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
2207.03337	Factorizing Knowledge in Neural Networks	In this paper, we explore a novel and ambitious knowledge-transfer task, termed Knowledge Factorization~(KF). The core idea of KF lies in the modularization and assemblability of knowledge: given a pretrained network model as input, KF aims to decompose it into several factor networks, each of which handles only a dedi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	306,805
1006.3455	An External Description for MIMO Systems Sampled in an Aperiodic Way	An external description for aperiodically sampled MIMO linear systems has been developed. Emphasis is on the sampling period sequence, included among the variables to be handled. The computational procedure is simple and no use of polynomial matrix theory is required. This input/output description is believed to be a b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	6,822
2205.11987	Word-order typology in Multilingual BERT: A case study in subordinate-clause detection	The capabilities and limitations of BERT and similar models are still unclear when it comes to learning syntactic abstractions, in particular across languages. In this paper, we use the task of subordinate-clause detection within and across languages to probe these properties. We show that this task is deceptively simp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,360
2303.14384	Reliability-Hierarchical Memory Network for Scribble-Supervised Video Object Segmentation	This paper aims to solve the video object segmentation (VOS) task in a scribble-supervised manner, in which VOS models are not only trained by the sparse scribble annotations but also initialized with the sparse target scribbles for inference. Thus, the annotation burdens for both training and initialization can be sub...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	354,065
2405.14555	Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models	Research on Large Language Models (LLMs) has often neglected subtle biases that, although less apparent, can significantly influence the models' outputs toward particular social narratives. This study addresses two such biases within LLMs: representative bias, which denotes a tendency of LLMs to generate outputs that m...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	456,488
2012.13489	Learning Robust Representation for Clustering through Locality Preserving Variational Discriminative Network	Clustering is one of the fundamental problems in unsupervised learning. Recent deep learning based methods focus on learning clustering oriented representations. Among those methods, Variational Deep Embedding achieves great success in various clustering tasks by specifying a Gaussian Mixture prior to the latent space....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	213,231
2402.13147	SPRINQL: Sub-optimal Demonstrations driven Offline Imitation Learning	We focus on offline imitation learning (IL), which aims to mimic an expert's behavior using demonstrations without any interaction with the environment. One of the main challenges in offline IL is the limited support of expert demonstrations, which typically cover only a small fraction of the state-action space. While ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	431,132
2010.05662	End-to-End Deep Learning for Reliable Cardiac Activity Monitoring using Seismocardiograms	Continuous monitoring of cardiac activity is paramount to understanding the functioning of the heart in addition to identifying precursors to conditions such as Atrial Fibrillation. Through continuous cardiac monitoring, early indications of any potential disorder can be detected before the actual event, allowing timel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	200,218
1009.6197	Secure Relay Beamforming over Cognitive Radio Channels	In this paper, a cognitive relay channel is considered, and amplify-and-forward (AF) relay beamforming designs in the presence of an eavesdropper and a primary user are studied. Our objective is to optimize the performance of the cognitive relay beamforming system while limiting the interference in the direction of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,730
2006.12485	On Creating Benchmark Dataset for Aerial Image Interpretation: Reviews, Guidances and Million-AID	The past years have witnessed great progress on remote sensing (RS) image interpretation and its wide applications. With RS images becoming more accessible than ever before, there is an increasing demand for the automatic interpretation of these images. In this context, the benchmark datasets serve as essential prerequ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	183,609
1211.6898	On the Use of Non-Stationary Policies for Stationary Infinite-Horizon Markov Decision Processes	We consider infinite-horizon stationary $\gamma$-discounted Markov Decision Processes, for which it is known that there exists a stationary optimal policy. Using Value and Policy Iteration with some error $\epsilon$ at each iteration, it is well-known that one can compute stationary policies that are $\frac{2\gamma}{(1...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	20,017
2208.08287	Noisy Nonnegative Tucker Decomposition with Sparse Factors and Missing Data	Tensor decomposition is a powerful tool for extracting physically meaningful latent factors from multi-dimensional nonnegative data, and has been an increasing interest in a variety of fields such as image processing, machine learning, and computer vision. In this paper, we propose a sparse nonnegative Tucker decomposi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,330
