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
2109.09607	Description of Corner Cases in Automated Driving: Goals and Challenges	Scaling the distribution of automated vehicles requires handling various unexpected and possibly dangerous situations, termed corner cases (CC). Since many modules of automated driving systems are based on machine learning (ML), CC are an essential part of the data for their development. However, there is only a limite...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	256,337
2310.17415	PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications	Large protein language models are adept at capturing the underlying evolutionary information in primary structures, offering significant practical value for protein engineering. Compared to natural language models, protein amino acid sequences have a smaller data volume and a limited combinatorial space. Choosing an ap...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	403,127
1807.05320	Analysis of social media content and search behavior related to seasonal topics using the sociophysics approach	We studied the time interval between posting social media content and search action related to seasonal topics. The analysis was performed using a mathematical model of the search behavior as in the theory of sociophysics. As seasonal topics, the word cherry blossom was considered for spring, bikini for summer, autumn ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	102,902
2306.16205	Towards a Better Understanding of Learning with Multiagent Teams	While it has long been recognized that a team of individual learning agents can be greater than the sum of its parts, recent work has shown that larger teams are not necessarily more effective than smaller ones. In this paper, we study why and under which conditions certain team structures promote effective learning fo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	376,312
1903.10083	A Higher-Order Kolmogorov-Smirnov Test	We present an extension of the Kolmogorov-Smirnov (KS) two-sample test, which can be more sensitive to differences in the tails. Our test statistic is an integral probability metric (IPM) defined over a higher-order total variation ball, recovering the original KS test as its simplest case. We give an exact representer...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	125,197
2207.09960	Measuring and signing fairness as performance under multiple stakeholder distributions	As learning machines increase their influence on decisions concerning human lives, analyzing their fairness properties becomes a subject of central importance. Yet, our best tools for measuring the fairness of learning systems are rigid fairness metrics encapsulated as mathematical one-liners, offer limited power to th...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	309,089
2308.06186	Software Doping Analysis for Human Oversight	This article introduces a framework that is meant to assist in mitigating societal risks that software can pose. Concretely, this encompasses facets of software doping as well as unfairness and discrimination in high-risk decision-making systems. The term software doping refers to software that contains surreptitiously...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	385,055
2406.14098	HeartBeat: Towards Controllable Echocardiography Video Synthesis with Multimodal Conditions-Guided Diffusion Models	Echocardiography (ECHO) video is widely used for cardiac examination. In clinical, this procedure heavily relies on operator experience, which needs years of training and maybe the assistance of deep learning-based systems for enhanced accuracy and efficiency. However, it is challenging since acquiring sufficient custo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	466,156
2008.06872	SMPLpix: Neural Avatars from 3D Human Models	Recent advances in deep generative models have led to an unprecedented level of realism for synthetically generated images of humans. However, one of the remaining fundamental limitations of these models is the ability to flexibly control the generative process, e.g.~change the camera and human pose while retaining the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,920
2011.11138	MAC for Machine Type Communications in Industrial IoT -- Part I: Protocol Design and Analysis	In this two-part paper, we propose a novel medium access control (MAC) protocol for machine-type communications in the industrial internet of things. The considered use case features a limited geographical area and a massive number of devices with sporadic data traffic and different priority types. We target at support...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	207,732
2306.01058	Are Layout-Infused Language Models Robust to Layout Distribution Shifts? A Case Study with Scientific Documents	Recent work has shown that infusing layout features into language models (LMs) improves processing of visually-rich documents such as scientific papers. Layout-infused LMs are often evaluated on documents with familiar layout features (e.g., papers from the same publisher), but in practice models encounter documents wi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,276
2202.11684	MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset	Misinformation is becoming increasingly prevalent on social media and in news articles. It has become so widespread that we require algorithmic assistance utilising machine learning to detect such content. Training these machine learning models require datasets of sufficient scale, diversity and quality. However, datas...	false	false	false	true	false	true	true	false	true	false	false	false	false	true	false	false	false	false	281,955
