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
2305.09369	Dynamics of niche construction in adaptable populations evolving in diverse environments	In both natural and artificial studies, evolution is often seen as synonymous to natural selection. Individuals evolve under pressures set by environments that are either reset or do not carry over significant changes from previous generations. Thus, niche construction (NC), the reciprocal process to natural selection ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	364,616
2405.10441	Trajectory tracking control of a Remotely Operated Underwater Vehicle based on Fuzzy Disturbance Adaptation and Controller Parameter Optimization	The exploration of under-ice environments presents unique challenges due to limited access for scientific research. This report investigates the potential of deploying a fully actuated Remotely Operated Vehicle (ROV) for shallow area exploration beneath ice sheets. Leveraging advancements in marine robotics technology,...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	454,758
2311.10291	Leveraging Function Space Aggregation for Federated Learning at Scale	The federated learning paradigm has motivated the development of methods for aggregating multiple client updates into a global server model, without sharing client data. Many federated learning algorithms, including the canonical Federated Averaging (FedAvg), take a direct (possibly weighted) average of the client para...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	408,477
2212.00964	JAX-FEM: A differentiable GPU-accelerated 3D finite element solver for automatic inverse design and mechanistic data science	This paper introduces JAX-FEM, an open-source differentiable finite element method (FEM) library. Constructed on top of Google JAX, a rising machine learning library focusing on high-performance numerical computing, JAX-FEM is implemented with pure Python while scalable to efficiently solve problems with moderate to la...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	334,255
2410.08364	Safe and Dynamically-Feasible Motion Planning using Control Lyapunov and Barrier Functions	This paper considers the problem of designing motion planning algorithms for control-affine systems that generate collision-free paths from an initial to a final destination and can be executed using safe and dynamically-feasible controllers. We introduce the C-CLF-CBF-RRT algorithm, which produces paths with such prop...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	497,078
1809.01497	Chinese Discourse Segmentation Using Bilingual Discourse Commonality	Discourse segmentation aims to segment Elementary Discourse Units (EDUs) and is a fundamental task in discourse analysis. For Chinese, previous researches identify EDUs just through discriminating the functions of punctuations. In this paper, we argue that Chinese EDUs may not end at the punctuation positions and shoul...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	106,820
2306.09066	A Bayesian approach to uncertainty in word embedding bias estimation	Multiple measures, such as WEAT or MAC, attempt to quantify the magnitude of bias present in word embeddings in terms of a single-number metric. However, such metrics and the related statistical significance calculations rely on treating pre-averaged data as individual data points and employing bootstrapping techniques...	true	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	373,659
1907.00874	System Misuse Detection via Informed Behavior Clustering and Modeling	One of the main tasks of cybersecurity is recognizing malicious interactions with an arbitrary system. Currently, the logging information from each interaction can be collected in almost unrestricted amounts, but identification of attacks requires a lot of effort and time of security experts. We propose an approach for...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	137,164
2301.02336	Exploring Levels of Control for a Navigation Assistant for Blind Travelers	Only a small percentage of blind and low-vision people use traditional mobility aids such as a cane or a guide dog. Various assistive technologies have been proposed to address the limitations of traditional mobility aids. These devices often give either the user or the device majority of the control. In this work, we ...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	339,480
2104.04203	TaylorMade VDD: Domain-adaptive Visual Defect Detector for High-mix Low-volume Production of Non-convex Cylindrical Metal Objects	Visual defect detection (VDD) for high-mix low-volume production of non-convex metal objects, such as high-pressure cylindrical piping joint parts (VDD-HPPPs), is challenging because subtle difference in domain (e.g., metal objects, imaging device, viewpoints, lighting) significantly affects the specular reflection cha...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	229,330
2407.00482	Quantifying Spuriousness of Biased Datasets Using Partial Information Decomposition	Spurious patterns refer to a mathematical association between two or more variables in a dataset that are not causally related. However, this notion of spuriousness, which is usually introduced due to sampling biases in the dataset, has classically lacked a formal definition. To address this gap, this work presents the...	false	false	false	false	true	false	true	false	false	true	false	true	false	true	false	false	false	false	468,878
2310.04874	AirIMU: Learning Uncertainty Propagation for Inertial Odometry	Inertial odometry (IO) using strap-down inertial measurement units (IMUs) is critical in many robotic applications where precise orientation and position tracking are essential. Prior kinematic motion model-based IO methods often use a simplified linearized IMU noise model and thus usually encounter difficulties in mod...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	397,863
