established sampling trajectory used in conjunction with magnetic resonance imaging. However, the radial k-space trajectory requires a large number of radial lines for high-resolution reconstruction. Increasing the number of radial lines causes longer acquisition time, m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	69,300
0911.4230	Introduction to Bioinformatics	Bioinformatics is a new discipline that addresses the need to manage and interpret the data that in the past decade was massively generated by genomic research. This discipline represents the convergence of genomics, biotechnology and information technology, and encompasses analysis and interpretation of data, modeling...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	4,994
1901.04962	Multihop Routing for Data Delivery in V2X Networks	Data delivery relying on the carry-and-forward strategy of vehicle-to-vehicle (V2V) communications is of significant importance, however highly challenging due to frequent connection disruption. Fortunately, incorporating vehicle-to-infrastructure (V2I) communications, motivated by its availability in bridging long-ran...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,696
2006.04984	Making Convolutions Resilient via Algorithm-Based Error Detection Techniques	The ability of Convolutional Neural Networks (CNNs) to accurately process real-time telemetry has boosted their use in safety-critical and high-performance computing systems. As such systems require high levels of resilience to errors, CNNs must execute correctly in the presence of hardware faults. Full duplication pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	180,882
2310.04436	Adaptive Control of an Inverted Pendulum by a Reinforcement Learning-based LQR Method	Inverted pendulums constitute one of the popular systems for benchmarking control algorithms. Several methods have been proposed for the control of this system, the majority of which rely on the availability of a mathematical model. However, deriving a mathematical model using physical parameters or system identificati...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	397,650
2112.15550	Improving Baselines in the Wild	We share our experience with the recently released WILDS benchmark, a collection of ten datasets dedicated to developing models and training strategies which are robust to domain shifts. Several experiments yield a couple of critical observations which we believe are of general interest for any future work on WILDS. Ou...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	273,820
2501.09064	Generative diffusion model with inverse renormalization group flows	Diffusion models represent a class of generative models that produce data by denoising a sample corrupted by white noise. Despite the success of diffusion models in computer vision, audio synthesis, and point cloud generation, so far they overlook inherent multiscale structures in data and have a slow generation proces...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,005
2304.05310	Neural Delay Differential Equations: System Reconstruction and Image Classification	Neural Ordinary Differential Equations (NODEs), a framework of continuous-depth neural networks, have been widely applied, showing exceptional efficacy in coping with representative datasets. Recently, an augmented framework has been developed to overcome some limitations that emerged in the application of the original...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	357,574
2105.00363	RADDet: Range-Azimuth-Doppler based Radar Object Detection for Dynamic Road Users	Object detection using automotive radars has not been explored with deep learning models in comparison to the camera based approaches. This can be attributed to the lack of public radar datasets. In this paper, we collect a novel radar dataset that contains radar data in the form of Range-Azimuth-Doppler tensors along ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,192
2406.12676	Systematic equation formulation for simulation of power electronic circuits using explicit methods	Use of explicit integration methods for power electronic circuits with ideal switch models significantly improves simulation speed. The PLECS package [1] has effectively used this idea; however, the implementation details involved in PLECS are not available in the public domain. Recently, a basic framework, called the ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	465,525
2204.00255	NC-DRE: Leveraging Non-entity Clue Information for Document-level Relation Extraction	Document-level relation extraction (RE), which requires reasoning on multiple entities in different sentences to identify complex inter-sentence relations, is more challenging than sentence-level RE. To extract the complex inter-sentence relations, previous studies usually employ graph neural networks (GNN) to perform ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,192
2201.09919	Faithiful Embeddings for EL++ Knowledge Bases	Recently, increasing efforts are put into learning continual representations for symbolic knowledge bases (KBs). However, these approaches either only embed the data-level knowledge (ABox) or suffer from inherent limitations when dealing with concept-level knowledge (TBox), i.e., they cannot faithfully model the logica...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	276,815
