node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
44,778 | 24 | Title: FedICT: Federated Multi-task Distillation for Multi-access Edge Computing
Abstract: The growing interest in intelligent services and privacy protection for mobile devices has given rise to the widespread application of federated learning in Multi-access Edge Computing (MEC). Diverse user behaviors call for perso... | [
30672,
10186,
28508
] | Test |
44,779 | 4 | Title: Security Enhancement of Quantum Noise Stream Cipher Based on Probabilistic Constellation Shaping
Abstract: We propose a QNSC pre-coding scheme based on probabilistic shaping of the basis, to reduce the probability of ciphertext bits that are easier to be intercepted. Experiment results show this scheme can impro... | [] | Test |
44,780 | 30 | Title: NLU on Data Diets: Dynamic Data Subset Selection for NLP Classification Tasks
Abstract: Finetuning large language models inflates the costs of NLU applications and remains the bottleneck of development cycles. Recent works in computer vision use data pruning to reduce training time. Pruned data selection with st... | [] | Train |
44,781 | 16 | Title: Distribution Aligned Diffusion and Prototype-guided network for Unsupervised Domain Adaptive Segmentation
Abstract: The Diffusion Probabilistic Model (DPM) has emerged as a highly effective generative model in the field of computer vision. Its intermediate latent vectors offer rich semantic information, making i... | [] | Test |
44,782 | 16 | Title: Online Unsupervised Video Object Segmentation via Contrastive Motion Clustering
Abstract: Online unsupervised video object segmentation (UVOS) uses the previous frames as its input to automatically separate the primary object(s) from a streaming video without using any further manual annotation. A major challeng... | [] | Train |
44,783 | 24 | Title: A new solution and concrete implementation steps for Artificial General Intelligence
Abstract: At present, the mainstream artificial intelligence generally adopts the technical path of"attention mechanism + deep learning"+"reinforcement learning". It has made great progress in the field of AIGC (Artificial Intel... | [
2219
] | Train |
44,784 | 16 | Title: SimpSON: Simplifying Photo Cleanup with Single-Click Distracting Object Segmentation Network
Abstract: In photo editing, it is common practice to remove visual distractions to improve the overall image quality and highlight the primary subject. However, manually selecting and removing these small and dense distr... | [] | Validation |
44,785 | 24 | Title: On the Minimax Regret for Linear Bandits in a wide variety of Action Spaces
Abstract: As noted in the works of Lattimore and Szepesv´ari [2020], it has been mentioned that it is an open problem to characterize the minimax regret of linear bandits in a wide variety of action spaces. In this article we present an ... | [] | Test |
44,786 | 6 | Title: Rethinking "Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare
Abstract: Risk assessment algorithms are being adopted by public sector agencies to make high-stakes decisions about human lives. Algorithms model “risk” based on individual client characteristics to... | [
10856,
44812
] | Train |
44,787 | 23 | Title: AI Safety Subproblems for Software Engineering Researchers
Abstract: In this 4-page manuscript we discuss the problem of long-term AI Safety from a Software Engineering (SE) research viewpoint. We briefly summarize long-term AI Safety, and the challenge of avoiding harms from AI as systems meet or exceed human c... | [
22899,
8580,
38615
] | Train |
44,788 | 30 | Title: mLongT5: A Multilingual and Efficient Text-To-Text Transformer for Longer Sequences
Abstract: We present our work on developing a multilingual, efficient text-to-text transformer that is suitable for handling long inputs. This model, called mLongT5, builds upon the architecture of LongT5, while leveraging the mu... | [
27292
] | Test |
44,789 | 8 | Title: Tensor Completion via Leverage Sampling and Tensor QR Decomposition for Network Latency Estimation
Abstract: In this paper, we consider the network latency estimation, which has been an important metric for network performance. However, a large scale of network latency estimation requires a lot of computing time... | [] | Train |
44,790 | 24 | Title: TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization
Abstract: Polynomial regression is widely used and can help to express nonlinear patterns. However, considering very high polynomial orders may lead to overfitting and poor extrapolation ability for unseen data. The paper presents a method... | [] | Train |
44,791 | 28 | Title: Stacked Intelligent Metasurfaces for Multiuser Downlink Beamforming in the Wave Domain
Abstract: Intelligent metasurface has recently emerged as a promising technology that enables the customization of wireless environments by harnessing large numbers of inexpensive configurable scattering elements. However, pri... | [
2409,
4781,
5171,
24347,
10300
] | Train |
44,792 | 30 | Title: Translate the Beauty in Songs: Jointly Learning to Align Melody and Translate Lyrics
Abstract: Song translation requires both translation of lyrics and alignment of music notes so that the resulting verse can be sung to the accompanying melody, which is a challenging problem that has attracted some interests in ... | [
15580
] | Train |
44,793 | 6 | Title: Designing Closed-Loop Models for Task Allocation
Abstract: Automatically assigning tasks to people is challenging because human performance can vary across tasks for many reasons. This challenge is further compounded in real-life settings in which no oracle exists to assess the quality of human decisions and tas... | [] | Train |
44,794 | 27 | Title: Modeling and Design of Longitudinal and Lateral Control System with a FeedForward Controller for a 4 Wheeled Robot
Abstract: The work show in this paper progresses through a sequence of physics-based increasing fidelity models that are used to design the robot controllers that respect the limits of the robot cap... | [] | Train |
44,795 | 34 | Title: Online Minimum Spanning Trees with Weight Predictions
Abstract: We consider the minimum spanning tree problem with predictions, using the weight-arrival model, i.e., the graph is given, together with predictions for the weights of all edges. Then the actual weights arrive one at a time and an irrevocable decisio... | [
43283
] | Test |
44,796 | 16 | Title: To pretrain or not to pretrain? A case study of domain-specific pretraining for semantic segmentation in histopathology
Abstract: Annotating medical imaging datasets is costly, so fine-tuning (or transfer learning) is the most effective method for digital pathology vision applications such as disease classificat... | [
5852
] | Train |
44,797 | 16 | Title: Detecting Out-of-distribution Objects Using Neuron Activation Patterns
Abstract: Object detection is essential to many perception algorithms used in modern robotics applications. Unfortunately, the existing models share a tendency to assign high confidence scores for out-of-distribution (OOD) samples. Although O... | [] | Validation |
44,798 | 6 | Title: Complex Daily Activities, Country-Level Diversity, and Smartphone Sensing: A Study in Denmark, Italy, Mongolia, Paraguay, and UK
Abstract: Smartphones enable understanding human behavior with activity recognition to support people’s daily lives. Prior studies focused on using inertial sensors to detect simple ac... | [
21824,
32903,
43880,
21931,
30769,
10932
] | Validation |
44,799 | 22 | Title: Deriving Abstract Interpreters from Skeletal Semantics
Abstract: This paper describes a methodology for defining an executable abstract interpreter from a formal description of the semantics of a programming language. Our approach is based on Skeletal Semantics and an abstract interpretation of its semantic meta... | [] | Train |
44,800 | 16 | Title: Exploiting Implicit Rigidity Constraints via Weight-Sharing Aggregation for Scene Flow Estimation from Point Clouds
Abstract: Scene flow estimation, which predicts the 3D motion of scene points from point clouds, is a core task in autonomous driving and many other 3D vision applications. Existing methods either ... | [] | Train |
44,801 | 6 | Title: Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out
Abstract: With the growing popularity of intelligent assistants (IAs), evaluating IA quality becomes an increasingly active field of research. This paper identifies and quantifies the feedback effect, a nov... | [] | Test |
44,802 | 27 | Title: Operational requirements for localization in autonomous vehicles
Abstract: Autonomous vehicles (AVs) need to determine their position and orientation accurately with respect to global coordinate system or local features under different scene geometries, traffic conditions and environmental conditions. \cite{reid... | [] | Test |
44,803 | 16 | Title: Identity-Preserving Aging of Face Images via Latent Diffusion Models
