node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
23,878 | 2 | Title: AutoHyper: Explicit-State Model Checking for HyperLTL
Abstract: HyperLTL is a temporal logic that can express hyperproperties, i.e., properties that relate multiple execution traces of a system. Such properties are becoming increasingly important and naturally occur, e.g., in information-flow control, robustness... | [
22520,
15897,
6186,
30615
] | Train |
23,879 | 8 | Title: Mitigating Unnecessary Handovers in Ultra-Dense Networks through Machine Learning-based Mobility Prediction
Abstract: In 5G wireless communication, Intelligent Transportation Systems (ITS) and automobile applications, such as autonomous driving, are widely examined. These applications have strict requirements an... | [] | Train |
23,880 | 2 | Title: Higher-Order LCTRSs and Their Termination
Abstract: Logically constrained term rewriting systems (LCTRSs) are a program analyzing formalism with native support for data types which are not (co)inductively defined. As a first-order formalism, LCTRSs have accommodated only analysis of imperative programs so far. I... | [] | Train |
23,881 | 30 | Title: A Novel Plagiarism Detection Approach Combining BERT-based Word Embedding, Attention-based LSTMs and an Improved Differential Evolution Algorithm
Abstract: Detecting plagiarism involves finding similar items in two different sources. In this article, we propose a novel method for detecting plagiarism that is bas... | [] | Train |
23,882 | 24 | Title: From Latent Graph to Latent Topology Inference: Differentiable Cell Complex Module
Abstract: Latent Graph Inference (LGI) relaxed the reliance of Graph Neural Networks (GNNs) on a given graph topology by dynamically learning it. However, most of LGI methods assume to have a (noisy, incomplete, improvable, ...) i... | [
20320,
28650,
36085,
41327
] | Train |
23,883 | 30 | Title: Empowering Cross-lingual Abilities of Instruction-tuned Large Language Models by Translation-following demonstrations
Abstract: The language ability of Large Language Models (LLMs) is often unbalanced towards English because of the imbalance in the distribution of the pre-training data. This disparity is demande... | [
14368,
15394,
13700,
16389,
21956,
35580,
747,
2764,
109,
44811,
34347,
18739,
15358,
20764,
11614
] | Test |
23,884 | 24 | Title: A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models
Abstract: Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model. MIAs on the classic classification models have been well-studied, and recent works ha... | [
3548,
7973
] | Test |
23,885 | 24 | Title: Towards Revealing the Mystery behind Chain of Thought: a Theoretical Perspective
Abstract: Recent studies have discovered that Chain-of-Thought prompting (CoT) can dramatically improve the performance of Large Language Models (LLMs), particularly when dealing with complex tasks involving mathematics or reasoning... | [
35488,
40099,
13700,
13510,
27879,
24087
] | Train |
23,886 | 16 | Title: LDL: Line Distance Functions for Panoramic Localization
Abstract: We introduce LDL, a fast and robust algorithm that localizes a panorama to a 3D map using line segments. LDL focuses on the sparse structural information of lines in the scene, which is robust to illumination changes and can potentially enable eff... | [] | Train |
23,887 | 16 | Title: Prototype Learning for Out-of-Distribution Polyp Segmentation
Abstract: Existing polyp segmentation models from colonoscopy images often fail to provide reliable segmentation results on datasets from different centers, limiting their applicability. Our objective in this study is to create a robust and well-gener... | [] | Train |
23,888 | 28 | Title: Multi-access Coded Caching with Linear Subpacketization
Abstract: We consider the multi-access coded caching problem, which contains a central server with N files, K caches with M units of memory each and K users where each one is connected to L(≥ 1) consecutive caches, with a cyclic wrap-around. Caches are popu... | [] | Train |
23,889 | 4 | Title: ANALYSE - Learning to Attack Cyber-Physical Energy Systems With Intelligent Agents
Abstract: The ongoing penetration of energy systems with information and communications technology (ICT) and the introduction of new markets increase the potential for malicious or profit-driven attacks that endanger system stabil... | [] | Train |
