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
2311.06805	Tunable Soft Prompts are Messengers in Federated Learning	Federated learning (FL) enables multiple participants to collaboratively train machine learning models using decentralized data sources, alleviating privacy concerns that arise from directly sharing local data. However, the lack of model privacy protection in FL becomes an unneglectable challenge, especially when peopl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	407,085
2012.14774	Generating Query Focused Summaries from Query-Free Resources	The availability of large-scale datasets has driven the development of neural models that create generic summaries from single or multiple documents. In this work we consider query focused summarization (QFS), a task for which training data in the form of queries, documents, and summaries is not readily available. We p...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	213,606
2103.10230	Collective Decision of One-vs-Rest Networks for Open Set Recognition	Unknown examples that are unseen during training often appear in real-world machine learning tasks, and an intelligent self-learning system should be able to distinguish between known and unknown examples. Accordingly, open set recognition (OSR), which addresses the problem of classifying knowns and identifying unknown...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	225,391
1803.08711	The Price of Uncertainty: Chance-constrained OPF vs. In-hindsight OPF	The operation of power systems has become more challenging due to feed-in of volatile renewable energy sources. Chance-constrained optimal power flow (ccOPF) is one possibility to explicitly consider volatility via probabilistic uncertainties resulting in mean-optimal feedback policies. These policies are computed befo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	93,330
2004.09710	Automatic Tag Recommendation for Painting Artworks Using Diachronic Descriptions	In this paper, we deal with the problem of automatic tag recommendation for painting artworks. Diachronic descriptions containing deviations on the vocabulary used to describe each painting usually occur when the work is done by many experts over time. The objective of this work is to provide a framework that produces ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,423
2402.16755	Towards Bridging the Gap between Near and Far-Field Characterizations of the Wireless Channel	The "near-field" propagation modeling of wireless channels is necessary to support sixth-generation (6G) technologies, such as intelligent reflecting surface (IRS), that are enabled by large aperture antennas and higher frequency carriers. As the conventional far-field model proves inadequate in this context, there is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	432,680
2203.00048	Multi-modal Alignment using Representation Codebook	Aligning signals from different modalities is an important step in vision-language representation learning as it affects the performance of later stages such as cross-modality fusion. Since image and text typically reside in different regions of the feature space, directly aligning them at instance level is challenging...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	282,844
2410.03253	Dynamic Curvature Constrained Path Planning	Effective path planning is a pivotal challenge across various domains, from robotics to logistics and beyond. This research is centred on the development and evaluation of the Dynamic Curvature-Constrained Path Planning Algorithm (DCCPPA) within two dimensional space. DCCPPA is designed to navigate constrained environm...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	494,700
2308.12870	VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition	LiDAR-based place recognition plays a crucial role in Simultaneous Localization and Mapping (SLAM) and LiDAR localization. Despite the emergence of various deep learning-based and hand-crafting-based methods, rotation-induced place recognition failure remains a critical challenge. Existing studies address this limi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,699
2207.12395	Tuning Stochastic Gradient Algorithms for Statistical Inference via Large-Sample Asymptotics	The tuning of stochastic gradient algorithms (SGAs) for optimization and sampling is often based on heuristics and trial-and-error rather than generalizable theory. We address this theory--practice gap by characterizing the large-sample statistical asymptotics of SGAs via a joint step-size--sample-size scaling limit. W...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,001
1706.00342	On the stable recovery of deep structured linear networks under sparsity constraints	We consider a deep structured linear network under sparsity constraints. We study sharp conditions guaranteeing the stability of the optimal parameters defining the network. More precisely, we provide sharp conditions on the network architecture and the sample under which the error on the parameters defining the networ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	74,601
2309.16569	Audio-Visual Speaker Verification via Joint Cross-Attention	Speaker verification has been widely explored using speech signals, which has shown significant improvement using deep models. Recently, there has been a surge in exploring faces and voices as they can offer more complementary and comprehensive information than relying only on a single modality of speech signals. Thoug...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	395,395
1610.00520	Semi-supervised Learning with Sparse Autoencoders in Phone Classification	We propose the application of a semi-supervised learning method to improve the performance of acoustic modelling for automatic speech recognition based on deep neural net- works. As opposed to unsupervised initialisation followed by supervised fine tuning, our method takes advantage of both unlabelled and labelled data...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	61,844
