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
1706.00977	Thompson Sampling for the MNL-Bandit	We consider a sequential subset selection problem under parameter uncertainty, where at each time step, the decision maker selects a subset of cardinality $K$ from $N$ possible items (arms), and observes a (bandit) feedback in the form of the index of one of the items in said subset, or none. Each item in the index set...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	74,726
2408.07877	BCR-DRL: Behavior- and Context-aware Reward for Deep Reinforcement Learning in Human-AI Coordination	Deep reinforcement Learning (DRL) offers a powerful framework for training AI agents to coordinate with human partners. However, DRL faces two critical challenges in human-AI coordination (HAIC): sparse rewards and unpredictable human behaviors. These challenges significantly limit DRL to identify effective coordinatio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	480,758
2202.06670	Learning Weakly-Supervised Contrastive Representations	We argue that a form of the valuable information provided by the auxiliary information is its implied data clustering information. For instance, considering hashtags as auxiliary information, we can hypothesize that an Instagram image will be semantically more similar with the same hashtags. With this intuition, we pre...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	280,301
2006.11740	An Entropy-based Proof of Threshold Saturation for Nonbinary SC-LDPC Ensembles on the BEC	In this paper we are concerned with the asymptotic analysis of nonbinary spatially-coupled low-density parity-check (SC-LDPC) ensembles defined over GL$\left(2^{m}\right)$ (the general linear group of degree $m$ over GF$\left(2\right)$). Our purpose is to prove threshold saturation when the transmission takes place on ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	183,357
2003.11090	Covid-19 Tweeting in English: Gender Differences	At the start of 2020, COVID-19 became the most urgent threat to global public health. Uniquely in recent times, governments have imposed partly voluntary, partly compulsory restrictions on the population to slow the spread of the virus. In this context, public attitudes and behaviors are vitally important for reducing ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	169,511
2410.05789	Hybrid Gripper with Passive Pneumatic Soft Joints for Grasping Deformable Thin Objects	Grasping a variety of objects remains a key challenge in the development of versatile robotic systems. The human hand is remarkably dexterous, capable of grasping and manipulating objects with diverse shapes, mechanical properties, and textures. Inspired by how humans use two fingers to pick up thin and large objects s...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	495,917
2310.10898	Analyzing Modularity Maximization in Approximation, Heuristic, and Graph Neural Network Algorithms for Community Detection	Community detection, which involves partitioning nodes within a network, has widespread applications across computational sciences. Modularity-based algorithms identify communities by attempting to maximize the modularity function across network node partitions. Our study assesses the performance of various modularity-...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	400,423
1909.03380	Automatic Image Pixel Clustering based on Mussels Wandering Optimiz	Image segmentation as a clustering problem is to identify pixel groups on an image without any preliminary labels available. It remains a challenge in machine vision because of the variations in size and shape of image segments. Furthermore, determining the segment number in an image is NP-hard without prior knowledge ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	144,458
2210.14077	Eigen Memory Trees	This work introduces the Eigen Memory Tree (EMT), a novel online memory model for sequential learning scenarios. EMTs store data at the leaves of a binary tree and route new samples through the structure using the principal components of previous experiences, facilitating efficient (logarithmic) access to relevant memo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,418
2412.02503	CA-MoE: Channel-Adapted MoE for Incremental Weather Forecasting	Atmospheric science is intricately connected with other fields, e.g., geography and aerospace. Most existing approaches involve training a joint atmospheric and geographic model from scratch, which incurs significant computational costs and overlooks the potential for incremental learning of weather variables across di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	513,559
2310.03432	Mitigating the Influence of Domain Shift in Skin Lesion Classification: A Benchmark Study of Unsupervised Domain Adaptation Methods on Dermoscopic Images	The potential of deep neural networks in skin lesion classification has already been demonstrated to be on-par if not superior to the dermatologists diagnosis. However, the performance of these models usually deteriorates when the test data differs significantly from the training data (i.e. domain shift). This concerni...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	397,285
0707.2792	Distributed Compression and Multiparty Squashed Entanglement	We study a protocol in which many parties use quantum communication to transfer a shared state to a receiver without communicating with each other. This protocol is a multiparty version of the fully quantum Slepian-Wolf protocol for two senders and arises through the repeated application of the two-sender protocol. We ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	451
