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
2007.00822	Understanding Road Layout from Videos as a Whole	In this paper, we address the problem of inferring the layout of complex road scenes from video sequences. To this end, we formulate it as a top-view road attributes prediction problem and our goal is to predict these attributes for each frame both accurately and consistently. In contrast to prior work, we exploit the ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,229
1802.00776	Green Stability Assumption: Unsupervised Learning for Statistics-Based Illumination Estimation	In the image processing pipeline of almost every digital camera there is a part dedicated to computational color constancy i.e. to removing the influence of illumination on the colors of the image scene. Some of the best known illumination estimation methods are the so called statistics-based methods. They are less acc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	89,471
1810.08640	On Extensions of CLEVER: A Neural Network Robustness Evaluation Algorithm	CLEVER (Cross-Lipschitz Extreme Value for nEtwork Robustness) is an Extreme Value Theory (EVT) based robustness score for large-scale deep neural networks (DNNs). In this paper, we propose two extensions on this robustness score. First, we provide a new formal robustness guarantee for classifier functions that are twic...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	110,866
1712.07206	Accelerating the computation of FLAPW methods on heterogeneous architectures	Legacy codes in computational science and engineering have been very successful in providing essential functionality to researchers. However, they are not capable of exploiting the massive parallelism provided by emerging heterogeneous architectures. The lack of portable performance and scalability puts them at high ri...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	87,009
2011.06346	Multi-View Dynamic Heterogeneous Information Network Embedding	Most existing Heterogeneous Information Network (HIN) embedding methods focus on static environments while neglecting the evolving characteristic of realworld networks. Although several dynamic embedding methods have been proposed, they are merely designed for homogeneous networks and cannot be directly applied in hete...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	206,217
2309.17072	MaaSDB: Spatial Databases in the Era of Large Language Models (Vision Paper)	Large language models (LLMs) are advancing rapidly. Such models have demonstrated strong capabilities in learning from large-scale (unstructured) text data and answering user queries. Users do not need to be experts in structured query languages to interact with systems built upon such models. This provides great oppor...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	395,616
2412.02271	MediaSpin: Exploring Media Bias Through Fine-Grained Analysis of News Headlines	In this paper, we introduce the MediaSpin dataset aiming to help in the development of models that can detect different forms of media bias present in news headlines, developed through human-supervised and -validated Large Language Model (LLM) labeling of media bias. This corpus comprises 78,910 pairs of news headlines...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	513,468
1702.07191	ViP-CNN: Visual Phrase Guided Convolutional Neural Network	As the intermediate level task connecting image captioning and object detection, visual relationship detection started to catch researchers' attention because of its descriptive power and clear structure. It detects the objects and captures their pair-wise interactions with a subject-predicate-object triplet, e.g. pers...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	68,743
2311.09741	P^3SUM: Preserving Author's Perspective in News Summarization with Diffusion Language Models	In this work, we take a first step towards designing summarization systems that are faithful to the author's intent, not only the semantic content of the article. Focusing on a case study of preserving political perspectives in news summarization, we find that existing approaches alter the political opinions and stance...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	408,271
2212.01650	Global memory transformer for processing long documents	Transformer variants dominate the state-of-the-art in different natural language processing tasks such as translation, reading comprehension and summarization. Our paper is more directed to use general memory slots added to the inputs and studying the results of adding these slots. This paper is a go on study of genera...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	334,514
2309.11568	BTLM-3B-8K: 7B Parameter Performance in a 3B Parameter Model	We introduce the Bittensor Language Model, called "BTLM-3B-8K", a new state-of-the-art 3 billion parameter open-source language model. BTLM-3B-8K was trained on 627B tokens from the SlimPajama dataset with a mixture of 2,048 and 8,192 context lengths. BTLM-3B-8K outperforms all existing 3B parameter models by 2-5.5% ac...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	393,450
2305.13516	Scaling Speech Technology to 1,000+ Languages	Expanding the language coverage of speech technology has the potential to improve access to information for many more people. However, current speech technology is restricted to about one hundred languages which is a small fraction of the over 7,000 languages spoken around the world. The Massively Multilingual Speech (...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	366,533
1811.03220	Secrecy Outage Analysis for Cooperative NOMA Systems with Relay Selection Scheme	This paper considers the secrecy outage performance of a multiple-relay assisted non-orthogonal multiple access (NOMA) network over Nakagami-$m$ fading channels. Two slots are utilized to transmit signals from the base station to destination. At the first slot, the base station broadcasts the superposition signal of th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	112,784
