Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
42,878	24	Title: No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier Abstract: Data heterogeneity is an inherent challenge that hinders the performance of federated learning (FL). Recent studies have identified the biased classifiers of local models as the key bottleneck....	[ 27209, 21484, 8077, 42869, 8505, 12925 ]	Test
42,879	27	Title: Recovery Policies for Safe Exploration of Lunar Permanently Shadowed Regions by a Solar-Powered Rover Abstract: The success of a multi-kilometre drive by a solar-powered rover at the lunar south pole depends upon careful planning in space and time due to highly dynamic solar illumination conditions. An additiona...	[]	Train
42,880	24	Title: A Subspace Projection Approach to Autoencoder-based Anomaly Detection Abstract: Autoencoder (AE) is a neural network (NN) architecture that is trained to reconstruct an input at its output. By measuring the reconstruction errors of new input samples, AE can detect anomalous samples deviated from the trained data...	[]	Test
42,881	16	Title: Phase Matching for Out-of-Distribution Generalization Abstract: The Fourier transform, serving as an explicit decomposition method for visual signals, has been employed to explain the out-of-distribution generalization behaviors of Convolutional Neural Networks (CNNs). Previous studies have indicated that the am...	[]	Train
42,882	16	Title: Automated Deception Detection from Videos: Using End-to-End Learning Based High-Level Features and Classification Approaches Abstract: Deception detection is an interdisciplinary field attracting researchers from psychology, criminology, computer science, and economics. We propose a multimodal approach combining...	[]	Validation
42,883	23	Title: An Empirical Study of Fault Localization in Python Programs Abstract: Despite its massive popularity as a programming language, especially in novel domains like data science programs, there is comparatively little research about fault localization that targets Python. Even though it is plausible that several fin...	[]	Train
42,884	30	Title: AI Coach Assist: An Automated Approach for Call Recommendation in Contact Centers for Agent Coaching Abstract: In recent years, the utilization of Artificial Intelligence (AI) in the contact center industry is on the rise. One area where AI can have a significant impact is in the coaching of contact center agent...	[ 29396 ]	Train
42,885	16	Title: PoseDiffusion: Solving Pose Estimation via Diffusion-aided Bundle Adjustment Abstract: Camera pose estimation is a long-standing computer vision problem that to date often relies on classical methods, such as handcrafted keypoint matching, RANSAC and bundle adjustment. In this paper, we propose to formulate the ...	[ 22163, 5942 ]	Train
42,886	24	Title: Evaluation of distance‐based approaches for forensic comparison: Application to hand odor evidence Abstract: The issue of distinguishing between the same‐source and different‐source hypotheses based on various types of traces is a generic problem in forensic science. This problem is often tackled with Bayesian a...	[]	Validation
42,887	30	Title: Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering Abstract: Short text clustering is challenging since it takes imbalanced and noisy data as inputs. Existing approaches cannot solve this problem well, since (1) they are prone to ob...	[]	Train
42,888	8	Title: NDNSD: Service Publishing and Discovery in NDN Abstract: Service discovery is a crucial component in today's massively distributed applications. In this paper, we propose NDNSD - a fully distributed and general-purpose service discovery protocol for Named Data Networking (NDN). By leveraging NDN's data synchroni...	[]	Train
42,889	24	Title: Collaborative Learning via Prediction Consensus Abstract: We consider a collaborative learning setting where each agent's goal is to improve their own model by leveraging the expertise of collaborators, in addition to their own training data. To facilitate the exchange of expertise among agents, we propose a dis...	[]	Validation
42,890	39	Title: Maximum values of the Sombor-index-like graph invariants of connected graphs Abstract: A set of novel vertex-degree-based invariants, similar to the Sombor-index, was introduced by Gutman, denoted by $SO_1, SO_2, \ldots,SO_6$. These invariants were constructed through geometric reasoning based on a new graph inv...	[]	Validation
42,891	31	Title: Beyond Rankings: Exploring the Impact of SERP Features on Organic Click-through Rates Abstract: Search Engine Result Pages (SERPs) serve as the digital gateways to the vast expanse of the internet. Past decades have witnessed a surge in research primarily centered on the influence of website ranking on these pag...	[ 28488, 36143 ]	Test
