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
2407.14829	Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks	In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets. We organize two tracks to handle the argumentative generation tasks in different scenarios, namely, Counter-Argument Generation (Track 1) and Claim-ba...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	474,923
2412.02249	Multi-robot autonomous 3D reconstruction using Gaussian splatting with Semantic guidance	Implicit neural representations and 3D Gaussian splatting (3DGS) have shown great potential for scene reconstruction. Recent studies have expanded their applications in autonomous reconstruction through task assignment methods. However, these methods are mainly limited to single robot, and rapid reconstruction of large...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	513,453
2404.05895	Interference Reduction Design for Improved Multitarget Detection in ISAC Systems	The advancement of wireless communication systems toward 5G and beyond is spurred by the demand for high data rates, exceedingly dependable low-latency communication, and extensive connectivity that aligns with sensing requisites such as advanced high-resolution sensing and target detection. Consequently, embedding sen...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	445,251
1807.11254	Extreme Network Compression via Filter Group Approximation	In this paper we propose a novel decomposition method based on filter group approximation, which can significantly reduce the redundancy of deep convolutional neural networks (CNNs) while maintaining the majority of feature representation. Unlike other low-rank decomposition algorithms which operate on spatial or chann...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,144
2009.10855	Controlling Style in Generated Dialogue	Open-domain conversation models have become good at generating natural-sounding dialogue, using very large architectures with billions of trainable parameters. The vast training data required to train these architectures aggregates many different styles, tones, and qualities. Using that data to train a single model mak...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	197,000
2303.08038	Progress Note Understanding -- Assessment and Plan Reasoning: Overview of the 2022 N2C2 Track 3 Shared Task	Daily progress notes are common types in the electronic health record (EHR) where healthcare providers document the patient's daily progress and treatment plans. The EHR is designed to document all the care provided to patients, but it also enables note bloat with extraneous information that distracts from the diagnose...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	351,483
1804.04109	Influence Estimation on Social Media Networks Using Causal Inference	Estimating influence on social media networks is an important practical and theoretical problem, especially because this new medium is widely exploited as a platform for disinformation and propaganda. This paper introduces a novel approach to influence estimation on social media networks and applies it to the real-worl...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	94,761
2502.12158	Mining Social Determinants of Health for Heart Failure Patient 30-Day Readmission via Large Language Model	Heart Failure (HF) affects millions of Americans and leads to high readmission rates, posing significant healthcare challenges. While Social Determinants of Health (SDOH) such as socioeconomic status and housing stability play critical roles in health outcomes, they are often underrepresented in structured EHRs and hid...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	534,718
1809.11074	Robot Representation and Reasoning with Knowledge from Reinforcement Learning	Reinforcement learning (RL) agents aim at learning by interacting with an environment, and are not designed for representing or reasoning with declarative knowledge. Knowledge representation and reasoning (KRR) paradigms are strong in declarative KRR tasks, but are ill-equipped to learn from such experiences. In this w...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	109,049
1902.10974	Gaussian Process Modulated Cox Processes under Linear Inequality Constraints	Gaussian process (GP) modulated Cox processes are widely used to model point patterns. Existing approaches require a mapping (link function) between the unconstrained GP and the positive intensity function. This commonly yields solutions that do not have a closed form or that are restricted to specific covariance funct...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,816
2202.13884	Numeric Lyndon-based feature embedding of sequencing reads for machine learning approaches	Feature embedding methods have been proposed in literature to represent sequences as numeric vectors to be used in some bioinformatics investigations, such as family classification and protein structure prediction. Recent theoretical results showed that the well-known Lyndon factorization preserves common factors in ov...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	282,783
1808.01821	Visual Question Generation for Class Acquisition of Unknown Objects	Traditional image recognition methods only consider objects belonging to already learned classes. However, since training a recognition model with every object class in the world is unfeasible, a way of getting information on unknown objects (i.e., objects whose class has not been learned) is necessary. A way for an im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,652
2303.04437	Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods	A hybrid model involves the cooperation of an interpretable model and a complex black box. At inference, any input of the hybrid model is assigned to either its interpretable or complex component based on a gating mechanism. The advantages of such models over classical ones are two-fold: 1) They grant users precise con...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	350,091
