node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
36,578 | 26 | Title: Danish National Election 2022 Twitter Data on Likes, Retweets, and Botscores for the Purpose of Exploring Coordinated Inauthenthic Behavior
Abstract: This note describes code and experiments related to a Twitter dataset on the Danish National Election 2022, available at Harvard Dataverse (doi.org/10.7910/DVN/RWP... | [
24657
] | Validation |
36,579 | 6 | Title: CoSINT: Designing a Collaborative Capture the Flag Competition to Investigate Misinformation
Abstract: Crowdsourced investigations shore up democratic institutions by debunking misinformation and uncovering human rights abuses. However, current crowdsourcing approaches rely on simplistic collaborative or competi... | [
34367
] | Train |
36,580 | 16 | Title: Combining HoloLens with Instant-NeRFs: Advanced Real-Time 3D Mobile Mapping
Abstract: Abstract. This work represents a large step into modern ways of fast 3D reconstruction based on RGB camera images. Utilizing a Microsoft HoloLens 2 as a multisensor platform that includes an RGB camera and an inertial measureme... | [
18302,
8854,
38751
] | Train |
36,581 | 30 | Title: Safety Analysis in the Era of Large Language Models: A Case Study of STPA using ChatGPT
Abstract: Large Language Models (LLMs), such as ChatGPT and BERT, are leading a new AI heatwave due to its human-like conversations with detailed and articulate answers across many domains of knowledge. While LLMs are being q... | [
40192,
33220,
28580,
13224,
41359
] | Train |
36,582 | 16 | Title: Rethinking the Localization in Weakly Supervised Object Localization
Abstract: Weakly supervised object localization (WSOL) is one of the most popular and challenging tasks in computer vision. This task is to localize the objects in the images given only the image-level supervision. Recently, dividing WSOL into ... | [
18391
] | Validation |
36,583 | 16 | Title: Point2Point : A Framework for Efficient Deep Learning on Hilbert sorted Point Clouds with applications in Spatio-Temporal Occupancy Prediction
Abstract: The irregularity and permutation invariance of point cloud data pose challenges for effective learning. Conventional methods for addressing this issue involve c... | [] | Train |
36,584 | 24 | Title: Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels
Abstract: In Multi-Label Learning (MLL), it is extremely challenging to accurately annotate every appearing object due to expensive costs and limited knowledge. When facing such a challenge, a more practical a... | [] | Test |
36,585 | 10 | Title: AI-Supported Assessment of Load Safety
Abstract: Load safety assessment and compliance is an essential step in the corporate process of every logistics service provider. In 2020, a total of 11,371 police checks of trucks were carried out, during which 9.6% (1091) violations against the load safety regulations we... | [
32320
] | Test |
36,586 | 27 | Title: Reinforcement Learning with Parameterized Manipulation Primitives for Robotic Assembly
Abstract: A common theme in robot assembly is the adoption of Manipulation Primitives as the atomic motion to compose assembly strategy, typically in the form of a state machine or a graph. While this approach has shown great ... | [] | Train |
36,587 | 34 | Title: A double-decomposition based parallel exact algorithm for the feedback length minimization problem
Abstract: Product development projects usually contain many interrelated activities with complex information dependences, which induce activity rework, project delay and cost overrun. To reduce negative impacts, sc... | [] | Validation |
36,588 | 24 | Title: Iterative Magnitude Pruning as a Renormalisation Group: A Study in The Context of The Lottery Ticket Hypothesis
Abstract: This thesis delves into the intricate world of Deep Neural Networks (DNNs), focusing on the exciting concept of the Lottery Ticket Hypothesis (LTH). The LTH posits that within extensive DNNs,... | [
31814
] | Validation |
36,589 | 16 | Title: Implicit Occupancy Flow Fields for Perception and Prediction in Self-Driving
Abstract: A self-driving vehicle (SDV) must be able to perceive its surroundings and predict the future behavior of other traffic participants. Existing works either perform object detection followed by trajectory forecasting of the det... | [
8610,
18283,
32995
] | Test |
36,590 | 16 | Title: Visual-LiDAR Odometry and Mapping with Monocular Scale Correction and Visual Bootstrapping
