node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
21,578 | 16 | Title: Neural Congealing: Aligning Images to a Joint Semantic Atlas
Abstract: We present Neural Congealing – a zero-shot self-supervised framework for detecting and jointly aligning semantically-common content across a given set of images. Our approach harnesses the power of pre-trained DINO-ViT features to learn: (i) ... | [
16833,
32261,
12541,
28647
] | Validation |
21,579 | 10 | Title: Science and engineering for what? A large-scale analysis of students' projects in science fairs
Abstract: Science and Engineering fairs offer K-12 students opportunities to engage with authentic STEM practices. Particularly, students are given the chance to experience authentic and open inquiry processes, by def... | [] | Train |
21,580 | 16 | Title: Selective Structured State-Spaces for Long-Form Video Understanding
Abstract: Effective modeling of complex spatiotemporal dependencies in long-form videos remains an open problem. The recently proposed Structured State-Space Sequence ($S4$) model with its linear complexity offers a promising direction in this s... | [
6457,
41534
] | Test |
21,581 | 6 | Title: Assessment HTN (A-HTN) for Automated Task Performance Assessment in 3D Serious Games
Abstract: In the recent years, various 3D mixed reality serious games have been developed for different applications such as physical training, rehabilitation, and education. Task performance in a serious game is a measurement o... | [] | Train |
21,582 | 16 | Title: Comparative Analysis of Deep Learning Models for Brand Logo Classification in Real-World Scenarios
Abstract: This report presents a comprehensive study on deep learning models for brand logo classification in real-world scenarios. The dataset contains 3,717 labeled images of logos from ten prominent brands. Two ... | [] | Train |
21,583 | 24 | Title: Local Kernel Renormalization as a mechanism for feature learning in overparametrized Convolutional Neural Networks
Abstract: Feature learning, or the ability of deep neural networks to automatically learn relevant features from raw data, underlies their exceptional capability to solve complex tasks. However, fea... | [
2604
] | Test |
21,584 | 24 | Title: Prognosis and Treatment Prediction of Type-2 Diabetes Using Deep Neural Network and Machine Learning Classifiers
Abstract: Type 2 Diabetes is a fast-growing, chronic metabolic disorder due to imbalanced insulin activity. As lots of people are suffering from it, access to proper treatment is necessary to control ... | [] | Train |
21,585 | 24 | Title: Interactive Hyperparameter Optimization in Multi-Objective Problems via Preference Learning
Abstract: Hyperparameter optimization (HPO) is important to leverage the full potential of machine learning (ML). In practice, users are often interested in multi-objective (MO) problems, i.e., optimizing potentially conf... | [] | Train |
21,586 | 24 | Title: Beyond Reward: Offline Preference-guided Policy Optimization
Abstract: This study focuses on the topic of offline preference-based reinforcement learning (PbRL), a variant of conventional reinforcement learning that dispenses with the need for online interaction or specification of reward functions. Instead, the... | [
17122,
17631,
31107,
5541,
4915,
23807
] | Validation |
21,587 | 27 | Title: One-4-All: Neural Potential Fields for Embodied Navigation
Abstract: A fundamental task in robotics is to navigate between two locations. In particular, real-world navigation can require long-horizon planning using high-dimensional RGB images, which poses a substantial challenge for end-to-end learning-based app... | [] | Validation |
21,588 | 16 | Title: SyMFM6D: Symmetry-Aware Multi-Directional Fusion for Multi-View 6D Object Pose Estimation
Abstract: Detecting objects and estimating their 6D poses is essential for automated systems to interact safely with the environment. Most 6D pose estimators, however, rely on a single camera frame and suffer from occlusion... | [] | Train |
21,589 | 16 | Title: Identification of Systematic Errors of Image Classifiers on Rare Subgroups
Abstract: Despite excellent average-case performance of many image classifiers, their performance can substantially deteriorate on semantically coherent subgroups of the data that were under-represented in the training data. These systema... | [
23456,
41152,
28532,
2168,
34074
] | Train |
21,590 | 24 | Title: A deep learning framework for multi-scale models based on physics-informed neural networks