1801.03975	Timely Status Update in Massive IoT Systems: Decentralized Scheduling for Wireless Uplinks	In a typical Internet of Things (IoT) application where a central controller collects status updates from multiple terminals, e.g., sensors and monitors, through a wireless multiaccess uplink, an important problem is how to attain timely status updates autonomously. In this paper, the timeliness of the status is measur...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,188
2001.02329	Emo-CNN for Perceiving Stress from Audio Signals: A Brain Chemistry Approach	Emotion plays a key role in many applications like healthcare, to gather patients emotional behavior. There are certain emotions which are given more importance due to their effectiveness in understanding human feelings. In this paper, we propose an approach that models human stress from audio signals. The research cha...	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	159,706
cmp-lg/9408005	A Modular and Flexible Architecture for an Integrated Corpus Query System	The paper describes the architecture of an integrated and extensible corpus query system developed at the University of Stuttgart and gives examples of some of the modules realized within this architecture. The modules form the core of a corpus workbench. Within the proposed architecture, information required for the e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,154
1905.01896	Distributional Semantics and Linguistic Theory	Distributional semantics provides multi-dimensional, graded, empirically induced word representations that successfully capture many aspects of meaning in natural languages, as shown in a large body of work in computational linguistics; yet, its impact in theoretical linguistics has so far been limited. This review pro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	129,834
2304.06053	TextANIMAR: Text-based 3D Animal Fine-Grained Retrieval	3D object retrieval is an important yet challenging task that has drawn more and more attention in recent years. While existing approaches have made strides in addressing this issue, they are often limited to restricted settings such as image and sketch queries, which are often unfriendly interactions for common users....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,842
2403.02334	Gradient Correlation Subspace Learning against Catastrophic Forgetting	Efficient continual learning techniques have been a topic of significant research over the last few years. A fundamental problem with such learning is severe degradation of performance on previously learned tasks, known also as catastrophic forgetting. This paper introduces a novel method to reduce catastrophic forgett...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	434,773
2109.01954	An Exploration of Deep Learning Methods in Hungry Geese	Hungry Geese is a n-player variation of the popular game snake. This paper looks at state of the art Deep Reinforcement Learning Value Methods. The goal of the paper is to aggregate research of value based methods and apply it as an exercise to other environments. A vanilla Deep Q Network, a Double Q-network and a Duel...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	253,590
2009.10947	Pose Imitation Constraints for Collaborative Robots	Achieving human-like motion in robots has been a fundamental goal in many areas of robotics research. Inverse kinematic (IK) solvers have been explored as a solution to provide kinematic structures with anthropomorphic movements. In particular, numeric solvers based on geometry, such as FABRIK, have shown potential for...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	197,027
1803.08420	Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data	The sizes of compressed images depend on their spatial resolution (number of pixels) and on their color resolution (number of color quantization levels). We introduce DaltonQuant, a new color quantization technique for image compression that cloud services can apply to images destined for a specific user with known col...	true	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	93,258
1501.01661	Provably Delay Efficient Data Retrieving in Storage Clouds	One key requirement for storage clouds is to be able to retrieve data quickly. Recent system measurements have shown that the data retrieving delay in storage clouds is highly variable, which may result in a long latency tail. One crucial idea to improve the delay performance is to retrieve multiple data copies by usin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	39,099
2501.16471	SIM: Surface-based fMRI Analysis for Inter-Subject Multimodal Decoding from Movie-Watching Experiments	Current AI frameworks for brain decoding and encoding, typically train and test models within the same datasets. This limits their utility for brain computer interfaces (BCI) or neurofeedback, for which it would be useful to pool experiences across individuals to better simulate stimuli not sampled during training. A k...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	527,977
2403.01244	Mitigating Catastrophic Forgetting in Large Language Models with Self-Synthesized Rehearsal	Large language models (LLMs) suffer from catastrophic forgetting during continual learning. Conventional rehearsal-based methods rely on previous training data to retain the model's ability, which may not be feasible in real-world applications. When conducting continual learning based on a publicly-released LLM checkpo...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,321
2204.04322	Iterative Depth-First Search for Fully Observable Non-Deterministic Planning	Fully Observable Non-Deterministic (FOND) planning models uncertainty through actions with non-deterministic effects. Existing FOND planning algorithms are effective and employ a wide range of techniques. However, most of the existing algorithms are not robust for dealing with both non-determinism and task size. In thi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	290,608
