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
2011.05180	Generation of Human-aware Navigation Maps using Graph Neural Networks	Minimising the discomfort caused by robots when navigating in social situations is crucial for them to be accepted. The paper presents a machine learning-based framework that bootstraps existing one-dimensional datasets to generate a cost map dataset and a model combining Graph Neural Network and Convolutional Neural N...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	205,827
2003.10526	Hessian metric via transport information geometry	We propose to study the Hessian metric of a functional on the space of probability measures endowed with the Wasserstein $2$-metric. We name it transport Hessian metric, which contains and extends the classical Wasserstein-$2$ metric. We formulate several dynamical systems associated with transport Hessian metrics. Sev...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	169,357
2208.09550	Sudakov-Fernique post-AMP, and a new proof of the local convexity of the TAP free energy	In many problems in modern statistics and machine learning, it is often of interest to establish that a first order method on a non-convex risk function eventually enters a region of parameter space in which the risk is locally convex. We derive an asymptotic comparison inequality, which we call the Sudakov-Fernique po...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	313,732
2108.05891	Page-level Optimization of e-Commerce Item Recommendations	The item details page (IDP) is a web page on an e-commerce website that provides information on a specific product or item listing. Just below the details of the item on this page, the buyer can usually find recommendations for other relevant items. These are typically in the form of a series of modules or carousels, w...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	250,449
2401.15377	Validation of artificial neural networks to model the acoustic behaviour of induction motors	In the last decade, the sound quality of electric induction motors is a hot topic in the research field. Specially, due to its high number of applications, the population is exposed to physical and psychological discomfort caused by the noise emission. Therefore, it is necessary to minimise its psychological impact on ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	424,429
2410.18111	Data Efficiency for Large Recommendation Models	Large recommendation models (LRMs) are fundamental to the multi-billion dollar online advertising industry, processing massive datasets of hundreds of billions of examples before transitioning to continuous online training to adapt to rapidly changing user behavior. The massive scale of data directly impacts both compu...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	501,754
1909.06296	Bayesian parameter estimation using conditional variational autoencoders for gravitational-wave astronomy	Gravitational wave (GW) detection is now commonplace and as the sensitivity of the global network of GW detectors improves, we will observe $\mathcal{O}(100)$s of transient GW events per year. The current methods used to estimate their source parameters employ optimally sensitive but computationally costly Bayesian inf...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	145,338
2202.00076	Optimal Estimation of Off-Policy Policy Gradient via Double Fitted Iteration	Policy gradient (PG) estimation becomes a challenge when we are not allowed to sample with the target policy but only have access to a dataset generated by some unknown behavior policy. Conventional methods for off-policy PG estimation often suffer from either significant bias or exponentially large variance. In this p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	278,011
2312.06674	Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations	We introduce Llama Guard, an LLM-based input-output safeguard model geared towards Human-AI conversation use cases. Our model incorporates a safety risk taxonomy, a valuable tool for categorizing a specific set of safety risks found in LLM prompts (i.e., prompt classification). This taxonomy is also instrumental in cla...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	414,627
2303.02411	The Contribution of Knowledge in Visiolinguistic Learning: A Survey on Tasks and Challenges	Recent advancements in visiolinguistic (VL) learning have allowed the development of multiple models and techniques that offer several impressive implementations, able to currently resolve a variety of tasks that require the collaboration of vision and language. Current datasets used for VL pre-training only contain a ...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	349,345
2009.14684	Benchmark for Anonymous Video Analytics	Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing interest, no commonly accepted benchmark exists to evaluate and compare their performance. In this paper, we pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	198,110
2401.05159	Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN	This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model training. Synthetic data generation plays a pivotal role in mitigating challenges associated with limited labeled datasets, thereby facilitat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	420,661
2109.09862	Language Identification with a Reciprocal Rank Classifier	Language identification is a critical component of language processing pipelines (Jauhiainen et al.,2019) and is not a solved problem in real-world settings. We present a lightweight and effective language identifier that is robust to changes of domain and to the absence of copious training data. The key idea for cla...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	256,427