23,890 | 34 | Title: Linear Query Approximation Algorithms for Non-monotone Submodular Maximization under Knapsack Constraint
Abstract: This work, for the first time, introduces two constant factor approximation algorithms with linear query complexity for non-monotone submodular maximization over a ground set of size n subject to a ... | [] | Train |
23,891 | 25 | Title: CALM: Contrastive Cross-modal Speaking Style Modeling for Expressive Text-to-Speech Synthesis
Abstract: To further improve the speaking styles of synthesized speeches, current text-to-speech (TTS) synthesis systems commonly employ reference speeches to stylize their outputs instead of just the input texts. These... | [] | Test |
23,892 | 24 | Title: Large-Batch, Neural Multi-Objective Bayesian Optimization
Abstract: Bayesian optimization provides a powerful framework for global optimization of black-box, expensive-to-evaluate functions. However, it has a limited capacity in handling data-intensive problems, especially in multi-objective settings, due to the... | [] | Train |
23,893 | 16 | Title: Crafting Training Degradation Distribution for the Accuracy-Generalization Trade-off in Real-World Super-Resolution
Abstract: Super-resolution (SR) techniques designed for real-world applications commonly encounter two primary challenges: generalization performance and restoration accuracy. We demonstrate that w... | [
21886,
43286
] | Train |
23,894 | 3 | Title: Leveraging Recommender Systems to Reduce Content Gaps on Peer Production Platforms
Abstract: Peer production platforms like Wikipedia commonly suffer from content gaps. Prior research suggests recommender systems can help solve this problem, by guiding editors towards underrepresented topics. However, it remains... | [] | Validation |
23,895 | 34 | Title: On minimum t-claw deletion in split graphs
Abstract: For $t\geq 3$, $K_{1, t}$ is called $t$-claw. In minimum $t$-claw deletion problem (\texttt{Min-$t$-Claw-Del}), given a graph $G=(V, E)$, it is required to find a vertex set $S$ of minimum size such that $G[V\setminus S]$ is $t$-claw free. In a split graph, th... | [] | Train |
23,896 | 31 | Title: Online Distillation for Pseudo-Relevance Feedback
Abstract: Model distillation has emerged as a prominent technique to improve neural search models. To date, distillation taken an offline approach, wherein a new neural model is trained to predict relevance scores between arbitrary queries and documents. In this ... | [
22901
] | Test |
23,897 | 31 | Title: Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation
Abstract: Transformer and its variants are a powerful class of architectures for sequential recommendation, owing to their ability of capturing a user’s dynamic interests from their past interaction... | [
25349,
7918
] | Train |
23,898 | 30 | Title: The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset
Abstract: As language models grow ever larger, the need for large-scale high-quality text datasets has never been more pressing, especially in multilingual settings. The BigScience workshop, a 1-year international and multidisciplinary initiativ... | [
40192,
28680,
16911,
6037,
24087,
38167,
15129,
44441,
23580,
16156,
34208,
21793,
25892,
33830,
25645,
14001,
10163,
20025,
25021,
29375,
6721,
21190,
3017,
25936,
37330,
38868,
33876,
24150,
16471,
13911,
35930,
2787,
28903,
109,
10480,
34423,
... | Test |
23,899 | 30 | Title: An Analysis of Abstractive Text Summarization Using Pre-trained Models
Abstract: nan | [
22683
] | Train |
23,900 | 16 | Title: U-TILISE: A Sequence-to-sequence Model for Cloud Removal in Optical Satellite Time Series
Abstract: Satellite image time series in the optical and infrared spectrum suffer from frequent data gaps due to cloud cover, cloud shadows, and temporary sensor outages. It has been a long-standing problem of remote sensin... | [
11682
] | Validation |
23,901 | 23 | Title: DACOS—A Manually Annotated Dataset of Code Smells
Abstract: Researchers apply machine-learning techniques for code smell detection to counter the subjectivity of many code smells. Such approaches need a large, manually annotated dataset for training and benchmarking. Existing literature offers a few datasets; ho... | [] | Test |
23,902 | 20 | Title: On the Parameterized Complexity of Bend-Minimum Orthogonal Planarity
