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
2312.09022	BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment	Effective connectivity estimation plays a crucial role in understanding the interactions and information flow between different brain regions. However, the functional time series used for estimating effective connectivity is derived from certain software, which may lead to large computing errors because of different pa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,567
2312.11470	An Improved Anomaly Detection Model for Automated Inspection of Power Line Insulators	Inspection of insulators is important to ensure reliable operation of the power system. Deep learning is being increasingly exploited to automate the inspection process by leveraging object detection models to analyse aerial images captured by drones. A purely object detection-based approach, however, suffers from clas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	416,581
2108.05814	Decoder Fusion RNN: Context and Interaction Aware Decoders for Trajectory Prediction	Forecasting the future behavior of all traffic agents in the vicinity is a key task to achieve safe and reliable autonomous driving systems. It is a challenging problem as agents adjust their behavior depending on their intentions, the others' actions, and the road layout. In this paper, we propose Decoder Fusion RNN (...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	250,419
2305.07779	Achieving Capacity on Non-Binary Channels with Generalized Reed-Muller Codes	Recently, the authors showed that Reed-Muller (RM) codes achieve capacity on binary memoryless symmetric (BMS) channels with respect to bit error rate. This paper extends that work by showing that RM codes defined on non-binary fields, known as generalized RM codes, achieve capacity on sufficiently symmetric non-binary...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	364,022
2402.01206	Comparative Evaluation of Weather Forecasting using Machine Learning Models	Gaining a deeper understanding of weather and being able to predict its future conduct have always been considered important endeavors for the growth of our society. This research paper explores the advancements in understanding and predicting nature's behavior, particularly in the context of weather forecasting, throu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	425,912
2007.05611	Deep Contextual Clinical Prediction with Reverse Distillation	Healthcare providers are increasingly using machine learning to predict patient outcomes to make meaningful interventions. However, despite innovations in this area, deep learning models often struggle to match performance of shallow linear models in predicting these outcomes, making it difficult to leverage such techn...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	186,726
2412.08742	In-Context Learning with Topological Information for Knowledge Graph Completion	Knowledge graphs (KGs) are crucial for representing and reasoning over structured information, supporting a wide range of applications such as information retrieval, question answering, and decision-making. However, their effectiveness is often hindered by incompleteness, limiting their potential for real-world impact....	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	516,209
2306.05431	LexGPT 0.1: pre-trained GPT-J models with Pile of Law	This research aims to build generative language models specialized for the legal domain. The manuscript presents the development of LexGPT models based on GPT-J models and pre-trained with Pile of Law. The foundation model built in this manuscript is the initial step for the development of future applications in the le...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	372,198
2404.11731	A Learning-to-Rank Formulation of Clustering-Based Approximate Nearest Neighbor Search	A critical piece of the modern information retrieval puzzle is approximate nearest neighbor search. Its objective is to return a set of $k$ data points that are closest to a query point, with its accuracy measured by the proportion of exact nearest neighbors captured in the returned set. One popular approach to this qu...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	447,585
1401.7020	A Stochastic Quasi-Newton Method for Large-Scale Optimization	The question of how to incorporate curvature information in stochastic approximation methods is challenging. The direct application of classical quasi- Newton updating techniques for deterministic optimization leads to noisy curvature estimates that have harmful effects on the robustness of the iteration. In this paper...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	30,421
2007.01884	High-recall causal discovery for autocorrelated time series with latent confounders	We present a new method for linear and nonlinear, lagged and contemporaneous constraint-based causal discovery from observational time series in the presence of latent confounders. We show that existing causal discovery methods such as FCI and variants suffer from low recall in the autocorrelated time series case and i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	185,559
2309.14329	Innovative Digital Storytelling with AIGC: Exploration and Discussion of Recent Advances	Digital storytelling, as an art form, has struggled with cost-quality balance. The emergence of AI-generated Content (AIGC) is considered as a potential solution for efficient digital storytelling production. However, the specific form, effects, and impacts of this fusion remain unclear, leaving the boundaries of AIGC ...	true	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	394,559