2112.02772	ActiveZero: Mixed Domain Learning for Active Stereovision with Zero Annotation	Traditional depth sensors generate accurate real world depth estimates that surpass even the most advanced learning approaches trained only on simulation domains. Since ground truth depth is readily available in the simulation domain but quite difficult to obtain in the real domain, we propose a method that leverages t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,956
2102.08462	Multi-Agent Multi-Armed Bandits with Limited Communication	We consider the problem where $N$ agents collaboratively interact with an instance of a stochastic $K$ arm bandit problem for $K \gg N$. The agents aim to simultaneously minimize the cumulative regret over all the agents for a total of $T$ time steps, the number of communication rounds, and the number of bits in each c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	220,462
1805.11768	"Press Space to Fire": Automatic Video Game Tutorial Generation	We propose the problem of tutorial generation for games, i.e. to generate tutorials which can teach players to play games, as an AI problem. This problem can be approached in several ways, including generating natural language descriptions of game rules, generating instructive game levels, and generating demonstrations...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	99,003
1701.03221	High-Mobility OFDM Downlink Transmission with Large-Scale Antenna Array	In this correspondence, we propose a new receiver design for high-mobility orthogonal frequency division multiplexing (OFDM) downlink transmissions with a large-scale antenna array. The downlink signal experiences the challenging fast time-varying propagation channel. The time-varying nature originates from the multipl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	66,668
1809.10617	Enabling FAIR Research in Earth Science through Research Objects	Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement, research objects contain and describe scientific information and resources in a way compliant with the FAIR principles and sustain the deve...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	108,946
2109.14233	A Next Basket Recommendation Reality Check	The goal of a next basket recommendation (NBR) system is to recommend items for the next basket for a user, based on the sequence of their prior baskets. Recently, a number of methods with complex modules have been proposed that claim state-of-the-art performance. They rarely look into the predicted basket and just pro...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	257,906
2312.09684	Context-Aware Sequential Model for Multi-Behaviour Recommendation	Sequential recommendation models are crucial for next-item recommendations in online platforms, capturing complex patterns in user interactions. However, many focus on a single behavior, overlooking valuable implicit interactions like clicks and favorites. Existing multi-behavioral models often fail to simultaneously c...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	415,842
1512.01418	Thermodynamic characterization of networks using graph polynomials	In this paper, we present a method for characterizing the evolution of time-varying complex networks by adopting a thermodynamic representation of network structure computed from a polynomial (or algebraic) characterization of graph structure. Commencing from a representation of graph structure based on a characteristi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,812
1508.03428	Codon Context Optimization in Synthetic Gene Design	Advances in de novo synthesis of DNA and computational gene design methods make possible the customization of genes by direct manipulation of features such as codon bias and mRNA secondary structure. Codon context is another feature significantly affecting mRNA translational efficiency, but existing methods and tools f...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	46,002
2310.00670	A Hierarchical Graph-based Approach for Recognition and Description Generation of Bimanual Actions in Videos	Nuanced understanding and the generation of detailed descriptive content for (bimanual) manipulation actions in videos is important for disciplines such as robotics, human-computer interaction, and video content analysis. This study describes a novel method, integrating graph based modeling with layered hierarchical at...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	396,087
2309.01686	MathAttack: Attacking Large Language Models Towards Math Solving Ability	With the boom of Large Language Models (LLMs), the research of solving Math Word Problem (MWP) has recently made great progress. However, there are few studies to examine the security of LLMs in math solving ability. Instead of attacking prompts in the use of LLMs, we propose a MathAttack model to attack MWP samples wh...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	389,770
2301.06570	Cross-institution text mining to uncover clinical associations: a case study relating social factors and code status in intensive care medicine	Objective: Text mining of clinical notes embedded in electronic medical records is increasingly used to extract patient characteristics otherwise not or only partly available, to assess their association with relevant health outcomes. As manual data labeling needed to develop text mining models is resource intensive, w...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	340,676