42,892	4	Title: The Landscape of Computing Symmetric n-Variable Functions with 2n Cards Abstract: Secure multi-party computation using a physical deck of cards, often called card-based cryptography, has been extensively studied during the past decade. Card-based protocols to compute various Boolean functions have been developed...	[]	Test
42,893	34	Title: Randomized Algorithm for the Maximum-Profit Routing Problem Abstract: In this paper, we consider the Maximum-Profit Routing Problem (MPRP), introduced in \cite{Armaselu-PETRA}. In MPRP, the goal is to route the given fleet of vehicles to pickup goods from specified sites in such a way as to maximize the profit, ...	[]	Train
42,894	16	Title: Pixel Difference Convolutional Network for RGB-D Semantic Segmentation Abstract: RGB-D semantic segmentation can be advanced with convolutional neural networks due to the availability of Depth data. Although objects cannot be easily discriminated by just the 2D appearance, with the local pixel difference and geo...	[ 4273 ]	Train
42,895	24	Title: RD-DPP: Rate-Distortion Theory Meets Determinantal Point Process to Diversify Learning Data Samples Abstract: In some practical learning tasks, such as traffic video analysis, the number of available training samples is restricted by different factors, such as limited communication bandwidth and computation powe...	[ 11258, 43671 ]	Test
42,896	34	Title: Planar Disjoint Paths, Treewidth, and Kernels Abstract: In the Planar Disjoint Paths problem, one is given an undirected planar graph with a set of $k$ vertex pairs $(s_i,t_i)$ and the task is to find $k$ pairwise vertex-disjoint paths such that the $i$-th path connects $s_i$ to $t_i$. We study the problem throu...	[]	Train
42,897	13	Title: Modular Differential Evolution Abstract: New contributions in the field of iterative optimisation heuristics are often made in an iterative manner. Novel algorithmic ideas are not proposed in isolation, but usually as extensions of a preexisting algorithm. Although these contributions are often compared to the b...	[ 22721 ]	Train
42,898	38	Title: How to measure research performance of single scientists? A proposal for an index based on scientific prizes: The Prize Winner Index (PWI) Abstract: In this study, we propose a new index for measuring excellence in science which is based on collaborations (co-authorship distances) in science. The index is based ...	[]	Test
42,899	13	Title: A Hybrid System for Systematic Generalization in Simple Arithmetic Problems Abstract: Solving symbolic reasoning problems that require compositionality and systematicity is considered one of the key ingredients of human intelligence. However, symbolic reasoning is still a great challenge for deep learning models...	[ 3583 ]	Train
42,900	38	Title: Application of an ontology for model cards to generate computable artifacts for linking machine learning information from biomedical research Abstract: Model card reports provide a transparent description of machine learning models which includes information about their evaluation, limitations, intended use, etc...	[]	Train
42,901	30	Title: A Drop of Ink Makes a Million Think: The Spread of False Information in Large Language Models Abstract: Large language models (LLMs) have gained increasing prominence in artificial intelligence, making a profound impact on society and various industries like business and science. However, the presence of false i...	[ 19968, 39680, 44482, 46016, 18564, 27140, 13510, 13700, 13224, 27945, 9518, 846, 497, 21880, 44603, 45182 ]	Validation
42,902	8	Title: Cyber-attack TTP analysis for EPES systems Abstract: The electrical grid constitutes of legacy systems that were built with no security in mind. As we move towards the Industry 4.0 area though a high-degree of automation and connectivity provides: 1) fast and flexible configuration and updates as well as 2) easi...	[]	Train
42,903	24	Title: Robust Learning from Explanations Abstract: Machine learning from explanations (MLX) is an approach to learning that uses human-provided annotations of relevant features for each input to ensure that model predictions are right for the right reasons. Existing MLX approaches rely heavily on a specific model inter...	[]	Train
42,904	31	Title: Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems Abstract: As the use of online platforms continues to grow across all demographics, users often express a desire to feel represented in the content. To improve representation in search results and recommendation...	[]	Validation
42,905	37	Title: An Overview on Cloud Distributed Databases for Business Environments Abstract: Cloud-based distributed databases are a popular choice for many current applications, especially those that run over the Internet. By incorporating distributed database systems within cloud environments, it has enabled businesses to s...	[]	Train
42,906	2	Title: Generalizing Level Ranking Constraints for Monotone and Convex Aggregates Abstract: In answer set programming (ASP), answer sets capture solutions to search problems of interest and thus the efficient computation of answer sets is of utmost importance. One viable implementation strategy is provided by translatio...	[]	Train