2006.13477	Road Network Metric Learning for Estimated Time of Arrival	Recently, deep learning have achieved promising results in Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the origin to the destination along a given path. One of the key techniques is to use embedding vectors to represent the elements of road network, such as the links (road se...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,927
1804.07881	Event Extraction with Generative Adversarial Imitation Learning	We propose a new method for event extraction (EE) task based on an imitation learning framework, specifically, inverse reinforcement learning (IRL) via generative adversarial network (GAN). The GAN estimates proper rewards according to the difference between the actions committed by the expert (or ground truth) and the...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	95,626
2302.11191	On the Emulation of Synchronous Machine Dynamics by Converter-Interfaced Generators	This paper discusses the conditions that a device needs to satisfy to replicate the behavior of a conventional synchronous machine (SM) connected to a power network. The conditions pertain to the device's stored energy, time scale of response, oscillation damping, and behavior during short-circuits. Relevant remarks fo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	347,120
2305.01920	Generative Meta-Learning for Zero-Shot Relation Triplet Extraction	The zero-shot relation triplet extraction (ZeroRTE) task aims to extract relation triplets from a piece of text with unseen relation types. The seminal work adopts the pre-trained generative model to generate synthetic samples for new relations. However, current generative models lack the optimization process of model ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	361,848
1809.06065	Focal Loss in 3D Object Detection	3D object detection is still an open problem in autonomous driving scenes. When recognizing and localizing key objects from sparse 3D inputs, autonomous vehicles suffer from a larger continuous searching space and higher fore-background imbalance compared to image-based object detection. In this paper, we aim to solve ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	107,956
1707.04477	Community Aliveness: Discovering Interaction Decay Patterns in Online Social Communities	Online Social Communities (OSCs) provide a medium for connecting people, sharing news, eliciting information, and finding jobs, among others. The dynamics of the interaction among the members of OSCs is not always growth dynamics. Instead, a $\textit{decay}$ or $\textit{inactivity}$ dynamics often happens, which makes ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	77,044
2102.07444	FAT: Learning Low-Bitwidth Parametric Representation via Frequency-Aware Transformation	Learning convolutional neural networks (CNNs) with low bitwidth is challenging because performance may drop significantly after quantization. Prior arts often discretize the network weights by carefully tuning hyper-parameters of quantization (e.g. non-uniform stepsize and layer-wise bitwidths), which are complicated a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	220,110
2305.00833	Learning to Reason and Memorize with Self-Notes	Large language models have been shown to struggle with multi-step reasoning, and do not retain previous reasoning steps for future use. We propose a simple method for solving both of these problems by allowing the model to take Self-Notes. Unlike recent chain-of-thought or scratchpad approaches, the model can deviate f...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	361,465
2312.07439	BIRB: A Generalization Benchmark for Information Retrieval in Bioacoustics	The ability for a machine learning model to cope with differences in training and deployment conditions--e.g. in the presence of distribution shift or the generalization to new classes altogether--is crucial for real-world use cases. However, most empirical work in this area has focused on the image domain with artific...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	414,926
2208.00880	Physics-informed Machine Learning of Parameterized Fundamental Diagrams	Fundamental diagrams describe the relationship between speed, flow, and density for some roadway (or set of roadway) configuration(s). These diagrams typically do not reflect, however, information on how speed-flow relationships change as a function of exogenous variables such as curb configuration, weather or other ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	311,005
2308.05732	PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers	Time-dependent partial differential equations (PDEs) are ubiquitous in science and engineering. Recently, mostly due to the high computational cost of traditional solution techniques, deep neural network based surrogates have gained increased interest. The practical utility of such neural PDE solvers relies on their ab...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	384,886
2412.13881	Understanding and Analyzing Model Robustness and Knowledge-Transfer in Multilingual Neural Machine Translation using TX-Ray	Neural networks have demonstrated significant advancements in Neural Machine Translation (NMT) compared to conventional phrase-based approaches. However, Multilingual Neural Machine Translation (MNMT) in extremely low-resource settings remains underexplored. This research investigates how knowledge transfer across lang...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	518,492
2201.01439	Construction of extremal Type II $\mathbb{Z}_{2k}$-codes	We give methods for constructing many self-dual $\mathbb{Z}_m$-codes and Type II $\mathbb{Z}_{2k}$-codes of length $2n$ starting from a given self-dual $\mathbb{Z}_m$-code and Type II $\mathbb{Z}_{2k}$-code of length $2n$, respectively. As an application, we construct extremal Type II $\mathbb{Z}_{2k}$-codes of length ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	274,254