2302.12822	Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data	Chain-of-thought (CoT) advances the reasoning abilities of large language models (LLMs) and achieves superior performance in complex reasoning tasks. However, most CoT studies rely on carefully designed human-annotated rational chains to prompt LLMs, posing challenges for real-world applications where labeled data is a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	347,702
2009.07825	Multiport Rapid Charging Power Converter	Rapid charger is getting more and more important as the electric vehicle (EV) getting popular. The rapid charging technique plays an important part in the electric vehicle development. Multiport converter is used in the rapid charging technique to reduce the required current and also provides some other advantages. In ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	196,058
2206.05166	Multi-dimensional dual-blind deconvolution approach toward joint radar-communications	We consider a joint multiple-antenna radar-communications system in a co-existence scenario. Contrary to conventional applications, wherein at least the radar waveform and communications channel are known or estimated \textit{a priori}, we investigate the case when the channels and transmit signals of both systems are ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	301,912
1909.03980	Incremental learning of environment interactive structures from trajectories of individuals	This work proposes a novel method for estimating the influence that unknown static objects might have over mobile agents. Since the motion of agents can be affected by the presence of fixed objects, it is possible use the information about trajectories deviations to infer the presence of obstacles and estimate the forc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	144,661
2403.17169	QuanTemp: A real-world open-domain benchmark for fact-checking numerical claims	Automated fact checking has gained immense interest to tackle the growing misinformation in the digital era. Existing systems primarily focus on synthetic claims on Wikipedia, and noteworthy progress has also been made on real-world claims. In this work, we release QuanTemp, a diverse, multi-domain dataset focused excl...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	441,338
2208.04010	Application of Guessing to Sequential Decoding of Polarization-Adjusted Convolutional (PAC) Codes	Despite the extreme error-correction performance, the amount of computation of sequential decoding of the polarization-adjusted convolutional (PAC) codes is random. In sequential decoding of convolutional codes, the computational cutoff rate denotes the region between rates whose average computational complexity of dec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	311,967
2101.01294	One vs Previous and Similar Classes Learning -- A Comparative Study	When dealing with multi-class classification problems, it is common practice to build a model consisting of a series of binary classifiers using a learning paradigm which dictates how the classifiers are built and combined to discriminate between the individual classes. As new data enters the system and the model needs...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	214,326
2303.10623	Active hypothesis testing in unknown environments using recurrent neural networks and model free reinforcement learning	A combination of deep reinforcement learning and supervised learning is proposed for the problem of active sequential hypothesis testing in completely unknown environments. We make no assumptions about the prior probability, the action and observation sets, and the observation generating process. Our method can be used...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	352,524
2409.16899	Robotic Backchanneling in Online Conversation Facilitation: A Cross-Generational Study	Japan faces many challenges related to its aging society, including increasing rates of cognitive decline in the population and a shortage of caregivers. Efforts have begun to explore solutions using artificial intelligence (AI), especially socially embodied intelligent agents and robots that can communicate with peopl...	true	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	491,564
2112.15466	Polynomial-Time Key Recovery Attack on the Lau-Tan Cryptosystem Based on Gabidulin Codes	This paper presents a key recovery attack on the cryptosystem proposed by Lau and Tan in a talk at ACISP 2018. The Lau-Tan cryptosystem uses Gabidulin codes as the underlying decodable code. To hide the algebraic structure of Gabidulin codes, the authors chose a matrix of column rank $n$ to mix with a generator matrix ...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	273,795
2002.06157	Generalization and Representational Limits of Graph Neural Networks	We address two fundamental questions about graph neural networks (GNNs). First, we prove that several important graph properties cannot be computed by GNNs that rely entirely on local information. Such GNNs include the standard message passing models, and more powerful spatial variants that exploit local graph structur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	164,097
1707.01992	On the Compactness, Efficiency, and Representation of 3D Convolutional Networks: Brain Parcellation as a Pretext Task	Deep convolutional neural networks are powerful tools for learning visual representations from images. However, designing efficient deep architectures to analyse volumetric medical images remains challenging. This work investigates efficient and flexible elements of modern convolutional networks such as dilated convolu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,629
