Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2311.11369	Optimal Locally Private Nonparametric Classification with Public Data	In this work, we investigate the problem of public data assisted non-interactive Local Differentially Private (LDP) learning with a focus on non-parametric classification. Under the posterior drift assumption, we for the first time derive the mini-max optimal convergence rate with LDP constraint. Then, we present a nov...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	408,923
1706.06941	Concept Drift and Anomaly Detection in Graph Streams	Graph representations offer powerful and intuitive ways to describe data in a multitude of application domains. Here, we consider stochastic processes generating graphs and propose a methodology for detecting changes in stationarity of such processes. The methodology is general and considers a process generating attrib...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,766
2203.15127	An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services	Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions that lead to significant inefficiency in the long term, vehicles should ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	288,249
1911.04143	Time2Graph: Revisiting Time Series Modeling with Dynamic Shapelets	Time series modeling has attracted extensive research efforts; however, achieving both reliable efficiency and interpretability from a unified model still remains a challenging problem. Among the literature, shapelets offer interpretable and explanatory insights in the classification tasks, while most existing works ig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,906
1307.5368	Quantum enigma machines and the locking capacity of a quantum channel	The locking effect is a phenomenon which is unique to quantum information theory and represents one of the strongest separations between the classical and quantum theories of information. The Fawzi-Hayden-Sen (FHS) locking protocol harnesses this effect in a cryptographic context, whereby one party can encode n bits in...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,939
2010.05713	Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network	Image-to-Image (I2I) translation is a heated topic in academia, and it also has been applied in real-world industry for tasks like image synthesis, super-resolution, and colorization. However, traditional I2I translation methods train data in two or more domains together. This requires lots of computation resources. Mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	200,235
2501.14112	CoPERLex: Content Planning with Event-based Representations for Legal Case Summarization	Legal professionals often struggle with lengthy judgments and require efficient summarization for quick comprehension. To address this challenge, we investigate the need for structured planning in legal case summarization, particularly through event-centric representations that reflect the narrative nature of legal cas...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	526,981
1810.02252	Measuring Football Players' On-the-ball Contributions From Passes During Games	Several performance metrics for quantifying the in-game performances of individual football players have been proposed in recent years. Although the majority of the on-the-ball actions during games constitutes of passes, many of the currently available metrics focus on measuring the quality of shots only. To help bridg...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,556
2403.19319	Mesh2NeRF: Direct Mesh Supervision for Neural Radiance Field Representation and Generation	We present Mesh2NeRF, an approach to derive ground-truth radiance fields from textured meshes for 3D generation tasks. Many 3D generative approaches represent 3D scenes as radiance fields for training. Their ground-truth radiance fields are usually fitted from multi-view renderings from a large-scale synthetic 3D datas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,296
1611.05590	Convex Optimization of Distributed Cooperative Detection in Multi-Receiver Molecular Communication	In this paper, the error performance achieved by cooperative detection among K distributed receivers in a diffusion-based molecular communication (MC) system is analyzed and optimized. In this system, the receivers first make local hard decisions on the transmitted symbol and then report these decisions to a fusion cen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	64,044
2306.03521	Machine learning in and out of equilibrium	The algorithms used to train neural networks, like stochastic gradient descent (SGD), have close parallels to natural processes that navigate a high-dimensional parameter space -- for example protein folding or evolution. Our study uses a Fokker-Planck approach, adapted from statistical physics, to explore these parall...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,369
1505.07930	Salient Object Detection via Augmented Hypotheses	In this paper, we propose using \textit{augmented hypotheses} which consider objectness, foreground and compactness for salient object detection. Our algorithm consists of four basic steps. First, our method generates the objectness map via objectness hypotheses. Based on the objectness map, we estimate the foreground ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	43,585
2312.08914	CogAgent: A Visual Language Model for GUI Agents	People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e.g., computer or smartphone screens. Large language models (LLMs) such as ChatGPT can assist people in tasks like writing emails, but struggle to understand and interact with GUIs, thus limiting their potential ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	415,515