1504.00822	Quantum Expander Codes	We present an efficient decoding algorithm for constant rate quantum hypergraph-product LDPC codes which provably corrects adversarial errors of weight $\Omega(\sqrt{n})$ for codes of length $n$. The algorithm runs in time linear in the number of qubits, which makes its performance the strongest to date for linear-time...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,733
2409.13919	Measuring Error Alignment for Decision-Making Systems	Given that AI systems are set to play a pivotal role in future decision-making processes, their trustworthiness and reliability are of critical concern. Due to their scale and complexity, modern AI systems resist direct interpretation, and alternative ways are needed to establish trust in those systems, and determine h...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	490,232
1807.01430	SGAD: Soft-Guided Adaptively-Dropped Neural Network	Deep neural networks (DNNs) have been proven to have many redundancies. Hence, many efforts have been made to compress DNNs. However, the existing model compression methods treat all the input samples equally while ignoring the fact that the difficulties of various input samples being correctly classified are different...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	102,059
2310.05366	Rotation Matters: Generalized Monocular 3D Object Detection for Various Camera Systems	Research on monocular 3D object detection is being actively studied, and as a result, performance has been steadily improving. However, 3D object detection performance is significantly reduced when applied to a camera system different from the system used to capture the training datasets. For example, a 3D detector tra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	398,116
2412.14188	CogSimulator: A Model for Simulating User Cognition & Behavior with Minimal Data for Tailored Cognitive Enhancement	The interplay between cognition and gaming, notably through educational games enhancing cognitive skills, has garnered significant attention in recent years. This research introduces the CogSimulator, a novel algorithm for simulating user cognition in small-group settings with minimal data, as the educational game Word...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	518,607
2407.16200	MCTS Based Dispatch of Autonomous Vehicles under Operational Constraints for Continuous Transportation	Continuous transportation of material in the mining industry is achieved by the dispatch of autonomous haul-trucks with discrete haulage capacities. Recently, Monte Carlo Tree Search (MCTS) was successfully deployed in tackling challenges of long-run optimality, scalability and adaptability in haul-truck dispatch. Typi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	475,503
1703.03340	Adaptive Non-uniform Compressive Sampling for Time-varying Signals	In this paper, adaptive non-uniform compressive sampling (ANCS) of time-varying signals, which are sparse in a proper basis, is introduced. ANCS employs the measurements of previous time steps to distribute the sensing energy among coefficients more intelligently. To this aim, a Bayesian inference method is proposed th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	69,716
1602.00487	Towards a Cognitive Routing Engine for Software Defined Networks	Most Software Defined Networks (SDN) traffic engineering applications use excessive and frequent global monitoring in order to find the optimal Quality-of-Service (QoS) paths for the current state of the network. In this work, we present the motivations, architecture and initial evaluation of a SDN application called C...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	51,587
1908.05762	Entity-aware ELMo: Learning Contextual Entity Representation for Entity Disambiguation	We present a new local entity disambiguation system. The key to our system is a novel approach for learning entity representations. In our approach we learn an entity aware extension of Embedding for Language Model (ELMo) which we call Entity-ELMo (E-ELMo). Given a paragraph containing one or more named entity mentions...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	141,803
2009.08864	Classification and Region Analysis of COVID-19 Infection using Lung CT Images and Deep Convolutional Neural Networks	COVID-19 is a global health problem. Consequently, early detection and analysis of the infection patterns are crucial for controlling infection spread as well as devising a treatment plan. This work proposes a two-stage deep Convolutional Neural Networks (CNNs) based framework for delineation of COVID-19 infected regio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,371
2407.19625	LoginMEA: Local-to-Global Interaction Network for Multi-modal Entity Alignment	Multi-modal entity alignment (MMEA) aims to identify equivalent entities between two multi-modal knowledge graphs (MMKGs), whose entities can be associated with relational triples and related images. Most previous studies treat the graph structure as a special modality, and fuse different modality information with sepa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	476,856
1906.02739	Mesh R-CNN	Rapid advances in 2D perception have led to systems that accurately detect objects in real-world images. However, these systems make predictions in 2D, ignoring the 3D structure of the world. Concurrently, advances in 3D shape prediction have mostly focused on synthetic benchmarks and isolated objects. We unify advance...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	134,161
1710.10295	Frame-Induced Group Polarization in Small Discussion Networks	We present a novel explanation for the group polarization effect whereby discussion among like-minded individuals induces shifts toward the extreme. Our theory distinguishes between a quantitative policy under debate and the discussion's rhetorical frame, such as the likelihood of an outcome. If policy and frame positi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	83,343