2308.15758	An Improved Greedy Curvature Bound in Finite-Horizon String Optimization with Application to a Sensor Coverage Problem	We study the optimization problem of choosing strings of finite length to maximize string submodular functions on string matroids, which is a broader class of problems than maximizing set submodular functions on set matroids. We provide a lower bound for the performance of the greedy algorithm in our problem, and then ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	388,783
2307.07582	A novel mesh regularization approach based on finite element distortion potentials: Application to material expansion processes with extreme volume change	The accuracy of finite element solutions is closely tied to the mesh quality. In particular, geometrically nonlinear problems involving large and strongly localized deformations often result in prohibitively large element distortions. In this work, we propose a novel mesh regularization approach allowing to restore a n...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	379,463
2203.16494	S-OPT: A Points Selection Algorithm for Hyper-Reduction in Reduced Order Models	While projection-based reduced order models can reduce the dimension of full order solutions, the resulting reduced models may still contain terms that scale with the full order dimension. Hyper-reduction techniques are sampling-based methods that further reduce this computational complexity by approximating such terms...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	288,804
2402.01431	Approximate Control for Continuous-Time POMDPs	This work proposes a decision-making framework for partially observable systems in continuous time with discrete state and action spaces. As optimal decision-making becomes intractable for large state spaces we employ approximation methods for the filtering and the control problem that scale well with an increasing num...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	426,019
2009.10365	Inter-database validation of a deep learning approach for automatic sleep scoring	In this work we describe a new deep learning approach for automatic sleep staging, and carry out its validation by addressing its generalization capabilities on a wide range of sleep staging databases. Prediction capabilities are evaluated in the context of independent local and external generalization scenarios. Effec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	196,878
2210.10817	A Continuum of Generation Tasks for Investigating Length Bias and Degenerate Repetition	Language models suffer from various degenerate behaviors. These differ between tasks: machine translation (MT) exhibits length bias, while tasks like story generation exhibit excessive repetition. Recent work has attributed the difference to task constrainedness, but evidence for this claim has always involved many con...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	325,069
2402.10940	Neural machine translation of clinical procedure codes for medical diagnosis and uncertainty quantification	A Clinical Decision Support System (CDSS) is designed to enhance clinician decision-making by combining system-generated recommendations with medical expertise. Given the high costs, intensive labor, and time-sensitive nature of medical treatments, there is a pressing need for efficient decision support, especially in ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	430,173
2501.03220	ProTracker: Probabilistic Integration for Robust and Accurate Point Tracking	In this paper, we propose ProTracker, a novel framework for robust and accurate long-term dense tracking of arbitrary points in videos. The key idea of our method is incorporating probabilistic integration to refine multiple predictions from both optical flow and semantic features for robust short-term and long-term tr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	522,796
2211.02646	Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions	As multimodal learning finds applications in a wide variety of high-stakes societal tasks, investigating their robustness becomes important. Existing work has focused on understanding the robustness of vision-and-language models to imperceptible variations on benchmark tasks. In this work, we investigate the robustness...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	328,650
2211.07696	Supervised Fine-tuning Evaluation for Long-term Visual Place Recognition	In this paper, we present a comprehensive study on the utility of deep convolutional neural networks with two state-of-the-art pooling layers which are placed after convolutional layers and fine-tuned in an end-to-end manner for visual place recognition task in challenging conditions, including seasonal and illuminatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	330,331
1112.2723	Correlation-aware Resource Allocation in Multi-Cell Networks	We propose a cross-layer strategy for resource allocation between spatially correlated sources in the uplink of multi-cell FDMA networks. Our objective is to find the optimum power and channel to sources, in order to minimize the maximum distortion achieved by any source in the network. Given that the network is multi-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,438
2301.06660	VaxxHesitancy: A Dataset for Studying Hesitancy towards COVID-19 Vaccination on Twitter	Vaccine hesitancy has been a common concern, probably since vaccines were created and, with the popularisation of social media, people started to express their concerns about vaccines online alongside those posting pro- and anti-vaccine content. Predictably, since the first mentions of a COVID-19 vaccine, social media ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	340,701