2307.08934	Multi-stage Neural Networks: Function Approximator of Machine Precision	Deep learning techniques are increasingly applied to scientific problems, where the precision of networks is crucial. Despite being deemed as universal function approximators, neural networks, in practice, struggle to reduce the prediction errors below $O(10^{-5})$ even with large network size and extended training ite...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	379,989
2210.10040	The Tail Wagging the Dog: Dataset Construction Biases of Social Bias Benchmarks	How reliably can we trust the scores obtained from social bias benchmarks as faithful indicators of problematic social biases in a given language model? In this work, we study this question by contrasting social biases with non-social biases stemming from choices made during dataset construction that might not even be ...	false	false	false	true	false	false	true	false	true	false	false	false	false	true	false	false	false	false	324,767
2002.08910	How Much Knowledge Can You Pack Into the Parameters of a Language Model?	It has recently been observed that neural language models trained on unstructured text can implicitly store and retrieve knowledge using natural language queries. In this short paper, we measure the practical utility of this approach by fine-tuning pre-trained models to answer questions without access to any external c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	164,899
2010.00417	Learning to be safe, in finite time	This paper aims to put forward the concept that learning to take safe actions in unknown environments, even with probability one guarantees, can be achieved without the need for an unbounded number of exploratory trials, provided that one is willing to relax its optimality requirements mildly. We focus on the canonical...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	198,286
1808.08124	Insect cyborgs: Bio-mimetic feature generators improve machine learning accuracy on limited data	Machine learning (ML) classifiers always benefit from more informative input features. We seek to auto-generate stronger feature sets in order to address the difficulty that ML methods often experience given limited training data. A wide range of biological neural nets (BNNs) excel at fast learning, implying that they ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	105,878
2311.17601	Continual Learning with Low Rank Adaptation	Recent work using pretrained transformers has shown impressive performance when fine-tuned with data from the downstream problem of interest. However, they struggle to retain that performance when the data characteristics changes. In this paper, we focus on continual learning, where a pre-trained transformer is updated...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	411,357
1810.07762	A Disease Diagnosis and Treatment Recommendation System Based on Big Data Mining and Cloud Computing	It is crucial to provide compatible treatment schemes for a disease according to various symptoms at different stages. However, most classification methods might be ineffective in accurately classifying a disease that holds the characteristics of multiple treatment stages, various symptoms, and multi-pathogenesis. More...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	110,687
2007.01152	Learning to Segment from Scribbles using Multi-scale Adversarial Attention Gates	Large, fine-grained image segmentation datasets, annotated at pixel-level, are difficult to obtain, particularly in medical imaging, where annotations also require expert knowledge. Weakly-supervised learning can train models by relying on weaker forms of annotation, such as scribbles. Here, we learn to segment using s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	185,340
1902.07938	Pretrained language model transfer on neural named entity recognition in Indonesian conversational texts	Named entity recognition (NER) is an important task in NLP, which is all the more challenging in conversational domain with their noisy facets. Moreover, conversational texts are often available in limited amount, making supervised tasks infeasible. To learn from small data, strong inductive biases are required. Previo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,096
1512.03225	Joint CSIT Acquisition Based on Low-Rank Matrix Completion for FDD Massive MIMO Systems	Channel state information at the transmitter (CSIT) is essential for frequency-division duplexing (FDD) massive MIMO systems, but conventional solutions involve overwhelming overhead both for downlink channel training and uplink channel feedback. In this letter, we propose a joint CSIT acquisition scheme to reduce the ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,015
2109.02053	GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated Learning	Federated Learning (FL) bridges the gap between collaborative machine learning and preserving data privacy. To sustain the long-term operation of an FL ecosystem, it is important to attract high quality data owners with appropriate incentive schemes. As an important building block of such incentive schemes, it is essen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	253,618
1902.09427	Fault Diagnosis Method Based on Scaling Law for On-line Refrigerant Leak Detection	Early fault detection using instrumented sensor data is one of the promising application areas of machine learning in industrial facilities. However, it is difficult to improve the generalization performance of the trained fault-detection model because of the complex system configuration in the target diagnostic system...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	122,409