1903.11308	Burstiness in activity-driven networks and the epidemic threshold	We study the effect of heterogeneous temporal activations on epidemic spreading in temporal networks. We focus on the susceptible-infected-susceptible (SIS) model on activity-driven networks with burstiness. By using an activity-based mean-field approach, we derive a closed analytical form for the epidemic threshold fo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	125,484
2401.12024	Multimodal Visual-Tactile Representation Learning through Self-Supervised Contrastive Pre-Training	The rapidly evolving field of robotics necessitates methods that can facilitate the fusion of multiple modalities. Specifically, when it comes to interacting with tangible objects, effectively combining visual and tactile sensory data is key to understanding and navigating the complex dynamics of the physical world, en...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	423,232
2111.09912	Efficiently Transforming Tables for Joinability	Data from different sources rarely conform to a single formatting even if they describe the same set of entities, and this raises concerns when data from multiple sources must be joined or cross-referenced. Such a formatting mismatch is unavoidable when data is gathered from various public and third-party sources. Comm...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	267,146
2210.10981	MGTUNet: An new UNet for colon nuclei instance segmentation and quantification	Colorectal cancer (CRC) is among the top three malignant tumor types in terms of morbidity and mortality. Histopathological images are the gold standard for diagnosing colon cancer. Cellular nuclei instance segmentation and classification, and nuclear component regression tasks can aid in the analysis of the tumor micr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	325,131
2210.02640	ForestQB: An Adaptive Query Builder to Support Wildlife Research	This paper presents ForestQB, a SPARQL query builder, to assist Bioscience and Wildlife Researchers in accessing Linked-Data. As they are unfamiliar with the Semantic Web and the data ontologies, ForestQB aims to empower them to benefit from using Linked-Data to extract valuable information without having to grasp the ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	321,723
1803.09196	Learning Type-Aware Embeddings for Fashion Compatibility	Outfits in online fashion data are composed of items of many different types (e.g. top, bottom, shoes) that share some stylistic relationship with one another. A representation for building outfits requires a method that can learn both notions of similarity (for example, when two tops are interchangeable) and compatibi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,449
2106.09274	Cooperative Multi-Agent Reinforcement Learning Based Distributed Dynamic Spectrum Access in Cognitive Radio Networks	With the development of the 5G and Internet of Things, amounts of wireless devices need to share the limited spectrum resources. Dynamic spectrum access (DSA) is a promising paradigm to remedy the problem of inefficient spectrum utilization brought upon by the historical command-and-control approach to spectrum allocat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	241,607
2408.07147	Controlling the World by Sleight of Hand	Humans naturally build mental models of object interactions and dynamics, allowing them to imagine how their surroundings will change if they take a certain action. While generative models today have shown impressive results on generating/editing images unconditionally or conditioned on text, current methods do not pro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,471
1802.04663	The Third Evolution Equation for Optimal Control Computation	The Variation Evolving Method (VEM) that originates from the continuous-time dynamics stability theory seeks the optimal solutions with variation evolution principle. After establishing the first and the second evolution equations within its frame, the third evolution equation is developed. This equation only solves th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	90,271
1904.06786	Curious iLQR: Resolving Uncertainty in Model-based RL	Curiosity as a means to explore during reinforcement learning problems has recently become very popular. However, very little progress has been made in utilizing curiosity for learning control. In this work, we propose a model-based reinforcement learning (MBRL) framework that combines Bayesian modeling of the system d...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	127,633
1611.02590	Veracity Computing from Lexical Cues and Perceived Certainty Trends	We present a data-driven method for determining the veracity of a set of rumorous claims on social media data. Tweets from different sources pertaining to a rumor are processed on three levels: first, factuality values are assigned to each tweet based on four textual cue categories relevant for our journalism use case;...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	63,583
2408.11662	Optimizing Federated Graph Learning with Inherent Structural Knowledge and Dual-Densely Connected GNNs	Federated Graph Learning (FGL) is an emerging technology that enables clients to collaboratively train powerful Graph Neural Networks (GNNs) in a distributed manner without exposing their private data. Nevertheless, FGL still faces the challenge of the severe non-Independent and Identically Distributed (non-IID) nature...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	482,378
2401.15841	2L3: Lifting Imperfect Generated 2D Images into Accurate 3D	Reconstructing 3D objects from a single image is an intriguing but challenging problem. One promising solution is to utilize multi-view (MV) 3D reconstruction to fuse generated MV images into consistent 3D objects. However, the generated images usually suffer from inconsistent lighting, misaligned geometry, and sparse ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	424,604