1401.2692	On the Optimality of Treating Interference as Noise for $K$ user Parallel Gaussian Interference Networks	It has been shown recently by Geng et al. that in a $K$ user Gaussian interference network, if for each user the desired signal strength is no less than the sum of the strengths of the strongest interference from this user and the strongest interference to this user (all signal strengths measured in dB scale), then pow...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	29,777
2409.19014	FLEX: Expert-level False-Less EXecution Metric for Reliable Text-to-SQL Benchmark	Text-to-SQL systems have become crucial for translating natural language into SQL queries in various industries, enabling non-technical users to perform complex data operations. The need for accurate evaluation methods has increased as these systems have grown more sophisticated. However, the Execution Accuracy (EX), t...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	492,508
2009.11943	A distributed service-matching coverage via heterogeneous mobile agents	We propose a distributed deployment solution for a group of mobile agents that should provide a service for a dense set of targets. The agents are heterogeneous in a sense that their quality of service (QoS), modeled as a spatial Gaussian distribution, is different. To provide the best service, the objective is to depl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	197,286
2012.12585	Accurate evaluation of integrals in slender-body formulations for fibers in viscous flow	A non-local slender body approximation for slender flexible fibers in Stokes flow can be derived, yielding an integral equation along the center lines of the fibers that involves a slenderness parameter. The formulation contains a so-called finite part singular integral, and can in the case of several fibers or evaluat...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	212,986
1612.03901	Enhancing the Physical Layer Security of Non-orthogonal Multiple Access in Large-Scale Networks	This paper investigates the physical layer security of non-orthogonal multiple access (NOMA) in large-scale networks with invoking stochastic geometry. Both single-antenna and multiple-antenna aided transmission scenarios are considered, where the base station (BS) communicates with randomly distributed NOMA users. In ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,439
2206.13517	ProGen2: Exploring the Boundaries of Protein Language Models	Attention-based models trained on protein sequences have demonstrated incredible success at classification and generation tasks relevant for artificial intelligence-driven protein design. However, we lack a sufficient understanding of how very large-scale models and data play a role in effective protein model developme...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	305,007
2406.04467	Small-E: Small Language Model with Linear Attention for Efficient Speech Synthesis	Recent advancements in text-to-speech (TTS) powered by language models have showcased remarkable capabilities in achieving naturalness and zero-shot voice cloning. Notably, the decoder-only transformer is the prominent architecture in this domain. However, transformers face challenges stemming from their quadratic comp...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	461,691
2404.11207	Exploring the Transferability of Visual Prompting for Multimodal Large Language Models	Although Multimodal Large Language Models (MLLMs) have demonstrated promising versatile capabilities, their performance is still inferior to specialized models on downstream tasks, which makes adaptation necessary to enhance their utility. However, fine-tuning methods require independent training for every model, leadi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	447,421
2405.13048	Human-Generative AI Collaborative Problem Solving Who Leads and How Students Perceive the Interactions	This research investigates distinct human-generative AI collaboration types and students' interaction experiences when collaborating with generative AI (i.e., ChatGPT) for problem-solving tasks and how these factors relate to students' sense of agency and perceived collaborative problem solving. By analyzing the survey...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	455,775
2104.09399	TREC Deep Learning Track: Reusable Test Collections in the Large Data Regime	The TREC Deep Learning (DL) Track studies ad hoc search in the large data regime, meaning that a large set of human-labeled training data is available. Results so far indicate that the best models with large data may be deep neural networks. This paper supports the reuse of the TREC DL test collections in three ways. F...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	231,226
2406.00375	Teledrive: An Embodied AI based Telepresence System	This article presents Teledrive, a telepresence robotic system with embodied AI features that empowers an operator to navigate the telerobot in any unknown remote place with minimal human intervention. We conceive Teledrive in the context of democratizing remote care-giving for elderly citizens as well as for isolated ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	459,822
2406.12703	Coarse-Fine Spectral-Aware Deformable Convolution For Hyperspectral Image Reconstruction	We study the inverse problem of Coded Aperture Snapshot Spectral Imaging (CASSI), which captures a spatial-spectral data cube using snapshot 2D measurements and uses algorithms to reconstruct 3D hyperspectral images (HSI). However, current methods based on Convolutional Neural Networks (CNNs) struggle to capture long-r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,536