1612.08037	Blind restoration for non-uniform aerial images using non-local Retinex model and shearlet-based higher-order regularization	Aerial images are often degraded by space-varying motion blur and simultaneous uneven illumination. To recover high-quality aerial image from its non-uniform version, we propose a novel patch-wise restoration approach based on a key observation that the degree of blurring is inevitably affected by the illuminated condi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	66,019
1911.05443	Dynamic Connected Neural Decision Classifier and Regressor with Dynamic Softing Pruning	To deal with various datasets over different complexity, this paper presents an self-adaptive learning model that combines the proposed Dynamic Connected Neural Decision Networks (DNDN) and a new pruning method--Dynamic Soft Pruning (DSP). DNDN is a combination of random forests and deep neural networks that enjoys bot...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	153,260
1902.09113	Star-Transformer	Although Transformer has achieved great successes on many NLP tasks, its heavy structure with fully-connected attention connections leads to dependencies on large training data. In this paper, we present Star-Transformer, a lightweight alternative by careful sparsification. To reduce model complexity, we replace the fu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,349
2011.13608	How Medical Crowdfunding Helps People? A Large-scale Case Study on Waterdrop Fundraising	While online medical crowdfunding achieved tremendous success, quantitative study about whether and how medical crowdfunding helps people remains little explored. In this paper, we empirically study how online medical crowdfunding helps people using more than 27, 000 fundraising cases in Waterdrop Fundraising, one of t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	208,539
1712.03084	An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing	The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways. The main elements of an integrated platform, which target tele-immersion and future 3D applications, are described in this paper, addressing the tasks of real-time capturing, robust 3D human shape/a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,392
2109.13023	An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling	Few-Shot Sequence Labeling (FSSL) is a canonical paradigm for the tagging models, e.g., named entity recognition and slot filling, to generalize on an emerging, resource-scarce domain. Recently, the metric-based meta-learning framework has been recognized as a promising approach for FSSL. However, most prior works assi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	257,493
2012.12311	Unboxing Engagement in YouTube Influencer Videos: An Attention-Based Approach	Influencer marketing videos have surged in popularity, yet significant gaps remain in understanding the relationships between video features and engagement. This challenge is intensified by the complexities of interpreting unstructured data. While deep learning models effectively leverage raw unstructured data to predi...	false	false	true	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	212,886
2006.16529	Lachesis: Automatic Partitioning for UDF-Centric Analytics	Persistent partitioning is effective in avoiding expensive shuffling operations. However it remains a significant challenge to automate this process for Big Data analytics workloads that extensively use user defined functions (UDFs), where sub-computations are hard to be reused for partitionings compared to relational ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	184,834
2210.08414	Using Virtual Reality to Simulate Human-Robot Emergency Evacuation Scenarios	This paper describes our recent effort to use virtual reality to simulate threatening emergency evacuation scenarios in which a robot guides a person to an exit. Our prior work has demonstrated that people will follow a robot's guidance, even when the robot is faulty, during an emergency evacuation. Yet, because physic...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	324,137
2302.05933	Generalization Ability of Wide Neural Networks on $\mathbb{R}$	We perform a study on the generalization ability of the wide two-layer ReLU neural network on $\mathbb{R}$. We first establish some spectral properties of the neural tangent kernel (NTK): $a)$ $K_{d}$, the NTK defined on $\mathbb{R}^{d}$, is positive definite; $b)$ $\lambda_{i}(K_{1})$, the $i$-th largest eigenvalue of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	345,231
2405.17976	Yuan 2.0-M32: Mixture of Experts with Attention Router	Yuan 2.0-M32, with a similar base architecture as Yuan-2.0 2B, uses a mixture-of-experts architecture with 32 experts of which 2 experts are active. A new router network, Attention Router, is proposed and adopted for a more efficient selection of experts, which improves the accuracy compared to the model with classical...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	458,216
2407.16624	Semantic Change Characterization with LLMs using Rhetorics	Languages continually evolve in response to societal events, resulting in new terms and shifts in meanings. These changes have significant implications for computer applications, including automatic translation and chatbots, making it essential to characterize them accurately. The recent development of LLMs has notably...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	475,663
2109.13907	The Role of Communication Technology Across the Life Course: A Field Guide to Social Support in East York	We examine how Canadians living in the East York section of Toronto exchange social support. Just as we have had to deconstruct social support to understand its component parts, we now deconstruct how different types of communication technologies play socially supportive roles. We draw on 101 in-depth interviews conduc...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	257,789