1309.6613	Continuous-time Proportional-Integral Distributed Optimization for Networked Systems	In this paper we explore the relationship between dual decomposition and the consensus-based method for distributed optimization. The relationship is developed by examining the similarities between the two approaches and their relationship to gradient-based constrained optimization. By formulating each algorithm in con...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	27,256
2308.13862	Late Stopping: Avoiding Confidently Learning from Mislabeled Examples	Sample selection is a prevalent method in learning with noisy labels, where small-loss data are typically considered as correctly labeled data. However, this method may not effectively identify clean hard examples with large losses, which are critical for achieving the model's close-to-optimal generalization performanc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	388,086
1503.01393	A Hierarchical Approach for Joint Multi-view Object Pose Estimation and Categorization	We propose a joint object pose estimation and categorization approach which extracts information about object poses and categories from the object parts and compositions constructed at different layers of a hierarchical object representation algorithm, namely Learned Hierarchy of Parts (LHOP). In the proposed approach,...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	40,820
2305.18228	SR-OOD: Out-of-Distribution Detection via Sample Repairing	Out-of-distribution (OOD) detection is a crucial task for ensuring the reliability and robustness of machine learning models. Recent works have shown that generative models often assign high confidence scores to OOD samples, indicating that they fail to capture the semantic information of the data. To tackle this probl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	368,908
2201.12082	Interplay between depth of neural networks and locality of target functions	It has been recognized that heavily overparameterized deep neural networks (DNNs) exhibit surprisingly good generalization performance in various machine-learning tasks. Although benefits of depth have been investigated from different perspectives such as the approximation theory and the statistical learning theory, ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	277,515
1808.09036	ParsRec: Meta-Learning Recommendations for Bibliographic Reference Parsing	Bibliographic reference parsers extract metadata (e.g. author names, title, year) from bibliographic reference strings. No reference parser consistently gives the best results in every scenario. For instance, one tool may be best in extracting titles, and another tool in extracting author names. In this paper, we addre...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	106,092
2107.03256	"Are you sure?": Preliminary Insights from Scaling Product Comparisons to Multiple Shops	Large eCommerce players introduced comparison tables as a new type of recommendations. However, building comparisons at scale without pre-existing training/taxonomy data remains an open challenge, especially within the operational constraints of shops in the long tail. We present preliminary results from building a com...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	245,104
2006.03647	Deployment-Efficient Reinforcement Learning via Model-Based Offline Optimization	Most reinforcement learning (RL) algorithms assume online access to the environment, in which one may readily interleave updates to the policy with experience collection using that policy. However, in many real-world applications such as health, education, dialogue agents, and robotics, the cost or potential risk of de...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	180,381
2406.07049	GridPE: Unifying Positional Encoding in Transformers with a Grid Cell-Inspired Framework	Understanding spatial location and relationships is a fundamental capability for modern artificial intelligence systems. Insights from human spatial cognition provide valuable guidance in this domain. Neuroscientific discoveries have highlighted the role of grid cells as a fundamental neural component for spatial repre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	462,876
2006.04050	Growing Together: Modeling Human Language Learning With n-Best Multi-Checkpoint Machine Translation	We describe our submission to the 2020 Duolingo Shared Task on Simultaneous Translation And Paraphrase for Language Education (STAPLE) (Mayhew et al., 2020). We view MT models at various training stages (i.e., checkpoints) as human learners at different levels. Hence, we employ an ensemble of multi-checkpoints from the...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	180,538
2404.00543	Dynamic Transfer Policies for Parallel Queues	We consider the problem of load balancing in parallel queues by transferring customers between them at discrete points in time. Holding costs accrue as customers wait in the queue, while transfer decisions incur both fixed (setup) and variable costs proportional to the number and direction of transfers. Our work is pri...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	442,981
2006.12061	Object Tracking through Residual and Dense LSTMs	Visual object tracking task is constantly gaining importance in several fields of application as traffic monitoring, robotics, and surveillance, to name a few. Dealing with changes in the appearance of the tracked object is paramount to achieve high tracking accuracy, and is usually achieved by continually learning fea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	183,460
2208.08552	A Framework for Understanding and Visualizing Strategies of RL Agents	Recent years have seen significant advances in explainable AI as the need to understand deep learning models has gained importance with the increased emphasis on trust and ethics in AI. Comprehensible models for sequential decision tasks are a particular challenge as they require understanding not only individual predi...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	313,390