2407.10954	A Unified Differentiable Boolean Operator with Fuzzy Logic	This paper presents a unified differentiable boolean operator for implicit solid shape modeling using Constructive Solid Geometry (CSG). Traditional CSG relies on min, max operators to perform boolean operations on implicit shapes. But because these boolean operators are discontinuous and discrete in the choice of oper...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	473,196
1706.09829	Towards Monocular Vision based Obstacle Avoidance through Deep Reinforcement Learning	Obstacle avoidance is a fundamental requirement for autonomous robots which operate in, and interact with, the real world. When perception is limited to monocular vision avoiding collision becomes significantly more challenging due to the lack of 3D information. Conventional path planners for obstacle avoidance require...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	76,208
1210.4695	Regulating the information in spikes: a useful bias	The bias/variance tradeoff is fundamental to learning: increasing a model's complexity can improve its fit on training data, but potentially worsens performance on future samples. Remarkably, however, the human brain effortlessly handles a wide-range of complex pattern recognition tasks. On the basis of these conflicti...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	19,156
1409.5340	Belief revision by examples	A common assumption in belief revision is that the reliability of the information sources is either given, derived from temporal information, or the same for all. This article does not describe a new semantics for integration but the problem of obtaining the reliability of the sources given the result of a previous mer...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	36,160
2309.03787	USA: Universal Sentiment Analysis Model & Construction of Japanese Sentiment Text Classification and Part of Speech Dataset	Sentiment analysis is a pivotal task in the domain of natural language processing. It encompasses both text-level sentiment polarity classification and word-level Part of Speech(POS) sentiment polarity determination. Such analysis challenges models to understand text holistically while also extracting nuanced informati...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	390,508
1902.07830	Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges	Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple sensing modalities can be fused to exploit their complementary p...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	122,066
1608.07017	Ambient Sound Provides Supervision for Visual Learning	The sound of crashing waves, the roar of fast-moving cars -- sound conveys important information about the objects in our surroundings. In this work, we show that ambient sounds can be used as a supervisory signal for learning visual models. To demonstrate this, we train a convolutional neural network to predict a stat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	60,186
2208.07442	Viability of Robot-supported Flipped Classes in English for Medical Use Reading Comprehension	This study delved into the viability of Robot-supported flipped classes in English for Medical Purposes reading comprehension. In a 16-session course, the reading comprehension and then workspace performance of 444 students, with Commercially-Off-The-Shelf and Self-Generated robot flipped classes were compared. The res...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	313,045
2205.08480	Effort Informed Roadmaps (EIRM*): Efficient Asymptotically Optimal Multiquery Planning by Actively Reusing Validation Effort	Multiquery planning algorithms find paths between various different starts and goals in a single search space. They are designed to do so efficiently by reusing information across planning queries. This information may be computed before or during the search and often includes knowledge of valid paths. Using known vali...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	296,956
2006.05623	Training with Multi-Layer Embeddings for Model Reduction	Modern recommendation systems rely on real-valued embeddings of categorical features. Increasing the dimension of embedding vectors improves model accuracy but comes at a high cost to model size. We introduce a multi-layer embedding training (MLET) architecture that trains embeddings via a sequence of linear layers to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,143
2005.11348	Microphone Array Based Surveillance Audio Classification	The work assessed seven classical classifiers and two beamforming algorithms for detecting surveillance sound events. The tests included the use of AWGN with -10 dB to 30 dB SNR. Data Augmentation was also employed to improve algorithms' performance. The results showed that the combination of SVM and Delay-and-Sum (DaS...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	178,446
1910.11691	Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm	Speaker diarization based on bottom-up clustering of speech segments by acoustic similarity is often highly sensitive to the choice of hyperparameters, such as the initial number of clusters and feature weighting. Optimizing these hyperparameters is difficult and often not robust across different data sets. We recently...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	150,862
2103.08308	Machine Learning for Massive Industrial Internet of Things	Industrial Internet of Things (IIoT) revolutionizes the future manufacturing facilities by integrating the Internet of Things technologies into industrial settings. With the deployment of massive IIoT devices, it is difficult for the wireless network to support the ubiquitous connections with diverse quality-of-service...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	224,866