Abstract: Computing planar orthogonal drawings with the minimum number of bends is one of the most relevant topics in Graph Drawing. The problem is known to be NP-hard, even when we want to test the existence of a rectilinear planar drawing, i.... | [] | Validation |
23,903 | 16 | Title: End-to-End Lane detection with One-to-Several Transformer
Abstract: Although lane detection methods have shown impressive performance in real-world scenarios, most of methods require post-processing which is not robust enough. Therefore, end-to-end detectors like DEtection TRansformer(DETR) have been introduced ... | [
38984,
40583
] | Train |
23,904 | 3 | Title: Graph Global Attention Network with Memory for Fake News Detection
Abstract: With the proliferation of social media, the detection of fake news has become a critical issue that poses a significant threat to society. The dissemination of fake information can lead to social harm and damage the credibility of infor... | [] | Validation |
23,905 | 24 | Title: Emergent Agentic Transformer from Chain of Hindsight Experience
Abstract: Large transformer models powered by diverse data and model scale have dominated natural language modeling and computer vision and pushed the frontier of multiple AI areas. In reinforcement learning (RL), despite many efforts into transform... | [
26673,
25660,
4822
] | Test |
23,906 | 16 | Title: Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering
Abstract: In this paper, a bridge member damage cause estimation framework is proposed by calculating the image position using Structure from Motion (SfM) and acquiring its information via Visual Question Answering (VQA). For... | [] | Test |
23,907 | 8 | Title: A Cooperative Content Dissemination Framework for Fog-Based Internet of Vehicles
Abstract: As the fog-based internet of vehicles (IoV) is equipped with rich perception, computing, communication and storage resources, it provides a new solution for the bulk data processing. However, the impact caused by the mobil... | [] | Train |
23,908 | 25 | Title: Boosting Fast and High-Quality Speech Synthesis with Linear Diffusion
Abstract: Denoising Diffusion Probabilistic Models have shown extraordinary ability on various generative tasks. However, their slow inference speed renders them impractical in speech synthesis. This paper proposes a linear diffusion model (Li... | [
8308
] | Train |
23,909 | 16 | Title: Improved Region Proposal Network for Enhanced Few-Shot Object Detection
Abstract: Despite significant success of deep learning in object detection tasks, the standard training of deep neural networks requires access to a substantial quantity of annotated images across all classes. Data annotation is an arduous a... | [
4769,
40355,
36276
] | Train |
23,910 | 26 | Title: Visually Wired NFTs: Exploring the Role of Inspiration in Non-Fungible Tokens
Abstract: The fervor for Non-Fungible Tokens (NFTs) attracted countless creators, leading to a Big Bang of digital assets driven by latent or explicit forms of inspiration, as in many creative processes. This work exploits Vision Trans... | [
18272
] | Train |
23,911 | 2 | Title: Lemmas: Generation, Selection, Application
Abstract: Noting that lemmas are a key feature of mathematics, we engage in an investigation of the role of lemmas in automated theorem proving. The paper describes experiments with a combined system involving learning technology that generates useful lemmas for automat... | [
3249,
6364
] | Train |
23,912 | 16 | Title: Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models
Abstract: This work aims to improve the applicability of diffusion models in realistic image restoration. Specifically, we enhance the diffusion model in several aspects such as network architecture, noise level, denoisi... | [
26115,
39628,
500,
11886
] | Train |
23,913 | 28 | Title: LTE SFBC MIMO Transmitter Modelling and Performance Evaluation
Abstract: High data rates are one of the most prevalent requirements in current mobile communications. To cover this and other high standards regarding performance, increasing coverage, capacity, and reliability, numerous works have proposed the deve... | [] | Train |
23,914 | 16 | Title: Group Pose: A Simple Baseline for End-to-End Multi-person Pose Estimation
Abstract: In this paper, we study the problem of end-to-end multi-person pose estimation. State-of-the-art solutions adopt the DETR-like framework, and mainly develop the complex decoder, e.g., regarding pose estimation as keypoint box det... | [
33218
] | Train |