2102.04033	A Hybrid Bandit Model with Visual Priors for Creative Ranking in Display Advertising	Creative plays a great important role in e-commerce for exhibiting products. Sellers usually create multiple creatives for comprehensive demonstrations, thus it is crucial to display the most appealing design to maximize the Click-Through Rate~(CTR). For this purpose, modern recommender systems dynamically rank creativ...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	218,969
2102.01479	Analyzing dynamical disorder for charge transport in organic semiconductors via machine learning	Organic semiconductors are indispensable for today's display technologies in form of organic light emitting diodes (OLEDs) and further optoelectronic applications. However, organic materials do not reach the same charge carrier mobility as inorganic semiconductors, limiting the efficiency of devices. To find or even de...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,126
1901.07261	Fast, Accurate and Lightweight Super-Resolution with Neural Architecture Search	Deep convolutional neural networks demonstrate impressive results in the super-resolution domain. A series of studies concentrate on improving peak signal noise ratio (PSNR) by using much deeper layers, which are not friendly to constrained resources. Pursuing a trade-off between the restoration capacity and the simpli...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	119,176
2101.00245	The Bayesian Method of Tensor Networks	Bayesian learning is a powerful learning framework which combines the external information of the data (background information) with the internal information (training data) in a logically consistent way in inference and prediction. By Bayes rule, the external information (prior distribution) and the internal informati...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	214,020
2006.13895	Modelling the Statistics of Cyclic Activities by Trajectory Analysis on the Manifold of Positive-Semi-Definite Matrices	In this paper, a model is presented to extract statistical summaries to characterize the repetition of a cyclic body action, for instance a gym exercise, for the purpose of checking the compliance of the observed action to a template one and highlighting the parts of the action that are not correctly executed (if any)....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	184,064
1912.10514	Tag-less Back-Translation	An effective method to generate a large number of parallel sentences for training improved neural machine translation (NMT) systems is the use of the back-translations of the target-side monolingual data. The standard back-translation method has been shown to be unable to efficiently utilize the available huge amount o...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	158,338
2407.09299	PID: Physics-Informed Diffusion Model for Infrared Image Generation	Infrared imaging technology has gained significant attention for its reliable sensing ability in low visibility conditions, prompting many studies to convert the abundant RGB images to infrared images. However, most existing image translation methods treat infrared images as a stylistic variation, neglecting the underl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,525
1907.08759	Latency Minimization for Multiuser Computation Offloading in Fog-Radio Access Networks	This paper considers computation offloading in fog-radio access networks (F-RAN), where multiple user equipments (UEs) offload their computation tasks to the F-RAN through a number of fog nodes. Each UE can choose one of the fog nodes to offload its task, and each fog node may serve multiple UEs. Depending on the compu...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	139,182
2409.16178	SDFit: 3D Object Pose and Shape by Fitting a Morphable SDF to a Single Image	We focus on recovering 3D object pose and shape from single images. This is highly challenging due to strong (self-)occlusions, depth ambiguities, the enormous shape variance, and lack of 3D ground truth for natural images. Recent work relies mostly on learning from finite datasets, so it struggles generalizing, while ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,234
2010.09803	Adversarial Training for Code Retrieval with Question-Description Relevance Regularization	Code retrieval is a key task aiming to match natural and programming languages. In this work, we propose adversarial learning for code retrieval, that is regularized by question-description relevance. First, we adapt a simple adversarial learning technique to generate difficult code snippets given the input question, w...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	true	201,664
1305.2686	Using Exclusive Web Crawlers to Store Better Results in Search Engines' Database	Crawler-based search engines are the mostly used search engines among web and Internet users, involve web crawling, storing in database, ranking, indexing and displaying to the user. But it is noteworthy that because of increasing changes in web sites search engines suffer high time and transfers costs which are consum...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	24,538
2112.12990	Deep Neuroevolution Squeezes More out of Small Neural Networks and Small Training Sets: Sample Application to MRI Brain Sequence Classification	Purpose: Deep Neuroevolution (DNE) holds the promise of providing radiology artificial intelligence (AI) that performs well with small neural networks and small training sets. We seek to realize this potential via a proof-of-principle application to MRI brain sequence classification. Methods: We analyzed a training s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	273,109
2405.14705	Learning Multi-dimensional Human Preference for Text-to-Image Generation	Current metrics for text-to-image models typically rely on statistical metrics which inadequately represent the real preference of humans. Although recent work attempts to learn these preferences via human annotated images, they reduce the rich tapestry of human preference to a single overall score. However, the prefer...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	456,551