2405.04406	R\'enyi divergence guarantees for hashing with linear codes	We consider the problem of distilling uniform random bits from an unknown source with a given $p$-entropy using linear hashing. As our main result, we estimate the expected $p$-divergence from the uniform distribution over the ensemble of random linear codes for all integer $p\ge 2$. The proof relies on analyzing how a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	452,563
1806.09421	Beamforming Design and Power Allocation for Secure Transmission with NOMA	In this work, we propose a novel beamforming design to enhance physical layer security of a non-orthogonal multiple access (NOMA) system with the aid of artificial noise (AN). The proposed design uses two scalars to balance the useful signal strength and interference at the strong and weak users, which is a generalized...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	101,349
2108.10066	Dynamic Neural Network Architectural and Topological Adaptation and Related Methods -- A Survey	Training and inference in deep neural networks (DNNs) has, due to a steady increase in architectural complexity and data set size, lead to the development of strategies for reducing time and space requirements of DNN training and inference, which is of particular importance in scenarios where training takes place in re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	251,790
2303.17468	Surrogate Neural Networks for Efficient Simulation-based Trajectory Planning Optimization	This paper presents a novel methodology that uses surrogate models in the form of neural networks to reduce the computation time of simulation-based optimization of a reference trajectory. Simulation-based optimization is necessary when there is no analytical form of the system accessible, only input-output data that c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,211
1306.0193	A Trust-based Recruitment Framework for Multi-hop Social Participatory Sensing	The idea of social participatory sensing provides a substrate to benefit from friendship relations in recruiting a critical mass of participants willing to attend in a sensing campaign. However, the selection of suitable participants who are trustable and provide high quality contributions is challenging. In this paper...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	24,941
2407.04925	RAMO: Retrieval-Augmented Generation for Enhancing MOOCs Recommendations	Massive Open Online Courses (MOOCs) have significantly enhanced educational accessibility by offering a wide variety of courses and breaking down traditional barriers related to geography, finance, and time. However, students often face difficulties navigating the vast selection of courses, especially when exploring ne...	true	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	470,746
1904.03335	Local Regularization of Noisy Point Clouds: Improved Global Geometric Estimates and Data Analysis	Several data analysis techniques employ similarity relationships between data points to uncover the intrinsic dimension and geometric structure of the underlying data-generating mechanism. In this paper we work under the model assumption that the data is made of random perturbations of feature vectors lying on a low-di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,682
2110.10255	A Simple Approach to Continual Learning by Transferring Skill Parameters	In order to be effective general purpose machines in real world environments, robots not only will need to adapt their existing manipulation skills to new circumstances, they will need to acquire entirely new skills on-the-fly. A great promise of continual learning is to endow robots with this ability, by using their a...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	262,082
2403.09766	An Image Is Worth 1000 Lies: Adversarial Transferability across Prompts on Vision-Language Models	Different from traditional task-specific vision models, recent large VLMs can readily adapt to different vision tasks by simply using different textual instructions, i.e., prompts. However, a well-known concern about traditional task-specific vision models is that they can be misled by imperceptible adversarial perturb...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,912
2305.14782	IBCL: Zero-shot Model Generation under Stability-Plasticity Trade-offs	Algorithms that balance the stability-plasticity trade-off are well-studied in the continual learning literature. However, only a few of them focus on obtaining models for specified trade-off preferences. When solving the problem of continual learning under specific trade-offs (CLuST), state-of-the-art techniques lever...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	367,253
2009.14237	Augmenting Scientific Papers with Just-in-Time, Position-Sensitive Definitions of Terms and Symbols	Despite the central importance of research papers to scientific progress, they can be difficult to read. Comprehension is often stymied when the information needed to understand a passage resides somewhere else: in another section, or in another paper. In this work, we envision how interfaces can bring definitions of t...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	197,968
2001.07973	On Simple Reactive Neural Networks for Behaviour-Based Reinforcement Learning	We present a behaviour-based reinforcement learning approach, inspired by Brook's subsumption architecture, in which simple fully connected networks are trained as reactive behaviours. Our working assumption is that a pick and place robotic task can be simplified by leveraging domain knowledge of a robotics developer t...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	161,172