2309.08134	AnyOKP: One-Shot and Instance-Aware Object Keypoint Extraction with Pretrained ViT	Towards flexible object-centric visual perception, we propose a one-shot instance-aware object keypoint (OKP) extraction approach, AnyOKP, which leverages the powerful representation ability of pretrained vision transformer (ViT), and can obtain keypoints on multiple object instances of arbitrary category after learnin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	392,042
2006.08880	On SCC-recursiveness in Quantitative Argumentation	Abstract argumentation is a reasoning model for evaluating arguments based on various semantics. SCC-recursiveness is a sophisticated property of semantics that provides a general schema for characterizing semantics through the decomposition along strongly connected components (SCCs). While this property has been exten...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	182,343
2106.08548	Mining Interpretable Spatio-temporal Logic Properties for Spatially Distributed Systems	The Internet-of-Things, complex sensor networks, multi-agent cyber-physical systems are all examples of spatially distributed systems that continuously evolve in time. Such systems generate huge amounts of spatio-temporal data, and system designers are often interested in analyzing and discovering structure within the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	241,330
2310.03752	A Deep Learning Sequential Decoder for Transient High-Density Electromyography in Hand Gesture Recognition Using Subject-Embedded Transfer Learning	Hand gesture recognition (HGR) has gained significant attention due to the increasing use of AI-powered human-computer interfaces that can interpret the deep spatiotemporal dynamics of biosignals from the peripheral nervous system, such as surface electromyography (sEMG). These interfaces have a range of applications, ...	true	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	397,405
2012.00483	ClimaText: A Dataset for Climate Change Topic Detection	Climate change communication in the mass media and other textual sources may affect and shape public perception. Extracting climate change information from these sources is an important task, e.g., for filtering content and e-discovery, sentiment analysis, automatic summarization, question-answering, and fact-checking....	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	209,154
2304.02688	Going Further: Flatness at the Rescue of Early Stopping for Adversarial Example Transferability	Transferability is the property of adversarial examples to be misclassified by other models than the surrogate model for which they were crafted. Previous research has shown that early stopping the training of the surrogate model substantially increases transferability. A common hypothesis to explain this is that deep ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,504
2312.01409	Generative Rendering: Controllable 4D-Guided Video Generation with 2D Diffusion Models	Traditional 3D content creation tools empower users to bring their imagination to life by giving them direct control over a scene's geometry, appearance, motion, and camera path. Creating computer-generated videos, however, is a tedious manual process, which can be automated by emerging text-to-video diffusion models. ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	412,432
2210.00518	High Precision Differentiation Techniques for Data-Driven Solution of Nonlinear PDEs by Physics-Informed Neural Networks	Time-dependent Partial Differential Equations with given initial conditions are considered in this paper. New differentiation techniques of the unknown solution with respect to time variable are proposed. It is shown that the proposed techniques allow to generate accurate higher order derivatives simultaneously for a s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	320,894
2003.13254	Environmental Adaptation of Robot Morphology and Control through Real-world Evolution	Robots operating in the real world will experience a range of different environments and tasks. It is essential for the robot to have the ability to adapt to its surroundings to work efficiently in changing conditions. Evolutionary robotics aims to solve this by optimizing both the control and body (morphology) of a ro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	170,153
1707.09695	Recurrent 3D Pose Sequence Machines	3D human articulated pose recovery from monocular image sequences is very challenging due to the diverse appearances, viewpoints, occlusions, and also the human 3D pose is inherently ambiguous from the monocular imagery. It is thus critical to exploit rich spatial and temporal long-range dependencies among body joints ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	78,051
1609.09582	Digitizing Municipal Street Inspections Using Computer Vision	"People want an authority to tell them how to value things. But they chose this authority not based on facts or results. They chose it because it seems authoritative and familiar." - The Big Short The pavement condition index is one such a familiar measure used by many US cities to measure street quality and justify ...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	61,747
2205.13226	Censor-aware Semi-supervised Learning for Survival Time Prediction from Medical Images	Survival time prediction from medical images is important for treatment planning, where accurate estimations can improve healthcare quality. One issue affecting the training of survival models is censored data. Most of the current survival prediction approaches are based on Cox models that can deal with censored data, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	298,858