2405.01312	Privacy-Enhanced Database Synthesis for Benchmark Publishing	Benchmarking is crucial for evaluating a DBMS, yet existing benchmarks often fail to reflect the varied nature of user workloads. As a result, there is increasing momentum toward creating databases that incorporate real-world user data to more accurately mirror business environments. However, privacy concerns deter use...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	451,308
2412.17612	CoSurfGS:Collaborative 3D Surface Gaussian Splatting with Distributed Learning for Large Scene Reconstruction	3D Gaussian Splatting (3DGS) has demonstrated impressive performance in scene reconstruction. However, most existing GS-based surface reconstruction methods focus on 3D objects or limited scenes. Directly applying these methods to large-scale scene reconstruction will pose challenges such as high memory costs, excessiv...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	520,049
2208.11303	Modeling Paragraph-Level Vision-Language Semantic Alignment for Multi-Modal Summarization	Most current multi-modal summarization methods follow a cascaded manner, where an off-the-shelf object detector is first used to extract visual features, then these features are fused with language representations to generate the summary with an encoder-decoder model. The cascaded way cannot capture the semantic alignm...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	314,377
2201.12311	REET: Robustness Evaluation and Enhancement Toolbox for Computational Pathology	Motivation: Digitization of pathology laboratories through digital slide scanners and advances in deep learning approaches for objective histological assessment have resulted in rapid progress in the field of computational pathology (CPath) with wide-ranging applications in medical and pharmaceutical research as well a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	277,597
2009.11172	Matrix Decomposition for Massive MIMO Detection	Massive multiple-input multiple-output (MIMO) is a key technology for fifth generation (5G) communication system. MIMO symbol detection is one of the most computationally intensive tasks for a massive MIMO baseband receiver. In this paper, we analyze matrix decomposition algorithms for massive MIMO systems, which were ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	197,095
2002.04752	Machine-Learning-Based Multiple Abnormality Prediction with Large-Scale Chest Computed Tomography Volumes	Machine learning models for radiology benefit from large-scale data sets with high quality labels for abnormalities. We curated and analyzed a chest computed tomography (CT) data set of 36,316 volumes from 19,993 unique patients. This is the largest multiply-annotated volumetric medical imaging data set reported. To an...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	163,687
2501.04062	ChronoLLM: A Framework for Customizing Large Language Model for Digital Twins generalization based on PyChrono	Recently, the integration of advanced simulation technologies with artificial intelligence (AI) is revolutionizing science and engineering research. ChronoLlama introduces a novel framework that customizes the open-source LLMs, specifically for code generation, paired with PyChrono for multi-physics simulations. This i...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	523,086
2110.15169	Multimotion Visual Odometry (MVO)	Visual motion estimation is a well-studied challenge in autonomous navigation. Recent work has focused on addressing multimotion estimation in highly dynamic environments. These environments not only comprise multiple, complex motions but also tend to exhibit significant occlusion. Estimating third-party motions simu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	263,790
2502.08235	The Danger of Overthinking: Examining the Reasoning-Action Dilemma in Agentic Tasks	Large Reasoning Models (LRMs) represent a breakthrough in AI problem-solving capabilities, but their effectiveness in interactive environments can be limited. This paper introduces and analyzes overthinking in LRMs. A phenomenon where models favor extended internal reasoning chains over environmental interaction. Throu...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	532,947
1908.03734	Unsupervised Stemming based Language Model for Telugu Broadcast News Transcription	In Indian Languages , native speakers are able to understand new words formed by either combining or modifying root words with tense and / or gender. Due to data insufficiency, Automatic Speech Recognition system (ASR) may not accommodate all the words in the language model irrespective of the size of the text corpus. ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	141,305
2405.01488	Digital Twin Generators for Disease Modeling	A patient's digital twin is a computational model that describes the evolution of their health over time. Digital twins have the potential to revolutionize medicine by enabling individual-level computer simulations of human health, which can be used to conduct more efficient clinical trials or to recommend personalized...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	451,369
2301.06790	2nd Swiss German Speech to Standard German Text Shared Task at SwissText 2022	We present the results and findings of the 2nd Swiss German speech to Standard German text shared task at SwissText 2022. Participants were asked to build a sentence-level Swiss German speech to Standard German text system specialized on the Grisons dialect. The objective was to maximize the BLEU score on a test set of...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	340,740