42,907	16	Title: Intelligent Grimm - Open-ended Visual Storytelling via Latent Diffusion Models Abstract: Generative models have recently exhibited exceptional capabilities in various scenarios, for example, image generation based on text description. In this work, we focus on the task of generating a series of coherent image se...	[ 42272, 6145, 3979, 45685, 34167, 35327 ]	Validation
42,908	30	Title: Do We Still Need Clinical Language Models? Abstract: Although recent advances in scaling large language models (LLMs) have resulted in improvements on many NLP tasks, it remains unclear whether these models trained primarily with general web text are the right tool in highly specialized, safety critical domains ...	[ 24512, 12001, 35041, 18053, 23801, 18539, 15724, 32176, 41139, 11476, 13749, 24308, 30775, 30264, 10681, 44502, 23421, 45822 ]	Train
42,909	16	Title: OPDMulti: Openable Part Detection for Multiple Objects Abstract: Openable part detection is the task of detecting the openable parts of an object in a single-view image, and predicting corresponding motion parameters. Prior work investigated the unrealistic setting where all input images only contain a single op...	[ 33916, 11570, 28244 ]	Train
42,910	2	Title: Allegories of Symbolic Manipulations Abstract: Moving from the mathematical theory of (abstract) syntax, we develop a general relational theory of symbolic manipulation parametric with respect to, and accounting for, general notions of syntax. We model syntax relying on categorical notions, such as free algebras...	[]	Train
42,911	30	Title: HiFi: High-Information Attention Heads Hold for Parameter-Efficient Model Adaptation Abstract: To fully leverage the advantages of large-scale pre-trained language models (PLMs) on downstream tasks, it has become a ubiquitous adaptation paradigm to fine-tune the entire parameters of PLMs. However, this paradigm ...	[]	Train
42,912	39	Title: Domino Snake Problems on Groups Abstract: In this article we study domino snake problems on finitely generated groups. We provide general properties of these problems and introduce new tools for their study. The first is the use of symbolic dynamics to understand the set of all possible snakes. Using this approa...	[]	Test
42,913	30	Title: Adversarial Conversational Shaping for Intelligent Agents Abstract: The recent emergence of deep learning methods has enabled the research community to achieve state-of-the art results in several domains including natural language processing. However, the current robocall system remains unstable and inaccurate: ...	[]	Validation
42,914	24	Title: Knowledge-based Refinement of Scientific Publication Knowledge Graphs Abstract: We consider the problem of identifying authorship by posing it as a knowledge graph construction and refinement. To this effect, we model this problem as learning a probabilistic logic model in the presence of human guidance (knowled...	[]	Test
42,915	3	Title: Beyond the ML Model: Applying Safety Engineering Frameworks to Text-to-Image Development Abstract: Identifying potential social and ethical risks in emerging machine learning (ML) models and their applications remains challenging. In this work, we applied two well-established safety engineering frameworks (FMEA,...	[ 40915 ]	Train
42,916	16	Title: CGBA: Curvature-aware Geometric Black-box Attack Abstract: Decision-based black-box attacks often necessitate a large number of queries to craft an adversarial example. Moreover, decision-based attacks based on querying boundary points in the estimated normal vector direction often suffer from inefficiency and c...	[]	Train
42,917	6	Title: Measuring the spatial Acuity of vibrotactile Stimuli: A new Approach to determine universal and individual Thresholds Abstract: Tactile perception is an increasingly popular gateway in human-machine interaction, yet universal design guidelines for tactile displays are still lacking, largely due to the absence of...	[]	Validation
42,918	5	Title: Resource Aware Clustering for Tackling the Heterogeneity of Participants in Federated Learning Abstract: Federated Learning is a training framework that enables multiple participants to collaboratively train a shared model while preserving data privacy and minimizing communication overhead. The heterogeneity of ...	[]	Train
42,919	34	Title: Degrees and Network Design: New Problems and Approximations Abstract: While much of network design focuses mostly on cost (number or weight of edges), node degrees have also played an important role. They have traditionally either appeared as an objective, to minimize the maximum degree (e.g., the Minimum Degree...	[ 20642 ]	Test