2305.03507	Read it Twice: Towards Faithfully Interpretable Fact Verification by Revisiting Evidence	Real-world fact verification task aims to verify the factuality of a claim by retrieving evidence from the source document. The quality of the retrieved evidence plays an important role in claim verification. Ideally, the retrieved evidence should be faithful (reflecting the model's decision-making process in claim ver...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	362,418
2407.16126	MxT: Mamba x Transformer for Image Inpainting	Image inpainting, or image completion, is a crucial task in computer vision that aims to restore missing or damaged regions of images with semantically coherent content. This technique requires a precise balance of local texture replication and global contextual understanding to ensure the restored image integrates sea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	475,462
2211.09722	Federated Multilingual Models for Medical Transcript Analysis	Federated Learning (FL) is a novel machine learning approach that allows the model trainer to access more data samples, by training the model across multiple decentralized data sources, while data access constraints are in place. Such trained models can achieve significantly higher performance beyond what can be done w...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	331,070
1811.11788	Formulating Camera-Adaptive Color Constancy as a Few-shot Meta-Learning Problem	Digital camera pipelines employ color constancy methods to estimate an unknown scene illuminant, in order to re-illuminate images as if they were acquired under an achromatic light source. Fully-supervised learning approaches exhibit state-of-the-art estimation accuracy with camera-specific labelled training imagery. R...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	114,848
1910.05262	Hear "No Evil", See "Kenansville": Efficient and Transferable Black-Box Attacks on Speech Recognition and Voice Identification Systems	Automatic speech recognition and voice identification systems are being deployed in a wide array of applications, from providing control mechanisms to devices lacking traditional interfaces, to the automatic transcription of conversations and authentication of users. Many of these applications have significant security...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	149,003
2502.08143	Data-dependent Bounds with $T$-Optimal Best-of-Both-Worlds Guarantees in Multi-Armed Bandits using Stability-Penalty Matching	Existing data-dependent and best-of-both-worlds regret bounds for multi-armed bandits problems have limited adaptivity as they are either data-dependent but not best-of-both-worlds (BOBW), BOBW but not data-dependent or have sub-optimal $O(\sqrt{T\ln{T}})$ worst-case guarantee in the adversarial regime. To overcome the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	532,909
2409.13869	Generative AI Carries Non-Democratic Biases and Stereotypes: Representation of Women, Black Individuals, Age Groups, and People with Disability in AI-Generated Images across Occupations	AI governance and ethics in AI development have become critical concerns, prompting active discussions among tech companies, governments, and researchers about the potential risks AI poses to our democracies. This short essay aims to highlight one such risk: how generative AI includes or excludes equity-deserving group...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	490,205
2411.12503	ManiSkill-ViTac 2025: Challenge on Manipulation Skill Learning With Vision and Tactile Sensing	This article introduces the ManiSkill-ViTac Challenge 2025, which focuses on learning contact-rich manipulation skills using both tactile and visual sensing. Expanding upon the 2024 challenge, ManiSkill-ViTac 2025 includes 3 independent tracks: tactile manipulation, tactile-vision fusion manipulation, and tactile senso...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	509,432
1409.6382	On the Category of Group Codes	For the category of group codes, that generalizes the category of linear codes over a finite field, and with the generalized notions of direct sums and ndecomposable group codes, we prove that every MDS non trivial code, every perfect non trivial code, and every constant weight nondegenerate group code are indecomposab...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,245
2311.13350	Fact-based Court Judgment Prediction	This extended abstract extends the research presented in "ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation" \cite{malik-etal-2021-ildc}, focusing on fact-based judgment prediction within the context of Indian legal documents. We introduce two distinct problem variations: one ba...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	409,713
1610.05507	Analysis and Implementation of an Asynchronous Optimization Algorithm for the Parameter Server	This paper presents an asynchronous incremental aggregated gradient algorithm and its implementation in a parameter server framework for solving regularized optimization problems. The algorithm can handle both general convex (possibly non-smooth) regularizers and general convex constraints. When the empirical data loss...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	62,523
1310.5684	Linear tree codes and the problem of explicit constructions	We reduce the problem of constructing asymptotically good tree codes to the construction of triangular totally nonsingular matrices over fields with polynomially many elements. We show a connection of this problem to Birkhoff interpolation in finite fields.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	27,916