23,915 | 18 | Title: Ratio Shift Keying Modulation for Time-Varying Molecular Communication Channels
Abstract: Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to encode and transfer information. Many efforts have been devoted to developing novel modulation techniques for MC based on variou... | [
10893
] | Train |
23,916 | 25 | Title: RMVPE: A Robust Model for Vocal Pitch Estimation in Polyphonic Music
Abstract: Vocal pitch is an important high-level feature in music audio processing. However, extracting vocal pitch in polyphonic music is more challenging due to the presence of accompaniment. To eliminate the influence of the accompaniment, m... | [
20401
] | Validation |
23,917 | 16 | Title: DUDES: Deep Uncertainty Distillation using Ensembles for Semantic Segmentation
Abstract: Deep neural networks lack interpretability and tend to be overconfident, which poses a serious problem in safety-critical applications like autonomous driving, medical imaging, or machine vision tasks with high demands on re... | [
20888,
34977
] | Train |
23,918 | 24 | Title: DualFL: A Duality-based Federated Learning Algorithm with Communication Acceleration in the General Convex Regime
Abstract: We propose a novel training algorithm called DualFL (Dualized Federated Learning), for solving a distributed optimization problem in federated learning. Our approach is based on a specific ... | [] | Validation |
23,919 | 10 | Title: Max-min Learning of Approximate Weight Matrices from Fuzzy Data
Abstract: In this article, we study the approximate solutions set $\Lambda_b$ of an inconsistent system of $\max-\min$ fuzzy relational equations $(S): A \Box_{\min}^{\max}x =b$. Using the $L_\infty$ norm, we compute by an explicit analytical formul... | [
45466
] | Train |
23,920 | 6 | Title: Validating a virtual human and automated feedback system for training doctor-patient communication skills
Abstract: Effective communication between a clinician and their patient is critical for delivering healthcare maximizing outcomes. Unfortunately, traditional communication training approaches that use human ... | [
33220,
13510
] | Train |
23,921 | 24 | Title: HCE: Improving Performance and Efficiency with Heterogeneously Compressed Neural Network Ensemble
Abstract: —Ensemble learning has gain attention in resent deep learning research as a way to further boost the accuracy and generalizability of deep neural network (DNN) models. Recent en- semble training method exp... | [] | Train |
23,922 | 16 | Title: Collaborative Tracking Learning for Frame-Rate-Insensitive Multi-Object Tracking
Abstract: Multi-object tracking (MOT) at low frame rates can reduce computational, storage and power overhead to better meet the constraints of edge devices. Many existing MOT methods suffer from significant performance degradation ... | [] | Train |
23,923 | 36 | Title: Quantum Potential Games, Replicator Dynamics, and the Separability Problem
Abstract: Gamification is an emerging trend in the field of machine learning that presents a novel approach to solving optimization problems by transforming them into game-like scenarios. This paradigm shift allows for the development of ... | [] | Train |
23,924 | 30 | Title: Generating Mathematical Derivations with Large Language Models
Abstract: The derivation of mathematical results in specialised fields, using Large Language Models (LLMs), is an emerging research direction that can help identify models' limitations, and potentially support mathematical discovery. In this paper, w... | [
40610,
13700,
23502,
16302,
18035,
44246,
31227,
35388
] | Test |
23,925 | 24 | Title: Improved Naive Bayes with Mislabeled Data
Abstract: Labeling mistakes are frequently encountered in real-world applications. If not treated well, the labeling mistakes can deteriorate the classification performances of a model seriously. To address this issue, we propose an improved Naive Bayes method for text c... | [] | Train |
23,926 | 3 | Title: Assessing enactment of content regulation policies: A post hoc crowd-sourced audit of election misinformation on YouTube
Abstract: With the 2022 US midterm elections approaching, conspiratorial claims about the 2020 presidential elections continue to threaten users’ trust in the electoral process. To regulate el... | [] | Validation |
23,927 | 26 | Title: CONTAIN: A Community-based Algorithm for Network Immunization