1904.10130	Spatio-temporal crop classification of low-resolution satellite imagery with capsule layers and distributed attention	Land use classification of low resolution spatial imagery is one of the most extensively researched fields in remote sensing. Despite significant advancements in satellite technology, high resolution imagery lacks global coverage and can be prohibitively expensive to procure for extended time periods. Accurately classi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	128,559
1501.07547	Individual secrecy for broadcast channels with receiver side information	This paper studies the problem of secure communication over the broadcast channel with receiver side information under the lens of individual secrecy constraints. That is, the transmitter wants to send two independent messages to two receivers which have, respectively, the desired message of the other receiver as side ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,718
1907.11374	Deep-learning-based Optimization of the Under-sampling Pattern in MRI	In compressed sensing MRI (CS-MRI), k-space measurements are under-sampled to achieve accelerated scan times. CS-MRI presents two fundamental problems: (1) where to sample and (2) how to reconstruct an under-sampled scan. In this paper, we tackle both problems simultaneously for the specific case of 2D Cartesian sampli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,832
1704.08300	Diversity driven Attention Model for Query-based Abstractive Summarization	Abstractive summarization aims to generate a shorter version of the document covering all the salient points in a compact and coherent fashion. On the other hand, query-based summarization highlights those points that are relevant in the context of a given query. The encode-attend-decode paradigm has achieved notable s...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,498
2402.03885	MOMENT: A Family of Open Time-series Foundation Models	We introduce MOMENT, a family of open-source foundation models for general-purpose time series analysis. Pre-training large models on time series data is challenging due to (1) the absence of a large and cohesive public time series repository, and (2) diverse time series characteristics which make multi-dataset trainin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	427,233
1804.06353	Not-so-supervised: a survey of semi-supervised, multi-instance, and transfer learning in medical image analysis	Machine learning (ML) algorithms have made a tremendous impact in the field of medical imaging. While medical imaging datasets have been growing in size, a challenge for supervised ML algorithms that is frequently mentioned is the lack of annotated data. As a result, various methods which can learn with less/other type...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	95,283
2102.03501	Two-Step Image Dehazing with Intra-domain and Inter-domain Adaptation	Caused by the difference of data distributions, intra-domain gap and inter-domain gap are widely present in image processing tasks. In the field of image dehazing, certain previous works have paid attention to the inter-domain gap between the synthetic domain and the real domain. However, those methods only establish t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	218,767
2011.05940	LittleYOLO-SPP: A Delicate Real-Time Vehicle Detection Algorithm	Vehicle detection in real-time is a challenging and important task. The existing real-time vehicle detection lacks accuracy and speed. Real-time systems must detect and locate vehicles during criminal activities like theft of vehicle and road traffic violations with high accuracy. Detection of vehicles in complex scene...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,090
1009.4683	Efficient Computation of Optimal Trading Strategies	Given the return series for a set of instruments, a \emph{trading strategy} is a switching function that transfers wealth from one instrument to another at specified times. We present efficient algorithms for constructing (ex-post) trading strategies that are optimal with respect to the total return, the Sterling ratio...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	7,640
2501.10741	Development of Application-Specific Large Language Models to Facilitate Research Ethics Review	Institutional review boards (IRBs) play a crucial role in ensuring the ethical conduct of human subjects research, but face challenges including inconsistency, delays, and inefficiencies. We propose the development and implementation of application-specific large language models (LLMs) to facilitate IRB review processe...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	525,642
2303.02392	Audio-Visual Quality Assessment for User Generated Content: Database and Method	With the explosive increase of User Generated Content (UGC), UGC video quality assessment (VQA) becomes more and more important for improving users' Quality of Experience (QoE). However, most existing UGC VQA studies only focus on the visual distortions of videos, ignoring that the user's QoE also depends on the accomp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	349,336
2104.04152	A unified Abaqus implementation of the phase field fracture method using only a user material subroutine	We present a simple and robust implementation of the phase field fracture method in Abaqus. Unlike previous works, only a user material (UMAT) subroutine is used. This is achieved by exploiting the analogy between the phase field balance equation and heat transfer, which avoids the need for a user element mesh and enab...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	229,307