2409.04133	Secure Traffic Sign Recognition: An Attention-Enabled Universal Image Inpainting Mechanism against Light Patch Attacks	Traffic sign recognition systems play a crucial role in assisting drivers to make informed decisions while driving. However, due to the heavy reliance on deep learning technologies, particularly for future connected and autonomous driving, these systems are susceptible to adversarial attacks that pose significant safet...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	486,304
2407.14170	Forbes: Face Obfuscation Rendering via Backpropagation Refinement Scheme	A novel algorithm for face obfuscation, called Forbes, which aims to obfuscate facial appearance recognizable by humans but preserve the identity and attributes decipherable by machines, is proposed in this paper. Forbes first applies multiple obfuscating transformations with random parameters to an image to remove the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,678
2412.05940	Digital Modeling of Massage Techniques and Reproduction by Robotic Arms	This paper explores the digital modeling and robotic reproduction of traditional Chinese medicine (TCM) massage techniques. We adopt an adaptive admittance control algorithm to optimize force and position control, ensuring safety and comfort. The paper analyzes key TCM techniques from kinematic and dynamic perspectives...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	515,034
2002.05411	Analysis and Evaluation of Handwriting in Patients with Parkinson's Disease Using kinematic, Geometrical, and Non-linear Features	Background and objectives: Parkinson's disease is a neurological disorder that affects the motor system producing lack of coordination, resting tremor, and rigidity. Impairments in handwriting are among the main symptoms of the disease. Handwriting analysis can help in supporting the diagnosis and in monitoring the pro...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	163,890
2003.04919	Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems	There is a growing consensus that solutions to complex science and engineering problems require novel methodologies that are able to integrate traditional physics-based modeling approaches with state-of-the-art machine learning (ML) techniques. This paper provides a structured overview of such techniques. Application-c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	167,696
2010.01180	Reinforcement Learning of Sequential Price Mechanisms	We introduce the use of reinforcement learning for indirect mechanisms, working with the existing class of sequential price mechanisms, which generalizes both serial dictatorship and posted price mechanisms and essentially characterizes all strongly obviously strategyproof mechanisms. Learning an optimal mechanism with...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	198,547
2111.07462	Federated Learning with Hyperparameter-based Clustering for Electrical Load Forecasting	Electrical load prediction has become an integral part of power system operation. Deep learning models have found popularity for this purpose. However, to achieve a desired prediction accuracy, they require huge amounts of data for training. Sharing electricity consumption data of individual households for load predict...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,380
2410.04784	Formality is Favored: Unraveling the Learning Preferences of Large Language Models on Data with Conflicting Knowledge	Having been trained on massive pretraining data, large language models have shown excellent performance on many knowledge-intensive tasks. However, pretraining data tends to contain misleading and even conflicting information, and it is intriguing to understand how LLMs handle these noisy data during training. In this ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	495,440
1502.02298	Belief Revision, Minimal Change and Relaxation: A General Framework based on Satisfaction Systems, and Applications to Description Logics	Belief revision of knowledge bases represented by a set of sentences in a given logic has been extensively studied but for specific logics, mainly propositional, and also recently Horn and description logics. Here, we propose to generalize this operation from a model-theoretic point of view, by defining revision in an ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	40,023
2206.05970	Hypernetwork-Based Adaptive Image Restoration	Adaptive image restoration models can restore images with different degradation levels at inference time without the need to retrain the model. We present an approach that is highly accurate and allows a significant reduction in the number of parameters. In contrast to existing methods, our approach can restore images ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	302,203
2003.00467	NeuroTac: A Neuromorphic Optical Tactile Sensor applied to Texture Recognition	Developing artificial tactile sensing capabilities that rival human touch is a long-term goal in robotics and prosthetics. Gradually more elaborate biomimetic tactile sensors are being developed and applied to grasping and manipulation tasks to help achieve this goal. Here we present the neuroTac, a novel neuromorphic ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	166,308
2207.01414	Controlling the Cascade: Kinematic Planning for N-ball Toss Juggling	Dynamic movements are ubiquitous in human motor behavior as they tend to be more efficient and can solve a broader range of skill domains than their quasi-static counterparts. For decades, robotic juggling tasks have been among the most frequently studied dynamic manipulation problems since the required dynamic dexteri...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	306,167
2102.08248	Hierarchical VAEs Know What They Don't Know	Deep generative models have been demonstrated as state-of-the-art density estimators. Yet, recent work has found that they often assign a higher likelihood to data from outside the training distribution. This seemingly paradoxical behavior has caused concerns over the quality of the attained density estimates. In the c...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	220,389