1711.06035	From Algorithmic Black Boxes to Adaptive White Boxes: Declarative Decision-Theoretic Ethical Programs as Codes of Ethics	Ethics of algorithms is an emerging topic in various disciplines such as social science, law, and philosophy, but also artificial intelligence (AI). The value alignment problem expresses the challenge of (machine) learning values that are, in some way, aligned with human requirements or values. In this paper I argue fo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	84,700
1912.07423	Faster and Simpler SNN Simulation with Work Queues	We present a clock-driven Spiking Neural Network simulator which is up to 3x faster than the state of the art while, at the same time, being more general and requiring less programming effort on both the user's and maintainer's side. This is made possible by designing our pipeline around "work queues" which act as inte...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	157,608
1407.2587	The Impact of Network Flows on Community Formation in Models of Opinion Dynamics	We study dynamics of opinion formation in a network of coupled agents. As the network evolves to a steady state, opinions of agents within the same community converge faster than those of other agents. This framework allows us to study how network topology and network flow, which mediates the transfer of opinions betwe...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	34,540
2405.17018	Structural cohesive element for the modelling of delamination in composite laminates without the cohesive zone limit	Delamination is a critical mode of failure that occurs between plies in a composite laminate. The cohesive element, developed based on the cohesive zone model, is widely used for modeling delamination. However, standard cohesive elements suffer from a well-known limit on the mesh density-the element size must be much s...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	457,719
2206.15159	EfficientGrasp: A Unified Data-Efficient Learning to Grasp Method for Multi-fingered Robot Hands	Autonomous grasping of novel objects that are previously unseen to a robot is an ongoing challenge in robotic manipulation. In the last decades, many approaches have been presented to address this problem for specific robot hands. The UniGrasp framework, introduced recently, has the ability to generalize to different t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	305,505
1802.09442	Self-organizing maps and generalization: an algorithmic description of Numerosity and Variability Effects	Category, or property generalization is a central function in the human cognition. It plays a crucial role in a variety of domains, such as learning, everyday reasoning, specialized reasoning, and decision making. Judging the content of a dish as edible, a hormone level as healthy, a building as belonging to the same a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	91,328
2408.04300	An Explainable Non-local Network for COVID-19 Diagnosis	The CNN has achieved excellent results in the automatic classification of medical images. In this study, we propose a novel deep residual 3D attention non-local network (NL-RAN) to classify CT images included COVID-19, common pneumonia, and normal to perform rapid and explainable COVID-19 diagnosis. We built a deep res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,336
2112.07176	ZUPT Aided GNSS Factor Graph with Inertial Navigation Integration for Wheeled Robots	In this work, we demonstrate the importance of zero velocity information for global navigation satellite system (GNSS) based navigation. The effectiveness of using the zero velocity information with zero velocity update (ZUPT) for inertial navigation applications have been shown in the literature. Here we leverage this...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	271,400
2401.11849	Self-Labeling the Job Shop Scheduling Problem	This work proposes a self-supervised training strategy designed for combinatorial problems. An obstacle in applying supervised paradigms to such problems is the need for costly target solutions often produced with exact solvers. Inspired by semi- and self-supervised learning, we show that generative models can be train...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	423,177
1401.4604	Completeness Guarantees for Incomplete Ontology Reasoners: Theory and Practice	To achieve scalability of query answering, the developers of Semantic Web applications are often forced to use incomplete OWL 2 reasoners, which fail to derive all answers for at least one query, ontology, and data set. The lack of completeness guarantees, however, may be unacceptable for applications in areas such as ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	30,099
1811.02059	STAR: Scaling Transactions through Asymmetric Replication	In this paper, we present STAR, a new distributed in-memory database with asymmetric replication. By employing a single-node non-partitioned architecture for some replicas and a partitioned architecture for other replicas, STAR is able to efficiently run both highly partitionable workloads and workloads that involve cr...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	112,492
2404.06219	Automatic Defect Detection in Sewer Network Using Deep Learning Based Object Detector	Maintaining sewer systems in large cities is important, but also time and effort consuming, because visual inspections are currently done manually. To reduce the amount of aforementioned manual work, defects within sewer pipes should be located and classified automatically. In the past, multiple works have attempted so...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,376
2211.03005	Graph Reinforcement Learning Application to Co-operative Decision-Making in Mixed Autonomy Traffic: Framework, Survey, and Challenges	Proper functioning of connected and automated vehicles (CAVs) is crucial for the safety and efficiency of future intelligent transport systems. Meanwhile, transitioning to fully autonomous driving requires a long period of mixed autonomy traffic, including both CAVs and human-driven vehicles. Thus, collaboration decisi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	328,785