2402.02317	INViT: A Generalizable Routing Problem Solver with Invariant Nested View Transformer	Recently, deep reinforcement learning has shown promising results for learning fast heuristics to solve routing problems. Meanwhile, most of the solvers suffer from generalizing to an unseen distribution or distributions with different scales. To address this issue, we propose a novel architecture, called Invariant Nes...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	426,488
1602.02282	Ladder Variational Autoencoders	Variational Autoencoders are powerful models for unsupervised learning. However deep models with several layers of dependent stochastic variables are difficult to train which limits the improvements obtained using these highly expressive models. We propose a new inference model, the Ladder Variational Autoencoder, that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	51,831
1504.03655	Scale Up Nonlinear Component Analysis with Doubly Stochastic Gradients	Nonlinear component analysis such as kernel Principle Component Analysis (KPCA) and kernel Canonical Correlation Analysis (KCCA) are widely used in machine learning, statistics and data analysis, but they can not scale up to big datasets. Recent attempts have employed random feature approximations to convert the proble...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	42,056
2105.09859	An examination of local strain fields evolution in ductile cast iron through micromechanical simulations based on 3D imaging	Microscopic digital volume correlation (DVC) and finite element precoalescence strain evaluations are compared for two nodular cast iron specimens. Displacement fields from \textit{in-situ} 3D synchrotron laminography images are obtained by DVC. Subsequently the microstructure is explicitely meshed from the images cons...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	236,187
2410.04722	A Strategy for Label Alignment in Deep Neural Networks	One recent research demonstrated successful application of the label alignment property for unsupervised domain adaptation in a linear regression settings. Instead of regularizing representation learning to be domain invariant, the research proposed to regularize the linear regression model to align with the top singul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	495,413
2401.12205	Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization	Logic synthesis, a pivotal stage in chip design, entails optimizing chip specifications encoded in hardware description languages like Verilog into highly efficient implementations using Boolean logic gates. The process involves a sequential application of logic minimization heuristics (``synthesis recipe"), with their...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	423,291
2005.13282	Simulation of the COVID-19 pandemic on the social network of Slovenia: estimating the intrinsic forecast uncertainty	In the article a virus transmission model is constructed on a simplified social network. The social network consists of more than 2 million nodes, each representing an inhabitant of Slovenia. The nodes are organised and interconnected according to the real household and elderly-care center distribution, while their con...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	178,969
1410.0443	Strong Converse for a Degraded Wiretap Channel via Active Hypothesis Testing	We establish an upper bound on the rate of codes for a wiretap channel with public feedback for a fixed probability of error and secrecy parameter. As a corollary, we obtain a strong converse for the capacity of a degraded wiretap channel with public feedback. Our converse proof is based on a reduction of active hypoth...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,468
2501.03162	Deep-Relative-Trust-Based Diffusion for Decentralized Deep Learning	Decentralized learning strategies allow a collection of agents to learn efficiently from local data sets without the need for central aggregation or orchestration. Current decentralized learning paradigms typically rely on an averaging mechanism to encourage agreement in the parameter space. We argue that in the contex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	522,780
1909.01409	Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making	It is widely believed that one's peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the pattern by which it receives these signals vary and when peer influence is direc...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	143,888
1409.8484	An agent-driven semantical identifier using radial basis neural networks and reinforcement learning	Due to the huge availability of documents in digital form, and the deception possibility raise bound to the essence of digital documents and the way they are spread, the authorship attribution problem has constantly increased its relevance. Nowadays, authorship attribution,for both information retrieval and analysis, h...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	true	true	false	false	36,413
2107.11214	A3GC-IP: Attention-Oriented Adjacency Adaptive Recurrent Graph Convolutions for Human Pose Estimation from Sparse Inertial Measurements	Conventional methods for human pose estimation either require a high degree of instrumentation, by relying on many inertial measurement units (IMUs), or constraint the recording space, by relying on extrinsic cameras. These deficits are tackled through the approach of human pose estimation from sparse IMU data. We defi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	247,536

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