1011.0328	Mining Frequent Itemsets Using Genetic Algorithm	In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm etc., which take too much computer time to compute all the frequent itemsets. By using Genetic Algorithm (GA) we can improve the scenario. ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	8,092
2405.14131	Statistical Advantages of Perturbing Cosine Router in Mixture of Experts	The cosine router in Mixture of Experts (MoE) has recently emerged as an attractive alternative to the conventional linear router. Indeed, the cosine router demonstrates favorable performance in image and language tasks and exhibits better ability to mitigate the representation collapse issue, which often leads to para...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	456,265
1911.12529	One-Shot Object Detection with Co-Attention and Co-Excitation	This paper aims to tackle the challenging problem of one-shot object detection. Given a query image patch whose class label is not included in the training data, the goal of the task is to detect all instances of the same class in a target image. To this end, we develop a novel {\em co-attention and co-excitation} (CoA...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	155,421
2307.09334	Approximating nonlinear functions with latent boundaries in low-rank excitatory-inhibitory spiking networks	Deep feedforward and recurrent rate-based neural networks have become successful functional models of the brain, but they neglect obvious biological details such as spikes and Dale's law. Here we argue that these details are crucial in order to understand how real neural circuits operate. Towards this aim, we put forth...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	380,138
2310.15411	Efficient Active Learning Halfspaces with Tsybakov Noise: A Non-convex Optimization Approach	We study the problem of computationally and label efficient PAC active learning $d$-dimensional halfspaces with Tsybakov Noise~\citep{tsybakov2004optimal} under structured unlabeled data distributions. Inspired by~\cite{diakonikolas2020learning}, we prove that any approximate first-order stationary point of a smooth no...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	402,288
2410.15522	M-RewardBench: Evaluating Reward Models in Multilingual Settings	Reward models (RMs) have driven the state-of-the-art performance of LLMs today by enabling the integration of human feedback into the language modeling process. However, RMs are primarily trained and evaluated in English, and their capabilities in multilingual settings remain largely understudied. In this work, we cond...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	500,586
2309.10251	Safe Control Design through Risk-Tunable Control Barrier Functions	We consider the problem of designing controllers to guarantee safety in a class of nonlinear systems under uncertainties in the system dynamics and/or the environment. We define a class of uncertain control barrier functions (CBFs), and formulate the safe control design problem as a chance-constrained optimization prob...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	392,926
2201.11866	Calibrating Histopathology Image Classifiers using Label Smoothing	The classification of histopathology images fundamentally differs from traditional image classification tasks because histopathology images naturally exhibit a range of diagnostic features, resulting in a diverse range of annotator agreement levels. However, examples with high annotator disagreement are often either as...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	277,428
2104.09272	The Impact of Hyper-Parameter Tuning for Landscape-Aware Performance Regression and Algorithm Selection	Automated algorithm selection and configuration methods that build on exploratory landscape analysis (ELA) are becoming very popular in Evolutionary Computation. However, despite a significantly growing number of applications, the underlying machine learning models are often chosen in an ad-hoc manner. We show in thi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	231,171
2303.02561	CAMEL: Curvature-Augmented Manifold Embedding and Learning	A novel method, named Curvature-Augmented Manifold Embedding and Learning (CAMEL), is proposed for high dimensional data classification, dimension reduction, and visualization. CAMEL utilizes a topology metric defined on the Riemannian manifold, and a unique Riemannian metric for both distance and curvature to enhance ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,403
2011.03745	Stealthy hacking and secrecy of controlled state estimation systems with random dropouts	We study the maximum information gain that an adversary may obtain through hacking without being detected. Consider a dynamical process observed by a sensor that transmits a local estimate of the system state to a remote estimator according to some reference transmission policy across a packet-dropping wireless channel...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	205,339
2406.00540	Optimal Transmission Power Scheduling for Networked Control System under DoS Attack	Designing networked control systems that are reliable and resilient against adversarial threats, is essential for ensuring the security of cyber-physical systems. This paper addresses the communication-control co-design problem for networked control systems under denial-of-service (DoS) attacks. In the wireless channel...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	459,906
1907.06099	Multi-Task Recurrent Convolutional Network with Correlation Loss for Surgical Video Analysis	Surgical tool presence detection and surgical phase recognition are two fundamental yet challenging tasks in surgical video analysis and also very essential components in various applications in modern operating rooms. While these two analysis tasks are highly correlated in clinical practice as the surgical process is ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	138,532