Abstract: This paper presents a novel visual-LiDAR odometry and mapping method with low-drift characteristics. The proposed method is based on two popular approaches, ORB-SLAM and A-LOAM, with monocular scale correction an... | [] | Train |
36,591 | 15 | Title: JASS: A Flexible Checkpointing System for NVM-based Systems
Abstract: NVM-based systems are naturally fit candidates for incor-porating periodic checkpointing (or snapshotting). This increases the reliability of the system, makes it more immune to power failures, and reduces wasted work in especially an HPC setup... | [] | Train |
36,592 | 18 | Title: Enhanced Read Resolution in Reconfigurable Memristive Synapses for Spiking Neural Networks
Abstract: Synapse is a key element of any neuromorphic computing system which is mostly constructed with memristor devices. A memristor is a two-terminal analog memory device. Memristive synapse suffers from various challe... | [
33525
] | Train |
36,593 | 24 | Title: Sparse Model Soups: A Recipe for Improved Pruning via Model Averaging
Abstract: Neural networks can be significantly compressed by pruning, leading to sparse models requiring considerably less storage and floating-point operations while maintaining predictive performance. Model soups (Wortsman et al., 2022) impr... | [
45074,
28325,
711
] | Train |
36,594 | 23 | Title: Measuring and Mitigating Gaps in Structural Testing
Abstract: Structural code coverage is a popular test adequacy metric that measures the percentage of program structure (e.g., statement, branch, decision) executed by a test suite. While structural coverage has several benefits, previous studies suggested that ... | [
36895
] | Train |
36,595 | 24 | Title: Connector 0.5: A unified framework for graph representation learning
Abstract: Graph representation learning models aim to represent the graph structure and its features into low-dimensional vectors in a latent space, which can benefit various downstream tasks, such as node classification and link prediction. Du... | [
8169,
40049
] | Train |
36,596 | 16 | Title: A Self-Supervised Miniature One-Shot Texture Segmentation (MOSTS) Model for Real-Time Robot Navigation and Embedded Applications
Abstract: Determining the drivable area, or free space segmentation, is critical for mobile robots to navigate indoor environments safely. However, the lack of coherent markings and st... | [] | Validation |
36,597 | 24 | Title: Multi-GPU Approach for Training of Graph ML Models on large CFD Meshes
Abstract: Mesh-based numerical solvers are an important part in many design tool chains. However, accurate simulations like computational fluid dynamics are time and resource consuming which is why surrogate models are employed to speed-up th... | [] | Train |
36,598 | 6 | Title: Understanding Context to Capture when Reconstructing Meaningful Spaces for Remote Instruction and Connecting in XR
Abstract: Recent technological advances are enabling HCI researchers to explore interaction possibilities for remote XR collaboration using high-fidelity reconstructions of physical activity spaces.... | [] | Test |
36,599 | 16 | Title: Towards Diverse and Consistent Typography Generation
Abstract: In this work, we consider the typography generation task that aims at producing diverse typographic styling for the given graphic document. We formulate typography generation as a fine-grained attribute generation for multiple text elements and build... | [
15939,
2633,
3631,
1077,
7678
] | Validation |
36,600 | 24 | Title: Hyperbolic Graph Diffusion Model for Molecule Generation
Abstract: Recently, diffusion models have achieved remarkable performance in data generation, e.g., generating high-quality images. Nevertheless, chemistry molecules often have complex non-Euclidean spatial structures, with the behavior changing dynamicall... | [] | Validation |
36,601 | 18 | Title: Training Deep Boltzmann Networks with Sparse Ising Machines
Abstract: The slowing down of Moore's law has driven the development of unconventional computing paradigms, such as specialized Ising machines tailored to solve combinatorial optimization problems. In this paper, we show a new application domain for pro... | [
22952,
42525,
45496
] | Train |
36,602 | 16 | Title: Data Augmentation in Training CNNs: Injecting Noise to Images