Abstract: Within the network analysis field, network immunization refers to the task of protecting a network from some arbitrary diffusion that tries to infect it. In this article, we consider the spread of harmful content in social networks, and we p... | [
31687,
39903
] | Test |
23,928 | 24 | Title: Model Pruning Enables Localized and Efficient Federated Learning for Yield Forecasting and Data Sharing
Abstract: Federated Learning (FL) presents a decentralized approach to model training in the agri-food sector and offers the potential for improved machine learning performance, while ensuring the safety and p... | [] | Train |
23,929 | 23 | Title: A Technical Report on Image Classification using AWS
Abstract: This project aims to build an elastic web application that can automatically scale out and scale in on-demand and cost-effectively by utilizing cloud resources, specifically from Amazon Web Services (AWS). The application is an image classification s... | [] | Train |
23,930 | 30 | Title: Towards Countering Essentialism through Social Bias Reasoning
Abstract: Essentialist beliefs (i.e., believing that members of the same group are fundamentally alike) play a central role in social stereotypes and can lead to harm when left unchallenged. In our work, we conduct exploratory studies into the task of... | [] | Train |
23,931 | 4 | Title: Classification of Quantum Computer Fault Injection Attacks
Abstract: The rapid growth of interest in quantum computing has brought about the need to secure these powerful machines against a range of physical attacks. As qubit counts increase and quantum computers achieve higher levels of fidelity, their potentia... | [] | Train |
23,932 | 4 | Title: Inferential Privacy: From Impossibility to Database Privacy
Abstract: We investigate the possibility of guaranteeing inferential privacy for mechanisms that release useful information about some data containing sensitive information, denoted by $X$. We describe a general model of utility and privacy in which uti... | [] | Test |
23,933 | 25 | Title: Whombat: An open-source annotation tool for machine learning development in bioacoustics
Abstract: 1. Automated analysis of bioacoustic recordings using machine learning (ML) methods has the potential to greatly scale biodiversity monitoring efforts. The use of ML for high-stakes applications, such as conservati... | [] | Validation |
23,934 | 24 | Title: Exploiting Multi-Label Correlation in Label Distribution Learning
Abstract: Label Distribution Learning (LDL) is a novel machine learning paradigm that assigns label distribution to each instance. Many LDL methods proposed to leverage label correlation in the learning process to solve the exponential-sized outpu... | [] | Validation |
23,935 | 16 | Title: Generative Image Inpainting with Segmentation Confusion Adversarial Training and Contrastive Learning
Abstract: This paper presents a new adversarial training framework for image inpainting with segmentation confusion adversarial training (SCAT) and contrastive learning. SCAT plays an adversarial game between an... | [] | Train |
23,936 | 24 | Title: Finite Expression Methods for Discovering Physical Laws from Data
Abstract: Nonlinear dynamics is a pervasive phenomenon observed in scientific and engineering disciplines. However, the task of deriving analytical expressions to describe nonlinear dynamics from limited data remains challenging. In this paper, we... | [] | Train |
23,937 | 26 | Title: Network Sampling Methods for Estimating Social Networks, Population Percentages and Totals of People Experiencing Homelessness
Abstract: In this article, we propose using network-based sampling strategies to estimate the number of unsheltered people experiencing homelessness within a given administrative service... | [] | Test |
23,938 | 16 | Title: Review of methods for automatic cerebral microbleeds detection
Abstract: Cerebral microbleeds detection is an important and challenging task. With the gaining popularity of the MRI, the ability to detect cerebral microbleeds also raises. Unfortunately, for radiologists, it is a time-consuming and laborious proce... | [] | Test |
23,939 | 10 | Title: FIMO: A Challenge Formal Dataset for Automated Theorem Proving
Abstract: We present FIMO, an innovative dataset comprising formal mathematical problem statements sourced from the International Mathematical Olympiad (IMO) Shortlisted Problems. Designed to facilitate advanced automated theorem proving at the IMO l... | [