2404.04935	Anomaly Detection in Electrocardiograms: Advancing Clinical Diagnosis Through Self-Supervised Learning	The electrocardiogram (ECG) is an essential tool for diagnosing heart disease, with computer-aided systems improving diagnostic accuracy and reducing healthcare costs. Despite advancements, existing systems often miss rare cardiac anomalies that could be precursors to serious, life-threatening issues or alterations in ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	444,870
2003.00123	Assessing Energy Storage Requirements Based on Accepted Risks	This paper presents a framework for deriving the storage capacity that an electricity system requires in order to satisfy a chosen risk appetite. The framework takes as inputs user-defined event categories, parameterised by peak power-not-served, acceptable number of events per year and permitted probability of exceedi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	166,197
2111.12395	I'll be back: Examining Restored Accounts On Twitter	Online social networks like Twitter actively monitor their platform to identify accounts that go against their rules. Twitter enforces account level moderation, i.e. suspension of a Twitter account in severe cases of platform abuse. A point of note is that these suspensions are sometimes temporary and even incorrect. T...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	267,955
2311.06481	Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning	To facilitate reliable deployments of autonomous robots in the real world, Out-of-Distribution (OOD) detection capabilities are often required. A powerful approach for OOD detection is based on density estimation with Normalizing Flows (NFs). However, we find that prior work with NFs attempts to match the complex targe...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	406,953
2401.13677	Process Mining for Unstructured Data: Challenges and Research Directions	The application of process mining for unstructured data might significantly elevate novel insights into disciplines where unstructured data is a common data format. To efficiently analyze unstructured data by process mining and to convey confidence into the analysis result, requires bridging multiple challenges. The pu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	423,815
1402.0587	Asymmetric Distributed Constraint Optimization Problems	Distributed Constraint Optimization (DCOP) is a powerful framework for representing and solving distributed combinatorial problems, where the variables of the problem are owned by different agents. Many multi-agent problems include constraints that produce different gains (or costs) for the participating agents. Asymme...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	30,601
1207.0135	Privacy Preservation by Disassociation	In this work, we focus on protection against identity disclosure in the publication of sparse multidimensional data. Existing multidimensional anonymization techniquesa) protect the privacy of users either by altering the set of quasi-identifiers of the original data (e.g., by generalization or suppression) or by addin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	17,129
2402.12702	From Cloud to Edge: Rethinking Generative AI for Low-Resource Design Challenges	Generative Artificial Intelligence (AI) has shown tremendous prospects in all aspects of technology, including design. However, due to its heavy demand on resources, it is usually trained on large computing infrastructure and often made available as a cloud-based service. In this position paper, we consider the potenti...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	430,953
2008.08502	Learning Trailer Moments in Full-Length Movies	A movie's key moments stand out of the screenplay to grab an audience's attention and make movie browsing efficient. But a lack of annotations makes the existing approaches not applicable to movie key moment detection. To get rid of human annotations, we leverage the officially-released trailers as the weak supervision...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	192,441
1207.3035	Fundamental Limits of Communications in Interference Networks-Part III: Information Flow in Strong Interference Regime	This third part of the paper is related to the study of information flow in networks with strong interference. First, the two-receiver networks are considered. A unified outer bound for the capacity region of these networks is established. It is shown that this outer bound can be systematically translated into simple c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,433
2212.05378	Neural Continuous-Time Markov Models	Continuous-time Markov chains are used to model stochastic systems where transitions can occur at irregular times, e.g., birth-death processes, chemical reaction networks, population dynamics, and gene regulatory networks. We develop a method to learn a continuous-time Markov chain's transition rate functions from full...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	335,771
2403.17656	SGHormer: An Energy-Saving Graph Transformer Driven by Spikes	Graph Transformers (GTs) with powerful representation learning ability make a huge success in wide range of graph tasks. However, the costs behind outstanding performances of GTs are higher energy consumption and computational overhead. The complex structure and quadratic complexity during attention calculation in vani...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	441,560