42,920	24	Title: Block-local learning with probabilistic latent representations Abstract: The ubiquitous backpropagation algorithm requires sequential updates across blocks of a network, introducing a locking problem. Moreover, backpropagation relies on the transpose of weight matrices to calculate updates, introducing a weight ...	[ 10496, 23249, 10762, 13700 ]	Train
42,921	27	Title: Quadrupedal Footstep Planning using Learned Motion Models of a Black-Box Controller Abstract: Legged robots are increasingly entering new domains and applications, including search and rescue, inspection, and logistics. However, for such systems to be valuable in real-world scenarios, they must be able to autono...	[]	Train
42,922	27	Title: MOMA-Force: Visual-Force Imitation for Real-World Mobile Manipulation Abstract: In this paper, we present a novel method for mobile manipulators to perform multiple contact-rich manipulation tasks. While learning-based methods have the potential to generate actions in an end-to-end manner, they often suffer from...	[ 4385 ]	Train
42,923	16	Title: A horizon line annotation tool for streamlining autonomous sea navigation experiments Abstract: Horizon line (or sea line) detection (HLD) is a critical component in multiple marine autonomous navigation tasks, such as identifying the navigation area (i.e., the sea), obstacle detection and geo-localization, and ...	[]	Test
42,924	30	Title: Agreement Tracking for Multi-Issue Negotiation Dialogues Abstract: Automated negotiation support systems aim to help human negotiators reach more favorable outcomes in multi-issue negotiations (e.g., an employer and a candidate negotiating over issues such as salary, hours, and promotions before a job offer). To...	[]	Train
42,925	4	Title: Security of XCB and HCTR Abstract: Tweakable Enciphering Scheme (TES) is a length preserving scheme which provides confidentiality and admissible integrity. XCB (Extended Code Book) is a TES which was introduced in 2004. In 2007, it was modified and security bound was provided. Later, these two versions were ref...	[]	Test
42,926	24	Title: Stochastic Submodular Bandits with Delayed Composite Anonymous Bandit Feedback Abstract: This paper investigates the problem of combinatorial multiarmed bandits with stochastic submodular (in expectation) rewards and full-bandit delayed feedback, where the delayed feedback is assumed to be composite and anonymou...	[ 42412, 29958 ]	Train
42,927	30	Title: A Large-Scale Comparative Study of Accurate COVID-19 Information versus Misinformation Abstract: The COVID-19 pandemic led to an infodemic where an overwhelming amount of COVID-19 related content was being disseminated at high velocity through social media. This made it challenging for citizens to differentiate ...	[]	Test
42,928	16	Title: RANSAC-NN: Unsupervised Image Outlier Detection using RANSAC Abstract: Image outlier detection (OD) is crucial for ensuring the quality and accuracy of image datasets used in computer vision tasks. The majority of OD algorithms, however, have not been targeted toward image data. Consequently, the results of appl...	[]	Train
42,929	2	Title: The Undecidability of Typability in the Lambda-Pi-Calculus Abstract: nan	[ 14906, 42740, 33170 ]	Test
42,930	24	Title: Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition Abstract: Naturalistic driving action recognition (NDAR) has proven to be an effective method for detecting driver distraction and reducing the risk of traffic accidents. However, the intrusive design of in-cabin cameras raises...	[ 18080, 17218, 10644, 7735, 45016, 8412 ]	Train
42,931	24	Title: Knowledge Distillation-based Information Sharing for Online Process Monitoring in Decentralized Manufacturing System Abstract: In advanced manufacturing, the incorporation of sensing technology provides an opportunity to achieve efficient in-situ process monitoring using machine learning methods. Meanwhile, the ...	[ 29985 ]	Train
42,932	24	Title: Lipschitz-bounded 1D convolutional neural networks using the Cayley transform and the controllability Gramian Abstract: We establish a layer-wise parameterization for 1D convolutional neural networks (CNNs) with built-in end-to-end robustness guarantees. Herein, we use the Lipschitz constant of the input-output ...	[ 7433, 40007 ]	Validation
42,933	24	Title: Random forests, sound symbolism and Pokémon evolution Abstract: This study constructs machine learning algorithms that are trained to classify samples using sound symbolism, and then it reports on an experiment designed to measure their understanding against human participants. Random forests are trained using t...	[]	Test
42,934	24	Title: Coherent Soft Imitation Learning Abstract: Imitation learning methods seek to learn from an expert either through behavioral cloning (BC) of the policy or inverse reinforcement learning (IRL) of the reward. Such methods enable agents to learn complex tasks from humans that are difficult to capture with hand-desi...	[ 14373, 36246 ]	Train