Abstract: The performance of automated face recognition systems is inevitably impacted by the facial aging process. However, high quality datasets of individuals collected over several years are typically small in scale. In this work, we propos... | [] | Train |
44,804 | 16 | Title: Self-Supervised and Semi-Supervised Polyp Segmentation using Synthetic Data
Abstract: Early detection of colorectal polyps is of utmost importance for their treatment and for colorectal cancer prevention. Computer vision techniques have the potential to aid professionals in the diagnosis stage, where colonoscopi... | [
23712,
33098
] | Validation |
44,805 | 4 | Title: Exploiting Out-of-band Motion Sensor Data to De-anonymize Virtual Reality Users
Abstract: Virtual Reality (VR) is an exciting new consumer technology which offers an immersive audio-visual experience to users through which they can navigate and interact with a digitally represented 3D space (i.e., a virtual worl... | [] | Train |
44,806 | 36 | Title: Geometric Convergence of Distributed Heavy-Ball Nash Equilibrium Algorithm Over Time-Varying Digraphs With Unconstrained Actions
Abstract: This letter presents a new distributed algorithm that leverages heavy-ball momentum and a consensus-based gradient method to find a Nash equilibrium (NE) in a class of non-co... | [
13466,
8765
] | Train |
44,807 | 1 | Title: Pivotuner: automatic real-time pure intonation and microtonal modulation
Abstract: Pivotuner is a VST3/AU MIDI effect plugin that automatically tunes note data in an adaptive pure intonation, in real time. Where previously pure intonation was out of reach for most musicians due to difficulty and impracticality, ... | [] | Train |
44,808 | 36 | Title: Blockchain-empowered Federated Learning for Healthcare Metaverses: User-centric Incentive Mechanism with Optimal Data Freshness
Abstract: Given the revolutionary role of metaverses, healthcare metaverses are emerging as a transformative force, creating intelligent healthcare systems that offer immersive and pers... | [
6768
] | Validation |
44,809 | 23 | Title: Architectural Support for Software Performance in Continuous Software Engineering: A Systematic Mapping Study
Abstract: The continuous software engineering paradigm is gaining popularity in modern development practices, where the interleaving of design and runtime activities is induced by the continuous evolutio... | [
33432
] | Test |
44,810 | 16 | Title: CEN-HDR: Computationally Efficient neural Network for real-time High Dynamic Range imaging
Abstract: High dynamic range (HDR) imaging is still a challenging task in modern digital photography. Recent research proposes solutions that provide high-quality acquisition but at the cost of a very large number of opera... | [
29009
] | Train |
44,811 | 30 | Title: Extrapolating Large Language Models to Non-English by Aligning Languages
Abstract: Due to the unbalanced training data distribution, the language ability of large language models (LLMs) is often biased towards English. In this paper, we propose to empower pre-trained LLMs on non-English languages by building sem... | [
26974,
13700,
16389,
21956,
1575,
25892,
35580,
23883,
2764,
12628,
15358,
6328,
2426,
39451,
20764,
11614
] | Train |
44,812 | 6 | Title: Algorithmic Harms in Child Welfare: Uncertainties in Practice, Organization, and Street-level Decision-Making
Abstract: Algorithms in public services such as child welfare, criminal justice, and education are increasingly being used to make high-stakes decisions about human lives. Drawing upon findings from a tw... | [
17346,
33067,
44786,
24829,
8990
] | Train |
44,813 | 2 | Title: Syntactically and semantically regular languages of lambda-terms coincide through logical relations
Abstract: A fundamental theme in automata theory is regular languages of words and trees, and their many equivalent definitions. Salvati has proposed a generalization to regular languages of simply typed lambda-te... | [
23665,
38273
] | Train |
44,814 | 30 | Title: Uncertainty-Aware Reward-based Deep Reinforcement Learning for Intent Analysis of Social Media Information
Abstract: Due to various and serious adverse impacts of spreading fake news, it is often known that only people with malicious intent would propagate fake news. However, it is not necessarily true based on ... | [] | Validation |
44,815 | 30 | Title: Modeling Appropriate Language in Argumentation