Abstract: Physics-informed neural networks (PINN) combine deep neural networks with the solution of partial differential equations (PDEs), creating a new and promising research area for numerically solving PDEs. Faced with... | [] | Validation |
21,591 | 23 | Title: Patch Space Exploration using Static Analysis Feedback
Abstract: Automated Program Repair (APR) techniques typically rely on a given test-suite to guide the repair process. Apart from the need to provide test oracles, this makes the produced patches prone to test data over-fitting. In this work, instead of relyi... | [] | Validation |
21,592 | 16 | Title: SAT: Size-Aware Transformer for 3D Point Cloud Semantic Segmentation
Abstract: Transformer models have achieved promising performances in point cloud segmentation. However, most existing attention schemes provide the same feature learning paradigm for all points equally and overlook the enormous difference in si... | [
8594
] | Train |
21,593 | 30 | Title: Generating Benchmarks for Factuality Evaluation of Language Models
Abstract: Before deploying a language model (LM) within a given domain, it is important to measure its tendency to generate factually incorrect information in that domain. Existing factual generation evaluation methods focus on facts sampled from... | [
31238,
109,
15410,
32213,
27669,
22422,
31291,
44063
] | Test |
21,594 | 30 | Title: AD-AutoGPT: An Autonomous GPT for Alzheimer's Disease Infodemiology
Abstract: In this pioneering study, inspired by AutoGPT, the state-of-the-art open-source application based on the GPT-4 large language model, we develop a novel tool called AD-AutoGPT which can conduct data collection, processing, and analysis ... | [
45505,
33220,
45189,
40136,
11273,
11497,
14569,
6124,
575,
29396,
16471,
39322,
7996,
1151
] | Validation |
21,595 | 27 | Title: Certifiably Correct Range-Aided SLAM
Abstract: We present the first algorithm to efficiently compute certifiably optimal solutions to range-aided simultaneous localization and mapping (RA-SLAM) problems. Robotic navigation systems increasingly incorporate point-to-point ranging sensors, leading to state estimati... | [
36231,
17009,
32729,
12063
] | Train |
21,596 | 24 | Title: The fine print on tempered posteriors
Abstract: We conduct a detailed investigation of tempered posteriors and uncover a number of crucial and previously undiscussed points. Contrary to previous results, we first show that for realistic models and datasets and the tightly controlled case of the Laplace approxima... | [] | Train |
21,597 | 5 | Title: Energy-Efficiency and Sustainability in New Generation Cloud Computing: A Vision and Directions for Integrated Management of Data Centre Resources and Workloads
Abstract: Cloud computing has become a critical infrastructure for modern society, like electric power grids and roads. As the backbone of the modern ec... | [] | Test |
21,598 | 10 | Title: Neuro-Symbolic AI for Compliance Checking of Electrical Control Panels
Abstract:
Artificial Intelligence plays a main role in supporting and improving smart manufacturing and Industry 4.0, by enabling the automation of different types of tasks manually performed by domain experts. In particular, assessing the ... | [] | Train |
21,599 | 23 | Title: Optimizing Workflow for Elite Developers: Perspectives on Leveraging SE Bots
Abstract: Small-scale automation services in Software Engineering, known as SE Bots, have gradually infiltrated every aspect of daily software development with the goal of enhancing productivity and well-being. While leading the OSS dev... | [] | Train |
21,600 | 24 | Title: TraVaG: Differentially Private Trace Variant Generation Using GANs
Abstract: Process mining is rapidly growing in the industry. Consequently, privacy concerns regarding sensitive and private information included in event data, used by process mining algorithms, are becoming increasingly relevant. State-of-the-ar... | [] | Train |
21,601 | 16 | Title: Semi-supervised 3D Video Information Retrieval with Deep Neural Network and Bi-directional Dynamic-time Warping Algorithm
Abstract: This paper presents a novel semi-supervised deep learning algorithm for retrieving similar 2D and 3D videos based on visual content. The proposed approach combines the power of deep... | [] | Validation |
21,602 | 16 | Title: SynDrone - Multi-modal UAV Dataset for Urban Scenarios