2407.17032	Gymnasium: A Standard Interface for Reinforcement Learning Environments	Reinforcement Learning (RL) is a continuously growing field that has the potential to revolutionize many areas of artificial intelligence. However, despite its promise, RL research is often hindered by the lack of standardization in environment and algorithm implementations. This makes it difficult for researchers to c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	475,828
2407.00635	Dense Retrieval with Continuous Explicit Feedback for Systematic Review Screening Prioritisation	The goal of screening prioritisation in systematic reviews is to identify relevant documents with high recall and rank them in early positions for review. This saves reviewing effort if paired with a stopping criterion, and speeds up review completion if performed alongside downstream tasks. Recent studies have shown t...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	468,947
2310.05484	IDTraffickers: An Authorship Attribution Dataset to link and connect Potential Human-Trafficking Operations on Text Escort Advertisements	Human trafficking (HT) is a pervasive global issue affecting vulnerable individuals, violating their fundamental human rights. Investigations reveal that a significant number of HT cases are associated with online advertisements (ads), particularly in escort markets. Consequently, identifying and connecting HT vendors ...	false	false	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	398,172
1809.00589	Affordance Extraction and Inference based on Semantic Role Labeling	Common-sense reasoning is becoming increasingly important for the advancement of Natural Language Processing. While word embeddings have been very successful, they cannot explain which aspects of 'coffee' and 'tea' make them similar, or how they could be related to 'shop'. In this paper, we propose an explicit word rep...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,611
1508.01011	Learning from LDA using Deep Neural Networks	Latent Dirichlet Allocation (LDA) is a three-level hierarchical Bayesian model for topic inference. In spite of its great success, inferring the latent topic distribution with LDA is time-consuming. Motivated by the transfer learning approach proposed by~\newcite{hinton2015distilling}, we present a novel method that us...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	true	false	false	45,740
1904.02033	SANNS: Scaling Up Secure Approximate k-Nearest Neighbors Search	The $k$-Nearest Neighbor Search ($k$-NNS) is the backbone of several cloud-based services such as recommender systems, face recognition, and database search on text and images. In these services, the client sends the query to the cloud server and receives the response in which case the query and response are revealed t...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	true	126,310
0905.2449	The Role of Self-Forensics in Vehicle Crash Investigations and Event Reconstruction	This paper further introduces and formalizes a novel concept of self-forensics for automotive vehicles, specified in the Forensic Lucid language. We argue that self-forensics, with the forensics taken out of the cybercrime domain, is applicable to "self-dissection" of intelligent vehicles and hardware systems for autom...	false	false	false	false	true	false	false	false	false	false	false	false	true	true	false	false	false	true	3,696
2305.16725	Merging control in mixed traffic with safety guarantees: a safe sequencing policy with optimal motion control	We address the problem of merging traffic from two roadways consisting of both Connected Autonomous Vehicles (CAVs) and Human Driven Vehicles (HDVs). Guaranteeing safe merging in such mixed traffic settings is challenging due to the unpredictability of possibly uncooperative HDVs. We develop a hierarchical controller w...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	368,226
2409.18222	Trustworthy AI: Securing Sensitive Data in Large Language Models	Large Language Models (LLMs) have transformed natural language processing (NLP) by enabling robust text generation and understanding. However, their deployment in sensitive domains like healthcare, finance, and legal services raises critical concerns about privacy and data security. This paper proposes a comprehensive ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	492,148
2502.09479	Assessing Generative AI value in a public sector context: evidence from a field experiment	The emergence of Generative AI (Gen AI) has motivated an interest in understanding how it could be used to enhance productivity across various tasks. We add to research results for the performance impact of Gen AI on complex knowledge-based tasks in a public sector setting. In a pre-registered experiment, after establi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	533,459
2404.09686	AntBatchInfer: Elastic Batch Inference in the Kubernetes Cluster	Offline batch inference is a common task in the industry for deep learning applications, but it can be challenging to ensure stability and performance when dealing with large amounts of data and complicated inference pipelines. This paper demonstrated AntBatchInfer, an elastic batch inference framework, which is specia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	446,790
1803.06067	Dynamic-structured Semantic Propagation Network	Semantic concept hierarchy is still under-explored for semantic segmentation due to the inefficiency and complicated optimization of incorporating structural inference into dense prediction. This lack of modeling semantic correlations also makes prior works must tune highly-specified models for each task due to the lab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	92,764