2501.14917	Self-reflecting Large Language Models: A Hegelian Dialectical Approach	Investigating NLP through a philosophical lens has recently caught researcher's eyes as it connects computational methods with classical schools of philosophy. This paper introduces a philosophical approach inspired by the Hegelian Dialectic for LLMs' self-reflection, utilizing a self-dialectical approach to emulate in...	true	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	527,317
2202.13251	Supervising Remote Sensing Change Detection Models with 3D Surface Semantics	Remote sensing change detection, identifying changes between scenes of the same location, is an active area of research with a broad range of applications. Recent advances in multimodal self-supervised pretraining have resulted in state-of-the-art methods which surpass vision models trained solely on optical imagery. I...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	282,539
2206.08855	Intelligent Trading System: Multidimensional financial time series clustering	Multidimensional time series clustering is an important problem in time series data analysis. This paper provides a new research idea for the behavioral analysis of financial markets, using the intrinsic correlation existing between transactions in the same segment of the financial market to cluster and analyze multidi...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	303,323
2210.01253	PLOT: Prompt Learning with Optimal Transport for Vision-Language Models	With the increasing attention to large vision-language models such as CLIP, there has been a significant amount of effort dedicated to building efficient prompts. Unlike conventional methods of only learning one single prompt, we propose to learn multiple comprehensive prompts to describe diverse characteristics of cat...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	321,182
2211.17030	A data set providing synthetic and real-world fisheye video sequences	In video surveillance as well as automotive applications, so-called fisheye cameras are often employed to capture a very wide angle of view. As such cameras depend on projections quite different from the classical perspective projection, the resulting fisheye image and video data correspondingly exhibits non-rectilinea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	333,834
2203.01362	Simplified Stability Assessment of Power Systems with Variable-Delay Wide-Area Damping Control	Power electronic devices such as HVDC and FACTS can be used to improve the damping of poorly damped inter-area modes in large power systems. This involves the use of wide-area feedback signals, which are transmitted via communication networks. The performance of the closed-loop system is strongly influenced by the dela...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,346
2402.16700	Generating Effective Ensembles for Sentiment Analysis	In recent years, transformer models have revolutionized Natural Language Processing (NLP), achieving exceptional results across various tasks, including Sentiment Analysis (SA). As such, current state-of-the-art approaches for SA predominantly rely on transformer models alone, achieving impressive accuracy levels on be...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	432,661
2304.03398	Quantum Conformal Prediction for Reliable Uncertainty Quantification in Quantum Machine Learning	In this work, we aim at augmenting the decisions output by quantum models with "error bars" that provide finite-sample coverage guarantees. Quantum models implement implicit probabilistic predictors that produce multiple random decisions for each input through measurement shots. Randomness arises not only from the inhe...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	356,791
2211.01847	Seeing the Unseen: Errors and Bias in Visual Datasets	From face recognition in smartphones to automatic routing on self-driving cars, machine vision algorithms lie in the core of these features. These systems solve image based tasks by identifying and understanding objects, subsequently making decisions from these information. However, errors in datasets are usually induc...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	328,384
2102.12668	Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach	This paper presents Learning-based Autonomous Guidance with RObustness and Stability guarantees (LAG-ROS), which provides machine learning-based nonlinear motion planners with formal robustness and stability guarantees, by designing a differential Lyapunov function using contraction theory. LAG-ROS utilizes a neural ne...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	false	false	false	false	221,807
1911.11195	A Novel Unsupervised Post-Processing Calibration Method for DNNS with Robustness to Domain Shift	The uncertainty estimation is critical in real-world decision making applications, especially when distributional shift between the training and test data are prevalent. Many calibration methods in the literature have been proposed to improve the predictive uncertainty of DNNs which are generally not well-calibrated. H...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,044
2210.09866	Towards Efficient and Effective Self-Supervised Learning of Visual Representations	Self-supervision has emerged as a propitious method for visual representation learning after the recent paradigm shift from handcrafted pretext tasks to instance-similarity based approaches. Most state-of-the-art methods enforce similarity between various augmentations of a given image, while some methods additionally ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	324,696
2312.12251	Fairness and Consensus in an Asynchronous Opinion Model for Social Networks (Technical Report)	We introduce a DeGroot-based model for opinion dynamics in social networks. A community of agents is represented as a weighted directed graph whose edges indicate how much agents influence one another. The model is formalized using labeled transition systems, henceforth called opinion transition systems (OTS), whose st...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	416,892