Abstract: The development of computer vision algorithms for Unmanned Aerial Vehicles (UAVs) imagery heavily relies on the availability of annotated high-resolution aerial data. However, the scarcity of large-scale real datasets with pixel-level annotations p... | [] | Train |
21,603 | 24 | Title: XInsight: Revealing Model Insights for GNNs with Flow-based Explanations
Abstract: Progress in graph neural networks has grown rapidly in recent years, with many new developments in drug discovery, medical diagnosis, and recommender systems. While this progress is significant, many networks are `black boxes' wit... | [] | Test |
21,604 | 13 | Title: Generative Meta-Learning Robust Quality-Diversity Portfolio
Abstract: This paper proposes a novel meta-learning approach to optimize a robust portfolio ensemble. The method uses a deep generative model to generate diverse and high-quality sub-portfolios combined to form the ensemble portfolio. The generative mod... | [] | Train |
21,605 | 24 | Title: Human-Aligned Calibration for AI-Assisted Decision Making
Abstract: Whenever a binary classifier is used to provide decision support, it typically provides both a label prediction and a confidence value. Then, the decision maker is supposed to use the confidence value to calibrate how much to trust the predictio... | [
28802
] | Train |
21,606 | 3 | Title: No Transfers Required: Integrating Last Mile with Public Transit Using Opti-Mile
Abstract: Public transit is a popular mode of transit due to its affordability, despite the inconveniences due to the necessity of transfers required to reach most areas. For example, in the bus and metro network of New Delhi, only ... | [] | Train |
21,607 | 4 | Title: A Hierarchical and Location-Aware Consensus Protocol for IoT-Blockchain Applications
Abstract: Blockchain-based IoT systems can manage IoT devices and achieve a high level of data integrity, security, and provenance. However, incorporating existing consensus protocols in many IoT systems limits scalability and l... | [
11402,
14075,
24148
] | Test |
21,608 | 16 | Title: EgoTracks: A Long-term Egocentric Visual Object Tracking Dataset
Abstract: Visual object tracking is a key component to many egocentric vision problems. However, the full spectrum of challenges of egocentric tracking faced by an embodied AI is underrepresented in many existing datasets; these tend to focus on re... | [
26484,
24693,
34902
] | Train |
21,609 | 16 | Title: Set-Membership Inference Attacks using Data Watermarking
Abstract: In this work, we propose a set-membership inference attack for generative models using deep image watermarking techniques. In particular, we demonstrate how conditional sampling from a generative model can reveal the watermark that was injected i... | [
45104,
3548
] | Train |
21,610 | 30 | Title: Leveraging LLMs for KPIs Retrieval from Hybrid Long-Document: A Comprehensive Framework and Dataset
Abstract: Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text, containing textual and... | [
29549,
25071,
4051,
23252,
5461,
31189,
33464,
42393,
37531
] | Train |
21,611 | 24 | Title: Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network
Abstract: Federated Graph Neural Network (FedGNN) has recently emerged as a rapidly growing research topic, as it integrates the strengths of graph neural networks and federated learning to enable advanced machine learn... | [
155,
41901
] | Test |
21,612 | 25 | Title: Whisper-KDQ: A Lightweight Whisper via Guided Knowledge Distillation and Quantization for Efficient ASR
Abstract: Due to the rapid development of computing hardware resources and the dramatic growth of data, pre-trained models in speech recognition, such as Whisper, have significantly improved the performance of... | [] | Train |
21,613 | 30 | Title: GPT-Sentinel: Distinguishing Human and ChatGPT Generated Content
Abstract: This paper presents a novel approach for detecting ChatGPT-generated vs. human-written text using language models. To this end, we first collected and released a pre-processed dataset named OpenGPTText, which consists of rephrased content... | [
31362
] | Train |
21,614 | 16 | Title: MVP-SEG: Multi-View Prompt Learning for Open-Vocabulary Semantic Segmentation
Abstract: CLIP (Contrastive Language-Image Pretraining) is well-developed for open-vocabulary zero-shot image-level recognition, while its applications in pixel-level tasks are less investigated, where most efforts directly adopt CLIP ... | [
10624
] | Validation |