Abstract: Noise injection is a fundamental tool for data augmentation, and yet there is no widely accepted procedure to incorporate it with learning frameworks. This study analyzes the effects of adding or applying different noise models of varying ma... | [] | Validation |
36,603 | 1 | Title: 3-D Markerless Tracking of Human Gait by Geometric Trilateration of Multiple Kinects
Abstract: In this paper, we develop an integrated markerless gait tracking system with three Kinect v2 sensors. A geometric principle-based trilateration method is proposed for optimizing the accuracy of the measured gait data. ... | [] | Test |
36,604 | 16 | Title: Distortion-Disentangled Contrastive Learning
Abstract: Self-supervised learning is well known for its remarkable performance in representation learning and various downstream computer vision tasks. Recently, Positive-pair-Only Contrastive Learning (POCL) has achieved reliable performance without the need to cons... | [] | Train |
36,605 | 16 | Title: UW-CVGAN: UnderWater Image Enhancement with Capsules Vectors Quantization
Abstract: The degradation in the underwater images is due to wavelength-dependent light attenuation, scattering, and to the diversity of the water types in which they are captured. Deep neural networks take a step in this field, providing ... | [] | Test |
36,606 | 30 | Title: BERT4CTR: An Efficient Framework to Combine Pre-trained Language Model with Non-textual Features for CTR Prediction
Abstract: Although deep pre-trained language models have shown promising benefit in a large set of industrial scenarios, including Click-Through-Rate (CTR) prediction, how to integrate pre-trained ... | [] | Train |
36,607 | 27 | Title: Waypoint-Based Imitation Learning for Robotic Manipulation
Abstract: While imitation learning methods have seen a resurgent interest for robotic manipulation, the well-known problem of compounding errors continues to afflict behavioral cloning (BC). Waypoints can help address this problem by reducing the horizon... | [
7224,
1121,
8994,
12567
] | Train |
36,608 | 30 | Title: KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation
Abstract: Self-training (ST) has come to fruition in language understanding tasks by producing pseudo labels, which reduces the labeling bottleneck of language model fine-tuning. Nevertheless, in facilitating semi-supe... | [] | Train |
36,609 | 24 | Title: FedML-HE: An Efficient Homomorphic-Encryption-Based Privacy-Preserving Federated Learning System
Abstract: Federated Learning (FL) enables machine learning model training on distributed edge devices by aggregating local model updates rather than local data. However, privacy concerns arise as the FL server's acce... | [
43256,
12468,
23326
] | Train |
36,610 | 31 | Title: Widespread Flaws in Offline Evaluation of Recommender Systems
Abstract: Even though offline evaluation is just an imperfect proxy of online performance – due to the interactive nature of recommenders – it will probably remain the primary way of evaluation in recommender systems research for the foreseeable futur... | [] | Train |
36,611 | 16 | Title: An Inverse Scaling Law for CLIP Training
Abstract: CLIP, the first foundation model that connects images and text, has enabled many recent breakthroughs in computer vision. However, its associated training cost is prohibitively high, imposing a significant barrier to its widespread exploration. In this paper, we... | [
33220,
37254,
17449,
43530,
1581,
12399,
29873,
8084,
23285,
40884,
23575,
10908
] | Train |
36,612 | 24 | Title: Correcting discount-factor mismatch in on-policy policy gradient methods
Abstract: The policy gradient theorem gives a convenient form of the policy gradient in terms of three factors: an action value, a gradient of the action likelihood, and a state distribution involving discounting called the \emph{discounted... | [] | Train |
36,613 | 16 | Title: Reasonable Anomaly Detection in Long Sequences
Abstract: Video anomaly detection is a challenging task due to the lack in approaches for representing samples. The visual representations of most existing approaches are limited by short-term sequences of observations which cannot provide enough clues for achieving... | [] | Train |
36,614 | 24 | Title: Function Value Learning: Adaptive Learning Rates Based on the Polyak Stepsize and Function Splitting in ERM
Abstract: Here we develop variants of SGD (stochastic gradient descent) with an adaptive step size that make use of the sampled loss values. In particular, we focus on solving a finite sum-of-terms problem... | [] | Test |