2103.08735	Joint Satellite Gateway Deployment & Controller Placement in Software-Defined 5G-Satellite Integrated Networks	Several challenging optimization problems arise while considering the deployment of the space-air-ground integrated networks (SAGINs), among which the optimal satellite gateway deployment problem is of significant importance. Moreover, with the increasing interest in the software-defined integration of 5G networks and ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	224,970
2003.08429	STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos	Existing methods for instance segmentation in videos typically involve multi-stage pipelines that follow the tracking-by-detection paradigm and model a video clip as a sequence of images. Multiple networks are used to detect objects in individual frames, and then associate these detections over time. Hence, these metho...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	168,733
2502.08417	Handwritten Text Recognition: A Survey	Handwritten Text Recognition (HTR) has become an essential field within pattern recognition and machine learning, with applications spanning historical document preservation to modern data entry and accessibility solutions. The complexity of HTR lies in the high variability of handwriting, which makes it challenging to...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	533,008
1810.12692	Research Issues in Mining User Behavioral Rules for Context-Aware Intelligent Mobile Applications	Context-awareness in smart mobile applications is a growing area of study, because of it's intelligence in the applications. In order to build context-aware intelligent applications, mining contextual behavioral rules of individual smartphone users utilizing their phone log data is the key. However, to mine these rules...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,825
1607.00662	Unsupervised Learning of 3D Structure from Images	A key goal of computer vision is to recover the underlying 3D structure from 2D observations of the world. In this paper we learn strong deep generative models of 3D structures, and recover these structures from 3D and 2D images via probabilistic inference. We demonstrate high-quality samples and report log-likelihoods...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	58,123
1910.02223	A Machine Learning Analysis of the Features in Deceptive and Credible News	Fake news is a type of pervasive propaganda that spreads misinformation online, taking advantage of social media's extensive reach to manipulate public perception. Over the past three years, fake news has become a focal discussion point in the media due to its impact on the 2016 U.S. presidential election. Fake news ca...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	148,178
2102.01593	FEDZIP: A Compression Framework for Communication-Efficient Federated Learning	Federated Learning marks a turning point in the implementation of decentralized machine learning (especially deep learning) for wireless devices by protecting users' privacy and safeguarding raw data from third-party access. It assigns the learning process independently to each client. First, clients locally train a ma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	218,168
1905.03416	Prioritized Inverse Kinematics: Nonsmoothness, Trajectory Existence, Task Convergence, Stability	In this paper, we study various theoretical properties of a class of prioritized inverse kinematics (PIK) solutions that can be considered as a class of (output regulation or tracking) control laws of a dynamical system with prioritized multiple outputs. We first develop tools to investigate nonsmoothness of PIK soluti...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	130,193
1601.04373	Rate Maximization of Decode-and-Forward Relaying Systems with RF Energy Harvesting	We consider a three-node decode-and-forward (DF) half-duplex relaying system, where the source first harvests RF energy from the relay, and then uses this energy to transmit information to the destination via the relay. We assume that the information transfer and wireless power transfer phases alternate over time in th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,012
2305.18304	Semantic-aware Digital Twin for Metaverse: A Comprehensive Review	To facilitate the deployment of digital twins in Metaverse, the paradigm with semantic awareness has been proposed as a means for enabling accurate and task-oriented information extraction with inherent intelligence. However, this framework requires all devices in the Metaverse environment to be directly linked with th...	false	false	false	false	false	true	false	false	true	false	false	false	false	true	false	false	false	true	368,946
2005.11064	Human-Like Decision Making for Autonomous Driving: A Noncooperative Game Theoretic Approach	Considering that human-driven vehicles and autonomous vehicles (AVs) will coexist on roads in the future for a long time, how to merge AVs into human drivers traffic ecology and minimize the effect of AVs and their misfit with human drivers, are issues worthy of consideration. Moreover, different passengers have differ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	178,371
2006.03762	Deep Octree-based CNNs with Output-Guided Skip Connections for 3D Shape and Scene Completion	Acquiring complete and clean 3D shape and scene data is challenging due to geometric occlusion and insufficient views during 3D capturing. We present a simple yet effective deep learning approach for completing the input noisy and incomplete shapes or scenes. Our network is built upon the octree-based CNNs (O-CNN) with...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	180,427