21,615 | 11 | Title: Cost Inference for Feedback Dynamic Games from Noisy Partial State Observations and Incomplete Trajectories
Abstract: In multi-agent dynamic games, the Nash equilibrium state trajectory of each agent is determined by its cost function and the information pattern of the game. However, the cost and trajectory of e... | [
1507,
38556
] | Train |
21,616 | 4 | Title: Gotcha! I Know What You are Doing on the FPGA Cloud: Fingerprinting Co-Located Cloud FPGA Accelerators via Measuring Communication Links
Abstract: In recent decades, due to the emerging requirements of computation acceleration, cloud FPGAs have become popular in public clouds. Major cloud service providers, e.g.... | [] | Train |
21,617 | 30 | Title: PWESuite: Phonetic Word Embeddings and Tasks They Facilitate
Abstract: Word embeddings that map words into a fixed-dimensional vector space are the backbone of modern NLP. Most word embedding methods encode semantic information. However, phonetic information, which is important for some tasks, is often overlooke... | [] | Train |
21,618 | 31 | Title: Adversarial Collaborative Filtering for Free
Abstract: Collaborative Filtering (CF) has been successfully used to help users discover the items of interest. Nevertheless, existing CF methods suffer from noisy data issue, which negatively impacts the quality of recommendation. To tackle this problem, many prior s... | [
7918
] | Train |
21,619 | 5 | Title: Flow-Based Energy Services Composition
Abstract: We propose a novel spatio-temporal service composition framework for crowdsourcing multiple IoT energy services to cater to multiple energy requests. We define a new energy service model to leverage the wearable-based energy and wireless power transfer technologie... | [
7720,
7579,
27310
] | Train |
21,620 | 27 | Title: A Bioinspired Synthetic Nervous System Controller for Pick-and-Place Manipulation
Abstract: The Synthetic Nervous System (SNS) is a biologically inspired neural network (NN). Due to its capability of capturing complex mechanisms underlying neural computation, an SNS model is a candidate for building compact and ... | [] | Train |
21,621 | 30 | Title: On the Computational Modeling of Meaning: Embodied Cognition Intertwined with Emotion
Abstract: This document chronicles this author's attempt to explore how words come to mean what they do, with a particular focus on child language acquisition and what that means for models of language understanding.\footnote{I... | [
27572
] | Train |
21,622 | 30 | Title: Adaptive Prompt Learning with Distilled Connective Knowledge for Implicit Discourse Relation Recognition
Abstract: Implicit discourse relation recognition (IDRR) aims at recognizing the discourse relation between two text segments without an explicit connective. Recently, the prompt learning has just been applie... | [] | Train |
21,623 | 24 | Title: Minimax Weight Learning for Absorbing MDPs
Abstract: Reinforcement learning policy evaluation problems are often modeled as finite or discounted/averaged infinite-horizon MDPs. In this paper, we study undiscounted off-policy policy evaluation for absorbing MDPs. Given the dataset consisting of the i.i.d episodes... | [] | Train |
21,624 | 31 | Title: Fairness-aware Differentially Private Collaborative Filtering
Abstract: Recently, there has been an increasing adoption of differential privacy guided algorithms for privacy-preserving machine learning tasks. However, the use of such algorithms comes with trade-offs in terms of algorithmic fairness, which has be... | [] | Train |
21,625 | 16 | Title: DreamPose: Fashion Image-to-Video Synthesis via Stable Diffusion
Abstract: We present DreamPose, a diffusion-based method for generating animated fashion videos from still images. Given an image and a sequence of human body poses, our method synthesizes a video containing both human and fabric motion. To achieve... | [
10216,
12841,
3690,
29527,
38713,
34074,
36286
] | Train |
21,626 | 20 | Title: $O(k)$-Equivariant Dimensionality Reduction on Stiefel Manifolds
Abstract: Many real-world datasets live on high-dimensional Stiefel and Grassmannian manifolds, $V_k(\mathbb{R}^N)$ and $Gr(k, \mathbb{R}^N)$ respectively, and benefit from projection onto lower-dimensional Stiefel (respectively, Grassmannian) mani... | [] | Train |
21,627 | 24 | Title: Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks
Abstract: Reducing the memory footprint of Machine Learning (ML) models, particularly Deep Neural Networks (DNNs), is essential to enable their deployment into resource-constrained tiny devices. However, a disadvantage of DNN ... | [