2111.07307	Improving usual Naive Bayes classifier performances with Neural Naive Bayes based models	Naive Bayes is a popular probabilistic model appreciated for its simplicity and interpretability. However, the usual form of the related classifier suffers from two major problems. First, as caring about the observations' law, it cannot consider complex features. Moreover, it considers the conditional independence of t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,332
2108.06888	Provable Data Clustering via Innovation Search	This paper studies the subspace clustering problem in which data points collected from high-dimensional ambient space lie in a union of linear subspaces. Subspace clustering becomes challenging when the dimension of intersection between subspaces is large and most of the self-representation based methods are sensitive ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,763
1807.09561	Enhancing keyword correlation for event detection in social networks using SVD and k-means: Twitter case study	Extracting textual features from tweets is a challenging process due to the noisy nature of the content and the weak signal of most of the words used. In this paper, we propose using singular value decomposition (SVD) with clustering to enhance the signals of the textual features in the tweets to improve the correlatio...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	103,748
0712.2592	Strongly consistent nonparametric forecasting and regression for stationary ergodic sequences	Let $\{(X_i,Y_i)\}$ be a stationary ergodic time series with $(X,Y)$ values in the product space $\R^d\bigotimes \R .$ This study offers what is believed to be the first strongly consistent (with respect to pointwise, least-squares, and uniform distance) algorithm for inferring $m(x)=E[Y_0\|X_0=x]$ under the presumption...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,042
2405.16120	Guaranteeing Accuracy and Fairness under Fluctuating User Traffic: A Bankruptcy-Inspired Re-ranking Approach	Out of sustainable and economical considerations, two-sided recommendation platforms must satisfy the needs of both users and providers. Previous studies often show that the two sides' needs show different urgency: providers need a relatively long-term exposure demand while users want more short-term and accurate servi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	457,267
2207.07570	The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement Learning	We study the multi-step off-policy learning approach to distributional RL. Despite the apparent similarity between value-based RL and distributional RL, our study reveals intriguing and fundamental differences between the two cases in the multi-step setting. We identify a novel notion of path-dependent distributional T...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	308,239
2310.04693	Robustness-enhanced Uplift Modeling with Adversarial Feature Desensitization	Uplift modeling has shown very promising results in online marketing. However, most existing works are prone to the robustness challenge in some practical applications. In this paper, we first present a possible explanation for the above phenomenon. We verify that there is a feature sensitivity problem in online market...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	397,771
2405.18563	Counterfactual Explanations for Multivariate Time-Series without Training Datasets	Machine learning (ML) methods have experienced significant growth in the past decade, yet their practical application in high-impact real-world domains has been hindered by their opacity. When ML methods are responsible for making critical decisions, stakeholders often require insights into how to alter these decisions...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	458,478
1606.05426	DecomposeMe: Simplifying ConvNets for End-to-End Learning	Deep learning and convolutional neural networks (ConvNets) have been successfully applied to most relevant tasks in the computer vision community. However, these networks are computationally demanding and not suitable for embedded devices where memory and time consumption are relevant. In this paper, we propose Decom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	57,407
1706.00620	Real-time Shared Energy Storage Management for Renewable Energy Integration in Smart Grid	Energy storage systems (ESSs) are essential components of the future smart grids with high penetration of renewable energy sources. However, deploying individual ESSs for all energy consumers, especially in large systems, may not be practically feasible mainly due to high upfront cost of purchasing many ESSs and space ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	74,655
2408.07930	MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL	Recent In-Context Learning based methods have achieved remarkable success in Text-to-SQL task. However, there is still a large gap between the performance of these models and human performance on datasets with complex database schema and difficult questions, such as BIRD. Besides, existing work has neglected to supervi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	480,783
1501.04564	Analyzing the Impact of Inter Cooperation Region Interference in Coordinated Multi-Point Uplink Networks	We analyze the uplink of coordinated multi-point (CoMP) networks in which cooperation can be amongst 2 or 3 base stations (BSs). We consider a 2D network of BSs on a regular hexagonal lattice wherein the cooperation tessellates the 2D plane into cooperation regions (CRs); specifically, we analyze the impact of the inte...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	39,387
2501.05892	Beyond Flat Text: Dual Self-inherited Guidance for Visual Text Generation	In real-world images, slanted or curved texts, especially those on cans, banners, or badges, appear as frequently, if not more so, than flat texts due to artistic design or layout constraints. While high-quality visual text generation has become available with the advanced generative capabilities of diffusion models, t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,760