2502.06559	Can We Trust AI Benchmarks? An Interdisciplinary Review of Current Issues in AI Evaluation	Quantitative Artificial Intelligence (AI) Benchmarks have emerged as fundamental tools for evaluating the performance, capability, and safety of AI models and systems. Currently, they shape the direction of AI development and are playing an increasingly prominent role in regulatory frameworks. As their influence grows,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	532,125
2009.08614	Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos	Temporal grounding of natural language in untrimmed videos is a fundamental yet challenging multimedia task facilitating cross-media visual content retrieval. We focus on the weakly supervised setting of this task that merely accesses to coarse video-level language description annotation without temporal boundary, whic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,292
2208.14326	GaitFi: Robust Device-Free Human Identification via WiFi and Vision Multimodal Learning	As an important biomarker for human identification, human gait can be collected at a distance by passive sensors without subject cooperation, which plays an essential role in crime prevention, security detection and other human identification applications. At present, most research works are based on cameras and comput...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	315,288
2006.12714	On Compression Principle and Bayesian Optimization for Neural Networks	Finding methods for making generalizable predictions is a fundamental problem of machine learning. By looking into similarities between the prediction problem for unknown data and the lossless compression we have found an approach that gives a solution. In this paper we propose a compression principle that states that ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	183,683
2105.09016	E(n) Equivariant Normalizing Flows	This paper introduces a generative model equivariant to Euclidean symmetries: E(n) Equivariant Normalizing Flows (E-NFs). To construct E-NFs, we take the discriminative E(n) graph neural networks and integrate them as a differential equation to obtain an invertible equivariant function: a continuous-time normalizing fl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	235,943
2010.11491	Overview of Networked Supervisory Control with Imperfect Communication Channels	This paper presents an overview of the networked supervisory control framework for discrete event systems with imperfect communication networks, which can be divided into the centralized supervisory control setup and the decentralized supervisory control setup. We review the state-of-art networked control frameworks wi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	202,278
2412.10982	MedG-KRP: Medical Graph Knowledge Representation Probing	Large language models (LLMs) have recently emerged as powerful tools, finding many medical applications. LLMs' ability to coalesce vast amounts of information from many sources to generate a response-a process similar to that of a human expert-has led many to see potential in deploying LLMs for clinical use. However, m...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	517,200
1907.12047	A difficulty ranking approach to personalization in E-learning	The prevalence of e-learning systems and on-line courses has made educational material widely accessible to students of varying abilities and backgrounds. There is thus a growing need to accommodate for individual differences in e-learning systems. This paper presents an algorithm called EduRank for personalizing educa...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	140,021
2110.00645	How To Not Drive: Learning Driving Constraints from Demonstration	We propose a new scheme to learn motion planning constraints from human driving trajectories. Behavioral and motion planning are the key components in an autonomous driving system. The behavioral planning is responsible for high-level decision making required to follow traffic rules and interact with other road partici...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	258,470
1403.3298	The role of network embeddedness on the selection of collaboration partners: An agent-based model with empirical validation	We use a data-driven agent-based model to study the core-periphery structure of two collaboration networks, R&D alliances between firms and co-authorship relations between scientists. To characterize the network embeddedness of agents, we introduce a coreness value, obtained from a weighted $k$-core decomposition. We s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	31,556
1307.7770	A Connection between Good Rate-distortion Codes and Backward DMCs	Let $X^n\in\mathcal{X}^n$ be a sequence drawn from a discrete memoryless source, and let $Y^n\in\mathcal{Y}^n$ be the corresponding reconstruction sequence that is output by a good rate-distortion code. This paper establishes a property of the joint distribution of $(X^n,Y^n)$. It is shown that for $D>0$, the input-out...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,128
2002.00583	CoTK: An Open-Source Toolkit for Fast Development and Fair Evaluation of Text Generation	In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions. We present CoTK, an open-source toolkit aiming to support fast development and fair evaluation of text generation. In mo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	162,403
2405.11658	A Starting Point for Dynamic Community Detection with Leiden Algorithm	Real-world graphs often evolve over time, making community or cluster detection a crucial task. In this technical report, we extend three dynamic approaches - Naive-dynamic (ND), Delta-screening (DS), and Dynamic Frontier (DF) - to our multicore implementation of the Leiden algorithm, known for its high-quality communi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	455,229