Abstract: Online discussion moderators must make ad-hoc decisions about whether the contributions of discussion participants are appropriate or should be removed to maintain civility. Existing research on offensive language and the resulting tools cover only one asp... | [
18583
] | Validation |
44,816 | 24 | Title: Implicit Design Choices and Their Impact on Emotion Recognition Model Development and Evaluation
Abstract: Emotion recognition is a complex task due to the inherent subjectivity in both the perception and production of emotions. The subjectivity of emotions poses significant challenges in developing accurate and... | [] | Train |
44,817 | 17 | Title: Accurate and Interpretable Solution of the Inverse Rig for Realistic Blendshape Models with Quadratic Corrective Terms
Abstract: We propose a new model-based algorithm solving the inverse rig problem in facial animation retargeting, exhibiting higher accuracy of the fit and sparser, more interpretable weight vec... | [] | Train |
44,818 | 16 | Title: Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples
Abstract: Deep Neural Networks (DNNs) for 3D point cloud recognition are vulnerable to adversarial examples, threatening their practical deployment. Despite the many research endeavors have been made to ta... | [
22334
] | Validation |
44,819 | 30 | Title: STA: Self-controlled Text Augmentation for Improving Text Classifications
Abstract: Despite recent advancements in Machine Learning, many tasks still involve working in low-data regimes which can make solving natural language problems difficult. Recently, a number of text augmentation techniques have emerged in ... | [] | Train |
44,820 | 27 | Title: An Object SLAM Framework for Association, Mapping, and High-Level Tasks
Abstract: Object SLAM is considered increasingly significant for robot high-level perception and decision-making. Existing studies fall short in terms of data association, object representation, and semantic mapping and frequently rely on ad... | [] | Train |
44,821 | 4 | Title: Serberus: Protecting Cryptographic Code from Spectres at Compile-Time
Abstract: We present Serberus, the first comprehensive mitigation for hardening constant-time (CT) code against Spectre attacks (involving the PHT, BTB, RSB, STL and/or PSF speculation primitives) on existing hardware. Serberus is based on thr... | [] | Train |
44,822 | 23 | Title: Using Language Models for Enhancing the Completeness of Natural-language Requirements
Abstract: [Context and motivation] Incompleteness in natural-language requirements is a challenging problem. [Question/problem] A common technique for detecting incompleteness in requirements is checking the requirements agains... | [
12475
] | Train |
44,823 | 4 | Title: Order but Not Execute in Order
Abstract: This work aims to address the general order manipulation issue in blockchain-based decentralized exchanges (DEX) by exploring the benefits of employing differentially order-fair atomic broadcast (of-ABC) mechanisms for transaction ordering and frequent batch auction (FBA)... | [] | Train |
44,824 | 26 | Title: Cost Sensitive GNN-based Imbalanced Learning for Mobile Social Network Fraud Detection
Abstract: With the rapid development of mobile networks, the people's social contacts have been considerably facilitated. However, the rise of mobile social network fraud upon those networks, has caused a great deal of distres... | [] | Train |
44,825 | 30 | Title: Disentangled Variational Autoencoder for Emotion Recognition in Conversations
Abstract: In Emotion Recognition in Conversations (ERC), the emotions of target utterances are closely dependent on their context. Therefore, existing works train the model to generate the response of the target utterance, which aims t... | [
30273,
40803
] | Train |
44,826 | 30 | Title: Using Data Augmentations and VTLN to Reduce Bias in Dutch End-to-End Speech Recognition Systems
Abstract: Speech technology has improved greatly for norm speakers, i.e., adult native speakers of a language without speech impediments or strong accents. However, non-norm or diverse speaker groups show a distinct p... | [] | Train |
44,827 | 24 | Title: Prompting Large Language Models With the Socratic Method
Abstract: This paper presents a systematic approach to using the Socratic method in developing prompt templates that effectively interact with large language models, including GPT-3. Various methods are examined, and those that yield precise answers and ju... | [
7936,
4387,
38349,
4916,
43930
] | Train |