2109.00545	Fair Representation: Guaranteeing Approximate Multiple Group Fairness for Unknown Tasks	Motivated by scenarios where data is used for diverse prediction tasks, we study whether fair representation can be used to guarantee fairness for unknown tasks and for multiple fairness notions simultaneously. We consider seven group fairness notions that cover the concepts of independence, separation, and calibration...	false	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	253,143
2204.08345	Extracting Targeted Training Data from ASR Models, and How to Mitigate It	Recent work has designed methods to demonstrate that model updates in ASR training can leak potentially sensitive attributes of the utterances used in computing the updates. In this work, we design the first method to demonstrate information leakage about training data from trained ASR models. We design Noise Masking, ...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	292,051
2005.09445	Two types of densification scaling in the evolution of temporal networks	Many real-world social networks constantly change their global properties over time, such as the number of edges, size and density. While temporal and local properties of social networks have been extensively studied, the origin of their dynamical nature is not yet well understood. Networks may grow or shrink if a) the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	177,933
1910.10143	Establishing an Evaluation Metric to Quantify Climate Change Image Realism	With success on controlled tasks, generative models are being increasingly applied to humanitarian applications [1,2]. In this paper, we focus on the evaluation of a conditional generative model that illustrates the consequences of climate change-induced flooding to encourage public interest and awareness on the issue....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,407
2101.05944	Experimental Validation of Eco-Driving and Eco-Heating Strategies for Connected and Automated HEVs	This paper presents experimental results that validate eco-driving and eco-heating strategies developed for connected and automated vehicles (CAVs). By exploiting vehicle-to-infrastructure (V2I) communications, traffic signal timing, and queue length estimations, optimized and smoothed speed profiles for the ego-vehicl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	215,555
2403.15481	Navigating Fairness: Practitioners' Understanding, Challenges, and Strategies in AI/ML Development	The rise in the use of AI/ML applications across industries has sparked more discussions about the fairness of AI/ML in recent times. While prior research on the fairness of AI/ML exists, there is a lack of empirical studies focused on understanding the perspectives and experiences of AI practitioners in developing a f...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	440,597
2302.09578	On Feasibility of Server-side Backdoor Attacks on Split Learning	Split learning is a collaborative learning design that allows several participants (clients) to train a shared model while keeping their datasets private. Recent studies demonstrate that collaborative learning models, specifically federated learning, are vulnerable to security and privacy attacks such as model inferenc...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	346,482
2303.10590	Multi-modal Facial Action Unit Detection with Large Pre-trained Models for the 5th Competition on Affective Behavior Analysis in-the-wild	Facial action unit detection has emerged as an important task within facial expression analysis, aimed at detecting specific pre-defined, objective facial expressions, such as lip tightening and cheek raising. This paper presents our submission to the Affective Behavior Analysis in-the-wild (ABAW) 2023 Competition for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	352,511
1907.13070	Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors	Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease characterized by a rapid motor decline, leading to respiratory failure and subsequently to death. In this context, researchers have sought for models to automatically predict disease progression to assisted ventilation in ALS patients. However, the clin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	140,290
1706.06934	Exact Learning of Juntas from Membership Queries	In this paper, we study adaptive and non-adaptive exact learning of Juntas from membership queries. We use new techniques to find new bounds, narrow some of the gaps between the lower bounds and upper bounds and find new deterministic and randomized algorithms with small query and time complexities. Some of the bound...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,764
2108.11276	Measurement of Hybrid Rocket Solid Fuel Regression Rate for a Slab Burner using Deep Learning	This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary layer combustion in hybrid rockets by the measurement of fuel regression rates. A D...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	252,138
2310.17852	Function Space Bayesian Pseudocoreset for Bayesian Neural Networks	A Bayesian pseudocoreset is a compact synthetic dataset summarizing essential information of a large-scale dataset and thus can be used as a proxy dataset for scalable Bayesian inference. Typically, a Bayesian pseudocoreset is constructed by minimizing a divergence measure between the posterior conditioning on the pseu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	403,312