2112.13681	Wholesale Electricity Price Forecasting using Integrated Long-term Recurrent Convolutional Network Model	Electricity price is a key factor affecting the decision-making for all market participants. Accurate forecasting of electricity prices is very important and is also very challenging since electricity price is highly volatile due to various factors. This paper proposes an integrated long-term recurrent convolutional ne...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	273,326
2410.05759	3D UAV Trajectory Planning for IoT Data Collection via Matrix-Based Evolutionary Computation	UAVs are increasingly becoming vital tools in various wireless communication applications including internet of things (IoT) and sensor networks, thanks to their rapid and agile non-terrestrial mobility. Despite recent research, planning three-dimensional (3D) UAV trajectories over a continuous temporal-spatial domain ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	495,898
1912.03787	Getting Topology and Point Cloud Generation to Mesh	In this work, we explore the idea that effective generative models for point clouds under the autoencoding framework must acknowledge the relationship between a continuous surface, a discretized mesh, and a set of points sampled from the surface. This view motivates a generative model that works by progressively deform...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,688
2410.01695	From Prohibition to Adoption: How Hong Kong Universities Are Navigating ChatGPT in Academic Workflows	This paper aims at comparing the time when Hong Kong universities used to ban ChatGPT to the current periods where it has become integrated in the academic processes. Bolted by concerns of integrity and ethical issues in technologies, institutions have adapted by moving towards the center adopting AI literacy and respo...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	493,896
2103.15912	Data Augmentation in a Hybrid Approach for Aspect-Based Sentiment Analysis	Data augmentation is a way to increase the diversity of available data by applying constrained transformations on the original data. This strategy has been widely used in image classification but has to the best of our knowledge not yet been used in aspect-based sentiment analysis (ABSA). ABSA is a text analysis techni...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	227,369
2307.10198	Has China caught up to the US in AI research? An exploration of mimetic isomorphism as a model for late industrializers	Artificial Intelligence (AI), a cornerstone of 21st-century technology, has seen remarkable growth in China. In this paper, we examine China's AI development process, demonstrating that it is characterized by rapid learning and differentiation, surpassing the export-oriented growth propelled by Foreign Direct Investmen...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	380,457
2206.10129	Automatic Concept Extraction for Concept Bottleneck-based Video Classification	Recent efforts in interpretable deep learning models have shown that concept-based explanation methods achieve competitive accuracy with standard end-to-end models and enable reasoning and intervention about extracted high-level visual concepts from images, e.g., identifying the wing color and beak length for bird-spec...	false	false	false	false	false	true	true	false	false	false	false	true	false	false	false	false	false	false	303,806
2409.04808	HULLMI: Human vs LLM identification with explainability	As LLMs become increasingly proficient at producing human-like responses, there has been a rise of academic and industrial pursuits dedicated to flagging a given piece of text as "human" or "AI". Most of these pursuits involve modern NLP detectors like T5-Sentinel and RoBERTa-Sentinel, without paying too much attention...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	486,517
1705.06211	An Investigation of Newton-Sketch and Subsampled Newton Methods	Sketching, a dimensionality reduction technique, has received much attention in the statistics community. In this paper, we study sketching in the context of Newton's method for solving finite-sum optimization problems in which the number of variables and data points are both large. We study two forms of sketching that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	73,606
1705.09597	Extracting 3D Vascular Structures from Microscopy Images using Convolutional Recurrent Networks	Vasculature is known to be of key biological significance, especially in the study of cancer. As such, considerable effort has been focused on the automated measurement and analysis of vasculature in medical and pre-clinical images. In tumors in particular, the vascular networks may be extremely irregular and the appea...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,231
2302.05046	Information-Theoretical Approach to Integrated Pulse-Doppler Radar and Communication Systems	Integrated sensing and communication improves the design of systems by combining sensing and communication functions for increased efficiency, accuracy, and cost savings. The optimal integration requires understanding the trade-off between sensing and communication, but this can be difficult due to the lack of unified ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	344,912
1807.10363	Message-passing neural networks for high-throughput polymer screening	Machine learning methods have shown promise in predicting molecular properties, and given sufficient training data machine learning approaches can enable rapid high-throughput virtual screening of large libraries of compounds. Graph-based neural network architectures have emerged in recent years as the most successful ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	103,920