44,828 | 16 | Title: Panoptic Scene Graph Generation with Semantics-prototype Learning
Abstract: Panoptic Scene Graph Generation (PSG) parses objects and predicts their relationships (predicate) to connect human language and visual scenes. However, different language preferences of annotators and semantic overlaps between predicates... | [
19172
] | Train |
44,829 | 30 | Title: ChatGPT may excel in States Medical Licensing Examination but falters in basic Linear Algebra
Abstract: The emergence of ChatGPT has been rapid, and although it has demonstrated positive impacts in certain domains, its influence is not universally advantageous. Our analysis focuses on ChatGPT's capabilities in M... | [] | Train |
44,830 | 24 | Title: Any-dimensional equivariant neural networks
Abstract: Traditional supervised learning aims to learn an unknown mapping by fitting a function to a set of input-output pairs with a fixed dimension. The fitted function is then defined on inputs of the same dimension. However, in many settings, the unknown mapping t... | [] | Train |
44,831 | 6 | Title: An Ambient Intelligence-based Approach For Longitudinal Monitoring of Verbal and Vocal Depression Symptoms
Abstract: Automatic speech recognition (ASR) technology can aid in the detection, monitoring, and assessment of depressive symptoms in individuals. ASR systems have been used as a tool to analyze speech pat... | [] | Test |
44,832 | 16 | Title: CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D Datasets
Abstract: Current RGB-D scene recognition approaches often train two standalone backbones for RGB and depth modalities with the same Places or ImageNet pre-training. However, the pre-trained depth network is still biased by RGB-based models wh... | [] | Test |
44,833 | 30 | Title: Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language Models
Abstract: This paper investigates the capabilities of Large Language Models (LLMs) in the context of understanding their own knowledge and measuring their uncertainty. We argue this is an important feature for mitigating hall... | [
12896,
13700,
44623,
21012,
38102,
28151
] | Train |
44,834 | 24 | Title: Efficient Trust Region-Based Safe Reinforcement Learning with Low-Bias Distributional Actor-Critic
Abstract: To apply reinforcement learning (RL) to real-world applications, agents are required to adhere to the safety guidelines of their respective domains. Safe RL can effectively handle the guidelines by conver... | [] | Train |
44,835 | 27 | Title: Effective Baselines for Multiple Object Rearrangement Planning in Partially Observable Mapped Environments
Abstract: Many real-world tasks, from house-cleaning to cooking, can be formulated as multi-object rearrangement problems – where an agent needs to get specific objects into appropriate goal states. For such... | [] | Validation |
44,836 | 24 | Title: NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
Abstract: Graph neural networks have been extensively studied for learning with inter-connected data. Despite this, recent evidence has revealed GNNs' deficiencies related to over-squashing, heterophily, handling long-range depen... | [
35843,
27268,
4486,
21647,
31375,
16915,
43162,
40478,
24356,
32301,
23233,
32210,
24286,
20321,
2539,
22765,
27630,
44529,
29560,
18297
] | Validation |
44,837 | 24 | Title: Using Visual and Vehicular Sensors for Driver Behavior Analysis: A Survey
Abstract: Risky drivers account for 70% of fatal accidents in the United States. With recent advances in sensors and intelligent vehicular systems, there has been significant research on assessing driver behavior to improve driving experie... | [] | Train |
44,838 | 24 | Title: SABRE: Robust Bayesian Peer-to-Peer Federated Learning
Abstract: We introduce SABRE, a novel framework for robust variational Bayesian peer-to-peer federated learning. We analyze the robustness of the known variational Bayesian peer-to-peer federated learning framework (BayP2PFL) against poisoning attacks and su... | [
44268,
10741
] | Train |
44,839 | 22 | Title: The Unexpected Efficiency of Bin Packing Algorithms for Dynamic Storage Allocation in the Wild: An Intellectual Abstract
Abstract: Two-dimensional rectangular bin packing (2DBP) is a known abstraction of dynamic storage allocation (DSA). We argue that such abstractions can aid practical purposes. 2DBP algorithms... | [
41720
] | Train |
44,840 | 39 | Title: Bounds for a alpha-eigenvalues