2409.12401	MambaRecon: MRI Reconstruction with Structured State Space Models	Magnetic Resonance Imaging (MRI) is one of the most important medical imaging modalities as it provides superior resolution of soft tissues, albeit with a notable limitation in scanning speed. The advent of deep learning has catalyzed the development of cutting-edge methods for the expedited reconstruction of MRI scans...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	489,570
2303.07530	Towards Unsupervised Learning based Denoising of Cyber Physical System Data to Mitigate Security Concerns	A dataset, collected under an industrial setting, often contains a significant portion of noises. In many cases, using trivial filters is not enough to retrieve useful information i.e., accurate value without the noise. One such data is time-series sensor readings collected from moving vehicles containing fuel informat...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	351,279
2306.14518	Toward Fairness Through Fair Multi-Exit Framework for Dermatological Disease Diagnosis	Fairness has become increasingly pivotal in medical image recognition. However, without mitigating bias, deploying unfair medical AI systems could harm the interests of underprivileged populations. In this paper, we observe that while features extracted from the deeper layers of neural networks generally offer higher a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,713
1402.0119	Randomized Nonlinear Component Analysis	Classical methods such as Principal Component Analysis (PCA) and Canonical Correlation Analysis (CCA) are ubiquitous in statistics. However, these techniques are only able to reveal linear relationships in data. Although nonlinear variants of PCA and CCA have been proposed, these are computationally prohibitive in the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	30,535
2203.05413	A Self-Tuning Impedance-based Interaction Planner for Robotic Haptic Exploration	This paper presents a novel interaction planning method that exploits impedance tuning techniques in response to environmental uncertainties and unpredictable conditions using haptic information only. The proposed algorithm plans the robot's trajectory based on the haptic interaction with the environment and adapts pla...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	284,806
2203.16973	Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition	Self-supervised learning (SSL) to learn high-level speech representations has been a popular approach to building Automatic Speech Recognition (ASR) systems in low-resource settings. However, the common assumption made in literature is that a considerable amount of unlabeled data is available for the same domain or lan...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	288,998
1906.04210	Network-based Fake News Detection: A Pattern-driven Approach	Fake news gains has gained significant momentum, strongly motivating the need for fake news research. Many fake news detection approaches have thus been proposed, where most of them heavily rely on news content. However, network-based clues revealed when analyzing news propagation on social networks is an information t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	134,633
2206.02234	Two Decades of Bengali Handwritten Digit Recognition: A Survey	Handwritten Digit Recognition (HDR) is one of the most challenging tasks in the domain of Optical Character Recognition (OCR). Irrespective of language, there are some inherent challenges of HDR, which mostly arise due to the variations in writing styles across individuals, writing medium and environment, inability to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	300,804
1110.3347	Dynamic Batch Bayesian Optimization	Bayesian optimization (BO) algorithms try to optimize an unknown function that is expensive to evaluate using minimum number of evaluations/experiments. Most of the proposed algorithms in BO are sequential, where only one experiment is selected at each iteration. This method can be time inefficient when each experiment...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	12,666
1904.13164	Learning Restricted Regular Expressions with Interleaving	The advantages for the presence of an XML schema for XML documents are numerous. However, many XML documents in practice are not accompanied by a schema or by a valid schema. Relax NG is a popular and powerful schema language, which supports the unconstrained interleaving operator. Focusing on the inference of Relax NG...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	129,312
1201.6043	The maximum number of minimal codewords in long codes	Upper bounds on the maximum number of minimal codewords in a binary code follow from the theory of matroids. Random coding provide lower bounds. In this paper we compare these bounds with analogous bounds for the cycle code of graphs. This problem (in the graphic case) was considered in 1981 by Entringer and Slater who...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,986
2206.04490	Redundancy in Deep Linear Neural Networks	Conventional wisdom states that deep linear neural networks benefit from expressiveness and optimization advantages over a single linear layer. This paper suggests that, in practice, the training process of deep linear fully-connected networks using conventional optimizers is convex in the same manner as a single linea...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	301,648