2310.04915	On Accelerating Diffusion-based Molecular Conformation Generation in SE(3)-invariant Space	Diffusion-based generative models in SE(3)-invariant space have demonstrated promising performance in molecular conformation generation, but typically require solving stochastic differential equations (SDEs) with thousands of update steps. Till now, it remains unclear how to effectively accelerate this procedure explic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	397,882
1005.3889	Capacity and Modulations with Peak Power Constraint	A practical communication channel often suffers from constraints on input other than the average power, such as the peak power constraint. In order to compare achievable rates with different constellations as well as the channel capacity under such constraints, it is crucial to take these constraints into consideration...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	6,531
1911.08277	Exploring the added value of blockchain technology for the healthcare domain	In this report, the University Medical Center Groningen (UMCG) has written down lessons learned on how blockchain technology can have an impact on the healthcare domain. By looking at two use-cases, the hospital challenged several teams, participating in an open innovation program and blockchain hackathon, to find a so...	true	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	false	154,147
2208.06245	Understanding the stochastic dynamics of sequential decision-making processes: A path-integral analysis of multi-armed bandits	The multi-armed bandit (MAB) model is one of the most classical models to study decision-making in an uncertain environment. In this model, a player chooses one of $K$ possible arms of a bandit machine to play at each time step, where the corresponding arm returns a random reward to the player, potentially from a speci...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,653
cs/0509007	Non-Data-Aided Parameter Estimation in an Additive White Gaussian Noise Channel	Non-data-aided (NDA) parameter estimation is considered for binary-phase-shift-keying transmission in an additive white Gaussian noise channel. Cramer-Rao lower bounds (CRLBs) for signal amplitude, noise variance, channel reliability constant and bit-error rate are derived and it is shown how these parameters relate to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,934
2501.13896	GUI-Bee: Align GUI Action Grounding to Novel Environments via Autonomous Exploration	Graphical User Interface (GUI) action grounding is a critical step in GUI automation that maps language instructions to actionable elements on GUI screens. Most recent works of GUI action grounding leverage large GUI datasets to fine-tune MLLMs. However, the fine-tuning data always covers limited GUI environments, and ...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	526,866
2310.03843	Less is More: On the Feature Redundancy of Pretrained Models When Transferring to Few-shot Tasks	Transferring a pretrained model to a downstream task can be as easy as conducting linear probing with target data, that is, training a linear classifier upon frozen features extracted from the pretrained model. As there may exist significant gaps between pretraining and downstream datasets, one may ask whether all dime...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	397,439
2111.00261	Explicit and Efficient Construction of (nearly) Optimal Rate Codes for Binary Deletion Channel and the Poisson Repeat Channel	Two of the most common models for channels with synchronisation errors are the Binary Deletion Channel with parameter $p$ ($\text{BDC}_p$) -- a channel where every bit of the codeword is deleted i.i.d with probability $p$, and the Poisson Repeat Channel with parameter $\lambda$ ($\text{PRC}_\lambda$) -- a channel where...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	264,161
1904.08139	Understanding the Signature of Controversial Wikipedia Articles through Motifs in Editor Revision Networks	Wikipedia serves as a good example of how editors collaborate to form and maintain an article. The relationship between editors, derived from their sequence of editing activity, results in a directed network structure called the revision network, that potentially holds valuable insights into editing activity. In this p...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	127,987
1509.06720	A Dual-Source Approach for 3D Pose Estimation from a Single Image	One major challenge for 3D pose estimation from a single RGB image is the acquisition of sufficient training data. In particular, collecting large amounts of training data that contain unconstrained images and are annotated with accurate 3D poses is infeasible. We therefore propose to use two independent training sourc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	47,182
2501.12254	Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos	Self-supervised learning holds the promise to learn good representations from real-world continuous uncurated data streams. However, most existing works in visual self-supervised learning focus on static images or artificial data streams. Towards exploring a more realistic learning substrate, we investigate streaming s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	526,228
2405.04669	Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics	Auto-regressive large language models (LLMs) show impressive capacities to solve many complex reasoning tasks while struggling with some simple logical reasoning tasks such as inverse search: when trained on '$A \to B$' (e.g., 'Tom is the parent of John'), LLM fails to directly conclude '$B \gets A$' (e.g., 'John is th...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	452,633