2502.05558	Large Memory Network for Recommendation	Modeling user behavior sequences in recommender systems is essential for understanding user preferences over time, enabling personalized and accurate recommendations for improving user retention and enhancing business values. Despite its significance, there are two challenges for current sequential modeling approaches....	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	531,668
2306.15676	KAPLA: Pragmatic Representation and Fast Solving of Scalable NN Accelerator Dataflow	Dataflow scheduling decisions are of vital importance to neural network (NN) accelerators. Recent scalable NN accelerators support a rich set of advanced dataflow techniques. The problems of comprehensively representing and quickly finding optimized dataflow schemes thus become significantly more complicated and challe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	376,104
1806.10827	Deep Learning-Aided Projected Gradient Detector for Massive Overloaded MIMO Channels	The paper presents a deep learning-aided iterative detection algorithm for massive overloaded MIMO systems. Since the proposed algorithm is based on the projected gradient descent method with trainable parameters, it is named as trainable projected descent-detector (TPG-detector). The trainable internal parameters can ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	101,610
1808.02874	Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer's Disease	Visualizing and interpreting convolutional neural networks (CNNs) is an important task to increase trust in automatic medical decision making systems. In this study, we train a 3D CNN to detect Alzheimer's disease based on structural MRI scans of the brain. Then, we apply four different gradient-based and occlusion-bas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	104,845
1902.09347	Efficient Path Prediction for Semi-Supervised and Weakly Supervised Hierarchical Text Classification	Hierarchical text classification has many real-world applications. However, labeling a large number of documents is costly. In practice, we can use semi-supervised learning or weakly supervised learning (e.g., dataless classification) to reduce the labeling cost. In this paper, we propose a path cost-sensitive learning...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	122,396
2306.05246	A Task-driven Network for Mesh Classification and Semantic Part Segmentation	With the rapid development of geometric deep learning techniques, many mesh-based convolutional operators have been proposed to bridge irregular mesh structures and popular backbone networks. In this paper, we show that while convolutions are helpful, a simple architecture based exclusively on multi-layer perceptrons (...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	372,111
1007.3208	Link Graph Analysis for Adult Images Classification	In order to protect an image search engine's users from undesirable results adult images' classifier should be built. The information about links from websites to images is employed to create such a classifier. These links are represented as a bipartite website-image graph. Each vertex is equipped with scores of adultn...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	7,074
2311.17429	TARGET: Template-Transferable Backdoor Attack Against Prompt-based NLP Models via GPT4	Prompt-based learning has been widely applied in many low-resource NLP tasks such as few-shot scenarios. However, this paradigm has been shown to be vulnerable to backdoor attacks. Most of the existing attack methods focus on inserting manually predefined templates as triggers in the pre-training phase to train the vic...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	411,295
2302.05995	Multi-dimensional discrimination in Law and Machine Learning -- A comparative overview	AI-driven decision-making can lead to discrimination against certain individuals or social groups based on protected characteristics/attributes such as race, gender, or age. The domain of fairness-aware machine learning focuses on methods and algorithms for understanding, mitigating, and accounting for bias in AI/ML mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	345,248
2101.05684	Generating coherent spontaneous speech and gesture from text	Embodied human communication encompasses both verbal (speech) and non-verbal information (e.g., gesture and head movements). Recent advances in machine learning have substantially improved the technologies for generating synthetic versions of both of these types of data: On the speech side, text-to-speech systems are n...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	215,502
2004.04871	MRQy: An Open-Source Tool for Quality Control of MR Imaging Data	We sought to develop a quantitative tool to quickly determine relative differences in MRI volumes both within and between large MR imaging cohorts (such as available in The Cancer Imaging Archive (TCIA)), in order to help determine the generalizability of radiomics and machine learning schemes to unseen datasets. The t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	172,013
2004.13875	6G White Paper on Machine Learning in Wireless Communication Networks	The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has l...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	174,699
2011.04193	Optimal Predefined-time Trajectory Planning for a Free-floating Space Robot	With the development of human space exploration, the space environment is gradually filled with abandoned satellite debris and unknown micrometeorites, which will seriously affect capture motion of space robot. Hence, a novel fast collision-avoidance trajectory planning strategy for a dual-arm free-floating space robot...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	205,498