1809.02657	dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning	Learning graph representations is a fundamental task aimed at capturing various properties of graphs in vector space. The most recent methods learn such representations for static networks. However, real world networks evolve over time and have varying dynamics. Capturing such evolution is key to predicting the propert...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	107,096
2010.01770	Second-Order NLP Adversarial Examples	Adversarial example generation methods in NLP rely on models like language models or sentence encoders to determine if potential adversarial examples are valid. In these methods, a valid adversarial example fools the model being attacked, and is determined to be semantically or syntactically valid by a second model. Re...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	198,784
2309.04190	SegmentAnything helps microscopy images based automatic and quantitative organoid detection and analysis	Organoids are self-organized 3D cell clusters that closely mimic the architecture and function of in vivo tissues and organs. Quantification of organoid morphology helps in studying organ development, drug discovery, and toxicity assessment. Recent microscopy techniques provide a potent tool to acquire organoid morphol...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	390,642
1605.04232	Review of state-of-the-arts in artificial intelligence with application to AI safety problem	Here, I review current state-of-the-arts in many areas of AI to estimate when it's reasonable to expect human level AI development. Predictions of prominent AI researchers vary broadly from very pessimistic predictions of Andrew Ng to much more moderate predictions of Geoffrey Hinton and optimistic predictions of Shane...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	55,841
2312.16623	Make BERT-based Chinese Spelling Check Model Enhanced by Layerwise Attention and Gaussian Mixture Model	BERT-based models have shown a remarkable ability in the Chinese Spelling Check (CSC) task recently. However, traditional BERT-based methods still suffer from two limitations. First, although previous works have identified that explicit prior knowledge like Part-Of-Speech (POS) tagging can benefit in the CSC task, they...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	418,458
2312.02548	GeNIe: Generative Hard Negative Images Through Diffusion	Data augmentation is crucial in training deep models, preventing them from overfitting to limited data. Recent advances in generative AI, e.g., diffusion models, have enabled more sophisticated augmentation techniques that produce data resembling natural images. We introduce GeNIe a novel augmentation method which leve...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	412,918
2203.08937	Backpropagation through Time and Space: Learning Numerical Methods with Multi-Agent Reinforcement Learning	We introduce Backpropagation Through Time and Space (BPTTS), a method for training a recurrent spatio-temporal neural network, that is used in a homogeneous multi-agent reinforcement learning (MARL) setting to learn numerical methods for hyperbolic conservation laws. We treat the numerical schemes underlying partial di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	285,960
1702.04863	Load Synchronization and Sustained Oscillations Induced by Transactive Control	Transactive or market-based coordination strategies have recently been proposed for controlling the aggregate demand of a large number of electric loads. Such schemes offer operational benefits such as enforcing distribution feeder capacity limits and providing users with flexibility to consume energy based on the pric...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	68,323
2311.02610	An adaptive standardisation methodology for Day-Ahead electricity price forecasting	The study of Day-Ahead prices in the electricity market is one of the most popular problems in time series forecasting. Previous research has focused on employing increasingly complex learning algorithms to capture the sophisticated dynamics of the market. However, there is a threshold where increased complexity fails ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,513
2302.07457	When Demonstrations Meet Generative World Models: A Maximum Likelihood Framework for Offline Inverse Reinforcement Learning	Offline inverse reinforcement learning (Offline IRL) aims to recover the structure of rewards and environment dynamics that underlie observed actions in a fixed, finite set of demonstrations from an expert agent. Accurate models of expertise in executing a task has applications in safety-sensitive applications such as ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,740
2408.03599	Activations Through Extensions: A Framework To Boost Performance Of Neural Networks	Activation functions are non-linearities in neural networks that allow them to learn complex mapping between inputs and outputs. Typical choices for activation functions are ReLU, Tanh, Sigmoid etc., where the choice generally depends on the application domain. In this work, we propose a framework/strategy that unifies...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	479,083
2410.20096	Velocity-History-Based Soft Actor-Critic Tackling IROS'24 Competition "AI Olympics with RealAIGym"	The ``AI Olympics with RealAIGym'' competition challenges participants to stabilize chaotic underactuated dynamical systems with advanced control algorithms. In this paper, we present a novel solution submitted to IROS'24 competition, which builds upon Soft Actor-Critic (SAC), a popular model-free entropy-regularized R...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	502,648