36,615 | 30 | Title: Lexical Simplification using multi level and modular approach
Abstract: Text Simplification is an ongoing problem in Natural Language Processing, solution to which has varied implications. In conjunction with the TSAR-2022 Workshop @EMNLP2022 Lexical Simplification is the process of reducing the lexical complexi... | [
8150
] | Train |
36,616 | 4 | Title: Masquerade: Simple and Lightweight Transaction Reordering Mitigation in Blockchains
Abstract: Blockchains offer strong security gurarantees, but cannot protect users against the ordering of transactions. Players such as miners, bots and validators can reorder various transactions and reap significant profits, ca... | [
32337
] | Validation |
36,617 | 24 | Title: Symmetry-Preserving Program Representations for Learning Code Semantics
Abstract: Large Language Models (LLMs) have shown promise in automated program reasoning, a crucial aspect of many security tasks. However, existing LLM architectures for code are often borrowed from other domains like natural language proce... | [
9571,
31817,
44553,
37105,
22681
] | Train |
36,618 | 16 | Title: Lip Reading for Low-resource Languages by Learning and Combining General Speech Knowledge and Language-specific Knowledge
Abstract: This paper proposes a novel lip reading framework, especially for low-resource languages, which has not been well addressed in the previous literature. Since low-resource languages ... | [
25698,
10534,
6440,
19464,
22602,
28234,
44141,
33326,
8186,
25052
] | Train |
36,619 | 5 | Title: RPDP: An Efficient Data Placement based on Residual Performance for P2P Storage Systems
Abstract: Storage systems using Peer-to-Peer (P2P) architecture are an alternative to the traditional client-server systems. They offer better scalability and fault tolerance while at the same time eliminate the single point ... | [] | Train |
36,620 | 24 | Title: Planning Multiple Epidemic Interventions with Reinforcement Learning
Abstract: Combating an epidemic entails finding a plan that describes when and how to apply different interventions, such as mask-wearing mandates, vaccinations, school or workplace closures. An optimal plan will curb an epidemic with minimal l... | [] | Train |
36,621 | 6 | Title: Continuous Scatterplot Operators for Bivariate Analysis and Study of Electronic Transitions
Abstract: Electronic transitions in molecules due to the absorption or emission of light is a complex quantum mechanical process. Their study plays an important role in the design of novel materials. A common yet challeng... | [
23994,
4495
] | Train |
36,622 | 24 | Title: Pruning Before Training May Improve Generalization, Provably
Abstract: It has been observed in practice that applying pruning-at-initialization methods to neural networks and training the sparsified networks can not only retain the testing performance of the original dense models, but also sometimes even slightl... | [] | Train |
36,623 | 24 | Title: Multi-task neural networks by learned contextual inputs
Abstract: This paper explores learned-context neural networks. It is a multi-task learning architecture based on a fully shared neural network and an augmented input vector containing trainable task parameters. The architecture is interesting due to its pow... | [] | Train |
36,624 | 8 | Title: One for All: Unified Workload Prediction for Dynamic Multi-tenant Edge Cloud Platforms
Abstract: Workload prediction in multi-tenant edge cloud platforms (MT-ECP) is vital for efficient application deployment and resource provisioning. However, the heterogeneous application patterns, variable infrastructure perf... | [] | Train |
36,625 | 16 | Title: Depth Super-Resolution from Explicit and Implicit High-Frequency Features
Abstract: We propose a novel multi-stage depth super-resolution network, which progressively reconstructs high-resolution depth maps from explicit and implicit high-frequency features. The former are extracted by an efficient transformer p... | [
18889,
1886
] | Validation |
36,626 | 24 | Title: Training Transformers with 4-bit Integers
Abstract: Quantizing the activation, weight, and gradient to 4-bit is promising to accelerate neural network training. However, existing 4-bit training methods require custom numerical formats which are not supported by contemporary hardware. In this work, we propose a t... | [
18227
] | Train |