2408.03877	Knowledge Probing for Graph Representation Learning	Graph learning methods have been extensively applied in diverse application areas. However, what kind of inherent graph properties e.g. graph proximity, graph structural information has been encoded into graph representation learning for downstream tasks is still under-explored. In this paper, we propose a novel graph ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	479,180
2101.11883	Evolutionary Neural Architecture Search Supporting Approximate Multipliers	There is a growing interest in automated neural architecture search (NAS) methods. They are employed to routinely deliver high-quality neural network architectures for various challenging data sets and reduce the designer's effort. The NAS methods utilizing multi-objective evolutionary algorithms are especially useful ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	217,417
2409.04597	Detecting Buggy Contracts via Smart Testing	Smart contracts are susceptible to critical vulnerabilities. Hybrid dynamic analyses, such as concolic execution assisted fuzzing and foundation model assisted fuzzing, have emerged as highly effective testing techniques for smart contract bug detection recently. This hybrid approach has shown initial promise in real-w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	486,436
2206.02946	On the Convergence of Optimizing Persistent-Homology-Based Losses	Topological loss based on persistent homology has shown promise in various applications. A topological loss enforces the model to achieve certain desired topological property. Despite its empirical success, less is known about the optimization behavior of the loss. In fact, the topological loss involves combinatorial c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	301,085
2303.03196	Population-based Evaluation in Repeated Rock-Paper-Scissors as a Benchmark for Multiagent Reinforcement Learning	Progress in fields of machine learning and adversarial planning has benefited significantly from benchmark domains, from checkers and the classic UCI data sets to Go and Diplomacy. In sequential decision-making, agent evaluation has largely been restricted to few interactions against experts, with the aim to reach some...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	349,640
1903.11650	Lens-based Millimeter Wave Reconfigurable Antenna NOMA	This paper proposes a new multiple access technique based on the millimeter wave lens-based reconfigurable antenna systems. In particular, to support a large number of groups of users with different angles of departures (AoDs), we integrate recently proposed reconfigurable antenna multiple access (RAMA) into non-orthog...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	125,550
1607.06793	On the Impact of a Single Edge on the Network Coding Capacity	In this paper, we study the effect of a single link on the capacity of a network of error-free bit pipes. More precisely, we study the change in network capacity that results when we remove a single link of capacity $\delta$. In a recent result, we proved that if all the sources are directly available to a single super...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	58,926
2401.04620	Agent Alignment in Evolving Social Norms	Agents based on Large Language Models (LLMs) are increasingly permeating various domains of human production and life, highlighting the importance of aligning them with human values. The current alignment of AI systems primarily focuses on passively aligning LLMs through human intervention. However, agents possess char...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	420,486
2102.05927	Theoretical and Experimental Perspectives of Quantum Verification	In this perspective we discuss verification of quantum devices in the context of specific examples, formulated as proposed experiments. Our first example is verification of analog quantum simulators as Hamiltonian learning, where the input Hamiltonian as design goal is compared with the parent Hamiltonian for the quant...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	219,585
2311.17812	DAP: Domain-aware Prompt Learning for Vision-and-Language Navigation	Following language instructions to navigate in unseen environments is a challenging task for autonomous embodied agents. With strong representation capabilities, pretrained vision-and-language models are widely used in VLN. However, most of them are trained on web-crawled general-purpose datasets, which incurs a consid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,424
2307.12613	Tuning-free one-bit covariance estimation using data-driven dithering	We consider covariance estimation of any subgaussian distribution from finitely many i.i.d. samples that are quantized to one bit of information per entry. Recent work has shown that a reliable estimator can be constructed if uniformly distributed dithers on $[-\lambda,\lambda]$ are used in the one-bit quantizer. This ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	381,319
1703.00352	Do Reichenbachian Common Cause Systems of Arbitrary Finite Size Exist?	The principle of common cause asserts that positive correlations between causally unrelated events ought to be explained through the action of some shared causal factors. Reichenbachian common cause systems are probabilistic structures aimed at accounting for cases where correlations of the aforesaid sort cannot be exp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	69,144
2105.11589	VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator	Interactive robots navigating photo-realistic environments need to be trained to effectively leverage and handle the dynamic nature of dialogue in addition to the challenges underlying vision-and-language navigation (VLN). In this paper, we present VISITRON, a multi-modal Transformer-based navigator better suited to th...	false	false	false	false	true	false	true	true	true	false	false	true	false	false	false	false	false	false	236,746