2403.06954	Quadruped-Frog: Rapid Online Optimization of Continuous Quadruped Jumping	Legged robots are becoming increasingly agile in exhibiting dynamic behaviors such as running and jumping. Usually, such behaviors are either optimized and engineered offline (i.e. the behavior is designed for before it is needed), either through model-based trajectory optimization, or through deep learning-based metho...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	436,679
cs/0607030	Towards a General Theory of Simultaneous Diophantine Approximation of Formal Power Series: Multidimensional Linear Complexity	We model the development of the linear complexity of multisequences by a stochastic infinite state machine, the Battery-Discharge-Model, BDM. The states s in S of the BDM have asymptotic probabilities or mass Pr(s)=1/(P(q,M) q^K(s)), where K(s) in N_0 is the class of the state s, and P(q,M)=\sum_(K in\N0) P_M(K)q^(-K)=...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,570
2306.02329	Multi-CLIP: Contrastive Vision-Language Pre-training for Question Answering tasks in 3D Scenes	Training models to apply common-sense linguistic knowledge and visual concepts from 2D images to 3D scene understanding is a promising direction that researchers have only recently started to explore. However, it still remains understudied whether 2D distilled knowledge can provide useful representations for downstream...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	370,858
2202.11333	Scalable Query Answering under Uncertainty to Neuroscientific Ontological Knowledge: The NeuroLang Approach	Researchers in neuroscience have a growing number of datasets available to study the brain, which is made possible by recent technological advances. Given the extent to which the brain has been studied, there is also available ontological knowledge encoding the current state of the art regarding its different areas, ac...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	281,854
1907.08953	High Dimensional Bayesian Optimization via Supervised Dimension Reduction	Bayesian optimization (BO) has been broadly applied to computational expensive problems, but it is still challenging to extend BO to high dimensions. Existing works are usually under strict assumption of an additive or a linear embedding structure for objective functions. This paper directly introduces a supervised dim...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,227
2311.17286	LEOD: Label-Efficient Object Detection for Event Cameras	Object detection with event cameras benefits from the sensor's low latency and high dynamic range. However, it is costly to fully label event streams for supervised training due to their high temporal resolution. To reduce this cost, we present LEOD, the first method for label-efficient event-based detection. Our appro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,236
1303.0644	Automatic symmetry based cluster approach for anomalous brain identification in PET scan image : An Analysis	Medical image segmentation is referred to the segmentation of known anatomic structures from different medical images. Normally, the medical data researches are more complicated and an exclusive structures. This computer aided diagnosis is used for assisting doctors in evaluating medical imagery or in recognizing abnor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	22,601
1912.12128	Deep Sparse Coding for Non-Intrusive Load Monitoring	Energy disaggregation is the task of segregating the aggregate energy of the entire building (as logged by the smartmeter) into the energy consumed by individual appliances. This is a single channel (the only channel being the smart-meter) blind source (different electrical appliances) separation problem. The tradition...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	158,763
2410.13966	Detecting AI-Generated Texts in Cross-Domains	Existing tools to detect text generated by a large language model (LLM) have met with certain success, but their performance can drop when dealing with texts in new domains. To tackle this issue, we train a ranking classifier called RoBERTa-Ranker, a modified version of RoBERTa, as a baseline model using a dataset we c...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	499,797
2403.10971	Task-Aware Low-Rank Adaptation of Segment Anything Model	The Segment Anything Model (SAM), with its remarkable zero-shot capability, has been proven to be a powerful foundation model for image segmentation tasks, which is an important task in computer vision. However, the transfer of its rich semantic information to multiple different downstream tasks remains unexplored. In ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,458
2401.15636	FreeStyle: Free Lunch for Text-guided Style Transfer using Diffusion Models	The rapid development of generative diffusion models has significantly advanced the field of style transfer. However, most current style transfer methods based on diffusion models typically involve a slow iterative optimization process, e.g., model fine-tuning and textual inversion of style concept. In this paper, we i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,528
2312.07001	Stein Coverage: a Variational Inference Approach to Distribution-matching Multisensor Deployment	This paper examines the spatial coverage optimization problem for multiple sensors in a known convex environment, where the coverage service of each sensor is heterogeneous and anisotropic. We introduce the Stein Coverage algorithm, a distribution-matching coverage approach that aims to place sensors at positions and o...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	414,758
2405.14168	A generative model for community types in directed networks	Large complex networks are often organized into groups or communities. In this paper, we introduce and investigate a generative model of network evolution that reproduces all four pairwise community types that exist in directed networks: assortative, core-periphery, disassortative, and the newly introduced source-basin...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	456,285