36,627 | 16 | Title: Prototypes-oriented Transductive Few-shot Learning with Conditional Transport
Abstract: Transductive Few-Shot Learning (TFSL) has recently attracted increasing attention since it typically outperforms its inductive peer by leveraging statistics of query samples. However, previous TFSL methods usually encode unif... | [
4662
] | Validation |
36,628 | 27 | Title: Wireless Network Demands of Data Products from Small Uncrewed Aerial Systems at Hurricane Ian
Abstract: Data collected at Hurricane Ian (2022) quantifies the demands that small uncrewed aerial systems (UAS), or drones, place on the network communication infrastructure and identifies gaps in the field. Drones hav... | [
15350
] | Train |
36,629 | 24 | Title: Cramer Type Distances for Learning Gaussian Mixture Models by Gradient Descent
Abstract: The learning of Gaussian Mixture Models (also referred to simply as GMMs) plays an important role in machine learning. Known for their expressiveness and interpretability, Gaussian mixture models have a wide range of applica... | [
39628
] | Train |
36,630 | 16 | Title: Maximally Compact and Separated Features with Regular Polytope Networks
Abstract: Convolutional Neural Networks (CNNs) trained with the Softmax loss are widely used classification models for several vision tasks. Typically, a learnable transformation (i.e. the classifier) is placed at the end of such models return... | [
16411,
45717
] | Test |
36,631 | 10 | Title: Understanding Natural Language Understanding Systems. A Critical Analysis
Abstract: The development of machines that {\guillemotleft}talk like us{\guillemotright}, also known as Natural Language Understanding (NLU) systems, is the Holy Grail of Artificial Intelligence (AI), since language is the quintessence of ... | [
19720,
34681,
41838
] | Test |
36,632 | 4 | Title: Specification and Verification of Side-channel Security for Open-source Processors via Leakage Contracts
Abstract: Leakage contracts have recently been proposed as a new security abstraction at the Instruction Set Architecture (ISA) level. Such contracts aim to faithfully capture the information processors may l... | [
36092,
34558
] | Validation |
36,633 | 16 | Title: UniSeg: A Prompt-driven Universal Segmentation Model as well as A Strong Representation Learner
Abstract: The universal model emerges as a promising trend for medical image segmentation, paving up the way to build medical imaging large model (MILM). One popular strategy to build universal models is to encode eac... | [
13744,
27817
] | Validation |
36,634 | 24 | Title: A new perspective on building efficient and expressive 3D equivariant graph neural networks
Abstract: Geometric deep learning enables the encoding of physical symmetries in modeling 3D objects. Despite rapid progress in encoding 3D symmetries into Graph Neural Networks (GNNs), a comprehensive evaluation of the e... | [
4089,
12378,
40133
] | Validation |
36,635 | 30 | Title: ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing
Abstract: This article discusses OpenAI's ChatGPT, a generative pre‐trained transformer, which uses natural language processing to fulfill text‐based user reques... | [
4996,
17542,
12487,
34121,
18250,
11087,
8208,
13239,
10749,
37726,
2493
] | Train |
36,636 | 31 | Title: ChatGPT for GTFS: From Words to Information
Abstract: The General Transit Feed Specification (GTFS) standard for publishing transit data is ubiquitous. GTFS being tabular data, with information spread across different files, necessitates specialized tools or packages to retrieve information. Concurrently, the us... | [
25227,
13700,
28221
] | Test |
36,637 | 30 | Title: Gaussian Prior Reinforcement Learning for Nested Named Entity Recognition
Abstract: Named Entity Recognition (NER) is a well and widely studied task in natural language processing. Recently, the nested NER has attracted more attention since its practicality and difficulty. Existing works for nested NER ignore th... | [
20872
] | Train |
36,638 | 30 | Title: W-procer: Weighted Prototypical Contrastive Learning for Medical Few-Shot Named Entity Recognition
Abstract: Contrastive learning has become a popular solution for few-shot Name Entity Recognization (NER). The conventional configuration strives to reduce the distance between tokens with the same labels and incre... | [
16527
] | Validation |
36,639 | 16 | Title: MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation
Abstract: Perception systems in modern autonomous driving vehicles typically take inputs from complementary multi-modal sensors, e.g., LiDAR and cameras. However, in real-world applications, sensor corruptions and failures lead to inferior p... | [
27857,
13564
] | Test |
36,640 | 16 | Title: Let's ViCE! Mimicking Human Cognitive Behavior in Image Generation Evaluation
Abstract: Research in Image Generation has recently made significant progress, particularly boosted by the introduction of Vision-Language models which are able to produce high-quality visual content based on textual inputs. Despite on... | [
10624,
15809,
40610,
5387,
24624,
20435,
8915
] | Train |
36,641 | 16 | Title: Image Embedding for Denoising Generative Models
Abstract: Denoising Diffusion models are gaining increasing popularity in the field of generative modeling for several reasons, including the simple and stable training, the excellent generative quality, and the solid probabilistic foundation. In this article, we a... | [
18586,
1148,
9310,
19222
] | Train |
36,642 | 24 | Title: Evaluating the Robustness of Test Selection Methods for Deep Neural Networks
Abstract: Testing deep learning-based systems is crucial but challenging due to the required time and labor for labeling collected raw data. To alleviate the labeling effort, multiple test selection methods have been proposed where only... | [] | Train |
36,643 | 30 | Title: Evolution of Efficient Symbolic Communication Codes
Abstract: The paper explores how the human natural language structure can be seen as a product of evolution of inter-personal communication code, targeting maximisation of such culture-agnostic and cross-lingual metrics such as anti-entropy, compression factor ... | [
40192,
4167
] | Train |
36,644 | 4 | Title: Secure access system using signature verification over tablet PC
Abstract: Low-cost portable devices capable of capturing signature signals are being increasingly used. Additionally, the social and legal acceptance of the written signature for authentication purposes is opening a range of new applications. We de... | [] | Test |
36,645 | 27 | Title: Multi-contact Stochastic Predictive Control for Legged Robots with Contact Locations Uncertainty
Abstract: Trajectory optimization under uncertainties is a challenging problem for robots in contact with the environment. Such uncertainties are inevitable due to estimation errors, control imperfections, and model ... | [] | Test |
36,646 | 36 | Title: Rationality and Behavior Feedback in a Model of Vehicle-to-Vehicle Communication
Abstract: Vehicle-to-Vehicle (V2V) communication is intended to improve road safety through distributed information sharing; however, this type of system faces a design challenge: it is difficult to predict and optimize how human ag... | [] | Train |
36,647 | 31 | Title: TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter
Abstract: Recommendation systems are a core feature of social media companies with their uses including recommending organic and promoted contents. Many modern recommendation systems are split into multiple stages - candidat... | [] | Train |
36,648 | 2 | Title: A Logical Account of Subtyping for Session Types
Abstract: We study the notion of subtyping for session types in a logical setting, where session types are propositions of multiplicative/additive linear logic extended with least and greatest fixed points. The resulting subtyping relation admits a simple characte... | [] | Train |
36,649 | 26 | Title: Topological Filtering for Visual Data Mining and Analysis of Complex Networks
Abstract: The discovery of small world and scale free properties of many real world networks has revolutionized the way we study, analyze, model and process networks. An important way to analyze these complex networks is to visualize t... | [] | Test |
36,650 | 5 | Title: Compiler Optimization for Irregular Memory Access Patterns in PGAS Programs
Abstract: Irregular memory access patterns pose performance and user productivity challenges on distributed-memory systems. They can lead to fine-grained remote communication and the data access patterns are often not known until runtime... | [] | Train |
36,651 | 5 | Title: Split-Et-Impera: A Framework for the Design of Distributed Deep Learning Applications
Abstract: Many recent pattern recognition applications rely on complex distributed architectures in which sensing and computational nodes interact together through a communication network. Deep neural networks (DNNs) play an im... | [