2104.01305	Nova-LSM: A Distributed, Component-based LSM-tree Key-value Store	The cloud infrastructure motivates disaggregation of monolithic data stores into components that are assembled together based on an application's workload. This study investigates disaggregation of an LSM-tree key-value store into components that communicate using RDMA. These components separate storage from processing...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	228,300
2306.09775	Using Machine Learning Methods for Automation of Size Grid Building and Management	Fashion apparel companies require planning for the next season, a year in advance for supply chain management. This study focuses on size selection decision making for Levi Strauss. Currently, the region and planning group level size grids are built and managed manually. The company suffers from the workload it creates...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	373,957
1305.2265	Quality Measures of Parameter Tuning for Aggregated Multi-Objective Temporal Planning	Parameter tuning is recognized today as a crucial ingredient when tackling an optimization problem. Several meta-optimization methods have been proposed to find the best parameter set for a given optimization algorithm and (set of) problem instances. When the objective of the optimization is some scalar quality of the ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	24,502
2108.07927	Fed-TGAN: Federated Learning Framework for Synthesizing Tabular Data	Generative Adversarial Networks (GANs) are typically trained to synthesize data, from images and more recently tabular data, under the assumption of directly accessible training data. Recently, federated learning (FL) is an emerging paradigm that features decentralized learning on client's local data with a privacy-pre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	251,063
2103.09279	Quadratic-exponential functionals of Gaussian quantum processes	This paper is concerned with exponential moments of integral-of-quadratic functions of quantum processes with canonical commutation relations of position-momentum type. Such quadratic-exponential functionals (QEFs) arise as robust performance criteria in control problems for open quantum harmonic oscillators (OQHOs) dr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	225,121
2103.16051	Reduced Dynamics and Control for an Autonomous Bicycle	In this paper, we propose the reduced model for the full dynamics of a bicycle and analyze its nonlinear behavior under a proportional control law for steering. Based on the Gibbs-Appell equations for the Whipple bicycle, we obtain a second-order nonlinear ordinary differential equation (ODE) that governs the bicycle's...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	227,436
2102.02885	Adversarial Robustness Study of Convolutional Neural Network for Lumbar Disk Shape Reconstruction from MR images	Machine learning technologies using deep neural networks (DNNs), especially convolutional neural networks (CNNs), have made automated, accurate, and fast medical image analysis a reality for many applications, and some DNN-based medical image analysis systems have even been FDA-cleared. Despite the progress, challenges...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	218,547
2410.09489	Towards Efficient Visual-Language Alignment of the Q-Former for Visual Reasoning Tasks	Recent advancements in large language models have demonstrated enhanced capabilities in visual reasoning tasks by employing additional encoders for aligning different modalities. While the Q-Former has been widely used as a general encoder for aligning several modalities including image, video, audio, and 3D with large...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	497,619
1202.3718	On the Complexity of Decision Making in Possibilistic Decision Trees	When the information about uncertainty cannot be quantified in a simple, probabilistic way, the topic of possibilistic decision theory is often a natural one to consider. The development of possibilistic decision theory has lead to a series of possibilistic criteria, e.g pessimistic possibilistic qualitative utility, p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	14,390
2307.12166	The Imitation Game: Detecting Human and AI-Generated Texts in the Era of ChatGPT and BARD	The potential of artificial intelligence (AI)-based large language models (LLMs) holds considerable promise in revolutionizing education, research, and practice. However, distinguishing between human-written and AI-generated text has become a significant task. This paper presents a comparative study, introducing a nove...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	381,164
2407.07229	Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models	Generative models producing images have enormous potential to advance discoveries across scientific fields and require metrics capable of quantifying the high dimensional output. We propose that astrophysics data, such as galaxy images, can test generative models with additional physics-motivated ground truths in addit...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	471,678
1802.09184	Variance Reduction Methods for Sublinear Reinforcement Learning	There is a technical issue in the analysis that is not easily fixable. We, therefore, withdraw the submission. Sorry for the inconvenience.	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	91,288
2006.04680	Dimensionality Reduction for Sentiment Classification: Evolving for the Most Prominent and Separable Features	In sentiment classification, the enormous amount of textual data, its immense dimensionality, and inherent noise make it extremely difficult for machine learning classifiers to extract high-level and complex abstractions. In order to make the data less sparse and more statistically significant, the dimensionality reduc...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	180,775