2410.13349	GlossyGS: Inverse Rendering of Glossy Objects with 3D Gaussian Splatting	Reconstructing objects from posed images is a crucial and complex task in computer graphics and computer vision. While NeRF-based neural reconstruction methods have exhibited impressive reconstruction ability, they tend to be time-comsuming. Recent strategies have adopted 3D Gaussian Splatting (3D-GS) for inverse rende...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	499,497
2306.06283	14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon	Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To explore these possibilities, we organized a hackathon. This article chronicles the projects built as part of this hackathon. Participants...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	372,543
2309.03989	CDFSL-V: Cross-Domain Few-Shot Learning for Videos	Few-shot video action recognition is an effective approach to recognizing new categories with only a few labeled examples, thereby reducing the challenges associated with collecting and annotating large-scale video datasets. Existing methods in video action recognition rely on large labeled datasets from the same domai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,577
1905.02171	Spatio-Temporal Action Localization in a Weakly Supervised Setting	Enabling computational systems with the ability to localize actions in video-based content has manifold applications. Traditionally, such a problem is approached in a fully-supervised setting where video-clips with complete frame-by-frame annotations around the actions of interest are provided for training. However, th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,907
1803.07326	Pushing for higher rates and efficiency in Satcom: the different perspectives within SatNExIV	SatNEx IV project aims at studying medium and long term directions of satellite telecommunication systems for any of the commercial or institutional applications that can be considered appealing by key players although still not mature enough for attracting industry or initiating dedicated ESA R&D activities. This pape...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	93,024
2501.10328	BoK: Introducing Bag-of-Keywords Loss for Interpretable Dialogue Response Generation	The standard language modeling (LM) loss by itself has been shown to be inadequate for effective dialogue modeling. As a result, various training approaches, such as auxiliary loss functions and leveraging human feedback, are being adopted to enrich open-domain dialogue systems. One such auxiliary loss function is Bag-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	525,473
2301.12821	Measuring and Analyzing Effects of HEMP Simulation on Synthetic Power Grids	There is significant uncertainty about the potential effects of a high-altitude electromagnetic pulse (HEMP) detonation on the bulk electric system. This study attempts to account for such uncertainty, in using Monte-Carlo methods to account for speculated range of effect of HEMP contingency. Through task parallelism a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	342,680
2107.01241	Temporal Regular Path Queries	In the last decade, substantial progress has been made towards standardizing the syntax of graph query languages, and towards understanding their semantics and complexity of evaluation. In this paper, we consider temporal property graphs (TPGs) and propose temporal regular path queries (TRPQs) that incorporate time int...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	244,414
1911.10683	Image-based table recognition: data, model, and evaluation	Important information that relates to a specific topic in a document is often organized in tabular format to assist readers with information retrieval and comparison, which may be difficult to provide in natural language. However, tabular data in unstructured digital documents, e.g., Portable Document Format (PDF) and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,906
1907.02230	Attention based Convolutional Recurrent Neural Network for Environmental Sound Classification	Environmental sound classification (ESC) is a challenging problem due to the complexity of sounds. The ESC performance is heavily dependent on the effectiveness of representative features extracted from the environmental sounds. However, ESC often suffers from the semantically irrelevant frames and silent frames. In or...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,567
1610.04551	Tonal consonance parameters link microscopic and macroscopic properties of music exposing a hidden order in melody	Consonance is related to the perception of pleasantness arising from a combination of sounds and has been approached quantitatively using mathematical relations, physics, information theory, and psychoacoustics. Tonal consonance is present in timbre, musical tuning, harmony, and melody, and it is used for conveying sen...	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	62,404
2111.14831	Multi-domain Integrative Swin Transformer network for Sparse-View Tomographic Reconstruction	Decreasing projection views to lower X-ray radiation dose usually leads to severe streak artifacts. To improve image quality from sparse-view data, a Multi-domain Integrative Swin Transformer network (MIST-net) was developed in this article. First, MIST-net incorporated lavish domain features from data, residual-data, ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	268,725
2306.07797	Monolingual and Cross-Lingual Knowledge Transfer for Topic Classification	This article investigates the knowledge transfer from the RuQTopics dataset. This Russian topical dataset combines a large sample number (361,560 single-label, 170,930 multi-label) with extensive class coverage (76 classes). We have prepared this dataset from the "Yandex Que" raw data. By evaluating the RuQTopics - tra...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	373,152