1802.07346	Cooperative Robot Localization Using Event-triggered Estimation	This paper describes a novel communication-spare cooperative localization algorithm for a team of mobile unmanned robotic vehicles. Exploiting an event-based estimation paradigm, robots only send measurements to neighbors when the expected innovation for state estimation is high. Since agents know the event-triggering ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	90,872
2112.03126	Label-Efficient Semantic Segmentation with Diffusion Models	Denoising diffusion probabilistic models have recently received much research attention since they outperform alternative approaches, such as GANs, and currently provide state-of-the-art generative performance. The superior performance of diffusion models has made them an appealing tool in several applications, includi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	270,095
1109.0530	Orthogonal Query Expansion	Over the last fifteen years, web searching has seen tremendous improvements. Starting from a nearly random collection of matching pages in 1995, today, search engines tend to satisfy the user's informational need on well-formulated queries. One of the main remaining challenges is to satisfy the users' needs when they p...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	11,942
2408.08146	KOALA: Enhancing Speculative Decoding for LLM via Multi-Layer Draft Heads with Adversarial Learning	Large Language Models (LLMs) exhibit high inference latency due to their autoregressive decoding nature. While the draft head in speculative decoding mitigates this issue, its full potential remains unexplored. In this paper, we introduce KOALA (K-layer Optimized Adversarial Learning Architecture), an orthogonal approa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	480,878
2205.13095	VizInspect Pro -- Automated Optical Inspection (AOI) solution	Traditional vision based Automated Optical Inspection (referred to as AOI in paper) systems present multiple challenges in factory settings including inability to scale across multiple product lines, requirement of vendor programming expertise, little tolerance to variations and lack of cloud connectivity for aggregate...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	298,801
1010.0150	Implementing Lego Agents Using Jason	Since many of the currently available multi-agent frameworks are generally mostly intended for research, it can be difficult to built multi-agent systems using physical robots. In this report I describe a way to combine the multi-agent framework Jason, an extended version of the agent-oriented programming language Agen...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	7,745
1710.03390	On Preemption and Overdetermination in Formal Theories of Causality	One of the key challenges when looking for the causes of a complex event is to determine the causal status of factors that are neither individually necessary nor individually sufficient to produce that event. In order to reason about how such factors should be taken into account, we need a vocabulary to distinguish dif...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	82,320
2402.05080	Designing three-way entangled and nonlocal two-way entangled single particle states via alternate quantum walks	Entanglement with single-particle states is advantageous in quantum technology because of their ability to encode and process information more securely than their multi-particle analogs. Threeway and nonlocal two-way entangled single-particle states are desirable in this context. Herein, we generate genuine three-way e...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	427,716
2412.19321	A novel framework for MCDM based on Z numbers and soft likelihood function	The optimization on the structure of process of information management under uncertain environment has attracted lots of attention from researchers around the world. Nevertheless, how to obtain accurate and rational evaluation from assessments produced by experts is still an open problem. Specially, intuitionistic fuzz...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,794
2108.13102	Measurement Setup Consideration and Implementation for Inductively Coupled Online Impedance Extraction	This thesis is organized as follows: Chapter 1 introduces the background, motivation, objectives, and contributions of this thesis. Chapter 2 presents a review of existing online impedance extraction approaches. Chapter 3 proposes the improved measurement setup of the inductive coupling approach and introduces the theo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	252,713
2307.07322	A Context-Aware Cutting Plane Selection Algorithm for Mixed-Integer Programming	The current cut selection algorithm used in mixed-integer programming solvers has remained largely unchanged since its creation. In this paper, we propose a set of new cut scoring measures, cut filtering techniques, and stopping criteria, extending the current state-of-the-art algorithm and obtaining a 5\% performance ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	379,361
2306.03287	ICDAR 2023 Competition on Structured Text Extraction from Visually-Rich Document Images	Structured text extraction is one of the most valuable and challenging application directions in the field of Document AI. However, the scenarios of past benchmarks are limited, and the corresponding evaluation protocols usually focus on the submodules of the structured text extraction scheme. In order to eliminate the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	371,260