1403.2124	Generating Music from Literature	We present a system, TransProse, that automatically generates musical pieces from text. TransProse uses known relations between elements of music such as tempo and scale, and the emotions they evoke. Further, it uses a novel mechanism to determine sequences of notes that capture the emotional activity in the text. The ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	31,462
2109.14755	Decentralized Role Assignment in Multi-Agent Teams via Empirical Game-Theoretic Analysis	We propose a method, based on empirical game theory, for a robot operating as part of a team to choose its role within the team without explicitly communicating with team members, by leveraging its knowledge about the team structure. To do this, we formulate the role assignment problem as a dynamic game, and borrow too...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	258,058
2109.04627	ACFNet: Adaptively-Cooperative Fusion Network for RGB-D Salient Object Detection	The reasonable employment of RGB and depth data show great significance in promoting the development of computer vision tasks and robot-environment interaction. However, there are different advantages and disadvantages in the early and late fusion of the two types of data. Besides, due to the diversity of object inform...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	254,472
1809.06473	Towards Deep and Representation Learning for Talent Search at LinkedIn	Talent search and recommendation systems at LinkedIn strive to match the potential candidates to the hiring needs of a recruiter or a hiring manager expressed in terms of a search query or a job posting. Recent work in this domain has mainly focused on linear models, which do not take complex relationships between feat...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	108,067
2302.12014	normflows: A PyTorch Package for Normalizing Flows	Normalizing flows model probability distributions through an expressive tractable density. They transform a simple base distribution, such as a Gaussian, through a sequence of invertible functions, which are referred to as layers. These layers typically use neural networks to become very expressive. Flows are ubiquitou...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	347,407
1807.08844	Lesion segmentation using U-Net network	This paper explains the method used in the segmentation challenge (Task 1) in the International Skin Imaging Collaboration's (ISIC) Skin Lesion Analysis Towards Melanoma Detection challenge held in 2018. We have trained a U-Net network to perform the segmentation. The key elements for the training were first to adjust ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	103,611
2301.08941	On the Algebraic Properties of Flame Graphs	Flame graphs are a popular way of representing profiling data. In this paper we propose a possible mathematical definition of flame graphs. In doing so, we gain some interesting algebraic properties almost for free, which in turn allow us to define some operations that can allow to perform an in-depth performance regre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	341,348
2202.10178	Formal Analysis of the Sampling Behaviour of Stochastic Event-Triggered Control	Analyzing Event-Triggered Control's (ETC) sampling behaviour is of paramount importance, as it enables formal assessment of its sampling performance and prediction of its sampling patterns. In this work, we formally analyze the sampling behaviour of stochastic linear periodic ETC (PETC) systems by computing bounds on a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	281,445
1012.4527	Harmonic Order Parameters for Characterizing Complex Particle Morphologies	Order parameters based on spherical harmonics and Fourier coefficients already play a significant role in condensed matter research in the context of systems of spherical or point particles. Here, we extend these types of order parameter to more complex shapes, such as those encountered in nanoscale self-assembly appli...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	8,605
2209.12890	It Takes Two: Learning to Plan for Human-Robot Cooperative Carrying	Cooperative table-carrying is a complex task due to the continuous nature of the action and state-spaces, multimodality of strategies, and the need for instantaneous adaptation to other agents. In this work, we present a method for predicting realistic motion plans for cooperative human-robot teams on the task. Using a...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	319,699
2107.05464	IGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control	Agriculture is the foundation of human civilization. However, the rapid increase of the global population poses a challenge on this cornerstone by demanding more food. Modern autonomous greenhouses, equipped with sensors and actuators, provide a promising solution to the problem by empowering precise control for high-e...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	245,786
2308.12381	Inferring gender from name: a large scale performance evaluation study	A person's gender is a crucial piece of information when performing research across a wide range of scientific disciplines, such as medicine, sociology, political science, and economics, to name a few. However, in increasing instances, especially given the proliferation of big data, gender information is not readily av...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	387,512