2203.06691	Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors	The main question this work aims at answering is: "can morphing attack detection (MAD) solutions be successfully developed based on synthetic data?". Towards that, this work introduces the first synthetic-based MAD development dataset, namely the Synthetic Morphing Attack Detection Development dataset (SMDD). This data...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,200
1801.05855	On Spectral Graph Embedding: A Non-Backtracking Perspective and Graph Approximation	Graph embedding has been proven to be efficient and effective in facilitating graph analysis. In this paper, we present a novel spectral framework called NOn-Backtracking Embedding (NOBE), which offers a new perspective that organizes graph data at a deep level by tracking the flow traversing on the edges with backtrac...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	88,523
1905.12394	Radio-Map-Based Robust Positioning Optimization for UAV-Enabled Wireless Power Transfer	This letter studies an unmanned aerial vehicle-enabled wireless power transfer system within a radio-map-based robust positioning design.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	132,756
1504.06274	A new approach for physiological time series	We developed a new approach for the analysis of physiological time series. An iterative convolution filter is used to decompose the time series into various components. Statistics of these components are extracted as features to characterize the mechanisms underlying the time series. Motivated by the studies that show ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	42,389
1804.07682	CUDA Support in GNA Data Analysis Framework	Usage of GPUs as co-processors is a well-established approach to accelerate costly algorithms operating on matrices and vectors. We aim to further improve the performance of the Global Neutrino Analysis framework (GNA) by adding GPU support in a way that is transparent to the end user. To achieve our goal we use CUDA...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	95,572
2406.19690	Deep Fusion Model for Brain Tumor Classification Using Fine-Grained Gradient Preservation	Brain tumors are one of the most common diseases that lead to early death if not diagnosed at an early stage. Traditional diagnostic approaches are extremely time-consuming and prone to errors. In this context, computer vision-based approaches have emerged as an effective tool for accurate brain tumor classification. W...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	468,528
2404.08979	BG-YOLO: A Bidirectional-Guided Method for Underwater Object Detection	Degraded underwater images decrease the accuracy of underwater object detection. However, existing methods for underwater image enhancement mainly focus on improving the indicators in visual aspects, which may not benefit the tasks of underwater image detection, and may lead to serious degradation in performance. To al...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	446,493
2407.03110	A Toolchain for Comprehensive Audio/Video Analysis Using Deep Learning Based Multimodal Approach (A use case of riot or violent context detection)	In this paper, we present a toolchain for a comprehensive audio/video analysis by leveraging deep learning based multimodal approach. To this end, different specific tasks of Speech to Text (S2T), Acoustic Scene Classification (ASC), Acoustic Event Detection (AED), Visual Object Detection (VOD), Image Captioning (IC), ...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	470,025
1905.02606	Optimal Control of Complex Systems through Variational Inference with a Discrete Event Decision Process	Complex social systems are composed of interconnected individuals whose interactions result in group behaviors. Optimal control of a real-world complex system has many applications, including road traffic management, epidemic prevention, and information dissemination. However, such real-world complex system control is ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	130,009
2008.08983	Randomness in appendage coordination facilitates strenuous ground self-righting	Randomness is common in biological and artificial systems, resulting either from stochasticity of the environment or noise in organisms or devices themselves. In locomotor control, randomness is typically considered a nuisance. For example, during dynamic walking, randomness in stochastic terrain leads to metastable dy...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	192,576
2401.13325	Memory Consistency Guided Divide-and-Conquer Learning for Generalized Category Discovery	Generalized category discovery (GCD) aims at addressing a more realistic and challenging setting of semi-supervised learning, where only part of the category labels are assigned to certain training samples. Previous methods generally employ naive contrastive learning or unsupervised clustering scheme for all the sample...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	423,692
2406.00329	Whole Heart 3D+T Representation Learning Through Sparse 2D Cardiac MR Images	Cardiac Magnetic Resonance (CMR) imaging serves as the gold-standard for evaluating cardiac morphology and function. Typically, a multi-view CMR stack, covering short-axis (SA) and 2/3/4-chamber long-axis (LA) views, is acquired for a thorough cardiac assessment. However, efficiently streamlining the complex, high-dime...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	459,801
2411.00075	{\mu}P$^2$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling	Sharpness Aware Minimization (SAM) enhances performance across various neural architectures and datasets. As models are continually scaled up to improve performance, a rigorous understanding of SAM's scaling behaviour is paramount. To this end, we study the infinite-width limit of neural networks trained with SAM, usin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,427