1509.05739	Low-Coherence Frames from Group Fourier Matrices	Many problems in areas such as compressive sensing and coding theory seek to design a set of equal-norm vectors with large angular separation. This idea is essentially equivalent to constructing a frame with low coherence. The elements of such frames can in turn be used to build high-performance spherical codes, quantu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,083
2412.09925	Simulating Hard Attention Using Soft Attention	We study conditions under which transformers using soft attention can simulate hard attention, that is, effectively focus all attention on a subset of positions. First, we examine several variants of linear temporal logic, whose formulas have been previously been shown to be computable using hard attention transformers...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	516,712
2204.02849	KNN-Diffusion: Image Generation via Large-Scale Retrieval	Recent text-to-image models have achieved impressive results. However, since they require large-scale datasets of text-image pairs, it is impractical to train them on new domains where data is scarce or not labeled. In this work, we propose using large-scale retrieval methods, in particular, efficient k-Nearest-Neighbo...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	true	290,105
2203.06895	Topological EEG Nonlinear Dynamics Analysis for Emotion Recognition	Emotional recognition through exploring the electroencephalography (EEG) characteristics has been widely performed in recent studies. Nonlinear analysis and feature extraction methods for understanding the complex dynamical phenomena are associated with the EEG patterns of different emotions. The phase space reconstruc...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	285,259
2108.08482	VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection	Lane detection plays a key role in autonomous driving. While car cameras always take streaming videos on the way, current lane detection works mainly focus on individual images (frames) by ignoring dynamics along the video. In this work, we collect a new video instance lane detection (VIL-100) dataset, which contains 1...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,267
2006.05030	High Tissue Contrast MRI Synthesis Using Multi-Stage Attention-GAN for Glioma Segmentation	Magnetic resonance imaging (MRI) provides varying tissue contrast images of internal organs based on a strong magnetic field. Despite the non-invasive advantage of MRI in frequent imaging, the low contrast MR images in the target area make tissue segmentation a challenging problem. This paper demonstrates the potential...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	180,907
2005.09683	Neural Collaborative Filtering vs. Matrix Factorization Revisited	Embedding based models have been the state of the art in collaborative filtering for over a decade. Traditionally, the dot product or higher order equivalents have been used to combine two or more embeddings, e.g., most notably in matrix factorization. In recent years, it was suggested to replace the dot product with a...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	177,980
2401.06445	Directed network comparison using motifs	Analyzing and characterizing the differences between networks is a fundamental and challenging problem in network science. Previously, most network comparison methods that rely on topological properties have been restricted to measuring differences between two undirected networks. However, many networks, such as biolog...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	421,164
2302.07958	Meta-Reinforcement Learning via Exploratory Task Clustering	Meta-reinforcement learning (meta-RL) aims to quickly solve new tasks by leveraging knowledge from prior tasks. However, previous studies often assume a single mode homogeneous task distribution, ignoring possible structured heterogeneity among tasks. Leveraging such structures can better facilitate knowledge sharing a...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	345,881
1711.07230	Optimism-Based Adaptive Regulation of Linear-Quadratic Systems	The main challenge for adaptive regulation of linear-quadratic systems is the trade-off between identification and control. An adaptive policy needs to address both the estimation of unknown dynamics parameters (exploration), as well as the regulation of the underlying system (exploitation). To this end, optimism-based...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	84,943
1409.5079	Predictive Capacity of Meteorological Data - Will it rain tomorrow	With the availability of high precision digital sensors and cheap storage medium, it is not uncommon to find large amounts of data collected on almost all measurable attributes, both in nature and man-made habitats. Weather in particular has been an area of keen interest for researchers to develop more accurate and rel...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	36,131
2009.03393	Generative Language Modeling for Automated Theorem Proving	We explore the application of transformer-based language models to automated theorem proving. This work is motivated by the possibility that a major limitation of automated theorem provers compared to humans -- the generation of original mathematical terms -- might be addressable via generation from language models. We...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	194,802
1009.0638	Clique Graphs and Overlapping Communities	It is shown how to construct a clique graph in which properties of cliques of a fixed order in a given graph are represented by vertices in a weighted graph. Various definitions and motivations for these weights are given. The detection of communities or clusters is used to illustrate how a clique graph may be exploite...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,472