5151
] | Train |
21,628 | 16 | Title: Deepfake Detection: A Comparative Analysis
Abstract: This paper present a comprehensive comparative analysis of supervised and self-supervised models for deepfake detection. We evaluate eight supervised deep learning architectures and two transformer-based models pre-trained using self-supervised strategies (DIN... | [] | Train |
21,629 | 16 | Title: Deep Unsupervised Learning Using Spike-Timing-Dependent Plasticity
Abstract: Spike-Timing-Dependent Plasticity (STDP) is an unsupervised learning mechanism for Spiking Neural Networks (SNNs) that has received significant attention from the neuromorphic hardware community. However, scaling such local learning tec... | [] | Validation |
21,630 | 16 | Title: 3Deformer: A Common Framework for Image-Guided Mesh Deformation
Abstract: We propose 3Deformer, a general-purpose framework for interactive 3D shape editing. Given a source 3D mesh with semantic materials, and a user-specified semantic image, 3Deformer can accurately edit the source mesh following the shape guid... | [
23638
] | Validation |
21,631 | 16 | Title: Membership Inference Attack for Beluga Whales Discrimination
Abstract: To efficiently monitor the growth and evolution of a particular wildlife population, one of the main fundamental challenges to address in animal ecology is the re-identification of individuals that have been previously encountered but also th... | [] | Train |
21,632 | 24 | Title: Graph Contextual Contrasting for Multivariate Time Series Classification
Abstract: Contrastive learning, as a self-supervised learning paradigm, becomes popular for Multivariate Time-Series (MTS) classification. It ensures the consistency across different views of unlabeled samples and then learns effective repr... | [
29857,
38569
] | Validation |
21,633 | 31 | Title: A Survey on Causal Inference for Recommendation
Abstract: Recently, causal inference has attracted increasing attention from researchers of recommender systems (RS), which analyzes the relationship between a cause and its effect and has a wide range of real-world applications in multiple fields. Causal inference... | [
11067,
36125
] | Train |
21,634 | 24 | Title: Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives
Abstract: We consider the problem of learning a sparse graph underlying an undirected Gaussian graphical model, a key problem in statistical machine learning. Given $n$ samples from a multivariate Gaussian dis... | [] | Test |
21,635 | 16 | Title: Improving Scene Text Recognition for Character-Level Long-Tailed Distribution
Abstract: Despite the recent remarkable improvements in scene text recognition (STR), the majority of the studies focused mainly on the English language, which only includes few number of characters. However, STR models show a large pe... | [] | Train |
21,636 | 24 | Title: State-wise Constrained Policy Optimization
Abstract: Reinforcement Learning (RL) algorithms have shown tremendous success in simulation environments, but their application to real-world problems faces significant challenges, with safety being a major concern. In particular, enforcing state-wise constraints is es... | [
3904,
1746,
34732
] | Validation |
21,637 | 28 | Title: Robust, Private and Secure Cache-Aided Scalar Linear Function Retrieval from Blind Servers
Abstract: This work investigates a system composed of multiple distributed servers and users, where each user is equiped with a local cache, and aims to retrieve a scalar linear function of the files of a library from the ... | [] | Train |
21,638 | 37 | Title: Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V (Technical Report)
Abstract:
In multi-user environments in which data science and analysis is collaborative, multiple versions of the same datasets are generated. While managing and storing data versions has received some attention in th... | [] | Validation |
21,639 | 30 | Title: Mitigating Negative Transfer with Task Awareness for Sexism, Hate Speech, and Toxic Language Detection
Abstract: This paper proposes a novelty approach to mitigate the negative transfer problem. In the field of machine learning, the common strategy is to apply the Single-Task Learning approach in order to train ... | [
21574
] | Train |
21,640 | 9 | Title: Dyadic Existential Rules
Abstract:
Existential rules form an expressive
${{\textsf{Datalog}}}$