2404.12899	Bayesian Co-navigation: Dynamic Designing of the Materials Digital Twins via Active Learning	Scientific advancement is universally based on the dynamic interplay between theoretical insights, modelling, and experimental discoveries. However, this feedback loop is often slow, including delayed community interactions and the gradual integration of experimental data into theoretical frameworks. This challenge is ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,078
2001.06917	Correcting Knowledge Base Assertions	The usefulness and usability of knowledge bases (KBs) is often limited by quality issues. One common issue is the presence of erroneous assertions, often caused by lexical or semantic confusion. We study the problem of correcting such assertions, and present a general correction framework which combines lexical matchin...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	160,921
2404.11269	DACAD: Domain Adaptation Contrastive Learning for Anomaly Detection in Multivariate Time Series	In time series anomaly detection (TSAD), the scarcity of labeled data poses a challenge to the development of accurate models. Unsupervised domain adaptation (UDA) offers a solution by leveraging labeled data from a related domain to detect anomalies in an unlabeled target domain. However, existing UDA methods assume c...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	447,442
2105.01202	All-Clear Flare Prediction Using Interval-based Time Series Classifiers	An all-clear flare prediction is a type of solar flare forecasting that puts more emphasis on predicting non-flaring instances (often relatively small flares and flare quiet regions) with high precision while still maintaining valuable predictive results. While many flare prediction studies do not address this problem ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	233,452
2211.11564	Adaptive Constraint Partition based Optimization Framework for Large-scale Integer Linear Programming(Student Abstract)	Integer programming problems (IPs) are challenging to be solved efficiently due to the NP-hardness, especially for large-scale IPs. To solve this type of IPs, Large neighborhood search (LNS) uses an initial feasible solution and iteratively improves it by searching a large neighborhood around the current solution. Howe...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	331,781
2002.02848	Unsupervised pretraining transfers well across languages	Cross-lingual and multi-lingual training of Automatic Speech Recognition (ASR) has been extensively investigated in the supervised setting. This assumes the existence of a parallel corpus of speech and orthographic transcriptions. Recently, contrastive predictive coding (CPC) algorithms have been proposed to pretrain A...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	163,051
1902.04697	Rethinking Generative Mode Coverage: A Pointwise Guaranteed Approach	Many generative models have to combat $\textit{missing modes}$. The conventional wisdom to this end is by reducing through training a statistical distance (such as $f$-divergence) between the generated distribution and provided data distribution. But this is more of a heuristic than a guarantee. The statistical distanc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	121,398
1907.12404	Computing the Value of Data: Towards Applied Data Minimalism	We present an approach to compute the monetary value of individual data points, in context of an automated decision system. The proposed method enables us to explore and implement a paradigm of data minimalism for large-scale machine learning systems. Data minimalistic implementations enhance scalability, while maintai...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	140,117
2106.00895	Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback	Recent years have seen an increased interest in using mean-field density based modelling and control strategy for deploying robotic swarms. In this paper, we study how to dynamically deploy the robots subject to their physical constraints to efficiently measure and reconstruct certain unknown spatial field (e.g. the ai...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	238,293
2102.03314	On Utility and Privacy in Synthetic Genomic Data	The availability of genomic data is essential to progress in biomedical research, personalized medicine, etc. However, its extreme sensitivity makes it problematic, if not outright impossible, to publish or share it. As a result, several initiatives have been launched to experiment with synthetic genomic data, e.g., us...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	218,703
2405.09459	Fourier Boundary Features Network with Wider Catchers for Glass Segmentation	Glass largely blurs the boundary between the real world and the reflection. The special transmittance and reflectance quality have confused the semantic tasks related to machine vision. Therefore, how to clear the boundary built by glass, and avoid over-capturing features as false positive information in deep structure...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	454,408
2409.05449	A semi-Lagrangian method for the direct numerical simulation of crystallization and precipitation at the pore scale	This article introduces a new efficient particle method for the numerical simulation of crystallization and precipitation at the pore scale of real rock geometries extracted by X-Ray tomography. It is based on the coupling between superficial velocity models of porous media, Lagrangian description of chemistry using Tr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	486,779
2207.03145	Active Learning and Multi-label Classification for Ellipsis and Coreference Detection in Conversational Question-Answering	In human conversations, ellipsis and coreference are commonly occurring linguistic phenomena. Although these phenomena are a mean of making human-machine conversations more fluent and natural, only few dialogue corpora contain explicit indications on which turns contain ellipses and/or coreferences. In this paper we ad...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	306,746