2103.11972	Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals	There has been a recent resurgence of interest in explainable artificial intelligence (XAI) that aims to reduce the opaqueness of AI-based decision-making systems, allowing humans to scrutinize and trust them. Prior work in this context has focused on the attribution of responsibility for an algorithm's decisions to it...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	226,024
1910.12043	Bayesian Experimental Design for Finding Reliable Level Set under Input Uncertainty	In the manufacturing industry, it is often necessary to repeat expensive operational testing of machine in order to identify the range of input conditions under which the machine operates properly. Since it is often difficult to accurately control the input conditions during the actual usage of the machine, there is a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	150,953
1910.04814	ErrorNet: Learning error representations from limited data to improve vascular segmentation	Deep convolutional neural networks have proved effective in segmenting lesions and anatomies in various medical imaging modalities. However, in the presence of small sample size and domain shift problems, these models often produce masks with non-intuitive segmentation mistakes. In this paper, we propose a segmentation...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	148,866
1607.03827	The KIT Motion-Language Dataset	Linking human motion and natural language is of great interest for the generation of semantic representations of human activities as well as for the generation of robot activities based on natural language input. However, while there have been years of research in this area, no standardized and openly available dataset...	false	false	false	false	false	false	true	true	true	false	false	true	false	false	false	false	false	false	58,560
1705.05935	Rise of the humanbot	The accelerated path of technological development, particularly at the interface between hardware and biology has been suggested as evidence for future major technological breakthroughs associated to our potential to overcome biological constraints. This includes the potential of becoming immortal, having expanded cogn...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	73,568
2301.10105	Does Search Engine Optimization come along with high-quality content? A comparison between optimized and non-optimized health-related web pages	Searching for medical information is both a common and important activity since it influences decisions people make about their healthcare. Using search engine optimization (SEO), content producers seek to increase the visibility of their content. SEO is more likely to be practiced by commercially motivated content pro...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	341,701
2407.10482	NGP-RT: Fusing Multi-Level Hash Features with Lightweight Attention for Real-Time Novel View Synthesis	This paper presents NGP-RT, a novel approach for enhancing the rendering speed of Instant-NGP to achieve real-time novel view synthesis. As a classic NeRF-based method, Instant-NGP stores implicit features in multi-level grids or hash tables and applies a shallow MLP to convert the implicit features into explicit color...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	473,006
2302.07946	Experimenting with Emerging RISC-V Systems for Decentralised Machine Learning	Decentralised Machine Learning (DML) enables collaborative machine learning without centralised input data. Federated Learning (FL) and Edge Inference are examples of DML. While tools for DML (especially FL) are starting to flourish, many are not flexible and portable enough to experiment with novel processors (e.g., R...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	345,876
1810.04637	Quantification of Trabeculae Inside the Heart from MRI Using Fractal Analysis	Left ventricular non-compaction (LVNC) is a rare cardiomyopathy (CMP) that should be considered as a possible diagnosis because of its potential complications which are heart failure, ventricular arrhythmias, and embolic events. For analysis cardiac functionality, extracting information from the Left ventricular (LV) i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	110,084
2109.14796	Phonetic Word Embeddings	This work presents a novel methodology for calculating the phonetic similarity between words taking motivation from the human perception of sounds. This metric is employed to learn a continuous vector embedding space that groups similar sounding words together and can be used for various downstream computational phonol...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	258,072
2308.14434	Using ChatGPT as a Static Application Security Testing Tool	In recent years, artificial intelligence has had a conspicuous growth in almost every aspect of life. One of the most applicable areas is security code review, in which a lot of AI-based tools and approaches have been proposed. Recently, ChatGPT has caught a huge amount of attention with its remarkable performance in f...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	388,333
2406.07146	Benchmarking and Boosting Radiology Report Generation for 3D High-Resolution Medical Images	Automatic radiology report generation can significantly benefit the labor-intensive process of report writing by radiologists, especially for 3D radiographs like CT scans, which are crucial for broad clinical diagnostics yet underexplored compared to 2D radiographs. Existing methods often handle 3D volumes either slice...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	462,927

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