1810.09590	The Lives of Bots	Automated software agents --- or bots --- have long been an important part of how Wikipedia's volunteer community of editors write, edit, update, monitor, and moderate content. In this paper, I discuss the complex social and technical environment in which Wikipedia's bots operate. This paper focuses on the establishmen...	true	false	false	true	true	false	false	false	false	false	false	false	false	true	false	false	false	false	111,086
2205.11916	Large Language Models are Zero-Shot Reasoners	Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars. Notably, chain of thought (CoT) prompting, a recent technique for eliciting complex multi-step reasoning through step-by-step a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	298,335
2310.13359	Electrical Fault Localisation Over a Distributed Parameter Transmission Line	Motivated by the need to localise faults along electrical power lines, this paper adopts a frequency-domain approach to parameter estimation for an infinite-dimensional linear dynamical system with one spatial variable. Since the time of the fault is unknown, and voltages and currents are measured at only one end of th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	401,415
2101.08013	Deep Learning for Intelligent Demand Response and Smart Grids: A Comprehensive Survey	Electricity is one of the mandatory commodities for mankind today. To address challenges and issues in the transmission of electricity through the traditional grid, the concepts of smart grids and demand response have been developed. In such systems, a large amount of data is generated daily from various sources such a...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	216,204
1512.03980	Action Recognition with Image Based CNN Features	Most of human actions consist of complex temporal compositions of more simple actions. Action recognition tasks usually relies on complex handcrafted structures as features to represent the human action model. Convolutional Neural Nets (CNN) have shown to be a powerful tool that eliminate the need for designing handcra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	50,081
1605.03426	An Overview of Transmission Theory and Techniques of Large-scale Antenna Systems for 5G Wireless Communications	To meet the future demand for huge traffic volume of wireless data service, the research on the fifth generation (5G) mobile communication systems has been undertaken in recent years. It is expected that the spectral and energy efficiencies in 5G mobile communication systems should be ten-fold higher than the ones in t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,745
1702.05581	Revisiting Perceptron: Efficient and Label-Optimal Learning of Halfspaces	It has been a long-standing problem to efficiently learn a halfspace using as few labels as possible in the presence of noise. In this work, we propose an efficient Perceptron-based algorithm for actively learning homogeneous halfspaces under the uniform distribution over the unit sphere. Under the bounded noise condit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,431
2205.06342	Generalized Variational Inference in Function Spaces: Gaussian Measures meet Bayesian Deep Learning	We develop a framework for generalized variational inference in infinite-dimensional function spaces and use it to construct a method termed Gaussian Wasserstein inference (GWI). GWI leverages the Wasserstein distance between Gaussian measures on the Hilbert space of square-integrable functions in order to determine a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,208
2401.06614	Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and Tracking	We introduce Motion2VecSets, a 4D diffusion model for dynamic surface reconstruction from point cloud sequences. While existing state-of-the-art methods have demonstrated success in reconstructing non-rigid objects using neural field representations, conventional feed-forward networks encounter challenges with ambiguou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,217
2110.05261	Automatic Recall of Software Lessons Learned for Software Project Managers	Lessons learned (LL) records constitute the software organization memory of successes and failures. LL are recorded within the organization repository for future reference to optimize planning, gain experience, and elevate market competitiveness. However, manually searching this repository is a daunting task, so it is ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	260,220
2409.18783	DualDn: Dual-domain Denoising via Differentiable ISP	Image denoising is a critical component in a camera's Image Signal Processing (ISP) pipeline. There are two typical ways to inject a denoiser into the ISP pipeline: applying a denoiser directly to captured raw frames (raw domain) or to the ISP's output sRGB images (sRGB domain). However, both approaches have their limi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,402
2009.11684	AliMe KG: Domain Knowledge Graph Construction and Application in E-commerce	Pre-sales customer service is of importance to E-commerce platforms as it contributes to optimizing customers' buying process. To better serve users, we propose AliMe KG, a domain knowledge graph in E-commerce that captures user problems, points of interests (POI), item information and relations thereof. It helps to un...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	197,227
1904.09472	ChoiceNet: CNN learning through choice of multiple feature map representations	We introduce a new architecture called ChoiceNet where each layer of the network is highly connected with skip connections and channelwise concatenations. This enables the network to alleviate the problem of vanishing gradients, reduces the number of parameters without sacrificing performance, and encourages feature re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,389