2006.11992	NOVAS: Non-convex Optimization via Adaptive Stochastic Search for End-to-End Learning and Control	In this work we propose the use of adaptive stochastic search as a building block for general, non-convex optimization operations within deep neural network architectures. Specifically, for an objective function located at some layer in the network and parameterized by some network parameters, we employ adaptive stocha...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	183,434
2304.07958	Recursive Joint Attention for Audio-Visual Fusion in Regression based Emotion Recognition	In video-based emotion recognition (ER), it is important to effectively leverage the complementary relationship among audio (A) and visual (V) modalities, while retaining the intra-modal characteristics of individual modalities. In this paper, a recursive joint attention model is proposed along with long short-term mem...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	358,539
1710.08637	Improving Accuracy of Nonparametric Transfer Learning via Vector Segmentation	Transfer learning using deep neural networks as feature extractors has become increasingly popular over the past few years. It allows to obtain state-of-the-art accuracy on datasets too small to train a deep neural network on its own, and it provides cutting edge descriptors that, combined with nonparametric learning m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	83,110
2009.05388	Automatic cinematography for 360 video	We describe our method for automatic generation of a visually interesting camera path (automatic cinematography)from a 360 video. Based on the information from the scene objects, multiple shot hypotheses for different shot types are constructed and the best one is rendered.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	195,309
2009.08928	A Study of Genetic Algorithms for Hyperparameter Optimization of Neural Networks in Machine Translation	With neural networks having demonstrated their versatility and benefits, the need for their optimal performance is as prevalent as ever. A defining characteristic, hyperparameters, can greatly affect its performance. Thus engineers go through a process, tuning, to identify and implement optimal hyperparameters. That be...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	196,390
2401.15621	SNAP: Semantic Stories for Next Activity Prediction	Predicting the next activity in an ongoing process is one of the most common classification tasks in the business process management (BPM) domain. It allows businesses to optimize resource allocation, enhance operational efficiency, and aids in risk mitigation and strategic decision-making. This provides a competitive ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	424,521
2412.14837	ObjVariantEnsemble: Advancing Point Cloud LLM Evaluation in Challenging Scenes with Subtly Distinguished Objects	3D scene understanding is an important task, and there has been a recent surge of research interest in aligning 3D representations of point clouds with text to empower embodied AI. However, due to the lack of comprehensive 3D benchmarks, the capabilities of 3D models in real-world scenes, particularly those that are ch...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,875
1604.00498	A Get-Together for Deaf and Dumb Robots in Three dimensional Space	This paper proposes a strategy for a group of deaf and dumb robots, carrying clocks from different countries, to meet at a geographical location which is not fixed in advanced. The robots act independently. They can observe others, compute some locations and walk towards those locations. They can only get a snapshot of...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	54,040
2407.05382	Rethinking Unsupervised Outlier Detection via Multiple Thresholding	In the realm of unsupervised image outlier detection, assigning outlier scores holds greater significance than its subsequent task: thresholding for predicting labels. This is because determining the optimal threshold on non-separable outlier score functions is an ill-posed problem. However, the lack of predicted label...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	470,953
2104.06039	MultiModalQA: Complex Question Answering over Text, Tables and Images	When answering complex questions, people can seamlessly combine information from visual, textual and tabular sources. While interest in models that reason over multiple pieces of evidence has surged in recent years, there has been relatively little work on question answering models that reason across multiple modalitie...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	229,939
1810.12825	Sizing the length of complex networks	Among all characteristics exhibited by natural and man-made networks the small-world phenomenon is surely the most relevant and popular. But despite its significance, a reliable and comparable quantification of the question `how small is a small-world network and how does it compare to others' has remained a difficult ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	111,855
2303.10870	Multi-task Transformer with Relation-attention and Type-attention for Named Entity Recognition	Named entity recognition (NER) is an important research problem in natural language processing. There are three types of NER tasks, including flat, nested and discontinuous entity recognition. Most previous sequential labeling models are task-specific, while recent years have witnessed the rising of generative models d...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	352,611
1910.13195	User's Centrality Analysis for Home Location Estimation	User attributes, such as home location, are useful for many applications. Many researchers have been tackling how to estimate users' home locations using relationships among users. It is known that the home locations of certain users, such as celebrities, are hard to estimate using relationships. However, because estim...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	151,322