2401.01542	Adversarial Machine Learning-Enabled Anonymization of OpenWiFi Data	Data privacy and protection through anonymization is a critical issue for network operators or data owners before it is forwarded for other possible use of data. With the adoption of Artificial Intelligence (AI), data anonymization augments the likelihood of covering up necessary sensitive information; preventing data ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	419,399
2402.16392	Placing Objects in Context via Inpainting for Out-of-distribution Segmentation	When deploying a semantic segmentation model into the real world, it will inevitably encounter semantic classes that were not seen during training. To ensure a safe deployment of such systems, it is crucial to accurately evaluate and improve their anomaly segmentation capabilities. However, acquiring and labelling sema...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,553
2307.15128	End-to-end Remote Sensing Change Detection of Unregistered Bi-temporal Images for Natural Disasters	Change detection based on remote sensing images has been a prominent area of interest in the field of remote sensing. Deep networks have demonstrated significant success in detecting changes in bi-temporal remote sensing images and have found applications in various fields. Given the degradation of natural environments...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	382,167
2101.05324	Multi-robot Symmetric Rendezvous Search on the Line	We study the Symmetric Rendezvous Search Problem for a multi-robot system. There are $n>2$ robots arbitrarily located on a line. Their goal is to meet somewhere on the line as quickly as possible. The robots do not know the initial location of any of the other robots or their own positions on the line. The symmetric ve...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	215,390
2101.02668	Towards Meaningful Statements in IR Evaluation. Mapping Evaluation Measures to Interval Scales	Recently, it was shown that most popular IR measures are not interval-scaled, implying that decades of experimental IR research used potentially improper methods, which may have produced questionable results. However, it was unclear if and to what extent these findings apply to actual evaluations and this opened a deba...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	214,701
2402.14988	Verifiable Boosted Tree Ensembles	Verifiable learning advocates for training machine learning models amenable to efficient security verification. Prior research demonstrated that specific classes of decision tree ensembles -- called large-spread ensembles -- allow for robustness verification in polynomial time against any norm-based attacker. This stud...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	431,942
2308.08259	Graph Relation Aware Continual Learning	Continual graph learning (CGL) studies the problem of learning from an infinite stream of graph data, consolidating historical knowledge, and generalizing it to the future task. At once, only current graph data are available. Although some recent attempts have been made to handle this task, we still face two potential ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	385,837
2410.01535	GaussianBlock: Building Part-Aware Compositional and Editable 3D Scene by Primitives and Gaussians	Recently, with the development of Neural Radiance Fields and Gaussian Splatting, 3D reconstruction techniques have achieved remarkably high fidelity. However, the latent representations learnt by these methods are highly entangled and lack interpretability. In this paper, we propose a novel part-aware compositional rec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	493,812
1611.07206	Learning to Distill: The Essence Vector Modeling Framework	In the context of natural language processing, representation learning has emerged as a newly active research subject because of its excellent performance in many applications. Learning representations of words is a pioneering study in this school of research. However, paragraph (or sentence and document) embedding lea...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	64,322
2402.02070	HotRAP: Hot Record Retention and Promotion for LSM-trees with Tiered Storage	The multi-level design of Log-Structured Merge-trees (LSM-trees) naturally fits the tiered storage architecture: the upper levels (recently inserted/updated records) are kept in fast storage to guarantee performance while the lower levels (the majority of records) are placed in slower but cheaper storage to reduce cost...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	426,368
1405.7254	Data-Driven Stochastic Models and Policies for Energy Harvesting Sensor Communications	Energy harvesting from the surroundings is a promising solution to perpetually power-up wireless sensor communications. This paper presents a data-driven approach of finding optimal transmission policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission parameters, pow...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	33,446
2111.02865	Testing using Privileged Information by Adapting Features with Statistical Dependence	Given an imperfect predictor, we exploit additional features at test time to improve the predictions made, without retraining and without knowledge of the prediction function. This scenario arises if training labels or data are proprietary, restricted, or no longer available, or if training itself is prohibitively expe...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	264,996
2406.19301	MCNC: Manifold Constrained Network Compression	The outstanding performance of large foundational models across diverse tasks-from computer vision to speech and natural language processing-has significantly increased their demand. However, storing and transmitting these models pose significant challenges due to their massive size (e.g., 350GB for GPT-3). Recent lite...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,372