-based language to specify ontological knowledge. The presence of existential quantification in rule-heads, however, makes the main reasoning tasks undecidable. To overcome this limitation, in the last two... | [] | Train |
21,641 | 24 | Title: Model-Free Robust Average-Reward Reinforcement Learning
Abstract: Robust Markov decision processes (MDPs) address the challenge of model uncertainty by optimizing the worst-case performance over an uncertainty set of MDPs. In this paper, we focus on the robust average-reward MDPs under the model-free setting. We... | [
24751
] | Train |
21,642 | 24 | Title: GDOD: Effective Gradient Descent using Orthogonal Decomposition for Multi-Task Learning
Abstract: Multi-task learning (MTL) aims at solving multiple related tasks simultaneously and has experienced rapid growth in recent years. However, MTL models often suffer from performance degeneration with negative transfer... | [] | Train |
21,643 | 32 | Title: DarSIA: An open-source Python toolbox for two-scale image processing of dynamics in porous media
Abstract: Understanding porous media flow is inherently a multi-scale challenge, where at the core lies the aggregation of pore-level processes to a continuum, or Darcy-scale, description. This challenge is directly ... | [] | Train |
21,644 | 10 | Title: Schema First! Learn Versatile Knowledge Graph Embeddings by Capturing Semantics with MASCHInE
Abstract: Knowledge graph embedding models (KGEMs) have gained considerable traction in recent years. These models learn a vector representation of knowledge graph entities and relations, a.k.a. knowledge graph embeddin... | [
12648,
5451,
2519
] | Train |
21,645 | 24 | Title: Neural Polytopes
Abstract: We find that simple neural networks with ReLU activation generate polytopes as an approximation of a unit sphere in various dimensions. The species of polytopes are regulated by the network architecture, such as the number of units and layers. For a variety of activation functions, gen... | [
6284
] | Test |
21,646 | 4 | Title: Malicious Package Detection in NPM and PyPI using a Single Model of Malicious Behavior Sequence
Abstract: Open-source software (OSS) supply chain enlarges the attack surface, which makes package registries attractive targets for attacks. Recently, package registries NPM and PyPI have been flooded with malicious ... | [] | Train |
21,647 | 24 | Title: OmniForce: On Human-Centered, Large Model Empowered and Cloud-Edge Collaborative AutoML System
Abstract: Automated machine learning (AutoML) seeks to build ML models with minimal human effort. While considerable research has been conducted in the area of AutoML in general, aiming to take humans out of the loop w... | [
15547,
44836,
37070
] | Validation |
21,648 | 30 | Title: Cross-Attention is Not Enough: Incongruity-Aware Multimodal Sentiment Analysis and Emotion Recognition
Abstract: Fusing multiple modalities for affective computing tasks has proven effective for performance improvement. However, how multimodal fusion works is not well understood, and its use in the real world us... | [] | Test |
21,649 | 24 | Title: AUTO: Adaptive Outlier Optimization for Online Test-Time OOD Detection
Abstract: Out-of-distribution (OOD) detection is a crucial aspect of deploying machine learning models in open-world applications. Empirical evidence suggests that training with auxiliary outliers substantially improves OOD detection. However... | [
1930,
18386,
8500,
13465,
14618
] | Test |
21,650 | 16 | Title: The role of object-centric representations, guided attention, and external memory on generalizing visual relations
Abstract: Visual reasoning is a long-term goal of vision research. In the last decade, several works have attempted to apply deep neural networks (DNNs) to the task of learning visual relations from... | [] | Train |
21,651 | 6 | Title: “If I Had All the Time in the World”: Ophthalmologists’ Perceptions of Anchoring Bias Mitigation in Clinical AI Support
Abstract: Clinical needs and technological advances have resulted in increased use of Artificial Intelligence (AI) in clinical decision support. However, such support can introduce new and ampl... | [] | Validation |
21,652 | 24 | Title: From Random Search to Bandit Learning in Metric Measure Spaces
Abstract: Random Search is one of the most widely-used method for Hyperparameter Optimization, and is critical to the success of deep learning models. Despite its astonishing performance, little non-heuristic theory has been developed to describe the... | [