41162
] | Train |
36,652 | 24 | Title: Wrapped Cauchy Distributed Angular Softmax for Long-Tailed Visual Recognition
Abstract: Addressing imbalanced or long-tailed data is a major challenge in visual recognition tasks due to disparities between training and testing distributions and issues with data noise. We propose the Wrapped Cauchy Distributed An... | [] | Validation |
36,653 | 10 | Title: Preference-Aware Delivery Planning for Last-Mile Logistics
Abstract: Optimizing delivery routes for last-mile logistics service is challenging and has attracted the attention of many researchers. These problems are usually modeled and solved as variants of vehicle routing problems (VRPs) with challenging real-wo... | [] | Train |
36,654 | 24 | Title: UAV Path Planning Employing MPC-Reinforcement Learning Method Considering Collision Avoidance
Abstract: In this paper, we tackle the problem of Unmanned Aerial (UAV) path planning in complex and uncertain environments by designing a Model Predictive Control (MPC), based on a Long-Short-Term Memory (LSTM) network... | [] | Train |
36,655 | 17 | Title: A Comparison of Fundamental Methods for Iso-surface Extraction
Abstract: This paper compares four fundamental methods for iso surface extraction based on cell decomposition to tetrahedra. The methods are compared both on mathematically generated data sets as well as on real data sets. The comparison using mathem... | [] | Test |
36,656 | 10 | Title: Mind the Gap - Modelling Difference Between Censored and Uncensored Electric Vehicle Charging Demand
Abstract: Electric vehicle charging demand models, with charging records as input, will inherently be biased toward the supply of available chargers. These models often fail to account for demand lost from occupi... | [] | Validation |
36,657 | 11 | Title: Inequity aversion reduces travel time in the traffic light control problem
Abstract: The traffic light control problem is to improve the traffic flow by coordinating between the traffic lights. Recently, a successful deep reinforcement learning model, CoLight, was developed to capture the influences of neighbori... | [] | Train |
36,658 | 6 | Title: PaRUS: A Virtual Reality Shopping Method Focusing on Context between Products and Real Usage Scenes
Abstract: The development of AR and VR technologies is enhancing users' online shopping experiences in various ways. However, in existing VR shopping applications, shopping contexts merely refer to the products an... | [] | Validation |
36,659 | 24 | Title: Optimal Differentially Private Learning with Public Data
Abstract: Differential Privacy (DP) ensures that training a machine learning model does not leak private data. However, the cost of DP is lower model accuracy or higher sample complexity. In practice, we may have access to auxiliary public data that is fre... | [
3254
] | Train |
36,660 | 31 | Title: Balancing Unobserved Confounding with a Few Unbiased Ratings in Debiased Recommendations
Abstract: Recommender systems are seen as an effective tool to address information overload, but it is widely known that the presence of various biases makes direct training on large-scale observational data result in sub-op... | [
17816,
28027,
42940
] | Train |
36,661 | 4 | Title: An Attack on The Speculative Vectorization: Leakage from Higher Dimensional Speculation
Abstract: This paper argues and shows that speculative vectorization, where a loop with rare or unknown memory dependencies are still vectorized, is fundamentally vulnerable and cannot be mitigated by existing defenses. We im... | [] | Test |
36,662 | 24 | Title: A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation
Abstract: In recent years, concept-based approaches have emerged as some of the most promising explainability methods to help us interpret the decisions of Artificial Neural Networks (ANNs). These methods seek to disco... | [] | Train |
36,663 | 16 | Title: Exploring Predicate Visual Context in Detecting of Human-Object Interactions
Abstract: Recently, the DETR framework has emerged as the dominant approach for human--object interaction (HOI) research. In particular, two-stage transformer-based HOI detectors are amongst the most performant and training-efficient ap... | [] | Train |
36,664 | 25 | Title: DasFormer: Deep Alternating Spectrogram Transformer for Multi/Single-Channel Speech Separation