Abstract: Let G be a graph with adjacency matrix A(G) and degree diagonal matrix D(G). In 2017, Nikiforov [1] defined the matrix Aalpha(G), as a convex combination of A(G) and D(G), the following way, Aalpha(G) = alpha A(G) + (1 - alpha)D(G), where alpha belongs to [0,1]. In this p... | [] | Test |
44,841 | 16 | Title: Weakly Supervised Scene Text Generation for Low-resource Languages
Abstract: A large number of annotated training images is crucial for training successful scene text recognition models. However, collecting sufficient datasets can be a labor-intensive and costly process, particularly for low-resource languages. ... | [] | Train |
44,842 | 30 | Title: SkillNet-X: A Multilingual Multitask Model with Sparsely Activated Skills
Abstract: Traditional multitask learning methods basically can only exploit common knowledge in task- or language-wise, which lose either cross-language or cross-task knowledge. This paper proposes a general multilingual multitask model, n... | [] | Test |
44,843 | 16 | Title: ASM: Adaptive Skinning Model for High-Quality 3D Face Modeling
Abstract: The research fields of parametric face models and 3D face reconstruction have been extensively studied. However, a critical question remains unanswered: how to tailor the face model for specific reconstruction settings. We argue that recons... | [] | Validation |
44,844 | 30 | Title: Persona-aware Generative Model for Code-mixed Language
Abstract: Code-mixing and script-mixing are prevalent across online social networks and multilingual societies. However, a user's preference toward code-mixing depends on the socioeconomic status, demographics of the user, and the local context, which existi... | [] | Validation |
44,845 | 26 | Title: Quantifying the Impact of Large Language Models on Collective Opinion Dynamics
Abstract: The process of opinion expression and exchange is a critical component of democratic societies. As people interact with large language models (LLMs) in the opinion shaping process different from traditional media, the impact... | [
19968,
40192,
33477,
38157,
23359
] | Validation |
44,846 | 27 | Title: Sampling-based Path Planning Algorithms: A Survey
Abstract: Path planning is a classic problem for autonomous robots. To ensure safe and efficient point-to-point navigation an appropriate algorithm should be chosen keeping the robot's dimensions and its classification in mind. Autonomous robots use path-planning... | [
5809,
16164,
43159
] | Test |
44,847 | 24 | Title: Vehicle lateral control using Machine Learning for automated vehicle guidance
Abstract: Uncertainty in decision-making is crucial in the machine learning model used for a safety-critical system that operates in the real world. Therefore, it is important to handle uncertainty in a graceful manner for the safe ope... | [
3668,
5095
] | Test |
44,848 | 23 | Title: Don’t Lie to Me: Avoiding Malicious Explanations With STEALTH
Abstract: STEALTH is a method for using some artificial intelligence-generated models without suffering from malicious attacks or associated unfairness issues. STEALTH asks so few queries (one per data cluster) that malicious algorithms cannot detect ... | [] | Validation |
44,849 | 10 | Title: Explainable AI applications in the Medical Domain: a systematic review
Abstract: Artificial Intelligence in Medicine has made significant progress with emerging applications in medical imaging, patient care, and other areas. While these applications have proven successful in retrospective studies, very few of th... | [] | Train |
44,850 | 22 | Title: Parameterized Algorithms for Scalable Interprocedural Data-flow Analysis
Abstract: Data-flow analysis is a general technique used to compute information of interest at different points of a program and is considered to be a cornerstone of static analysis. In this thesis, we consider interprocedural data-flow ana... | [] | Train |
44,851 | 16 | Title: GyroFlow+: Gyroscope-Guided Unsupervised Deep Homography and Optical Flow Learning
Abstract: Existing homography and optical flow methods are erroneous in challenging scenes, such as fog, rain, night, and snow because the basic assumptions such as brightness and gradient constancy are broken. To address this iss... | [
23991
] | Validation |
44,852 | 37 | Title: Efficient Black-box Checking of Snapshot Isolation in Databases
Abstract: Snapshot isolation (SI) is a prevalent weak isolation level that avoids the performance penalty imposed by serializability and simultaneously prevents various undesired data anomalies. Nevertheless, SI anomalies have recently been found in... | [] | Train |