1211.6658	Nature-Inspired Mateheuristic Algorithms: Success and New Challenges	Despite the increasing popularity of metaheuristics, many crucially important questions remain unanswered. There are two important issues: theoretical framework and the gap between theory and applications. At the moment, the practice of metaheuristics is like heuristic itself, to some extent, by trial and error. Mathem...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	19,996
2410.03782	DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation	Adapting a pre-trained foundation model on downstream tasks should ensure robustness against distribution shifts without the need to retrain the whole model. Although existing weight interpolation methods are simple yet effective, we argue their static nature limits downstream performance while achieving efficiency. In...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	494,966
1611.09926	Choquet integral in decision analysis - lessons from the axiomatization	The Choquet integral is a powerful aggregation operator which lists many well-known models as its special cases. We look at these special cases and provide their axiomatic analysis. In cases where an axiomatization has been previously given in the literature, we connect the existing results with the framework that we h...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	64,742
2402.00438	The GREENBOT dataset: Multimodal mobile robotic dataset for a typical Mediterranean greenhouse	This paper introduces an innovative dataset specifically crafted for challenging agricultural settings (a greenhouse), where achieving precise localization is of paramount importance. The dataset was gathered using a mobile platform equipped with a set of sensors typically used in mobile robots, as it was moved through...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	425,610
2406.05821	F-LMM: Grounding Frozen Large Multimodal Models	Endowing Large Multimodal Models (LMMs) with visual grounding capability can significantly enhance AIs' understanding of the visual world and their interaction with humans. However, existing methods typically fine-tune the parameters of LMMs to learn additional segmentation tokens and overfit grounding and segmentation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	462,308
2301.09680	Quantum Heavy-tailed Bandits	In this paper, we study multi-armed bandits (MAB) and stochastic linear bandits (SLB) with heavy-tailed rewards and quantum reward oracle. Unlike the previous work on quantum bandits that assumes bounded/sub-Gaussian distributions for rewards, here we investigate the quantum bandits problem under a weaker assumption th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	341,567
2106.07348	Is it a click bait? Let's predict using Machine Learning	In this era of digitisation, news reader tend to read news online. This is because, online media instantly provides access to a wide variety of content. Thus, people don't have to wait for tomorrow's newspaper to know what's happening today. Along with these virtues, online news have some vices as well. One such vice i...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	240,887
2501.10093	An Energy-Aware RIoT System: Analysis, Modeling and Prediction in the SUPERIOT Framework	This paper presents a comprehensive analysis of the energy consumption characteristics of a Silicon (Si)-based Reconfigurable IoT (RIoT) node developed in the initial phase of the SUPERIOT project, focusing on key operating states, including Bluetooth Low Energy (BLE) communication, Narrow-Band Visible Light Communicat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	525,387
2309.15265	Finding Biomechanically Safe Trajectories for Robot Manipulation of the Human Body in a Search and Rescue Scenario	There has been increasing awareness of the difficulties in reaching and extracting people from mass casualty scenarios, such as those arising from natural disasters. While platforms have been designed to consider reaching casualties and even carrying them out of harm's way, the challenge of repositioning a casualty fro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,900
2012.07113	Uniform Circle Formation By Oblivious Swarm Robots	In this paper, we study the circle formation problem by multiple autonomous and homogeneous disc-shaped robots (also known as fat robots). The goal of the robots is to place themselves on the periphery of a circle. Circle formation has many real-world applications, such as boundary surveillance. This paper addresses on...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	211,347
1710.01895	Eugene Garfield's Scholarly Impact: A Scientometric Review	The concept of citation indexing has become deeply involved in many parts of research itself and the broad environment in which research plays an integral role, ranging from research evaluation, numerous indicators, to an increasingly wider range of scientific disciplines. In this article, we pay tribute to Eugene Garf...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	82,083
2401.17791	Graph Transformers without Positional Encodings	Recently, Transformers for graph representation learning have become increasingly popular, achieving state-of-the-art performance on a wide-variety of graph datasets, either alone or in combination with message-passing graph neural networks (MP-GNNs). Infusing graph inductive-biases in the innately structure-agnostic t...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	425,324