34342
] | Train |
21,653 | 24 | Title: BO-Muse: A human expert and AI teaming framework for accelerated experimental design
Abstract: In this paper we introduce BO-Muse, a new approach to human-AI teaming for the optimization of expensive black-box functions. Inspired by the intrinsic difficulty of extracting expert knowledge and distilling it back i... | [] | Test |
21,654 | 10 | Title: Vision-Based Traffic Accident Detection and Anticipation: A Survey
Abstract: Traffic accident detection and anticipation is an obstinate road safety problem and painstaking efforts have been devoted. With the rapid growth of video data, Vision-based Traffic Accident Detection and Anticipation (named Vision-TAD a... | [
21784,
14677,
23646
] | Train |
21,655 | 5 | Title: A Journey Towards the Most Efficient State Database for Hyperledger Fabric
Abstract: The Hyperledger Fabric is well known and the most prominent enterprise-grade permissioned blockchain. The architecture of the Hyperledger Fabric introduces a new architecture paradigm of simulate-order-validate and pluggable arc... | [] | Train |
21,656 | 30 | Title: Counterfactual reasoning: Testing language models’ understanding of hypothetical scenarios
Abstract: Current pre-trained language models have enabled remarkable improvements in downstream tasks, but it remains difficult to distinguish effects of statistical correlation from more systematic logical reasoning grou... | [
7239
] | Test |
21,657 | 34 | Title: Efficient Algorithms and Hardness Results for the Weighted k-Server Problem
Abstract: In this paper, we study the weighted $k$-server problem on the uniform metric in both the offline and online settings. We start with the offline setting. In contrast to the (unweighted) $k$-server problem which has a polynomial... | [] | Train |
21,658 | 27 | Title: Implicit Shape Model Trees: Recognition of 3-D Indoor Scenes and Prediction of Object Poses for Mobile Robots
Abstract: For a mobile robot, we present an approach to recognize scenes in arrangements of objects distributed over cluttered environments. Recognition is made possible by letting the robot alternately ... | [] | Train |
21,659 | 10 | Title: PDSketch: Integrated Planning Domain Programming and Learning
Abstract: This paper studies a model learning and online planning approach towards building flexible and general robots. Specifically, we investigate how to exploit the locality and sparsity structures in the underlying environmental transition model ... | [] | Test |
21,660 | 16 | Title: Amélioration de la qualité d'images avec un algorithme d'optimisation inspirée par la nature
Abstract: Reproducible images preprocessing is important in the field of computer vision, for efficient algorithms comparison or for new images corpus preparation. In this paper, we propose a method to obtain an explicit... | [] | Train |
21,661 | 16 | Title: Boosting Adversarial Transferability using Dynamic Cues
Abstract: The transferability of adversarial perturbations between image models has been extensively studied. In this case, an attack is generated from a known surrogate \eg, the ImageNet trained model, and transferred to change the decision of an unknown (... | [
42109,
1063
] | Test |
21,662 | 16 | Title: MomentDiff: Generative Video Moment Retrieval from Random to Real
Abstract: Video moment retrieval pursues an efficient and generalized solution to identify the specific temporal segments within an untrimmed video that correspond to a given language description. To achieve this goal, we provide a generative diff... | [
8576
] | Train |
21,663 | 28 | Title: Interpreting Training Aspects of Deep-Learned Error-Correcting Codes
Abstract: As new deep-learned error-correcting codes continue to be introduced, it is important to develop tools to interpret the designed codes and understand the training process. Prior work focusing on the deep-learned TurboAE has both inter... | [] | Test |
21,664 | 30 | Title: Retentive or Forgetful? Diving into the Knowledge Memorizing Mechanism of Language Models
Abstract: Memory is one of the most essential cognitive functions serving as a repository of world knowledge and episodes of activities. In recent years, large-scale pre-trained language models have shown remarkable memoriz... | [
1333
] | Validation |
21,665 | 16 | Title: Vanishing Activations: A Symptom of Deep Capsule Networks