2006.00575	Neural Entity Linking: A Survey of Models Based on Deep Learning	This survey presents a comprehensive description of recent neural entity linking (EL) systems developed since 2015 as a result of the "deep learning revolution" in natural language processing. Its goal is to systemize design features of neural entity linking systems and compare their performance to the remarkable class...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,509
2006.14655	Can 3D Adversarial Logos Cloak Humans?	With the trend of adversarial attacks, researchers attempt to fool trained object detectors in 2D scenes. Among many of them, an intriguing new form of attack with potential real-world usage is to append adversarial patches (e.g. logos) to images. Nevertheless, much less have we known about adversarial attacks from 3D ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	184,288
2209.07057	MIPI 2022 Challenge on RGB+ToF Depth Completion: Dataset and Report	Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	317,609
2012.06138	AdvantageNAS: Efficient Neural Architecture Search with Credit Assignment	Neural architecture search (NAS) is an approach for automatically designing a neural network architecture without human effort or expert knowledge. However, the high computational cost of NAS limits its use in commercial applications. Two recent NAS paradigms, namely one-shot and sparse propagation, which reduce the ti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	211,008
1804.02638	OATM: Occlusion Aware Template Matching by Consensus Set Maximization	We present a novel approach to template matching that is efficient, can handle partial occlusions, and comes with provable performance guarantees. A key component of the method is a reduction that transforms the problem of searching a nearest neighbor among $N$ high-dimensional vectors, to searching neighbors among two...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,451
1707.00086	Disinformation and Social Bot Operations in the Run Up to the 2017 French Presidential Election	Recent accounts from researchers, journalists, as well as federal investigators, reached a unanimous conclusion: social media are systematically exploited to manipulate and alter public opinion. Some disinformation campaigns have been coordinated by means of bots, social media accounts controlled by computer scripts th...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	76,291
2202.00454	TableQuery: Querying tabular data with natural language	This paper presents TableQuery, a novel tool for querying tabular data using deep learning models pre-trained to answer questions on free text. Existing deep learning methods for question answering on tabular data have various limitations, such as having to feed the entire table as input into a neural network model, ma...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	true	false	278,145
2009.07896	Captum: A unified and generic model interpretability library for PyTorch	In this paper we introduce a novel, unified, open-source model interpretability library for PyTorch [12]. The library contains generic implementations of a number of gradient and perturbation-based attribution algorithms, also known as feature, neuron and layer importance algorithms, as well as a set of evaluation metr...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	196,071
1501.05683	Polar Lattices for Lossy Compression	Polar lattices, which are constructed from polar codes, have recently been proved to be able to achieve the capacity of the additive white Gaussian noise (AWGN) channel. In this work, we propose a new construction of polar lattices to solve the dual problem, i.e., achieving the rate-distortion bound of a memoryless Gau...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,511
2312.06126	Spreeze: High-Throughput Parallel Reinforcement Learning Framework	The promotion of large-scale applications of reinforcement learning (RL) requires efficient training computation. While existing parallel RL frameworks encompass a variety of RL algorithms and parallelization techniques, the excessively burdensome communication frameworks hinder the attainment of the hardware's limit f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	414,382
1002.0123	Achievable rate regions and outer bounds for a multi-pair bi-directional relay network	In a bi-directional relay channel, a pair of nodes wish to exchange independent messages over a shared wireless half-duplex channel with the help of relays. Recent work has mostly considered information theoretic limits of the bi-directional relay channel with two terminal nodes (or end users) and one relay. In this wo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,570
2403.01887	On $3$-dimensional MRD codes of type $\langle x^{q^t},x+\delta x^{q^{2t}},G(x) \rangle$	In this work we present results on the classification of $\mathbb{F}_{q^n}$-linear MRD codes of dimension three. In particular, using connections with certain algebraic varieties over finite fields, we provide non-existence results for MRD codes $\mathcal{C}=\langle x^{q^t}, F(x), G(x) \rangle \subseteq \mathcal{L}_{n,...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	434,620
2408.02582	Clustering and Mining Accented Speech for Inclusive and Fair Speech Recognition	Modern automatic speech recognition (ASR) systems are typically trained on more than tens of thousands hours of speech data, which is one of the main factors for their great success. However, the distribution of such data is typically biased towards common accents or typical speech patterns. As a result, those systems ...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	478,685