2104.13742	MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains	GANs largely increases the potential impact of generative models. Therefore, we propose a novel knowledge transfer method for generative models based on mining the knowledge that is most beneficial to a specific target domain, either from a single or multiple pretrained GANs. This is done using a miner network that ide...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	232,598
1608.06420	A Harmonic Potential Field Approach for Joint Planning & Control of a Rigid, Separable Nonholonomic, Mobile Robot	The main objective of this paper is to provide a tool for performing path planning at the servo level of a mobile robot. The ability to perform, in a provably correct manner, such a complex task at the servo level can lead to a large increase in the speed of operation, low energy consumption and high quality of respons...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	60,113
2305.05477	Entanglement-Assisted Covert Communication via Qubit Depolarizing Channels	We consider entanglement-assisted communication over the qubit depolarizing channel under the security requirement of covert communication, where not only the information is kept secret, but the transmission itself must be concealed from detection by an adversary. Previous work showed that $O(\sqrt{n})$ information bit...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	363,165
2502.06258	Emergent Response Planning in LLM	In this work, we argue that large language models (LLMs), though trained to predict only the next token, exhibit emergent planning behaviors: $\textbf{their hidden representations encode future outputs beyond the next token}$. Through simple probing, we demonstrate that LLM prompt representations encode global attribut...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	532,008
2109.01761	An empirical evaluation of attention-based multi-head models for improved turbofan engine remaining useful life prediction	A single unit (head) is the conventional input feature extractor in deep learning architectures trained on multivariate time series signals. The importance of the fixed-dimensional vector representation generated by the single-head network has been demonstrated for industrial machinery condition monitoring and predicti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	253,524
2403.01607	Respiratory motion forecasting with online learning of recurrent neural networks for safety enhancement in externally guided radiotherapy	In lung radiotherapy, infrared cameras can record the location of reflective objects on the chest to infer the position of the tumor moving due to breathing, but treatment system latencies hinder radiation beam precision. Real-time recurrent learning (RTRL), is a potential solution as it can learn patterns within non-s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	434,498
2105.11301	DaN+: Danish Nested Named Entities and Lexical Normalization	This paper introduces DaN+, a new multi-domain corpus and annotation guidelines for Danish nested named entities (NEs) and lexical normalization to support research on cross-lingual cross-domain learning for a less-resourced language. We empirically assess three strategies to model the two-layer Named Entity Recognitio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	236,656
2406.07096	Fast Context-Biasing for CTC and Transducer ASR models with CTC-based Word Spotter	Accurate recognition of rare and new words remains a pressing problem for contextualized Automatic Speech Recognition (ASR) systems. Most context-biasing methods involve modification of the ASR model or the beam-search decoding algorithm, complicating model reuse and slowing down inference. This work presents a new app...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	462,904
2301.12519	3D Object Detection in LiDAR Point Clouds using Graph Neural Networks	LiDAR (Light Detection and Ranging) is an advanced active remote sensing technique working on the principle of time of travel (ToT) for capturing highly accurate 3D information of the surroundings. LiDAR has gained wide attention in research and development with the LiDAR industry expected to reach 2.8 billion $ by 202...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	342,559
2409.03749	Dynamics of Supervised and Reinforcement Learning in the Non-Linear Perceptron	The ability of a brain or a neural network to efficiently learn depends crucially on both the task structure and the learning rule. Previous works have analyzed the dynamical equations describing learning in the relatively simplified context of the perceptron under assumptions of a student-teacher framework or a linear...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	486,153
2308.14994	ICARUS: An Android-Based Unmanned Aerial Vehicle (UAV) Search and Rescue Eye in the Sky	The purpose of this paper is to develop an unmanned aerial vehicle (UAV) using a quadcopter with the capability of video surveillance, map coordinates, a deployable parachute with a medicine kit or a food pack as a payload, a collision warning system, remotely controlled, integrated with an android application to assis...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	388,524
2208.02613	Semantic Interleaving Global Channel Attention for Multilabel Remote Sensing Image Classification	Multi-Label Remote Sensing Image Classification (MLRSIC) has received increasing research interest. Taking the cooccurrence relationship of multiple labels as additional information helps to improve the performance of this task. Current methods focus on using it to constrain the final feature output of a Convolutional ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,518