Abstract: Capsule Networks, an extension to Neural Networks utilizing vector or matrix representations instead of scalars, were initially developed to create a dynamic parse tree where visual concepts evolve from parts to complete objects. Early implement... | [
22305,
45895
] | Train |
21,666 | 25 | Title: UniBriVL: Robust Universal Representation and Generation of Audio Driven Diffusion Models
Abstract: Multimodal large models have been recognized for their advantages in various performance and downstream tasks. The development of these models is crucial towards achieving general artificial intelligence in the fu... | [
23545
] | Train |
21,667 | 9 | Title: A note on the complexity of addition
Abstract: We show that the sum of a sequence of integers can be computed in linear time on a Turing machine. In particular, the most obvious algorithm for this problem, which appears to require quadratic time due to carry propagation, actually runs in linear time by amortized... | [] | Train |
21,668 | 3 | Title: Moral intuitions behind deepfake-related discussions in Reddit communities
Abstract: Deepfakes are AI-synthesized content that are becoming popular on many social media platforms, meaning the use of deepfakes is increasing in society, regardless of its societal implications. Its implications are harmful if the m... | [] | Train |
21,669 | 31 | Title: GNNUERS: Fairness Explanation in GNNs for Recommendation via Counterfactual Reasoning
Abstract: Nowadays, research into personalization has been focusing on explainability and fairness. Several approaches proposed in recent works are able to explain individual recommendations in a post-hoc manner or by explanati... | [
5961,
3169,
263
] | Train |
21,670 | 24 | Title: Multi-step prediction of chlorophyll concentration based on Adaptive Graph-Temporal Convolutional Network with Series Decomposition
Abstract: Chlorophyll concentration can well reflect the nutritional status and algal blooms of water bodies, and is an important indicator for evaluating water quality. The predict... | [] | Train |
21,671 | 30 | Title: GPT-Calls: Enhancing Call Segmentation and Tagging by Generating Synthetic Conversations via Large Language Models
Abstract: Transcriptions of phone calls are of significant value across diverse fields, such as sales, customer service, healthcare, and law enforcement. Nevertheless, the analysis of these recorded... | [] | Test |
21,672 | 4 | Title: Towards Robust GAN-generated Image Detection: a Multi-view Completion Representation
Abstract: GAN-generated image detection now becomes the first line of defense against the malicious uses of machine-synthesized image manipulations such as deepfakes. Although some existing detectors work well in detecting clean... | [] | Test |
21,673 | 16 | Title: Propheter: Prophetic Teacher Guided Long-Tailed Distribution Learning
Abstract: The problem of deep long-tailed learning, a prevalent challenge in the realm of generic visual recognition, persists in a multitude of real-world applications. To tackle the heavily-skewed dataset issue in long-tailed classification,... | [
33523
] | Test |
21,674 | 30 | Title: Discourse-Aware Text Simplification: From Complex Sentences to Linked Propositions
Abstract: Sentences that present a complex syntax act as a major stumbling block for downstream Natural Language Processing applications whose predictive quality deteriorates with sentence length and complexity. The task of Text S... | [] | Test |
21,675 | 16 | Title: FDCT: Fast Depth Completion for Transparent Objects
Abstract: Depth completion is crucial for many robotic tasks such as autonomous driving, 3-D reconstruction, and manipulation. Despite the significant progress, existing methods remain computationally intensive and often fail to meet the real-time requirements ... | [] | Train |
21,676 | 16 | Title: TransferD2: Automated Defect Detection Approach in Smart Manufacturing using Transfer Learning Techniques
Abstract: Quality assurance is crucial in the smart manufacturing industry as it identifies the presence of defects in finished products before they are shipped out. Modern machine learning techniques can be... | [] | Train |
21,677 | 6 | Title: Visual Explanations with Attributions and Counterfactuals on Time Series Classification
Abstract: With the rising necessity of explainable artificial intelligence (XAI), we see an increase in task-dependent XAI methods on varying abstraction levels. XAI techniques on a global level explain model behavior and on ... | [] | Train |
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