42,935	16	Title: Coupling Global Context and Local Contents for Weakly-Supervised Semantic Segmentation Abstract: Thanks to the advantages of the friendly annotations and the satisfactory performance, weakly-supervised semantic segmentation (WSSS) approaches have been extensively studied. Recently, the single-stage WSSS (SS-WSSS...	[]	Test
42,936	16	Title: Foresee What You Will Learn: Data Augmentation for Domain Generalization in Non-Stationary Environments Abstract: Existing domain generalization aims to learn a generalizable model to perform well even on unseen domains. For many real-world machine learning applications, the data distribution often shifts gradua...	[]	Train
42,937	16	Title: SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing Field Abstract: Despite the great success in 2D editing using user-friendly tools, such as Photoshop, semantic strokes, or even text prompts, similar capabilities in 3D areas are still limited, either relying on 3D modeling skills or allowi...	[ 7076, 42666, 3438, 30995, 17075, 40790, 18487 ]	Train
42,938	24	Title: Language models as master equation solvers Abstract: Master equations are of fundamental importance in modeling stochastic dynamical systems.However, solving master equations is challenging due to the exponential increase in the number of possible states or trajectories with the dimension of the state space. In ...	[ 12128, 7585, 13700, 20228, 23302, 33220, 12087 ]	Train
42,939	31	Title: Causality-based CTR prediction using graph neural networks Abstract: nan	[ 15691 ]	Train
42,940	31	Title: Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework Abstract: With the proliferation of short video applications, the significance of short video recommendations has vastly increased. Unlike other recommendation scenarios, short video recommendation systems heavily rely on...	[ 8945, 36660 ]	Validation
42,941	16	Title: Absorption-Based, Passive Range Imaging from Hyperspectral Thermal Measurements Abstract: Passive hyperspectral long-wave infrared measurements are remarkably informative about the surroundings, such as remote object material composition, temperature, and range; and air temperature and gas concentrations. Remote...	[]	Validation
42,942	24	Title: Understanding Oversquashing in GNNs through the Lens of Effective Resistance Abstract: Message passing graph neural networks (GNNs) are a popular learning architectures for graph-structured data. However, one problem GNNs experience is oversquashing, where a GNN has difficulty sending information between distant...	[ 2656, 42306, 28263, 10555, 28948, 40890, 39483 ]	Train
42,943	16	Title: Clustered-patch Element Connection for Few-shot Learning Abstract: Weak feature representation problem has influenced the performance of few-shot classification task for a long time. To alleviate this problem, recent researchers build connections between support and query instances through embedding patch featur...	[]	Test
42,944	2	Title: Enjoy the Silence: Analysis of Stochastic Petri Nets with Silent Transitions Abstract: Capturing stochastic behaviors in business and work processes is essential to quantitatively understand how nondeterminism is resolved when taking decisions within the process. This is of special interest in process mining, wh...	[]	Train
42,945	24	Title: The Challenges of Machine Learning for Trust and Safety: A Case Study on Misinformation Detection Abstract: We examine the disconnect between scholarship and practice in applying machine learning to trust and safety problems, using misinformation detection as a case study. We systematize literature on automated ...	[]	Train
42,946	27	Title: QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control Abstract: Reinforcement learning (RL) has shown promise in creating robust policies for robotics tasks. However, contemporary RL algorithms are data-hungry, often requiring billions of environment transition...	[ 20732 ]	Train
42,947	15	Title: Computing and Compressing Electron Repulsion Integrals on FPGAs Abstract: The computation of electron repulsion integrals (ERIs) over Gaussian-type orbitals (GTOs) is a challenging problem in quantum-mechanics-based atomistic simulations. In practical simulations, several trillions of ERIs may have to be compute...	[]	Test
42,948	30	Title: SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression Abstract: Recent advances in large language model (LLM) pretraining have led to high-quality LLMs with impressive abilities. By compressing such LLMs via quantization to 3-4 bits per parameter, they can fit into memory-limited devic...	[ 6979, 33220, 12851, 1141, 43452, 37438 ]	Train
42,949	30	Title: Are Large Language Models Really Good Logical Reasoners? A Comprehensive Evaluation and Beyond Abstract: Logical reasoning consistently plays a fundamental and significant role in the domains of knowledge engineering and artificial intelligence. Recently, Large Language Models (LLMs) have emerged as a noteworthy...	[ 12128, 13345, 40192, 28151, 35427, 4071, 1575, 29396, 45909, 5078, 13495, 35580, 7518 ]	Test