2003.07936	Boosting Unconstrained Face Recognition with Auxiliary Unlabeled Data	In recent years, significant progress has been made in face recognition, which can be partially attributed to the availability of large-scale labeled face datasets. However, since the faces in these datasets usually contain limited degree and types of variation, the resulting trained models generalize poorly to more re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,581
2412.05901	Thermal Image-based Fault Diagnosis in Induction Machines via Self-Organized Operational Neural Networks	Condition monitoring of induction machines is crucial to prevent costly interruptions and equipment failure. Mechanical faults such as misalignment and rotor issues are among the most common problems encountered in industrial environments. To effectively monitor and detect these faults, a variety of sensors, including ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	515,022
2210.07315	Design and Evaluation of a Generic Visual SLAM Framework for Multi-Camera Systems	Multi-camera systems have been shown to improve the accuracy and robustness of SLAM estimates, yet state-of-the-art SLAM systems predominantly support monocular or stereo setups. This paper presents a generic sparse visual SLAM framework capable of running on any number of cameras and in any arrangement. Our SLAM syste...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	323,650
2405.13160	Borrowing Strength in Distributionally Robust Optimization via Hierarchical Dirichlet Processes	This paper presents a novel optimization framework to address key challenges presented by modern machine learning applications: High dimensionality, distributional uncertainty, and data heterogeneity. Our approach unifies regularized estimation, distributionally robust optimization (DRO), and hierarchical Bayesian mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	455,827
2105.12806	A Universal Law of Robustness via Isoperimetry	Classically, data interpolation with a parametrized model class is possible as long as the number of parameters is larger than the number of equations to be satisfied. A puzzling phenomenon in deep learning is that models are trained with many more parameters than what this classical theory would suggest. We propose a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	237,101
1809.02305	Data Augmentation for Spoken Language Understanding via Joint Variational Generation	Data scarcity is one of the main obstacles of domain adaptation in spoken language understanding (SLU) due to the high cost of creating manually tagged SLU datasets. Recent works in neural text generative models, particularly latent variable models such as variational autoencoder (VAE), have shown promising results in ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	107,023
1901.00399	Unary and Binary Classification Approaches and their Implications for Authorship Verification	Retrieving indexed documents, not by their topical content but their writing style opens the door for a number of applications in information retrieval (IR). One application is to retrieve textual content of a certain author X, where the queried IR system is provided beforehand with a set of reference texts of X. Autho...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	117,762
1711.08195	On the Automatic Generation of Medical Imaging Reports	Medical imaging is widely used in clinical practice for diagnosis and treatment. Report-writing can be error-prone for unexperienced physicians, and time- consuming and tedious for experienced physicians. To address these issues, we study the automatic generation of medical imaging reports. This task presents several c...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	85,154
1512.08103	Data Driven Robust Image Guided Depth Map Restoration	Depth maps captured by modern depth cameras such as Kinect and Time-of-Flight (ToF) are usually contaminated by missing data, noises and suffer from being of low resolution. In this paper, we present a robust method for high-quality restoration of a degraded depth map with the guidance of the corresponding color image....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	50,490
2011.02838	Real-time parameter inference in reduced-order flame models with heteroscedastic Bayesian neural network ensembles	The estimation of model parameters with uncertainties from observed data is a ubiquitous inverse problem in science and engineering. In this paper, we suggest an inexpensive and easy to implement parameter estimation technique that uses a heteroscedastic Bayesian Neural Network trained using anchored ensembling. The he...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	205,054
2405.12476	Benchmarking Fish Dataset and Evaluation Metric in Keypoint Detection -- Towards Precise Fish Morphological Assessment in Aquaculture Breeding	Accurate phenotypic analysis in aquaculture breeding necessitates the quantification of subtle morphological phenotypes. Existing datasets suffer from limitations such as small scale, limited species coverage, and inadequate annotation of keypoints for measuring refined and complex morphological phenotypes of fish body...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	455,540
2304.06027	Continual Diffusion: Continual Customization of Text-to-Image Diffusion with C-LoRA	Recent works demonstrate a remarkable ability to customize text-to-image diffusion models while only providing a few example images. What happens if you try to customize such models using multiple, fine-grained concepts in a sequential (i.e., continual) manner? In our work, we show that recent state-of-the-art customiz...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	357,826
2411.11930	AtomThink: A Slow Thinking Framework for Multimodal Mathematical Reasoning	In this paper, we address the challenging task of multimodal mathematical reasoning by incorporating the ability of ``slow thinking" into multimodal large language models (MLLMs). Contrary to existing methods that rely on direct or fast thinking, our key idea is to construct long chains of thought (CoT) consisting of a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	509,239