2402.03667	Large Language Models as an Indirect Reasoner: Contrapositive and Contradiction for Automated Reasoning	Recently, increasing attention has been focused on improving the ability of Large Language Models (LLMs) to perform complex reasoning. Advanced methods, such as Chain-of-Thought (CoT) and its variants, are found to enhance their reasoning skills by designing suitable prompts or breaking down complex problems into more ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	427,127
2110.06543	EIHW-MTG DiCOVA 2021 Challenge System Report	This paper aims to automatically detect COVID-19 patients by analysing the acoustic information embedded in coughs. COVID-19 affects the respiratory system, and, consequently, respiratory-related signals have the potential to contain salient information for the task at hand. We focus on analysing the spectrogram repres...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,662
1311.6510	Are all training examples equally valuable?	When learning a new concept, not all training examples may prove equally useful for training: some may have higher or lower training value than others. The goal of this paper is to bring to the attention of the vision community the following considerations: (1) some examples are better than others for training detector...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	28,659
1911.12815	Neural Network-Inspired Analog-to-Digital Conversion to Achieve Super-Resolution with Low-Precision RRAM Devices	Recent works propose neural network- (NN-) inspired analog-to-digital converters (NNADCs) and demonstrate their great potentials in many emerging applications. These NNADCs often rely on resistive random-access memory (RRAM) devices to realize the NN operations and require high-precision RRAM cells (6~12-bit) to achiev...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	155,496
1312.0288	Preliminary Results on 3D Channel Modeling: From Theory to Standardization	Three dimensional beamforming (3D) (also elevation beamforming) is now gaining a growing interest among researchers in wireless communication. The reason can be attributed to its potential to enable a variety of strategies like sector or user specific elevation beamforming and cell-splitting. Since these techniques can...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,777
2001.11258	Harnessing Code Switching to Transcend the Linguistic Barrier	Code mixing (or code switching) is a common phenomenon observed in social-media content generated by a linguistically diverse user-base. Studies show that in the Indian sub-continent, a substantial fraction of social media posts exhibit code switching. While the difficulties posed by code mixed documents to further dow...	false	false	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	162,024
2209.10681	A Supervisory Volt/VAR Control Scheme for Coordinating Voltage Regulators with Smart Inverters on a Distribution System	This paper focuses on the effective use of smart inverters for Volt/Var control (VVC) on a distribution system. New smart inverters offer Var support capability but for their effective use they need to be coordinated with existing Volt/Var schemes. A new VVC scheme is proposed to facilitate such coordination. The propo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	318,937
2411.03620	A Subsampling Based Neural Network for Spatial Data	The application of deep neural networks in geospatial data has become a trending research problem in the present day. A significant amount of statistical research has already been introduced, such as generalized least square optimization by incorporating spatial variance-covariance matrix, considering basis functions i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	505,969
2106.03904	When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting	Accurate and trustworthy epidemic forecasting is an important problem that has impact on public health planning and disease mitigation. Most existing epidemic forecasting models disregard uncertainty quantification, resulting in mis-calibrated predictions. Recent works in deep neural models for uncertainty-aware time-s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	239,500
2412.18107	SongGLM: Lyric-to-Melody Generation with 2D Alignment Encoding and Multi-Task Pre-Training	Lyric-to-melody generation aims to automatically create melodies based on given lyrics, requiring the capture of complex and subtle correlations between them. However, previous works usually suffer from two main challenges: 1) lyric-melody alignment modeling, which is often simplified to one-syllable/word-to-one-note a...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	520,259
2212.10320	Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data	Importance: The prevalence of severe mental illnesses (SMIs) in the United States is approximately 3% of the whole population. The ability to conduct risk screening of SMIs at large scale could inform early prevention and treatment. Objective: A scalable machine learning based tool was developed to conduct population...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	337,415
2404.07032	An Evidential-enhanced Tri-Branch Consistency Learning Method for Semi-supervised Medical Image Segmentation	Semi-supervised segmentation presents a promising approach for large-scale medical image analysis, effectively reducing annotation burdens while achieving comparable performance. This methodology holds substantial potential for streamlining the segmentation process and enhancing its feasibility within clinical settings...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,695
1812.06585	Generalizable Meta-Heuristic based on Temporal Estimation of Rewards for Large Scale Blackbox Optimization	The generalization abilities of heuristic optimizers may deteriorate with the increment of the search space dimensionality. To achieve generalized performance across Large Scale Blackbox Optimization (LSBO) tasks, it ispossible to ensemble several heuristics and devise a meta-heuristic to control their initiation. This...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	116,643