2408.07869	A Systematic Evaluation of Generated Time Series and Their Effects in Self-Supervised Pretraining	Self-supervised Pretrained Models (PTMs) have demonstrated remarkable performance in computer vision and natural language processing tasks. These successes have prompted researchers to design PTMs for time series data. In our experiments, most self-supervised time series PTMs were surpassed by simple supervised models....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	480,754
1906.10009	Development Framework for Longitudinal Automated Driving Functions with Off-board Information Integration	Increasingly sophisticated function development is taking place with the aim of developing efficient, safe and increasingly Automated Driving Functions. This development is possible with the use of diverse data from sources such as Navigation Systems, eHorizon, on-board sensor data, Vehicle-to-Infrastructure (V2I) and ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	136,330
1906.01599	Motivo: fast motif counting via succinct color coding and adaptive sampling	The randomized technique of color coding is behind state-of-the-art algorithms for estimating graph motif counts. Those algorithms, however, are not yet capable of scaling well to very large graphs with billions of edges. In this paper we develop novel tools for the `motif counting via color coding' framework. As a res...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	133,767
2405.13094	KPG: Key Propagation Graph Generator for Rumor Detection based on Reinforcement Learning	The proliferation of rumors on social media platforms during significant events, such as the US elections and the COVID-19 pandemic, has a profound impact on social stability and public health. Existing approaches for rumor detection primarily rely on propagation graphs to enhance model effectiveness. However, the pres...	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	false	false	455,808
1901.11013	Top performing stocks recommendation strategy for portfolio	Stock return forecasting is of utmost importance in the business world. This has been the favourite topic of research for many academicians since decades. Recently, regularization techniques have reported to tremendously increase the forecast accuracy of the simple regression model. Still, this model cannot incorporate...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	120,151
2111.01947	An Evaluation of WebAssembly and eBPF as Offloading Mechanisms in the Context of Computational Storage	As the volume of data that needs to be processed continues to increase, we also see renewed interests in near-data processing in the form of computational storage, with eBPF (extended Berkeley Packet Filter) being proposed as a vehicle for computation offloading. However, discussions in this regard have so far ignored ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	264,712
2206.07869	Let Invariant Rationale Discovery Inspire Graph Contrastive Learning	Leading graph contrastive learning (GCL) methods perform graph augmentations in two fashions: (1) randomly corrupting the anchor graph, which could cause the loss of semantic information, or (2) using domain knowledge to maintain salient features, which undermines the generalization to other domains. Taking an invarian...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	302,918
1511.05065	Proposal Flow	Finding image correspondences remains a challenging problem in the presence of intra-class variations and large changes in scene layout.~Semantic flow methods are designed to handle images depicting different instances of the same object or scene category. We introduce a novel approach to semantic flow, dubbed proposal...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	48,984
2307.00165	Counterfactual Collaborative Reasoning	Causal reasoning and logical reasoning are two important types of reasoning abilities for human intelligence. However, their relationship has not been extensively explored under machine intelligence context. In this paper, we explore how the two reasoning abilities can be jointly modeled to enhance both accuracy and ex...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	376,896
2105.11069	InfoFair: Information-Theoretic Intersectional Fairness	Algorithmic fairness is becoming increasingly important in data mining and machine learning. Among others, a foundational notation is group fairness. The vast majority of the existing works on group fairness, with a few exceptions, primarily focus on debiasing with respect to a single sensitive attribute, despite the f...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	236,584
2412.09649	Pole-based Vehicle Localization with Vector Maps: A Camera-LiDAR Comparative Study	For autonomous navigation, accurate localization with respect to a map is needed. In urban environments, infrastructure such as buildings or bridges cause major difficulties to Global Navigation Satellite Systems (GNSS) and, despite advances in inertial navigation, it is necessary to support them with other sources of ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	516,588
2402.15864	Field-based Molecule Generation	This work introduces FMG, a field-based model for drug-like molecule generation. We show how the flexibility of this method provides crucial advantages over the prevalent, point-cloud based methods, and achieves competitive molecular stability generation. We tackle optical isomerism (enantiomers), a previously omitted ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	432,315
2201.01709	The Effect of Model Compression on Fairness in Facial Expression Recognition	Deep neural networks have proved hugely successful, achieving human-like performance on a variety of tasks. However, they are also computationally expensive, which has motivated the development of model compression techniques which reduce the resource consumption associated with deep learning models. Nevertheless, rece...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	274,329