2109.00150	Federated Reconnaissance: Efficient, Distributed, Class-Incremental Learning	We describe federated reconnaissance, a class of learning problems in which distributed clients learn new concepts independently and communicate that knowledge efficiently. In particular, we propose an evaluation framework and methodological baseline for a system in which each client is expected to learn a growing set ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	253,020
2211.15621	A Boosting Approach to Constructing an Ensemble Stack	An approach to evolutionary ensemble learning for classification is proposed in which boosting is used to construct a stack of programs. Each application of boosting identifies a single champion and a residual dataset, i.e. the training records that thus far were not correctly classified. The next program is only train...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	333,341
2106.10876	Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes	We propose a novel and unified Cycle in Cycle Generative Adversarial Network (C2GAN) for generating human faces, hands, bodies, and natural scenes. Our proposed C2GAN is a cross-modal model exploring the joint exploitation of the input image data and guidance data in an interactive manner. C2GAN contains two different ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	242,192
2107.07335	Towards Natural Brain-Machine Interaction using Endogenous Potentials based on Deep Neural Networks	Human-robot collaboration has the potential to maximize the efficiency of the operation of autonomous robots. Brain-machine interface (BMI) would be a desirable technology to collaborate with robots since the intention or state of users can be translated from the neural activities. However, the electroencephalogram (EE...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	246,383
2408.01923	Scalable Signal Temporal Logic Guided Reinforcement Learning via Value Function Space Optimization	The integration of reinforcement learning (RL) and formal methods has emerged as a promising framework for solving long-horizon planning problems. Conventional approaches typically involve abstraction of the state and action spaces and manually created labeling functions or predicates. However, the efficiency of these ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	478,420
2409.16948	The Power-Oriented Graphs Modeling Technique: From the Fundamental Principles to the Systematic, Step-by-Step Modeling of Complex Physical Systems	Modeling physical systems is an essential skill for a control engineer, since it enables to achieve a deep understanding of their dynamic behavior and, consequently, the development of effective control strategies. The first part of this article provides a tutorial description of the fundamental principles and properti...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	491,589
2104.05980	Experiments of ASR-based mispronunciation detection for children and adult English learners	Pronunciation is one of the fundamentals of language learning, and it is considered a primary factor of spoken language when it comes to an understanding and being understood by others. The persistent presence of high error rates in speech recognition domains resulting from mispronunciations motivates us to find altern...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	229,919
2204.01681	End-to-end multi-particle reconstruction in high occupancy imaging calorimeters with graph neural networks	We present an end-to-end reconstruction algorithm to build particle candidates from detector hits in next-generation granular calorimeters similar to that foreseen for the high-luminosity upgrade of the CMS detector. The algorithm exploits a distance-weighted graph neural network, trained with object condensation, a gr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	289,682
1806.09321	Kick control: using the attracting states arising within the sensorimotor loop of self-organized robots as motor primitives	Self-organized robots may develop attracting states within the sensorimotor loop, that is within the phase space of neural activity, body, and environmental variables. Fixpoints, limit cycles, and chaotic attractors correspond in this setting to a non-moving robot, to directed, and to irregular locomotion respectively....	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	101,334
2103.10626	Cluster-to-Conquer: A Framework for End-to-End Multi-Instance Learning for Whole Slide Image Classification	In recent years, the availability of digitized Whole Slide Images (WSIs) has enabled the use of deep learning-based computer vision techniques for automated disease diagnosis. However, WSIs present unique computational and algorithmic challenges. WSIs are gigapixel-sized ($\sim$100K pixels), making them infeasible to b...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	225,517
1712.00003	Modeling Information Flow Through Deep Neural Networks	This paper proposes a principled information theoretic analysis of classification for deep neural network structures, e.g. convolutional neural networks (CNN). The output of convolutional filters is modeled as a random variable Y conditioned on the object class C and network filter bank F. The conditional entropy (CENT...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,810
2204.06699	SNP2Vec: Scalable Self-Supervised Pre-Training for Genome-Wide Association Study	Self-supervised pre-training methods have brought remarkable breakthroughs in the understanding of text, image, and speech. Recent developments in genomics has also adopted these pre-training methods for genome understanding. However, they focus only on understanding haploid sequences, which hinders their applicability...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	291,428