2501.01994	Fuzzy Model Identification and Self Learning with Smooth Compositions	This paper develops a smooth model identification and self-learning strategy for dynamic systems taking into account possible parameter variations and uncertainties. We have tried to solve the problem such that the model follows the changes and variations in the system on a continuous and smooth surface. Running the mo...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	522,295
2107.02517	An Evaluation of Machine Learning and Deep Learning Models for Drought Prediction using Weather Data	Drought is a serious natural disaster that has a long duration and a wide range of influence. To decrease the drought-caused losses, drought prediction is the basis of making the corresponding drought prevention and disaster reduction measures. While this problem has been studied in the literature, it remains unknown w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	244,852
2403.18742	Understanding the Learning Dynamics of Alignment with Human Feedback	Aligning large language models (LLMs) with human intentions has become a critical task for safely deploying models in real-world systems. While existing alignment approaches have seen empirical success, theoretically understanding how these methods affect model behavior remains an open question. Our work provides an in...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	442,062
1908.00323	JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English	In the current work, we present a description of the system submitted to WMT 2018 News Translation Shared task. The system was created to translate news text from Finnish to English. The system used a Character Based Neural Machine Translation model to accomplish the given task. The current paper documents the preproce...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	140,487
2111.10195	Real-time Coherency Identification using a Window-Size-Based Recursive Typicality Data Analysis	This work presents a data-driven analysis of minimal length necessary for coherency detection considering a recursive form of the typicality-based Data analysis (TDA). It proposes a methodology that encloses the observation of the variance of the typicality ({\tau} ) to asses the minimal window length necessary to dete...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	267,238
2104.02651	A Modified Convolutional Network for Auto-encoding based on Pattern Theory Growth Function	This brief paper reports the shortcoming of a variant of convolutional neural network whose components are developed based on the pattern theory framework.	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	228,802
2302.14698	Heuristic Modularity Maximization Algorithms for Community Detection Rarely Return an Optimal Partition or Anything Similar	Community detection is a fundamental problem in computational sciences with extensive applications in various fields. The most commonly used methods are the algorithms designed to maximize modularity over different partitions of the network nodes. Using 80 real and random networks from a wide range of contexts, we inve...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	true	348,401
2106.14112	Time-Series Representation Learning via Temporal and Contextual Contrasting	Learning decent representations from unlabeled time-series data with temporal dynamics is a very challenging task. In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabeled data. First, the...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	243,291
1511.03415	The Dune FoamGrid implementation for surface and network grids	We present FoamGrid, a new implementation of the DUNE grid interface. FoamGrid implements one- and two-dimensional grids in a physical space of arbitrary dimension, which allows for grids for curved domains. Even more, the grids are not expected to have a manifold structure, i.e., more than two elements can share a com...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	48,754
2412.17571	HPCNeuroNet: A Neuromorphic Approach Merging SNN Temporal Dynamics with Transformer Attention for FPGA-based Particle Physics	This paper presents the innovative HPCNeuroNet model, a pioneering fusion of Spiking Neural Networks (SNNs), Transformers, and high-performance computing tailored for particle physics, particularly in particle identification from detector responses. Our approach leverages SNNs' intrinsic temporal dynamics and Transform...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	520,031
2301.10987	A Decentralized Policy for Minimization of Age of Incorrect Information in Slotted ALOHA Systems	The Age of Incorrect Information (AoII) is a metric that can combine the freshness of the information available to a gateway in an Internet of Things (IoT) network with the accuracy of that information. As such, minimizing the AoII can allow the operators of IoT systems to have a more precise and up-to-date picture of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	341,987
1706.00679	Testing Gaussian Process with Applications to Super-Resolution	This article introduces exact testing procedures on the mean of a Gaussian process $X$ derived from the outcomes of $\ell_1$-minimization over the space of complex valued measures. The process $X$ can be thought as the sum of two terms: first, the convolution between some kernel and a target atomic measure (mean of the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	74,667
2304.05141	Dexterous In-Hand Manipulation of Slender Cylindrical Objects through Deep Reinforcement Learning with Tactile Sensing	Continuous in-hand manipulation is an important physical interaction skill, where tactile sensing provides indispensable contact information to enable dexterous manipulation of small objects. This work proposed a framework for end-to-end policy learning with tactile feedback and sim-to-real transfer, which achieved fin...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	357,508