2303.01391	The Ladder in Chaos: A Simple and Effective Improvement to General DRL Algorithms by Policy Path Trimming and Boosting	Knowing the learning dynamics of policy is significant to unveiling the mysteries of Reinforcement Learning (RL). It is especially crucial yet challenging to Deep RL, from which the remedies to notorious issues like sample inefficiency and learning instability could be obtained. In this paper, we study how the policy n...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	348,951
2502.09674	The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Safety Analysis	Large Language Models' safety-aligned behaviors, such as refusing harmful queries, can be represented by linear directions in activation space. Previous research modeled safety behavior with a single direction, limiting mechanistic understanding to an isolated safety feature. In this work, we discover that safety-align...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	533,556
2406.16801	RES-Q: Evaluating Code-Editing Large Language Model Systems at the Repository Scale	The instruction-following ability of Large Language Models (LLMs) has cultivated a class of LLM-based systems capable of approaching complex tasks such as making edits to large code repositories. Due to the high sensitivity and unpredictability of LLM behavior in response to changes in prompting, robust evaluation tool...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	467,281
1304.7971	Adaptive Mode Selection and Power Allocation in Bidirectional Buffer-aided Relay Networks	In this paper, we consider the problem of sum rate maximization in a bidirectional relay network with fading. Hereby, user 1 and user 2 communicate with each other only through a relay, i.e., a direct link between user 1 and user 2 is not present. In this network, there exist six possible transmission modes: four point...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	24,300
1303.6120	Reliability and efficiency of generalized rumor spreading model on complex social networks	We introduce the generalized rumor spreading model and investigate some properties of this model on different complex social networks. Despite pervious rumor models that both the spreader-spreader ($SS$) and the spreader-stifler ($SR$) interactions have the same rate $\alpha$, we define $\alpha^{(1)}$ and $\alpha^{(2)}...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	23,247
2102.09761	Scaling Creative Inspiration with Fine-Grained Functional Aspects of Ideas	Large repositories of products, patents and scientific papers offer an opportunity for building systems that scour millions of ideas and help users discover inspirations. However, idea descriptions are typically in the form of unstructured text, lacking key structure that is required for supporting creative innovation ...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	220,884
2110.13389	A Normalized Gaussian Wasserstein Distance for Tiny Object Detection	Detecting tiny objects is a very challenging problem since a tiny object only contains a few pixels in size. We demonstrate that state-of-the-art detectors do not produce satisfactory results on tiny objects due to the lack of appearance information. Our key observation is that Intersection over Union (IoU) based metri...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	263,160
2303.13064	Unmanned Surface Vehicle: Yaw Modeling and Identification	In this article, a simplified modeling and system identification procedure for yaw motion of an unmanned surface vehicle (USV) is presented. Two thrusters that allow for both speed and direction control propel the USV. The outputs of the vehicle under inquiry include parameters that define the mobility of the USV in ho...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	353,531
2409.08379	The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot	Generative AI (GenAI) has been shown to enhance individual productivity in a guided setting. While it is also likely to transform processes in a collaborative work setting, it is unclear what trajectory this transformation will follow. Collaborative environment is characterized by a blend of origination tasks that invo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	487,879
2502.14416	Reliable Explainability of Deep Learning Spatial-Spectral Classifiers for Improved Semantic Segmentation in Autonomous Driving	Integrating hyperspectral imagery (HSI) with deep neural networks (DNNs) can strengthen the accuracy of intelligent vision systems by combining spectral and spatial information, which is useful for tasks like semantic segmentation in autonomous driving. To advance research in such safety-critical systems, determining t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	535,822
2103.03082	An Optimization Approach for a Robust and Flexible Control in Collaborative Applications	In Human-Robot Collaboration, the robot operates in a highly dynamic environment. Thus, it is pivotal to guarantee the robust stability of the system during the interaction but also a high flexibility of the robot behavior in order to ensure safety and reactivity to the variable conditions of the collaborative scenario...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	223,165
2009.09993	A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components	Although machine learning approaches have been widely used in the field of finance, to very successful degrees, these approaches remain bespoke to specific investigations and opaque in terms of explainability, comparability, and reproducibility. The primary objective of this research was to shed light upon this field b...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,769