2410.03538	Dreaming User Multimodal Representation Guided by The Platonic Representation Hypothesis for Micro-Video Recommendation	The proliferation of online micro-video platforms has underscored the necessity for advanced recommender systems to mitigate information overload and deliver tailored content. Despite advancements, accurately and promptly capturing dynamic user interests remains a formidable challenge. Inspired by the Platonic Represen...	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	false	494,836
2012.08732	Learning-Based Quality Assessment for Image Super-Resolution	Image Super-Resolution (SR) techniques improve visual quality by enhancing the spatial resolution of images. Quality evaluation metrics play a critical role in comparing and optimizing SR algorithms, but current metrics achieve only limited success, largely due to the lack of large-scale quality databases, which are es...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	211,850
2110.00116	#ContextMatters: Advantages and Limitations of Using Machine Learning to Support Women in Politics	The United Nations identified gender equality as a Sustainable Development Goal in 2015, recognizing the underrepresentation of women in politics as a specific barrier to achieving gender equality. Political systems around the world experience gender inequality across all levels of elected government as fewer women run...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	258,284
2412.10257	Targeted Angular Reversal of Weights (TARS) for Knowledge Removal in Large Language Models	The sheer scale of data required to train modern large language models (LLMs) poses significant risks, as models are likely to gain knowledge of sensitive topics such as bio-security, as well the ability to replicate copyrighted works. Methods designed to remove such knowledge must do so from all prompt directions, in ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	516,844
0804.3171	Optimization Approach for Detecting the Critical Data on a Database	Through purposeful introduction of malicious transactions (tracking transactions) into randomly select nodes of a (database) graph, soiled and clean segments are identified. Soiled and clean measures corresponding those segments are then computed. These measures are used to repose the problem of critical database eleme...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	1,603
2101.07492	Optimizing Hyperparameters in CNNs using Bilevel Programming in Time Series Data	Hyperparameter optimization has remained a central topic within the machine learning community due to its ability to produce state-of-the-art results. With the recent interest growing in the usage of CNNs for time series prediction, we propose the notion of optimizing Hyperparameters in CNNs for the purpose of time ser...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	216,046
2310.12888	Generalized GM-MDS: Polynomial Codes are Higher Order MDS	The GM-MDS theorem, conjectured by Dau-Song-Dong-Yuen and proved by Lovett and Yildiz-Hassibi, shows that the generator matrices of Reed-Solomon codes can attain every possible configuration of zeros for an MDS code. The recently emerging theory of higher order MDS codes has connected the GM-MDS theorem to other import...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	401,190
2011.02686	Investigating Societal Biases in a Poetry Composition System	There is a growing collection of work analyzing and mitigating societal biases in language understanding, generation, and retrieval tasks, though examining biases in creative tasks remains underexplored. Creative language applications are meant for direct interaction with users, so it is important to quantify and mitig...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	205,001
2309.02754	Pre- and post-contact policy decomposition for non-prehensile manipulation with zero-shot sim-to-real transfer	We present a system for non-prehensile manipulation that require a significant number of contact mode transitions and the use of environmental contacts to successfully manipulate an object to a target location. Our method is based on deep reinforcement learning which, unlike state-of-the-art planning algorithms, does n...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	390,156
2406.05891	GCtx-UNet: Efficient Network for Medical Image Segmentation	Medical image segmentation is crucial for disease diagnosis and monitoring. Though effective, the current segmentation networks such as UNet struggle with capturing long-range features. More accurate models such as TransUNet, Swin-UNet, and CS-UNet have higher computation complexity. To address this problem, we propose...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	462,339
2109.08877	DuRecDial 2.0: A Bilingual Parallel Corpus for Conversational Recommendation	In this paper, we provide a bilingual parallel human-to-human recommendation dialog dataset (DuRecDial 2.0) to enable researchers to explore a challenging task of multilingual and cross-lingual conversational recommendation. The difference between DuRecDial 2.0 and existing conversational recommendation datasets is tha...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	256,056
2206.05277	Superresolution and Segmentation of OCT scans using Multi-Stage adversarial Guided Attention Training	Optical coherence tomography (OCT) is one of the non-invasive and easy-to-acquire biomarkers (the thickness of the retinal layers, which is detectable within OCT scans) being investigated to diagnose Alzheimer's disease (AD). This work aims to segment the OCT images automatically; however, it is a challenging task due ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,952