1706.09601	Actor-Critic Sequence Training for Image Captioning	Generating natural language descriptions of images is an important capability for a robot or other visual-intelligence driven AI agent that may need to communicate with human users about what it is seeing. Such image captioning methods are typically trained by maximising the likelihood of ground-truth annotated caption...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,167
1409.8183	An Improved Constraint-Tightening Approach for Stochastic MPC	The problem of achieving a good trade-off in Stochastic Model Predictive Control between the competing goals of improving the average performance and reducing conservativeness, while still guaranteeing recursive feasibility and low computational complexity, is addressed. We propose a novel, less restrictive scheme whic...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	36,388
2304.01041	Integrated Behavior Planning and Motion Control for Autonomous Vehicles with Traffic Rules Compliance	In this article, we propose an optimization-based integrated behavior planning and motion control scheme, which is an interpretable and adaptable urban autonomous driving solution that complies with complex traffic rules while ensuring driving safety. Inherently, to ensure compliance with traffic rules, an innovative d...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	355,910
2109.10187	Oriented Object Detection in Aerial Images Based on Area Ratio of Parallelogram	Oriented object detection is a challenging task in aerial images since the objects in aerial images are displayed in arbitrary directions and are frequently densely packed. The mainstream detectors describe rotating objects using a five-parament or eight-parament representations, which suffer from representation ambigu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	256,537
2207.05672	DDI Prediction via Heterogeneous Graph Attention Networks	Polypharmacy, defined as the use of multiple drugs together, is a standard treatment method, especially for severe and chronic diseases. However, using multiple drugs together may cause interactions between drugs. Drug-drug interaction (DDI) is the activity that occurs when the impact of one drug changes when combined ...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	307,618
1610.05670	Stylometric Analysis of Early Modern Period English Plays	Function word adjacency networks (WANs) are used to study the authorship of plays from the Early Modern English period. In these networks, nodes are function words and directed edges between two nodes represent the relative frequency of directed co-appearance of the two words. For every analyzed play, a WAN is construc...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	62,546
2311.04578	A New Version of q-ary Varshamov-Tenengolts Codes with More Efficient Encoders: The Differential VT Codes and The Differential Shifted VT Codes	The problem of correcting deletions and insertions has recently received significantly increased attention due to the DNA-based data storage technology, which suffers from deletions and insertions with extremely high probability. In this work, we study the problem of constructing non-binary burst-deletion/insertion cor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	406,281
1503.02286	Three-Source Extractors for Polylogarithmic Min-Entropy	We continue the study of constructing explicit extractors for independent general weak random sources. The ultimate goal is to give a construction that matches what is given by the probabilistic method --- an extractor for two independent $n$-bit weak random sources with min-entropy as small as $\log n+O(1)$. Previousl...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	40,916
2107.05849	Model Selection for Generic Reinforcement Learning	We address the problem of model selection for the finite horizon episodic Reinforcement Learning (RL) problem where the transition kernel $P^$ belongs to a family of models $\mathcal{P}^$ with finite metric entropy. In the model selection framework, instead of $\mathcal{P}^*$, we are given $M$ nested families of tran...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	245,907
1805.04016	Automatic Estimation of Simultaneous Interpreter Performance	Simultaneous interpretation, translation of the spoken word in real-time, is both highly challenging and physically demanding. Methods to predict interpreter confidence and the adequacy of the interpreted message have a number of potential applications, such as in computer-assisted interpretation interfaces or pedagogi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	97,157
2410.14340	Zero-shot Action Localization via the Confidence of Large Vision-Language Models	Precise action localization in untrimmed video is vital for fields such as professional sports and minimally invasive surgery, where the delineation of particular motions in recordings can dramatically enhance analysis. But in many cases, large scale datasets with video-label pairs for localization are unavailable, lim...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	499,989
cs/0701163	Using Table Valued Functions in SQL Server 2005 To Implement a Spatial Data Library	This article explains how to add spatial search functions (point-near-point and point in polygon) to Microsoft SQL Server 2005 using C# and table-valued functions. It is possible to use this library to add spatial search to your application without writing any special code. The library implements the public-domain C# H...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	540,103

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