42,950	16	Title: PatchMixer: Rethinking network design to boost generalization for 3D point cloud understanding Abstract: The recent trend in deep learning methods for 3D point cloud understanding is to propose increasingly sophisticated architectures either to better capture 3D geometries or by introducing possibly undesired in...	[]	Validation
42,951	35	Title: HotOS XIX Panel Report: Panel on Future of Reproduction and Replication of Systems Research Abstract: At HotOS XIX (2023), we organized a panel to discuss the future of reproducibility and replication in systems research. In this document, we highlight the key points and themes that were discussed in the panel a...	[]	Train
42,952	25	Title: Large-Scale Automatic Audiobook Creation Abstract: An audiobook can dramatically improve a work of literature's accessibility and improve reader engagement. However, audiobooks can take hundreds of hours of human effort to create, edit, and publish. In this work, we present a system that can automatically genera...	[]	Train
42,953	30	Title: Active Learning for Neural Machine Translation Abstract: The machine translation mechanism translates texts automatically between different natural languages, and Neural Machine Translation (NMT) has gained attention for its rational context analysis and fluent translation accuracy. However, processing low-resou...	[]	Test
42,954	30	Title: In-Context Demonstration Selection with Cross Entropy Difference Abstract: Large language models (LLMs) can use in-context demonstrations to improve performance on zero-shot tasks. However, selecting the best in-context examples is challenging because model performance can vary widely depending on the selected e...	[ 7397, 13510, 8087 ]	Train
42,955	25	Title: Adversarial Speaker Disentanglement Using Unannotated External Data for Self-supervised Representation-based Voice Conversion Abstract: Nowadays, recognition-synthesis-based methods have been quite popular with voice conversion (VC). By introducing linguistics features with good disentangling characters extracte...	[]	Train
42,956	22	Title: Higher-Order Asynchronous Effects Abstract: We explore asynchronous programming with algebraic effects. We complement their conventional synchronous treatment by showing how to naturally also accommodate asynchrony within them, namely, by decoupling the execution of operation calls into signalling that an operat...	[]	Train
42,957	24	Title: ImDiffusion: Imputed Diffusion Models for Multivariate Time Series Anomaly Detection Abstract: Anomaly detection in multivariate time series data is of paramount importance for ensuring the efficient operation of large-scale systems across diverse domains. However, accurately detecting anomalies in such data pos...	[ 27257, 29857, 42339, 13375 ]	Train
42,958	10	Title: Probabilistic Results on the Architecture of Mathematical Reasoning Aligned by Cognitive Alternation Abstract: We envision a machine capable of solving mathematical problems. Dividing the quantitative reasoning system into two parts: thought processes and cognitive processes, we provide probabilistic description...	[]	Train
42,959	16	Title: Learning to Estimate Two Dense Depths from LiDAR and Event Data Abstract: Event cameras do not produce images, but rather a continuous flow of events, which encode changes of illumination for each pixel independently and asynchronously. While they output temporally rich information, they lack any depth informati...	[]	Train
42,960	25	Title: Unified Keyword Spotting and Audio Tagging on Mobile Devices with Transformers Abstract: Keyword spotting (KWS) is a core human-machine-interaction front-end task for most modern intelligent assistants. Recently, a unified (UniKW-AT) framework has been proposed that adds additional capabilities in the form of au...	[ 12715 ]	Train
42,961	16	Title: From Semi-supervised to Omni-supervised Room Layout Estimation Using Point Clouds Abstract: Room layout estimation is a long-existing robotic vision task that benefits both environment sensing and motion planning. However, layout estimation using point clouds (PCs) still suffers from data scarcity due to annotat...	[ 24057, 6916 ]	Train
42,962	24	Title: The G-invariant graph Laplacian Abstract: Graph Laplacian based algorithms for data lying on a manifold have been proven effective for tasks such as dimensionality reduction, clustering, and denoising. In this work, we consider data sets whose data points not only lie on a manifold, but are also closed under the...	[ 12444 ]	Train
42,963	6	Title: Navigating in the Dark - Designing Autonomous Driving Features to Assist Old Adults with Visual Impairments Abstract: Age-related macular degeneration is a leading cause of blindness worldwide and is one of many limitations to independent driving among old adults. Highly autonomous vehicles present a prospective...	[]	Train