2212.09666	MultiCoder: Multi-Programming-Lingual Pre-Training for Low-Resource Code Completion	Code completion is a valuable topic in both academia and industry. Recently, large-scale mono-programming-lingual (MonoPL) pre-training models have been proposed to boost the performance of code completion. However, the code completion on low-resource programming languages (PL) is difficult for the data-driven paradigm...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,183
1710.08079	Online Boosting Algorithms for Multi-label Ranking	We consider the multi-label ranking approach to multi-label learning. Boosting is a natural method for multi-label ranking as it aggregates weak predictions through majority votes, which can be directly used as scores to produce a ranking of the labels. We design online boosting algorithms with provable loss bounds for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,036
2212.14694	Machine Learning as an Accurate Predictor for Percolation Threshold of Diverse Networks	The percolation threshold is an important measure to determine the inherent rigidity of large networks. Predictors of the percolation threshold for large networks are computationally intense to run, hence it is a necessity to develop predictors of the percolation threshold of networks, that do not rely on numerical sim...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	338,705
1004.4801	Ontology-based inference for causal explanation	We define an inference system to capture explanations based on causal statements, using an ontology in the form of an IS-A hierarchy. We first introduce a simple logical language which makes it possible to express that a fact causes another fact and that a fact explains another fact. We present a set of formal inferenc...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	6,302
2206.10953	Toward An Optimal Selection of Dialogue Strategies: A Target-Driven Approach for Intelligent Outbound Robots	With the growth of the economy and society, enterprises, especially in the FinTech industry, have increasing demands of outbound calls for customers such as debt collection, marketing, anti-fraud calls, and so on. But a large amount of repetitive and mechanical work occupies most of the time of human agents, so the cos...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	304,098
1909.06133	Towards Sharing Task Environments to Support Reproducible Evaluations of Interactive Recommender Systems	Beyond sharing datasets or simulations, we believe the Recommender Systems (RS) community should share Task Environments. In this work, we propose a high-level logical architecture that will help to reason about the core components of a RS Task Environment, identify the differences between Environments, datasets and si...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	145,297
2404.16282	Adaptive tracking control for non-periodic reference signals under quantized observations	This paper considers an adaptive tracking control problem for stochastic regression systems with multi-threshold quantized observations. Different from the existing studies for periodic reference signals, the reference signal in this paper is non-periodic. Its main difficulty is how to ensure that the designed controll...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	449,422
2211.00111	Unsafe's Betrayal: Abusing Unsafe Rust in Binary Reverse Engineering via Machine Learning	Memory-safety bugs introduce critical software-security issues. Rust provides memory-safe mechanisms to avoid memory-safety bugs in programming, while still allowing unsafe escape hatches via unsafe code. However, the unsafe code that enhances the usability of Rust provides clear spots for finding memory-safety bugs in...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	327,758
1801.04339	Estimating the Number of Connected Components in a Graph via Subgraph Sampling	Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman \cite{Goodman1949} and Frank \cite{Frank1978}. We revisit a problem formulated by Frank \cite{Frank1978} of estimating the number of connected components in a large graph based ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	88,254
2403.16163	An Analytic Solution to Covariance Propagation in Neural Networks	Uncertainty quantification of neural networks is critical to measuring the reliability and robustness of deep learning systems. However, this often involves costly or inaccurate sampling methods and approximations. This paper presents a sample-free moment propagation technique that propagates mean vectors and covarianc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	440,904
1703.05560	Combining Contrast Invariant L1 Data Fidelities with Nonlinear Spectral Image Decomposition	This paper focuses on multi-scale approaches for variational methods and corresponding gradient flows. Recently, for convex regularization functionals such as total variation, new theory and algorithms for nonlinear eigenvalue problems via nonlinear spectral decompositions have been developed. Those methods open new di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,104
1707.00051	Failing to Learn: Autonomously Identifying Perception Failures for Self-driving Cars	One of the major open challenges in self-driving cars is the ability to detect cars and pedestrians to safely navigate in the world. Deep learning-based object detector approaches have enabled great advances in using camera imagery to detect and classify objects. But for a safety critical application, such as autonomou...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	76,282

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