2212.09523	Natural Language Processing in Customer Service: A Systematic Review	Artificial intelligence and natural language processing (NLP) are increasingly being used in customer service to interact with users and answer their questions. The goal of this systematic review is to examine existing research on the use of NLP technology in customer service, including the research domain, application...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	337,141
1704.02420	Average-radius list-recovery of random linear codes: it really ties the room together	We analyze the list-decodability, and related notions, of random linear codes. This has been studied extensively before: there are many different parameter regimes and many different variants. Previous works have used complementary styles of arguments---which each work in their own parameter regimes but not in others--...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,442
1805.11461	Syntactic Dependency Representations in Neural Relation Classification	We investigate the use of different syntactic dependency representations in a neural relation classification task and compare the CoNLL, Stanford Basic and Universal Dependencies schemes. We further compare with a syntax-agnostic approach and perform an error analysis in order to gain a better understanding of the resu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,924
2410.15287	Training Language Models to Critique With Multi-agent Feedback	Critique ability, a meta-cognitive capability of humans, presents significant challenges for LLMs to improve. Recent works primarily rely on supervised fine-tuning (SFT) using critiques generated by a single LLM like GPT-4. However, these model-generated critiques often exhibit flaws due to the inherent complexity of t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	500,463
2203.05237	Entropy Rate Bounds via Second-Order Statistics	This work contains two single-letter upper bounds on the entropy rate of a discrete-valued stationary stochastic process, which only depend on second-order statistics, and are primarily suitable for models which consist of relatively large alphabets. The first bound stems from Gaussian maximum-entropy considerations an...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	284,753
2301.01877	When Cyber Aggression Prediction Meets BERT on Social Media	Increasingly, cyber aggression becomes the prevalent phenomenon that erodes the social media environment. However, due to subjective and expense, the traditional self-reporting questionnaire is hard to be employed in the current cyber area. In this study, we put forward the prediction model for cyber aggression based o...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	339,352
2302.11344	Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning	Humans excel at lifelong learning, as the brain has evolved to be robust to distribution shifts and noise in our ever-changing environment. Deep neural networks (DNNs), however, exhibit catastrophic forgetting and the learned representations drift drastically as they encounter a new task. This alludes to a different er...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	347,177
2406.12442	Abstraction-of-Thought Makes Language Models Better Reasoners	Abstract reasoning, the ability to reason from the abstract essence of a problem, serves as a key to generalization in human reasoning. However, eliciting language models to perform reasoning with abstraction remains unexplored. This paper seeks to bridge this gap by introducing a novel structured reasoning format call...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	465,413
2401.03619	AA-DLADMM: An Accelerated ADMM-based Framework for Training Deep Neural Networks	Stochastic gradient descent (SGD) and its many variants are the widespread optimization algorithms for training deep neural networks. However, SGD suffers from inevitable drawbacks, including vanishing gradients, lack of theoretical guarantees, and substantial sensitivity to input. The Alternating Direction Method of M...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	420,173
1705.01041	Estimating the Information Rate of a Channel with Classical Input and Output and a Quantum State (Extended Version)	We consider the problem of transmitting classical information over a time-invariant channel with memory. A popular class of time-invariant channels with memory are finite-state-machine channels, where a \emph{classical} state evolves over time and governs the relationship between the classical input and the classical o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	72,787
1909.00631	Design of Ambient Backscatter Training for Wireless Power Transfer	Wireless power transfer (WPT) using energy beamforming is a promising solution for low power Internet of Things (IoT) devices. In this work, we consider WPT from an energy transmitter (ET) employing retrodirective WPT using a large phased antenna array to an energy receiver (ER) capable of ambient backscatter. The adva...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	143,683
2310.19403	A Lightweight Method to Generate Unanswerable Questions in English	If a question cannot be answered with the available information, robust systems for question answering (QA) should know _not_ to answer. One way to build QA models that do this is with additional training data comprised of unanswerable questions, created either by employing annotators or through automated methods for u...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,976