33220
] | Test |
23,940 | 24 | Title: Poster: Towards Battery-Free Machine Learning Inference and Model Personalization on MCUs
Abstract: Machine learning (ML) is moving towards edge devices. However, ML models with high computational demands and energy consumption pose challenges for ML inference in resource-constrained environments, such as the de... | [] | Train |
23,941 | 24 | Title: Near-Optimal Adversarial Reinforcement Learning with Switching Costs
Abstract: Switching costs, which capture the costs for changing policies, are regarded as a critical metric in reinforcement learning (RL), in addition to the standard metric of losses (or rewards). However, existing studies on switching costs ... | [] | Validation |
23,942 | 3 | Title: For Women, Life, Freedom: A Participatory AI-Based Social Web Analysis of a Watershed Moment in Iran's Gender Struggles
Abstract: In this paper, we present a computational analysis of the Persian language Twitter discourse with the aim to estimate the shift in stance toward gender equality following the death of... | [] | Train |
23,943 | 24 | Title: ELRA: Exponential learning rate adaption gradient descent optimization method
Abstract: We present a novel, fast (exponential rate adaption), ab initio (hyper-parameter-free) gradient based optimizer algorithm. The main idea of the method is to adapt the learning rate $\alpha$ by situational awareness, mainly st... | [
39522,
16094
] | Train |
23,944 | 16 | Title: Co-Occurrence Matters: Learning Action Relation for Temporal Action Localization
Abstract: Temporal action localization (TAL) is a prevailing task due to its great application potential. Existing works in this field mainly suffer from two weaknesses: (1) They often neglect the multi-label case and only focus on ... | [] | Test |
23,945 | 30 | Title: History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
Abstract: Context information modeling is an important task in conversational KBQA. However, existing methods usually assume the independence of utterances and model them in isolation. In this paper, we propose a History Seman... | [] | Train |
23,946 | 16 | Title: UGC Quality Assessment: Exploring the Impact of Saliency in Deep Feature-Based Quality Assessment
Abstract: The volume of User Generated Content (UGC) has increased in recent years. The challenge with this type of content is assessing its quality. So far, the state-of-the-art metrics are not exhibiting a very hi... | [] | Train |
23,947 | 24 | Title: Personalised Federated Learning On Heterogeneous Feature Spaces
Abstract: Most personalised federated learning (FL) approaches assume that raw data of all clients are defined in a common subspace i.e. all clients store their data according to the same schema. For real-world applications, this assumption is restri... | [] | Train |
23,948 | 10 | Title: Human adaptation to adaptive machines converges to game-theoretic equilibria
Abstract: Adaptive machines have the potential to assist or interfere with human behavior in a range of contexts, from cognitive decision-making to physical device assistance. Therefore it is critical to understand how machine learning ... | [
41283
] | Train |
23,949 | 16 | Title: EgoVSR: Towards High-Quality Egocentric Video Super-Resolution
Abstract: Due to the limitations of capture devices and scenarios, egocentric videos frequently have low visual quality, mainly caused by high compression and severe motion blur. With the increasing application of egocentric videos, there is an urgen... | [] | Train |
23,950 | 24 | Title: Rethinking Evaluation Metric for Probability Estimation Models Using Esports Data
Abstract: Probability estimation models play an important role in various fields, such as weather forecasting, recommendation systems, and sports analysis. Among several models estimating probabilities, it is difficult to evaluate ... | [] | Train |
23,951 | 24 | Title: Out-of-distributional risk bounds for neural operators with applications to the Helmholtz equation
Abstract: Despite their remarkable success in approximating a wide range of operators defined by PDEs, existing neural operators (NOs) do not necessarily perform well for all physics problems. We focus here on high... | [
11273,
13227,
41711
] | Validation |
23,952 | 24 | Title: The Adversarial Consistency of Surrogate Risks for Binary Classification