2409.17476	Improving the Shortest Plank: Vulnerability-Aware Adversarial Training for Robust Recommender System	Recommender systems play a pivotal role in mitigating information overload in various fields. Nonetheless, the inherent openness of these systems introduces vulnerabilities, allowing attackers to insert fake users into the system's training data to skew the exposure of certain items, known as poisoning attacks. Adversa...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	491,819
2310.14663	DPP-TTS: Diversifying prosodic features of speech via determinantal point processes	With the rapid advancement in deep generative models, recent neural Text-To-Speech(TTS) models have succeeded in synthesizing human-like speech. There have been some efforts to generate speech with various prosody beyond monotonous prosody patterns. However, previous works have several limitations. First, typical TTS m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	401,963
1702.01075	Safe Certificate-Based Maneuvers for Teams of Quadrotors Using Differential Flatness	Safety Barrier Certificates that ensure collision-free maneuvers for teams of differential flatness-based quadrotors are presented in this paper. Synthesized with control barrier functions, the certificates are used to modify the nominal trajectory in a minimally invasive way to avoid collisions. The proposed collision...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	67,745
2501.15374	Evaluating the Effectiveness of XAI Techniques for Encoder-Based Language Models	The black-box nature of large language models (LLMs) necessitates the development of eXplainable AI (XAI) techniques for transparency and trustworthiness. However, evaluating these techniques remains a challenge. This study presents a general evaluation framework using four key metrics: Human-reasoning Agreement (HA), ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	527,522
1702.06925	Regularizing Face Verification Nets For Pain Intensity Regression	Limited labeled data are available for the research of estimating facial expression intensities. For instance, the ability to train deep networks for automated pain assessment is limited by small datasets with labels of patient-reported pain intensities. Fortunately, fine-tuning from a data-extensive pre-trained domain...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	68,702
1809.10877	Learning for Single-Shot Confidence Calibration in Deep Neural Networks through Stochastic Inferences	We propose a generic framework to calibrate accuracy and confidence of a prediction in deep neural networks through stochastic inferences. We interpret stochastic regularization using a Bayesian model, and analyze the relation between predictive uncertainty of networks and variance of the prediction scores obtained by ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,009
1306.1346	Rethinking the Secrecy Outage Formulation: A Secure Transmission Design Perspective	This letter studies information-theoretic security without knowing the eavesdropper's channel fading state. We present an alternative secrecy outage formulation to measure the probability that message transmissions fail to achieve perfect secrecy. Using this formulation, we design two transmission schemes that satisfy ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	25,040
1704.05415	An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification	End-to-end neural machine translation has overtaken statistical machine translation in terms of translation quality for some language pairs, specially those with large amounts of parallel data. Besides this palpable improvement, neural networks provide several new properties. A single system can be trained to translate...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,005
2311.10707	Multimodal Representation Learning by Alternating Unimodal Adaptation	Multimodal learning, which integrates data from diverse sensory modes, plays a pivotal role in artificial intelligence. However, existing multimodal learning methods often struggle with challenges where some modalities appear more dominant than others during multimodal learning, resulting in suboptimal performance. To ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	408,611
2407.01595	Fairpriori: Improving Biased Subgroup Discovery for Deep Neural Network Fairness	While deep learning has become a core functional module of most software systems, concerns regarding the fairness of ML predictions have emerged as a significant issue that affects prediction results due to discrimination. Intersectional bias, which disproportionately affects members of subgroups, is a prime example of...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	469,375
1810.03043	Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning	Prediction is an appealing objective for self-supervised learning of behavioral skills, particularly for autonomous robots. However, effectively utilizing predictive models for control, especially with raw image inputs, poses a number of major challenges. How should the predictions be used? What happens when they are i...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	109,718
2207.08592	Symmetrized Robust Procrustes: Constant-Factor Approximation and Exact Recovery	The classical $\textit{Procrustes}$ problem is to find a rigid motion (orthogonal transformation and translation) that best aligns two given point-sets in the least-squares sense. The $\textit{Robust Procrustes}$ problem is an important variant, in which a power-1 objective is used instead of least squares to improve r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	308,636