44,853 | 16 | Title: Controlling Geometric Abstraction and Texture for Artistic Images
Abstract: We present a novel method for the interactive control of geometric abstraction and texture in artistic images. Previous example-based stylization methods often entangle shape, texture, and color, while generative methods for image synthe... | [] | Train |
44,854 | 16 | Title: SAM on Medical Images: A Comprehensive Study on Three Prompt Modes
Abstract: The Segment Anything Model (SAM) made an eye-catching debut recently and inspired many researchers to explore its potential and limitation in terms of zero-shot generalization capability. As the first promptable foundation model for seg... | [
27027,
43795,
26269,
12704,
44707,
22713,
23356,
35263,
6089,
19920,
38612,
29270,
27866,
17633,
25955,
25703,
5864,
45546,
4083,
33267,
40700
] | Train |
44,855 | 24 | Title: Learning Trajectories are Generalization Indicators
Abstract: This paper explores the connection between learning trajectories of Deep Neural Networks (DNNs) and their generalization capabilities when optimized using (stochastic) gradient descent algorithms. Instead of concentrating solely on the generalization ... | [
42192
] | Validation |
44,856 | 10 | Title: River of No Return: Graph Percolation Embeddings for Efficient Knowledge Graph Reasoning
Abstract: We study Graph Neural Networks (GNNs)-based embedding techniques for knowledge graph (KG) reasoning. For the first time, we link the path redundancy issue in the state-of-the-art KG reasoning models based on path e... | [] | Train |
44,857 | 24 | Title: Hard Sample Mining Enabled Supervised Contrastive Feature Learning for Wind Turbine Pitch System Fault Diagnosis
Abstract: The efficient utilization of wind power by wind turbines relies on the ability of their pitch systems to adjust blade pitch angles in response to varying wind speeds. However, the presence o... | [] | Train |
44,858 | 6 | Title: Enabling Voice-Accompanying Hand-to-Face Gesture Recognition with Cross-Device Sensing
Abstract: Gestures performed accompanying the voice are essential for voice interaction to convey complementary semantics for interaction purposes such as wake-up state and input modality. In this paper, we investigated voice-... | [
32856,
12717
] | Train |
44,859 | 24 | Title: An interpretable deep learning method for bearing fault diagnosis
Abstract: Deep learning (DL) has gained popularity in recent years as an effective tool for classifying the current health and predicting the future of industrial equipment. However, most DL models have black-box components with an underlying stru... | [] | Train |
44,860 | 36 | Title: TSO Games - On the decidability of safety games under the total store order semantics (extended version with appendix)
Abstract: We consider an extension of the classical Total Store Order (TSO) semantics by expanding it to turn-based 2-player safety games. During her turn, a player can select any of the communi... | [
6950
] | Train |
44,861 | 27 | Title: Task and Configuration Space Compliance of Continuum Robots via Lie Group and Modal Shape Formulations
Abstract: Continuum robots suffer large deflections due to internal and external forces. Accurate modeling of their passive compliance is necessary for accurate environmental interaction, especially in scenario... | [] | Train |
44,862 | 34 | Title: Influence Maximization in Ising Models
Abstract: Given a complex high-dimensional distribution over $\{\pm 1\}^n$, what is the best way to increase the expected number of $+1$'s by controlling the values of only a small number of variables? Such a problem is known as influence maximization and has been widely st... | [] | Train |
44,863 | 16 | Title: PU-EdgeFormer: Edge Transformer for Dense Prediction in Point Cloud Upsampling
Abstract: Despite the recent development of deep learning-based point cloud upsampling, most MLP-based point cloud upsampling methods have limitations in that it is difficult to train the local and global structure of the point cloud ... | [] | Train |
44,864 | 30 | Title: A Novel Framework for Multimodal Named Entity Recognition with Multi-level Alignments
Abstract: Mining structured knowledge from tweets using named entity recognition (NER) can be beneficial for many downstream applications such as recommendation and intention under standing. With tweet posts tending to be multi... | [] | Test |
44,865 | 24 | Title: RLBoost: Boosting Supervised Models using Deep Reinforcement Learning