1807.03108	Discriminating between Indo-Aryan Languages Using SVM Ensembles	In this paper we present a system based on SVM ensembles trained on characters and words to discriminate between five similar languages of the Indo-Aryan family: Hindi, Braj Bhasha, Awadhi, Bhojpuri, and Magahi. We investigate the performance of individual features and combine the output of single classifiers to maximi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	102,428
2301.08038	A Unified Architecture for Dynamic Role Allocation and Collaborative Task Planning in Mixed Human-Robot Teams	The growing deployment of human-robot collaborative processes in several industrial applications, such as handling, welding, and assembly, unfolds the pursuit of systems which are able to manage large heterogeneous teams and, at the same time, monitor the execution of complex tasks. In this paper, we present a novel ar...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	341,078
1604.01325	Deep Image Retrieval: Learning global representations for image search	We propose a novel approach for instance-level image retrieval. It produces a global and compact fixed-length representation for each image by aggregating many region-wise descriptors. In contrast to previous works employing pre-trained deep networks as a black box to produce features, our method leverages a deep archi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,179
2302.04771	Designing Fairness in Autonomous Peer-to-peer Energy Trading	Several autonomous energy management and peer-to-peer trading mechanisms for future energy markets have been recently proposed based on optimization and game theory. In this paper, we study the impact of trading prices on the outcome of these market designs for energy-hub networks. We prove that, for a generic choice o...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	344,809
1607.02171	Argumentation Models for Cyber Attribution	A major challenge in cyber-threat analysis is combining information from different sources to find the person or the group responsible for the cyber-attack. It is one of the most important technical and policy challenges in cyber-security. The lack of ground truth for an individual responsible for an attack has limited...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	58,309
2409.18585	Unscented Transform-based Pure Pursuit Path-Tracking Algorithm under Uncertainty	Automated driving has become more and more popular due to its potential to eliminate road accidents by taking over driving tasks from humans. One of the remaining challenges is to follow a planned path autonomously, especially when uncertainties in self-localizing or understanding the surroundings can influence the dec...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	492,321
1103.0127	Fuzzy Approach to Critical Bus Ranking under Normal and Line Outage Contingencies	Identification of critical or weak buses for a given operating condition is an important task in the load dispatch centre. It has become more vital in view of the threat of voltage instability leading to voltage collapse. This paper presents a fuzzy approach for ranking critical buses in a power system under normal and...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	9,427
1811.07104	On Hallucinating Context and Background Pixels from a Face Mask using Multi-scale GANs	We propose a multi-scale GAN model to hallucinate realistic context (forehead, hair, neck, clothes) and background pixels automatically from a single input face mask. Instead of swapping a face on to an existing picture, our model directly generates realistic context and background pixels based on the features of the p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	113,673
2001.02568	A Group Norm Regularized Factorization Model for Subspace Segmentation	Subspace segmentation assumes that data comes from the union of different subspaces and the purpose of segmentation is to partition the data into the corresponding subspace. Low-rank representation (LRR) is a classic spectral-type method for solving subspace segmentation problems, that is, one first obtains an affinity...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,767
2303.17276	Humans in Humans Out: On GPT Converging Toward Common Sense in both Success and Failure	Increase in computational scale and fine-tuning has seen a dramatic improvement in the quality of outputs of large language models (LLMs) like GPT. Given that both GPT-3 and GPT-4 were trained on large quantities of human-generated text, we might ask to what extent their outputs reflect patterns of human thinking, both...	true	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	355,161
2308.10899	TADA! Text to Animatable Digital Avatars	We introduce TADA, a simple-yet-effective approach that takes textual descriptions and produces expressive 3D avatars with high-quality geometry and lifelike textures, that can be animated and rendered with traditional graphics pipelines. Existing text-based character generation methods are limited in terms of geometry...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	386,929
2303.17644	Vision-Language Modelling For Radiological Imaging and Reports In The Low Data Regime	This paper explores training medical vision-language models (VLMs) -- where the visual and language inputs are embedded into a common space -- with a particular focus on scenarios where training data is limited, as is often the case in clinical datasets. We explore several candidate methods to improve low-data performa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,290
2206.00738	Composition of Relational Features with an Application to Explaining Black-Box Predictors	Relational machine learning programs like those developed in Inductive Logic Programming (ILP) offer several advantages: (1) The ability to model complex relationships amongst data instances; (2) The use of domain-specific relations during model construction; and (3) The models constructed are human-readable, which is ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	300,229