2010.11506	Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data	Fine-tuned pre-trained language models can suffer from severe miscalibration for both in-distribution and out-of-distribution (OOD) data due to over-parameterization. To mitigate this issue, we propose a regularized fine-tuning method. Our method introduces two types of regularization for better calibration: (1) On-man...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	202,283
2403.12010	VideoMV: Consistent Multi-View Generation Based on Large Video Generative Model	Generating multi-view images based on text or single-image prompts is a critical capability for the creation of 3D content. Two fundamental questions on this topic are what data we use for training and how to ensure multi-view consistency. This paper introduces a novel framework that makes fundamental contributions to ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	438,974
2112.08557	Protograph Bit-Interleaved Coded Modulation: A Bandwidth-Efficient Design Paradigm for 6G Wireless Communications	Bit-interleaved coded modulation (BICM) has attracted considerable attention from the research community in the past three decades, because it can achieve desirable error performance with relatively low implementation complexity for a large number of communication and storage systems. By exploiting the iterative demapp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	271,836
2004.04278	Estimating Grape Yield on the Vine from Multiple Images	Estimating grape yield prior to harvest is important to commercial vineyard production as it informs many vineyard and winery decisions. Currently, the process of yield estimation is time consuming and varies in its accuracy from 75-90\% depending on the experience of the viticulturist. This paper proposes a multiple t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	171,829
2208.13778	Rosenblatt's first theorem and frugality of deep learning	First Rosenblatt's theorem about omnipotence of shallow networks states that elementary perceptrons can solve any classification problem if there are no discrepancies in the training set. Minsky and Papert considered elementary perceptrons with restrictions on the neural inputs: a bounded number of connections or a rel...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	315,139
2301.08109	Predicting the Channel Access of Bluetooth Low Energy	Bluetooth Low Energy (BLE) is one of the key enablers for low-power and low-cost applications in consumer electronics and the Internet of Things. The latest features such as audio and direction finding will introduce more and more devices that rely on BLE for communication. However, like many other wireless standards, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	341,097
2011.12750	AI virtues -- The missing link in putting AI ethics into practice	Several seminal ethics initiatives have stipulated sets of principles and standards for good technology development in the AI sector. However, widespread criticism has pointed out a lack of practical realization of these principles. Following that, AI ethics underwent a practical turn, but without deviating from the pr...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	208,261
2406.00275	StyDeSty: Min-Max Stylization and Destylization for Single Domain Generalization	Single domain generalization (single DG) aims at learning a robust model generalizable to unseen domains from only one training domain, making it a highly ambitious and challenging task. State-of-the-art approaches have mostly relied on data augmentations, such as adversarial perturbation and style enhancement, to synt...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	459,773
2406.01480	Towards Automating the Retrospective Generation of BIM Models: A Unified Framework for 3D Semantic Reconstruction of the Built Environment	The adoption of Building Information Modeling (BIM) is beneficial in construction projects. However, it faces challenges due to the lack of a unified and scalable framework for converting 3D model details into BIM. This paper introduces SRBIM, a unified semantic reconstruction architecture for BIM generation. Our appro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	460,337
1809.00233	Sleep Stage Classification: Scalability Evaluations of Distributed Approaches	Processing and analyzing of massive clinical data are resource intensive and time consuming with traditional analytic tools. Electroencephalogram (EEG) is one of the major technologies in detecting and diagnosing various brain disorders, and produces huge volume big data to process. In this study, we propose a big data...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	106,530
2109.10086	SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval	In neural Information Retrieval (IR), ongoing research is directed towards improving the first retriever in ranking pipelines. Learning dense embeddings to conduct retrieval using efficient approximate nearest neighbors methods has proven to work well. Meanwhile, there has been a growing interest in learning \emph{spar...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	256,508
2108.10748	Federated Learning for UAV Swarms Under Class Imbalance and Power Consumption Constraints	The usage of unmanned aerial vehicles (UAVs) in civil and military applications continues to increase due to the numerous advantages that they provide over conventional approaches. Despite the abundance of such advantages, it is imperative to investigate the performance of UAV utilization while considering their design...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	251,995
1702.03510	On the capacity of bandlimited optical intensity channels with Gaussian noise	We determine lower and upper bounds on the capacity of bandlimited optical intensity channels (BLOIC) with white Gaussian noise. Three types of input power constraints are considered: 1) only an average power constraint, 2) only a peak power constraint, and 3) an average and a peak power constraint. Capacity lower boun...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,148