1811.12560	An Introduction to Deep Reinforcement Learning	Deep reinforcement learning is the combination of reinforcement learning (RL) and deep learning. This field of research has been able to solve a wide range of complex decision-making tasks that were previously out of reach for a machine. Thus, deep RL opens up many new applications in domains such as healthcare, roboti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	115,039
2012.04832	Proactive Interaction Framework for Intelligent Social Receptionist Robots	Proactive human-robot interaction (HRI) allows the receptionist robots to actively greet people and offer services based on vision, which has been found to improve acceptability and customer satisfaction. Existing approaches are either based on multi-stage decision processes or based on end-to-end decision models. Howe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	210,582
2004.09376	Conditional-UNet: A Condition-aware Deep Model for Coherent Human Activity Recognition From Wearables	Recognizing human activities from multi-channel time series data collected from wearable sensors is ever more practical. However, in real-world conditions, coherent activities and body movements could happen at the same time, like moving head during walking or sitting. A new problem, so-called "Coherent Human Activity ...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,329
2007.08260	Weighing Counts: Sequential Crowd Counting by Reinforcement Learning	We formulate counting as a sequential decision problem and present a novel crowd counting model solvable by deep reinforcement learning. In contrast to existing counting models that directly output count values, we divide one-step estimation into a sequence of much easier and more tractable sub-decision problems. Such ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,577
2409.00585	McCaD: Multi-Contrast MRI Conditioned, Adaptive Adversarial Diffusion Model for High-Fidelity MRI Synthesis	Magnetic Resonance Imaging (MRI) is instrumental in clinical diagnosis, offering diverse contrasts that provide comprehensive diagnostic information. However, acquiring multiple MRI contrasts is often constrained by high costs, long scanning durations, and patient discomfort. Current synthesis methods, typically focuse...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,980
2407.21034	Watermarking Recommender Systems	Recommender systems embody significant commercial value and represent crucial intellectual property. However, the integrity of these systems is constantly challenged by malicious actors seeking to steal their underlying models. Safeguarding against such threats is paramount to upholding the rights and interests of the ...	false	false	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	477,369
2407.06660	Collaborative Design of AI-Enhanced Learning Activities	Artificial intelligence has accelerated innovations in different aspects of citizens' lives. Many contexts have already addressed technology-enhanced learning, but educators at different educational levels now need to develop AI literacy and the ability to integrate appropriate AI usage into their teaching. We take int...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	471,487
2110.01909	A Table-Based Representation for Probabilistic Logic: Preliminary Results	We present Probabilistic Decision Model and Notation (pDMN), a probabilistic extension of Decision Model and Notation (DMN). DMN is a modeling notation for deterministic decision logic, which intends to be user-friendly and low in complexity. pDMN extends DMN with probabilistic reasoning, predicates, functions, quantif...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	258,939
2101.02345	A generalization of the Von Neumann extractor	An iterative randomness extraction algorithm which generalized the Von Neumann's extraction algorithm is detailed, analyzed and implemented in standard C++. Given a sequence of independently and identically distributed biased Bernoulli random variables, to extract randomness from the aforementioned sequence pertains to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	214,592
2008.12736	RKT : Relation-Aware Self-Attention for Knowledge Tracing	The world has transitioned into a new phase of online learning in response to the recent Covid19 pandemic. Now more than ever, it has become paramount to push the limits of online learning in every manner to keep flourishing the education system. One crucial component of online learning is Knowledge Tracing (KT). The a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	193,666
2411.14511	Variational Autoencoders for Efficient Simulation-Based Inference	We present a generative modeling approach based on the variational inference framework for likelihood-free simulation-based inference. The method leverages latent variables within variational autoencoders to efficiently estimate complex posterior distributions arising from stochastic simulations. We explore two variati...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	510,213
2309.10168	Few-Shot Adaptation for Parsing Contextual Utterances with LLMs	We evaluate the ability of semantic parsers based on large language models (LLMs) to handle contextual utterances. In real-world settings, there typically exists only a limited number of annotated contextual utterances due to annotation cost, resulting in an imbalance compared to non-contextual utterances. Therefore, p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	392,886
2109.00594	Wearable-based Classification of Running Styles with Deep Learning	Automatic classification of running styles can enable runners to obtain feedback with the aim of optimizing performance in terms of minimizing energy expenditure, fatigue, and risk of injury. To develop a system capable of classifying running styles using wearables, we collect a dataset from 10 healthy runners performi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	253,154

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