2109.10797	Improved Multi-label Classification with Frequent Label-set Mining and Association	Multi-label (ML) data deals with multiple classes associated with individual samples at the same time. This leads to the co-occurrence of several classes repeatedly, which indicates some existing correlation among them. In this article, the correlation among classes has been explored to improve the classification perfo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	256,752
1511.04515	An Algorithmic Framework for Efficient Large-Scale Circuit Simulation Using Exponential Integrators	We propose an efficient algorithmic framework for time domain circuit simulation using exponential integrator. This work addresses several critical issues exposed by previous matrix exponential based circuit simulation research, and makes it capable of simulating stiff nonlinear circuit system at a large scale. In this...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	48,902
2108.02234	Multi-Branch with Attention Network for Hand-Based Person Recognition	In this paper, we propose a novel hand-based person recognition method for the purpose of criminal investigations since the hand image is often the only available information in cases of serious crime such as sexual abuse. Our proposed method, Multi-Branch with Attention Network (MBA-Net), incorporates both channel and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	249,254
2109.02700	Intelligent Motion Planning for a Cost-effective Object Follower Mobile Robotic System with Obstacle Avoidance	There are few industries which use manually controlled robots for carrying material and this cannot be used all the time in all the places. So, it is very tranquil to have robots which can follow a specific human by following the unique coloured object held by that person. So, we propose a robotic system which uses rob...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	253,819
1805.09749	MobiFace: A Novel Dataset for Mobile Face Tracking in the Wild	Face tracking serves as the crucial initial step in mobile applications trying to analyse target faces over time in mobile settings. However, this problem has received little attention, mainly due to the scarcity of dedicated face tracking benchmarks. In this work, we introduce MobiFace, the first dataset for single fa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	98,490
2006.14890	CyRes -- Avoiding Catastrophic Failure in Connected and Autonomous Vehicles (Extended Abstract)	Existing approaches to cyber security and regulation in the automotive sector cannot achieve the quality of outcome necessary to ensure the safe mass deployment of advanced vehicle technologies and smart mobility systems. Without sustainable resilience hard-fought public trust will evaporate, derailing emerging global ...	false	false	false	false	false	false	false	true	false	false	true	false	true	true	false	false	false	false	184,362
2108.06197	A comparison of latent semantic analysis and correspondence analysis of document-term matrices	Latent semantic analysis (LSA) and correspondence analysis (CA) are two techniques that use a singular value decomposition (SVD) for dimensionality reduction. LSA has been extensively used to obtain low-dimensional representations that capture relationships among documents and terms. In this article, we present a theor...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	250,530
1306.5960	Computation of Diet Composition for Patients Suffering from Kidney and Urinary Tract Diseases with the Fuzzy Genetic System	Determination of dietary food consumed a day for patients with diseases in general, greatly affect the health of the body and the healing process, is no exception for people with kidney disease and urinary tract. This paper presents the determination of diet composition in the form of food subtance for people with kidn...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	25,444
2211.07909	Selective Memory Recursive Least Squares: Recast Forgetting into Memory in RBF Neural Network Based Real-Time Learning	In radial basis function neural network (RBFNN) based real-time learning tasks, forgetting mechanisms are widely used such that the neural network can keep its sensitivity to new data. However, with forgetting mechanisms, some useful knowledge will get lost simply because they are learned a long time ago, which we refe...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	330,413
1909.10704	Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints	In this paper, we present a learning method to solve the unlabelled motion problem with motion constraints and space constraints in 2D space for a large number of robots. To solve the problem of arbitrary dynamics and constraints we propose formulating the problem as a multi-agent problem. In contrast to previous works...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	146,613
2112.03710	CapsProm: A Capsule Network For Promoter Prediction	Locating the promoter region in DNA sequences is of paramount importance in the field of bioinformatics. This is a problem widely studied in the literature, however, not yet fully resolved. Some researchers have presented remarkable results using convolution networks, that allowed the automatic extraction of features f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	270,315
2405.10748	Deep Data Consistency: a Fast and Robust Diffusion Model-based Solver for Inverse Problems	Diffusion models have become a successful approach for solving various image inverse problems by providing a powerful diffusion prior. Many studies tried to combine the measurement into diffusion by score function replacement, matrix decomposition, or optimization algorithms, but it is hard to balance the data consiste...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,877