Abstract: We study the consistency of surrogate risks for robust binary classification. It is common to learn robust classifiers by adversarial training, which seeks to minimize the expected $0$-$1$ loss when each example can be maliciously... | [
15228
] | Train |
23,953 | 2 | Title: Algebraic Model Management: A Survey
Abstract: nan | [
38087
] | Train |
23,954 | 16 | Title: Frequency-Aware Self-Supervised Long-Tailed Learning
Abstract: Data collected from the real world typically exhibit long-tailed distributions, where frequent classes contain abundant data while rare ones have only a limited number of samples. While existing supervised learning approaches have been proposed to ta... | [
40714
] | Test |
23,955 | 16 | Title: Text recognition on images using pre-trained CNN
Abstract: A text on an image often stores important information and directly carries high level semantics, makes it as important source of information and become a very active research topic. Many studies have shown that the use of CNN-based neural networks is qui... | [] | Train |
23,956 | 16 | Title: Methodology for generating synthetic labeled datasets for visual container inspection
Abstract: nan | [] | Train |
23,957 | 24 | Title: Fourier neural operator for learning solutions to macroscopic traffic flow models: Application to the forward and inverse problems
Abstract: Deep learning methods are emerging as popular computational tools for solving forward and inverse problems in traffic flow. In this paper, we study a neural operator framew... | [
19584,
37600,
37078,
14070
] | Train |
23,958 | 24 | Title: Improved uncertainty quantification for neural networks with Bayesian last layer
Abstract: Uncertainty quantification is an essential task in machine learning - a task in which neural networks (NNs) have traditionally not excelled. This can be a limitation for safety-critical applications, where uncertainty-awar... | [] | Test |
23,959 | 16 | Title: LAW-Diffusion: Complex Scene Generation by Diffusion with Layouts
Abstract: Thanks to the rapid development of diffusion models, unprecedented progress has been witnessed in image synthesis. Prior works mostly rely on pre-trained linguistic models, but a text is often too abstract to properly specify all the spa... | [] | Validation |
23,960 | 17 | Title: HuMoT: Human Motion Representation using Topology-Agnostic Transformers for Character Animation Retargeting
Abstract: Motion retargeting is the long-standing problem in character animation that consists in transferring and adapting the motion of a source character to another target character. A typical applicati... | [
5512
] | Train |
23,961 | 16 | Title: A Multi-modal Garden Dataset and Hybrid 3D Dense Reconstruction Framework Based on Panoramic Stereo Images for a Trimming Robot
Abstract: Recovering an outdoor environment's surface mesh is vital for an agricultural robot during task planning and remote visualization. Our proposed solution is based on a newly-de... | [] | Validation |
23,962 | 27 | Title: Real-Time Walking Pattern Generation of Quadrupedal Dynamic-Surface Locomotion based on a Linear Time-Varying Pendulum Model
Abstract: This study introduces an analytically tractable and computationally efficient model of the legged robot dynamics associated with locomotion on a dynamic rigid surface (DRS), and ... | [
2040
] | Train |
23,963 | 24 | Title: Towards Interpretability in Audio and Visual Affective Machine Learning: A Review
Abstract: Machine learning is frequently used in affective computing, but presents challenges due the opacity of state-of-the-art machine learning methods. Because of the impact affective machine learning systems may have on an ind... | [] | Train |
23,964 | 26 | Title: Assessing Peer Award Diversification on Reddit
Abstract: Monetizing user-generated content in social media such as Reddit, in which users are both content creators and consumers, is challenging. Among the platform’s strategies we find Reddit Awards, paid tokens of appreciation given by peer users who markedly en... | [] | Train |
23,965 | 16 | Title: Improving Neural Radiance Fields with Depth-aware Optimization for Novel View Synthesis
Abstract: With dense inputs, Neural Radiance Fields (NeRF) is able to render photo-realistic novel views under static conditions. Although the synthesis quality is excellent, existing NeRF-based methods fail to obtain moderat... | [
14491
] | Train |