2308.11154	Mobility-Aware Computation Offloading for Swarm Robotics using Deep Reinforcement Learning	Swarm robotics is envisioned to automate a large number of dirty, dangerous, and dull tasks. Robots have limited energy, computation capability, and communication resources. Therefore, current swarm robotics have a small number of robots, which can only provide limited spatio-temporal information. In this paper, we pro...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	387,025
1903.03556	Geometry-Aware Graph Transforms for Light Field Compact Representation	The paper addresses the problem of energy compaction of dense 4D light fields by designing geometry-aware local graph-based transforms. Local graphs are constructed on super-rays that can be seen as a grouping of spatially and geometry-dependent angularly correlated pixels. Both non separable and separable transforms a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,765
2308.08414	Tem-adapter: Adapting Image-Text Pretraining for Video Question Answer	Video-language pre-trained models have shown remarkable success in guiding video question-answering (VideoQA) tasks. However, due to the length of video sequences, training large-scale video-based models incurs considerably higher costs than training image-based ones. This motivates us to leverage the knowledge from im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,893
2304.08447	RadarFormer: Lightweight and Accurate Real-Time Radar Object Detection Model	The performance of perception systems developed for autonomous driving vehicles has seen significant improvements over the last few years. This improvement was associated with the increasing use of LiDAR sensors and point cloud data to facilitate the task of object detection and recognition in autonomous driving. Howev...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	358,710
2206.02743	A Neural Corpus Indexer for Document Retrieval	Current state-of-the-art document retrieval solutions mainly follow an index-retrieve paradigm, where the index is hard to be directly optimized for the final retrieval target. In this paper, we aim to show that an end-to-end deep neural network unifying training and indexing stages can significantly improve the recall...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	301,014
2105.10983	Weakly Supervised Instance Attention for Multisource Fine-Grained Object Recognition with an Application to Tree Species Classification	Multisource image analysis that leverages complementary spectral, spatial, and structural information benefits fine-grained object recognition that aims to classify an object into one of many similar subcategories. However, for multisource tasks that involve relatively small objects, even the smallest registration erro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,562
1712.08324	Towards dense object tracking in a 2D honeybee hive	From human crowds to cells in tissue, the detection and efficient tracking of multiple objects in dense configurations is an important and unsolved problem. In the past, limitations of image analysis have restricted studies of dense groups to tracking a single or subset of marked individuals, or to coarse-grained group...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	87,178
2502.01187	Skewed Memorization in Large Language Models: Quantification and Decomposition	Memorization in Large Language Models (LLMs) poses privacy and security risks, as models may unintentionally reproduce sensitive or copyrighted data. Existing analyses focus on average-case scenarios, often neglecting the highly skewed distribution of memorization. This paper examines memorization in LLM supervised fin...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	529,739
2212.13667	Learning When to Use Adaptive Adversarial Image Perturbations against Autonomous Vehicles	The deep neural network (DNN) models for object detection using camera images are widely adopted in autonomous vehicles. However, DNN models are shown to be susceptible to adversarial image perturbations. In the existing methods of generating the adversarial image perturbations, optimizations take each incoming image f...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	338,365
2103.15261	One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks	Can deep learning solve multiple tasks simultaneously, even when they are unrelated and very different? We investigate how the representations of the underlying tasks affect the ability of a single neural network to learn them jointly. We present theoretical and empirical findings that a single neural network is capabl...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	227,135
1608.00161	Localizing and Orienting Street Views Using Overhead Imagery	In this paper we aim to determine the location and orientation of a ground-level query image by matching to a reference database of overhead (e.g. satellite) images. For this task we collect a new dataset with one million pairs of street view and overhead images sampled from eleven U.S. cities. We explore several deep ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,234
2201.04069	A novel method for error analysis in radiation thermometry with application to industrial furnaces	Accurate temperature measurements are essential for the proper monitoring and control of industrial furnaces. However, measurement uncertainty is a risk for such a critical parameter. Certain instrumental and environmental errors must be considered when using spectral-band radiation thermometry techniques, such as the ...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	275,011

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