2404.03380	On the Theoretical Expressive Power and the Design Space of Higher-Order Graph Transformers	Graph transformers have recently received significant attention in graph learning, partly due to their ability to capture more global interaction via self-attention. Nevertheless, while higher-order graph neural networks have been reasonably well studied, the exploration of extending graph transformers to higher-order ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	444,232
2101.10734	Consistent Mesh Colors for Multi-View Reconstructed 3D Scenes	We address the issue of creating consistent mesh texture maps captured from scenes without color calibration. We find that the method for aggregation of the multiple views is crucial for creating spatially consistent meshes without the need to explicitly optimize for spatial consistency. We compute a color prior from t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	217,031
2205.04362	FC$^3$: Feasibility-Based Control Chain Coordination	Hierarchical coordination of controllers often uses symbolic state representations that fully abstract their underlying low-level controllers, treating them as "black boxes" to the symbolic action abstraction. This paper proposes a framework to realize robust behavior, which we call Feasibility-based Control Chain Coor...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,620
2301.13591	Zero3D: Semantic-Driven Multi-Category 3D Shape Generation	Semantic-driven 3D shape generation aims to generate 3D objects conditioned on text. Previous works face problems with single-category generation, low-frequency 3D details, and requiring a large number of paired datasets for training. To tackle these challenges, we propose a multi-category conditional diffusion model. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	342,967
2311.07355	ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach	Given a complex graph database of node- and edge-attributed multi-graphs as well as associated metadata for each graph, how can we spot the anomalous instances? Many real-world problems can be cast as graph inference tasks where the graph representation could capture complex relational phenomena (e.g., transactions amo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	407,292
2404.16743	Automatic Speech Recognition System-Independent Word Error Rate Estimation	Word error rate (WER) is a metric used to evaluate the quality of transcriptions produced by Automatic Speech Recognition (ASR) systems. In many applications, it is of interest to estimate WER given a pair of a speech utterance and a transcript. Previous work on WER estimation focused on building models that are traine...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	449,604
2210.07037	Self-Supervised Learning of Linear Precoders under Non-Linear PA Distortion for Energy-Efficient Massive MIMO Systems	Massive multiple input multiple output (MIMO) systems are typically designed under the assumption of linear power amplifiers (PAs). However, PAs are typically most energy-efficient when operating close to their saturation point, where they cause non-linear distortion. Moreover, when using conventional precoders, this d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,552
1704.07766	A lower bound on the differential entropy of log-concave random vectors with applications	We derive a lower bound on the differential entropy of a log-concave random variable $X$ in terms of the $p$-th absolute moment of $X$. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds on the rate-distortion function and the channel capacity. Specifically, we stud...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	72,419
2412.04738	DHIL-GT: Scalable Graph Transformer with Decoupled Hierarchy Labeling	Graph Transformer (GT) has recently emerged as a promising neural network architecture for learning graph-structured data. However, its global attention mechanism with quadratic complexity concerning the graph scale prevents wider application to large graphs. While current methods attempt to enhance GT scalability by a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,541
2204.08848	I still have Time(s): Extending HeidelTime for German Texts	HeidelTime is one of the most widespread and successful tools for detecting temporal expressions in texts. Since HeidelTime's pattern matching system is based on regular expression, it can be extended in a convenient way. We present such an extension for the German resources of HeidelTime: HeidelTime-EXT . The extensio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	292,235
2210.10231	Speaker- and Age-Invariant Training for Child Acoustic Modeling Using Adversarial Multi-Task Learning	One of the major challenges in acoustic modelling of child speech is the rapid changes that occur in the children's articulators as they grow up, their differing growth rates and the subsequent high variability in the same age group. These high acoustic variations along with the scarcity of child speech corpora have im...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	324,831
2204.09271	A Survey of Video-based Action Quality Assessment	Human action recognition and analysis have great demand and important application significance in video surveillance, video retrieval, and human-computer interaction. The task of human action quality evaluation requires the intelligent system to automatically and objectively evaluate the action completed by the human. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,374
2501.09893	Sparse Binary Representation Learning for Knowledge Tracing	Knowledge tracing (KT) models aim to predict students' future performance based on their historical interactions. Most existing KT models rely exclusively on human-defined knowledge concepts (KCs) associated with exercises. As a result, the effectiveness of these models is highly dependent on the quality and completene...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,309

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