23,966 | 30 | Title: Exploring Paracrawl for Document-level Neural Machine Translation
Abstract: Document-level neural machine translation (NMT) has outperformed sentence-level NMT on a number of datasets. However, document-level NMT is still not widely adopted in realworld translation systems mainly due to the lack of large-scale g... | [] | Train |
23,967 | 23 | Title: Supporting Early-Safety Analysis of IoT Systems by Exploiting Testing Techniques
Abstract: IoT systems complexity and susceptibility to failures pose significant challenges in ensuring their reliable operation Failures can be internally generated or caused by external factors impacting both the systems correctne... | [] | Train |
23,968 | 27 | Title: RoboAgent: Generalization and Efficiency in Robot Manipulation via Semantic Augmentations and Action Chunking
Abstract: The grand aim of having a single robot that can manipulate arbitrary objects in diverse settings is at odds with the paucity of robotics datasets. Acquiring and growing such datasets is strenuo... | [
22913,
41224,
11211,
43309,
10199,
4948,
12567,
14168,
17981
] | Train |
23,969 | 24 | Title: Stochastic Gradient Bayesian Optimal Experimental Designs for Simulation-based Inference
Abstract: Simulation-based inference (SBI) methods tackle complex scientific models with challenging inverse problems. However, SBI models often face a significant hurdle due to their non-differentiable nature, which hampers... | [] | Train |
23,970 | 24 | Title: SMART: Self-supervised Multi-task pretrAining with contRol Transformers
Abstract: Self-supervised pretraining has been extensively studied in language and vision domains, where a unified model can be easily adapted to various downstream tasks by pretraining representations without explicit labels. When it comes ... | [
2528,
37188,
16869,
37477,
487,
42858,
25582
] | Validation |
23,971 | 16 | Title: Fast Neural Scene Flow
Abstract: Neural Scene Flow Prior (NSFP) is of significant interest to the vision community due to its inherent robustness to out-of-distribution (OOD) effects and its ability to deal with dense lidar points. The approach utilizes a coordinate neural network to estimate scene flow at runti... | [] | Train |
23,972 | 16 | Title: MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation
Abstract: Monocular 3D object detection (Mono3D) in mobile settings (e.g., on a vehicle, a drone, or a robot) is an important yet challenging task. Due to the near-far disparity phenomenon of monocular vision and the ever-changing ... | [
23513
] | Train |
23,973 | 31 | Title: Continual Learning for Generative Retrieval over Dynamic Corpora
Abstract: Generative retrieval (GR) directly predicts the identifiers of relevant documents (i.e., docids) based on a parametric model. It has achieved solid performance on many ad-hoc retrieval tasks. So far, these tasks have assumed a static docu... | [
27496,
9678
] | Train |
23,974 | 24 | Title: A Survey on Vertical Federated Learning: From a Layered Perspective
Abstract: Vertical federated learning (VFL) is a promising category of federated learning for the scenario where data is vertically partitioned and distributed among parties. VFL enriches the description of samples using features from different ... | [
14073,
31705,
10597,
33078
] | Test |
23,975 | 24 | Title: Learning MDL logic programs from noisy data
Abstract: Many inductive logic programming approaches struggle to learn programs from noisy data. To overcome this limitation, we introduce an approach that learns minimal description length programs from noisy data, including recursive programs. Our experiments on sev... | [] | Validation |
23,976 | 16 | Title: RATs-NAS: Redirection of Adjacent Trails on GCN for Neural Architecture Search
Abstract: Various hand-designed CNN architectures have been developed, such as VGG, ResNet, DenseNet, etc., and achieve State-of-the-Art (SoTA) levels on different tasks. Neural Architecture Search (NAS) now focuses on automatically f... | [] | Validation |
23,977 | 30 | Title: Explanation Graph Generation via Generative Pre-training over Synthetic Graphs
Abstract: The generation of explanation graphs is a significant task that aims to produce explanation graphs in response to user input, revealing the internal reasoning process. This task is challenging due to the significant discrepa... | [
6155
] | Train |
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