1205.3549	Normalized Maximum Likelihood Coding for Exponential Family with Its Applications to Optimal Clustering	We are concerned with the issue of how to calculate the normalized maximum likelihood (NML) code-length. There is a problem that the normalization term of the NML code-length may diverge when it is continuous and unbounded and a straightforward computation of it is highly expensive when the data domain is finite . In p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,031
2407.13137	OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation	Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-view images into 3D world space. Recently, BEV segmentation has made notable progress, attributed to better view transformation modules, larger...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	474,248
2407.19773	Unmasking unlearnable models: a classification challenge for biomedical images without visible cues	Predicting traits from images lacking visual cues is challenging, as algorithms are designed to capture visually correlated ground truth. This problem is critical in biomedical sciences, and their solution can improve the efficacy of non-invasive methods. For example, a recent challenge of predicting MGMT methylation s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	476,917
1704.01314	Character-based Joint Segmentation and POS Tagging for Chinese using Bidirectional RNN-CRF	We present a character-based model for joint segmentation and POS tagging for Chinese. The bidirectional RNN-CRF architecture for general sequence tagging is adapted and applied with novel vector representations of Chinese characters that capture rich contextual information and lower-than-character level features. The ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	71,242
2409.10370	Uncovering the Mechanism of Hepatotoxiciy of PFAS Targeting L-FABP Using GCN and Computational Modeling	Per- and polyfluoroalkyl substances (PFAS) are persistent environmental pollutants with known toxicity and bioaccumulation issues. Their widespread industrial use and resistance to degradation have led to global environmental contamination and significant health concerns. While a minority of PFAS have been extensively ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	488,725
2005.07755	Momentum with Variance Reduction for Nonconvex Composition Optimization	Composition optimization is widely-applied in nonconvex machine learning. Various advanced stochastic algorithms that adopt momentum and variance reduction techniques have been developed for composition optimization. However, these algorithms do not fully exploit both techniques to accelerate the convergence and are la...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,370
2407.09811	CellAgent: An LLM-driven Multi-Agent Framework for Automated Single-cell Data Analysis	Single-cell RNA sequencing (scRNA-seq) data analysis is crucial for biological research, as it enables the precise characterization of cellular heterogeneity. However, manual manipulation of various tools to achieve desired outcomes can be labor-intensive for researchers. To address this, we introduce CellAgent (http:/...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	472,728
2412.07880	Towards Foundation-model-based Multiagent System to Accelerate AI for Social Impact	AI for social impact (AI4SI) offers significant potential for addressing complex societal challenges in areas such as public health, agriculture, education, conservation, and public safety. However, existing AI4SI research is often labor-intensive and resource-demanding, limiting its accessibility and scalability; the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	515,840
2407.15045	Efficient Sampling for Data-Driven Frequency Stability Constraint via Forward-Mode Automatic Differentiation	Encoding frequency stability constraints in the operation problem is challenging due to its complex dynamics. Recently, data-driven approaches have been proposed to learn the stability criteria offline with the trained model embedded as a constraint of online optimization. However, random sampling of stationary operati...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	475,008
2204.13082	Electrified Autonomous Freight Benefit analysis on Fleet, Infrastructure and Grid Leveraging Grid-Electrified Mobility (GEM) Model	This paper analyzes the potential benefit of heavy-duty vehicle (HDV) electrification and automation on fleet cost, infrastructure cost, grid, and environmental impact. In this work, we extended the vehicle electrification benefit analysis tool: Grid-Electrified Mobility (GEM) model, which had primarily been used to st...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	293,698
2203.14328	On the Neural Tangent Kernel Analysis of Randomly Pruned Neural Networks	Motivated by both theory and practice, we study how random pruning of the weights affects a neural network's neural tangent kernel (NTK). In particular, this work establishes an equivalence of the NTKs between a fully-connected neural network and its randomly pruned version. The equivalence is established under two cas...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	287,966
2104.08862	End-to-End Interactive Prediction and Planning with Optical Flow Distillation for Autonomous Driving	With the recent advancement of deep learning technology, data-driven approaches for autonomous car prediction and planning have achieved extraordinary performance. Nevertheless, most of these approaches follow a non-interactive prediction and planning paradigm, hypothesizing that a vehicle's behaviors do not affect oth...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	231,019

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