Abstract: Data quality or data evaluation is sometimes a task as important as collecting a large volume of data when it comes to generating accurate artificial intelligence models. In fact, being able to evaluate the data can lead to a larger ... | [] | Train |
44,866 | 24 | Title: Instance-Optimality in Interactive Decision Making: Toward a Non-Asymptotic Theory
Abstract: We consider the development of adaptive, instance-dependent algorithms for interactive decision making (bandits, reinforcement learning, and beyond) that, rather than only performing well in the worst case, adapt to favo... | [
7959
] | Train |
44,867 | 16 | Title: Road Disease Detection based on Latent Domain Background Feature Separation and Suppression
Abstract: Road disease detection is challenging due to the the small proportion of road damage in target region and the diverse background,which introduce lots of domain information.Besides, disease categories have high s... | [
27798
] | Train |
44,868 | 10 | Title: The Governance of Physical Artificial Intelligence
Abstract: Physical artificial intelligence can prove to be one of the most important challenges of the artificial intelligence. The governance of physical artificial intelligence would define its responsible intelligent application in the society. | [] | Train |
44,869 | 5 | Title: Robust decentralised proof-of-position algorithms for smart city applications
Abstract: We present a decentralised class of algorithms called Tree-Proof-of-Position (T-PoP). T-PoP algorithms rely on the web of interconnected devices in a smart city to establish how likely it is that an agent is in the position t... | [] | Test |
44,870 | 2 | Title: Graph Sequence Learning for Premise Selection
Abstract: Premise selection is crucial for large theory reasoning as the sheer size of the problems quickly leads to resource starvation. This paper proposes a premise selection approach inspired by the domain of image captioning, where language models automatically ... | [] | Train |
44,871 | 24 | Title: Elliptic PDE learning is provably data-efficient
Abstract: PDE learning is an emerging field that combines physics and machine learning to recover unknown physical systems from experimental data. While deep learning models traditionally require copious amounts of training data, recent PDE learning techniques ach... | [
14070
] | Test |
44,872 | 5 | Title: Workload Behavior Driven Memory Subsystem Design for Hyperscale
Abstract: Hyperscalars run services across a large fleet of servers, serving billions of users worldwide. These services, however, behave differently than commonly available benchmark suites, resulting in server architectures that are not optimized ... | [] | Validation |
44,873 | 16 | Title: DePT: Decoupled Prompt Tuning
Abstract: This work breaks through the Base-New Tradeoff (BNT)dilemma in prompt tuning, i.e., the better the tuned model generalizes to the base (or target) task, the worse it generalizes to new tasks, and vice versa. Specifically, through an in-depth analysis of the learned feature... | [
6556,
22910
] | Train |
44,874 | 27 | Title: Path Planning Under Uncertainty to Localize mmWave Sources
Abstract: In this paper, we study a navigation problem where a mobile robot needs to locate a mmWave wireless signal. Using the directionality properties of the signal, we propose an estimation and path planning algorithm that can efficiently navigate in... | [] | Train |
44,875 | 33 | Title: The Expansion Problem for Infinite Trees
Abstract: We study Ramsey like theorems for infinite trees and similar combinatorial tools. As an application we consider the expansion problem for tree algebras. | [] | Train |
44,876 | 27 | Title: Kalman Filter Auto-tuning through Enforcing Chi-Squared Normalized Error Distributions with Bayesian Optimization
Abstract: The nonlinear and stochastic relationship between noise covariance parameter values and state estimator performance makes optimal filter tuning a very challenging problem. Popular optimizat... | [] | Train |
44,877 | 2 | Title: Monus semantics in vector addition systems with states
Abstract: Vector addition systems with states (VASS) are a popular model for concurrent systems. However, many decision problems have prohibitively high complexity. Therefore, it is sometimes useful to consider overapproximating semantics in which these prob... | [
22712,
35886
] | Train |
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