42,964	24	Title: Enhancing Machine Learning Performance with Continuous In-Session Ground Truth Scores: Pilot Study on Objective Skeletal Muscle Pain Intensity Prediction Abstract: Machine learning (ML) models trained on subjective self-report scores struggle to objectively classify pain accurately due to the significant varianc...	[]	Train
42,965	24	Title: Parametrizing Product Shape Manifolds by Composite Networks Abstract: Parametrizations of data manifolds in shape spaces can be computed using the rich toolbox of Riemannian geometry. This, however, often comes with high computational costs, which raises the question if one can learn an efficient neural network ...	[]	Test
42,966	15	Title: Improving DRAM Performance, Reliability, and Security by Rigorously Understanding Intrinsic DRAM Operation Abstract: DRAM is the primary technology used for main memory in modern systems. Unfortunately, as DRAM scales down to smaller technology nodes, it faces key challenges in both data integrity and latency, w...	[]	Validation
42,967	5	Title: On the Minimal Knowledge Required for Solving Stellar Consensus Abstract: Byzantine Consensus is fundamental for building consistent and fault-tolerant distributed systems. In traditional quorum-based consensus protocols, quorums are defined using globally known assumptions shared among all participants. Motivat...	[]	Train
42,968	16	Title: On the fly Deep Neural Network Optimization Control for Low-Power Computer Vision Abstract: Processing visual data on mobile devices has many applications, e.g., emergency response and tracking. State-of-the-art computer vision techniques rely on large Deep Neural Networks (DNNs) that are usually too power-hungr...	[]	Test
42,969	31	Title: Towards Personalized Prompt-Model Retrieval for Generative Recommendation Abstract: Recommender Systems are built to retrieve relevant items to satisfy users' information needs. The candidate corpus usually consists of a finite set of items that are ready to be served, such as videos, products, or articles. With...	[ 6145, 28674, 34074, 2317, 15983, 5744, 17647, 36084, 35800, 15258 ]	Train
42,970	16	Title: Efficiently Robustify Pre-trained Models Abstract: A recent trend in deep learning algorithms has been towards training large scale models, having high parameter count and trained on big dataset. However, robustness of such large scale models towards real-world settings is still a less-explored topic. In this wo...	[ 4643 ]	Test
42,971	7	Title: Burnback Analysis of Solid Propellant Rocket Motors Abstract: Burnback analysis is a geometric exercise, whose correct solution leads to obtaining the thrust curve of solid propellant rockets. Traditionally, Piobert statement, which introduces a certain amount of intuition, is used as an argument to construct an...	[]	Validation
42,972	30	Title: Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation Abstract: Recently, continuous diffusion models (CDM) have been introduced into non-autoregressive (NAR) text-to-text generation. However, the discrete nature of text increases the difficulty of CDM to generate coherent and f...	[ 23120, 34351 ]	Train
42,973	27	Title: EV-Planner: Energy-Efficient Robot Navigation via Event-Based Physics-Guided Neuromorphic Planner Abstract: Vision-based object tracking is an essential precursor to performing autonomous aerial navigation in order to avoid obstacles. Biologically inspired neuromorphic event cameras are emerging as a powerful al...	[ 30520 ]	Train
42,974	30	Title: Improving Factuality of Abstractive Summarization without Sacrificing Summary Quality Abstract: Improving factual consistency of abstractive summarization has been a widely studied topic. However, most of the prior works on training factuality-aware models have ignored the negative effect it has on summary quali...	[ 38102 ]	Train
42,975	15	Title: HiSEP-Q: A Highly Scalable and Efficient Quantum Control Processor for Superconducting Qubits Abstract: Quantum computing promises an effective way to solve targeted problems that are classically intractable. Among them, quantum computers built with superconducting qubits are considered one of the most advanced ...	[]	Train
42,976	24	Title: Efficient Propagation of Uncertainty via Reordering Monte Carlo Samples Abstract: Uncertainty analysis in the outcomes of model predictions is a key element in decision-based material design to establish confidence in the models and evaluate the fidelity of models. Uncertainty Propagation (UP) is a technique to ...	[]	Train
42,977	36	Title: Evolutionary Carrier Selection for Shared Truck Delivery Services Abstract: With multiple carriers in a logistics market, customers can choose the best carrier to deliver their products and packages. In this paper, we present a novel approach of using the stochastic evolutionary game to analyze the decision-maki...	[]	Test

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