2501.09311	Shape-Based Single Object Classification Using Ensemble Method Classifiers	Nowadays, more and more images are available. Annotation and retrieval of the images pose classification problems, where each class is defined as the group of database images labelled with a common semantic label. Various systems have been proposed for content-based retrieval, as well as for image classification and in...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	525,094
2412.18024	Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion	Multimodal AI models are increasingly used in fields like healthcare, finance, and autonomous driving, where information is drawn from multiple sources or modalities such as images, texts, audios, videos. However, effectively managing uncertainty - arising from noise, insufficient evidence, or conflicts between modalit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	520,215
2310.04413	Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets	Offline policy learning is aimed at learning decision-making policies using existing datasets of trajectories without collecting additional data. The primary motivation for using reinforcement learning (RL) instead of supervised learning techniques such as behavior cloning is to find a policy that achieves a higher ave...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	397,635
1908.00358	Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education	Spoken language proficiency is critically important for children's growth and personal development. Due to the limited and imbalanced educational resources in China, elementary students barely have chances to improve their oral language skills in classes. Verbal fluency tasks (VFTs) were invented to let the students pr...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	140,495
2411.06211	Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy	Advances in artificial intelligence (AI) have great potential to help address societal challenges that are both collective in nature and present at national or trans-national scale. Pressing challenges in healthcare, finance, infrastructure and sustainability, for instance, might all be productively addressed by levera...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	507,015
1604.02815	Beyond Brightness Constancy: Learning Noise Models for Optical Flow	Optical flow is typically estimated by minimizing a "data cost" and an optional regularizer. While there has been much work on different regularizers many modern algorithms still use a data cost that is not very different from the ones used over 30 years ago: a robust version of brightness constancy or gradient constan...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,393
2311.07919	Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models	Recently, instruction-following audio-language models have received broad attention for audio interaction with humans. However, the absence of pre-trained audio models capable of handling diverse audio types and tasks has hindered progress in this field. Consequently, most existing works have only been able to support ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	407,519
2304.07560	Continual Domain Adaptation through Pruning-aided Domain-specific Weight Modulation	In this paper, we propose to develop a method to address unsupervised domain adaptation (UDA) in a practical setting of continual learning (CL). The goal is to update the model on continually changing domains while preserving domain-specific knowledge to prevent catastrophic forgetting of past-seen domains. To this end...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,396
2402.00097	Code-Aware Prompting: A study of Coverage Guided Test Generation in Regression Setting using LLM	Testing plays a pivotal role in ensuring software quality, yet conventional Search Based Software Testing (SBST) methods often struggle with complex software units, achieving suboptimal test coverage. Recent works using large language models (LLMs) for test generation have focused on improving generation quality throug...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	425,489
2302.10021	Medical Face Masks and Emotion Recognition from the Body: Insights from a Deep Learning Perspective	The COVID-19 pandemic has undoubtedly changed the standards and affected all aspects of our lives, especially social communication. It has forced people to extensively wear medical face masks, in order to prevent transmission. This face occlusion can strongly irritate emotional reading from the face and urges us to inc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	346,654
2304.12447	Predicting Pulmonary Hypertension by Electrocardiograms Using Machine Learning	Pulmonary hypertension (PH) is a condition of high blood pressure that affects the arteries in the lungs and the right side of the heart (Mayo Clinic, 2017). A mean pulmonary artery pressure greater than 25 mmHg is defined as Pulmonary hypertension. The estimated 5-year survival rate from the time of diagnosis of pulmo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	360,212
1502.02407	A Social Spider Algorithm for Global Optimization	The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Metaheuristics based on evolutionary computation and swarm intelligence are outstanding examples of nature-inspired solution techniques. Inspired by the social spiders, we propose a novel Soc...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	40,033
2204.13931	KERMIT -- A Transformer-Based Approach for Knowledge Graph Matching	One of the strongest signals for automated matching of knowledge graphs and ontologies are textual concept descriptions. With the rise of transformer-based language models, text comparison based on meaning (rather than lexical features) is available to researchers. However, performing pairwise comparisons of all textua...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	293,998

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