2104.10857	Attribute-Modulated Generative Meta Learning for Zero-Shot Classification	Zero-shot learning (ZSL) aims to transfer knowledge from seen classes to semantically related unseen classes, which are absent during training. The promising strategies for ZSL are to synthesize visual features of unseen classes conditioned on semantic side information and to incorporate meta-learning to eliminate the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	231,741
2106.04176	Efficient solution method based on inverse dynamics for optimal control problems of rigid body systems	We propose an efficient way of solving optimal control problems for rigid-body systems on the basis of inverse dynamics and the multiple-shooting method. We treat all variables, including the state, acceleration, and control input torques, as optimization variables and treat the inverse dynamics as an equality constrai...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	239,619
2310.05070	CO-ASnet :A Smart Contract Architecture Design based on Blockchain Technology with Active Sensor Networks	The influence of opinion leaders impacts different aspects of social finance. How to analyse the utility of opinion leaders' influence in realizing assets on the blockchain and adopt a compliant regulatory scheme is worth exploring and pondering. Taking Musk's call on social media to buy Dogecoin as an example, this pa...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	397,967
2307.12437	Robust explicit model predictive control for hybrid linear systems with parameter uncertainties	Explicit model-predictive control (MPC) is a widely used control design method that employs optimization tools to find control policies offline; commonly it is posed as a semi-definite program (SDP) or as a mixed-integer SDP in the case of hybrid systems. However, mixed-integer SDPs are computationally expensive, motiv...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	381,255
1504.07615	Throughput Maximization for Two-way Relay Channels with Energy Harvesting Nodes: The Impact of Relaying Strategies	In this paper, we study the two-way relay channel with energy harvesting nodes. In particular, we find transmission policies that maximize the sum-throughput for two-way relay channels when the relay does not employ a data buffer. The relay can perform decode-and-forward, compress-and-forward, compute-and-forward or am...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,561
2310.03617	RouteKG: A knowledge graph-based framework for route prediction on road networks	Short-term route prediction on road networks allows us to anticipate the future trajectories of road users, enabling a plethora of intelligent transportation applications such as dynamic traffic control or personalized route recommendation. Despite recent advances in this area, existing methods focus primarily on learn...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	397,351
2205.06684	The Effectiveness of Temporal Dependency in Deepfake Video Detection	Deepfakes are a form of synthetic image generation used to generate fake videos of individuals for malicious purposes. The resulting videos may be used to spread misinformation, reduce trust in media, or as a form of blackmail. These threats necessitate automated methods of deepfake video detection. This paper investig...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,315
1902.06289	Neural Network-Based Dynamic Threshold Detection for Non-Volatile Memories	The memory physics induced unknown offset of the channel is a critical and difficult issue to be tackled for many non-volatile memories (NVMs). In this paper, we first propose novel neural network (NN) detectors by using the multilayer perceptron (MLP) network and the recurrent neural network (RNN), which can effective...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	121,731
1907.00408	GarmNet: Improving Global with Local Perception for Robotic Laundry Folding	Developing autonomous assistants to help with domestic tasks is a vital topic in robotics research. Among these tasks, garment folding is one of them that is still far from being achieved mainly due to the large number of possible configurations that a crumpled piece of clothing may exhibit. Research has been done on e...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	137,032
1204.3100	Modular design of jointly optimal controllers and forwarding policies for wireless control	We consider the joint design of packet forwarding policies and controllers for wireless control loops where sensor measurements are sent to the controller over an unreliable and energy-constrained multi-hop wireless network. For fixed sampling rate of the sensor, the co-design problem separates into two well-defined an...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	15,462
2410.18460	Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcare	Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in various healthcare applications. However, despite such a promising future, there are multiple challenges and obstacles that remain for their...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	501,895
2208.09997	Spatially Selective Active Noise Control Systems	Active noise control (ANC) systems are commonly designed to achieve maximal sound reduction regardless of the incident direction of the sound. When desired sound is present, the state-of-the-art methods add a separate system to reconstruct it. This can result in distortion and latency. In this work, we propose a multi-...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	313,909

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