2312.12806	MedBench: A Large-Scale Chinese Benchmark for Evaluating Medical Large Language Models	The emergence of various medical large language models (LLMs) in the medical domain has highlighted the need for unified evaluation standards, as manual evaluation of LLMs proves to be time-consuming and labor-intensive. To address this issue, we introduce MedBench, a comprehensive benchmark for the Chinese medical dom...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	417,113
2011.02809	Semi-supervised Learning for Singing Synthesis Timbre	We propose a semi-supervised singing synthesizer, which is able to learn new voices from audio data only, without any annotations such as phonetic segmentation. Our system is an encoder-decoder model with two encoders, linguistic and acoustic, and one (acoustic) decoder. In a first step, the system is trained in a supe...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,041
2106.04195	Learning by Distillation: A Self-Supervised Learning Framework for Optical Flow Estimation	We present DistillFlow, a knowledge distillation approach to learning optical flow. DistillFlow trains multiple teacher models and a student model, where challenging transformations are applied to the input of the student model to generate hallucinated occlusions as well as less confident predictions. Then, a self-supe...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	239,629
2106.04988	Optimal Inspection of Network Systems via Value of Information Analysis	This paper develops computable metrics to assign priorities for information collection on network systems made up by binary components. Components are worth inspecting because their condition state is uncertain and the system functioning depends on it. The Value of Information (VoI) allows assessing the impact of infor...	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	239,931
2112.05742	A Puzzle-Based Dataset for Natural Language Inference	We provide here a dataset for tasks related to natural language understanding and natural language inference. The dataset contains logical puzzles in natural language from three domains: comparing puzzles, knighs and knaves, and zebra puzzles. Each puzzle is associated with the entire set of atomic questions that can b...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	270,936
2303.02707	Industry Risk Assessment via Hierarchical Financial Data Using Stock Market Sentiment Indicators	Risk assessment across industries is paramount for ensuring a robust and sustainable economy. While previous studies have relied heavily on official statistics for their accuracy, they often lag behind real-time developments. Addressing this gap, our research endeavors to integrate market microstructure theory with AI ...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	349,457
2407.11033	Hadamard Adapter: An Extreme Parameter-Efficient Adapter Tuning Method for Pre-trained Language Models	Recent years, Pre-trained Language models (PLMs) have swept into various fields of artificial intelligence and achieved great success. However, most PLMs, such as T5 and GPT3, have a huge amount of parameters, fine-tuning them is often expensive and time consuming, and storing them takes up a lot of space. Therefore, i...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	473,254
2109.11086	Scenario Aware Speech Recognition: Advancements for Apollo Fearless Steps & CHiME-4 Corpora	In this study, we propose to investigate triplet loss for the purpose of an alternative feature representation for ASR. We consider a general non-semantic speech representation, which is trained with a self-supervised criteria based on triplet loss called TRILL, for acoustic modeling to represent the acoustic character...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	256,840
2409.12213	SemAI: Semantic Artificial Intelligence-enhanced DNA storage for Internet-of-Things	In the wake of the swift evolution of technologies such as the Internet of Things (IoT), the global data landscape undergoes an exponential surge, propelling DNA storage into the spotlight as a prospective medium for contemporary cloud storage applications. This paper introduces a Semantic Artificial Intelligence-enhan...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	489,492
2501.16997	MAUCell: An Adaptive Multi-Attention Framework for Video Frame Prediction	Temporal sequence modeling stands as the fundamental foundation for video prediction systems and real-time forecasting operations as well as anomaly detection applications. The achievement of accurate predictions through efficient resource consumption remains an ongoing issue in contemporary temporal sequence modeling....	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	528,178
2211.10188	Piecewise Affine Curvature model: a reduced-order model for soft robot-environment interaction beyond PCC	Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and manipulation capabilities and safe human-robot interactions. Howe...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	331,236
2112.14448	A transfer learning enhanced the physics-informed neural network model for vortex-induced vibration	Vortex-induced vibration (VIV) is a typical nonlinear fluid-structure interaction phenomenon, which widely exists in practical engineering (the flexible riser, the bridge and the aircraft wing, etc). The conventional finite element model (FEM)-based and data-driven approaches for VIV analysis often suffer from the chal...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,538

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