Abstract: For the task of speech separation, previous study usually treats multi-channel and single-channel scenarios as two research tracks with specialized solutions developed respectively. Instead, we propose a simp... | [
38442
] | Train |
36,665 | 27 | Title: Learning from Pixels with Expert Observations
Abstract: In reinforcement learning (RL), sparse rewards can present a significant challenge. Fortunately, expert actions can be utilized to overcome this issue. However, acquiring explicit expert actions can be costly, and expert observations are often more readily ... | [] | Validation |
36,666 | 27 | Title: AdaLIO: Robust Adaptive LiDAR-Inertial Odometry in Degenerate Indoor Environments
Abstract: In recent years, the demand for mapping construction sites or buildings using light detection and ranging (LiDAR) sensors has been increased to model environments for efficient site management. However, it is observed tha... | [
32061,
14431
] | Test |
36,667 | 24 | Title: Selective Pre-training for Private Fine-tuning
Abstract: Suppose we want to train text prediction models in email clients or word processors. The models must preserve the privacy of user data and adhere to a specific fixed size to meet memory and inference time requirements. We introduce a generic framework to s... | [
34788,
43530,
17517,
14702,
45332
] | Train |
36,668 | 27 | Title: Learning Position From Vehicle Vibration Using an Inertial Measurement Unit
Abstract: This paper presents a novel approach to vehicle positioning that operates without reliance on the global navigation satellite system (GNSS). Traditional GNSS approaches are vulnerable to interference in certain environments, re... | [] | Train |
36,669 | 30 | Title: AMR Parsing with Instruction Fine-tuned Pre-trained Language Models
Abstract: Instruction fine-tuned language models on a collection of instruction annotated datasets (FLAN) have shown highly effective to improve model performance and generalization to unseen tasks. However, a majority of standard parsing tasks ... | [
13185,
44482,
25892
] | Train |
36,670 | 31 | Title: Hybrid Multi-Criteria Preference Ranking by Subsorting
Abstract: Multi-criteria recommender systems can improve the quality of recommendations by considering user preferences on multiple criteria. One promising approach proposed recently is multi-criteria ranking, which uses Pareto ranking to assign a ranking sc... | [] | Test |
36,671 | 24 | Title: Transformers are Universal Predictors
Abstract: We find limits to the Transformer architecture for language modeling and show it has a universal prediction property in an information-theoretic sense. We further analyze performance in non-asymptotic data regimes to understand the role of various components of the... | [
29396
] | Train |
36,672 | 39 | Title: The Fagnano Triangle Patrolling Problem
Abstract: We investigate a combinatorial optimization problem that involves patrolling the edges of an acute triangle using a unit-speed agent. The goal is to minimize the maximum (1-gap) idle time of any edge, which is defined as the time gap between consecutive visits to... | [] | Test |
36,673 | 24 | Title: Automatic pain recognition from Blood Volume Pulse (BVP) signal using machine learning techniques
Abstract: Physiological responses to pain have received increasing attention among researchers for developing an automated pain recognition sensing system. Though less explored, Blood Volume Pulse (BVP) is one of th... | [] | Test |
36,674 | 23 | Title: Towards a Blockchain-based Software Engineering Education
Abstract: Blockchain technologies for rewards in education are gaining attraction as a promising approach to motivate student learning and promote academic achievement. By providing tangible rewards for educational attainment and engagement, such as digit... | [] | Train |
36,675 | 4 | Title: A Survey on Enterprise Network Security: Asset Behavioral Monitoring and Distributed Attack Detection
Abstract: Enterprise networks that host valuable assets and services are popular and frequent targets of distributed network attacks. In order to cope with the ever-increasing threats, industrial and research co... | [] | Train |
36,676 | 30 | Title: Sci-CoT: Leveraging Large Language Models for Enhanced Knowledge Distillation in Small Models for Scientific QA
Abstract: Large Language Models (LLMs) have shown outstanding performance across wide range of downstream tasks. This competency is attributed to their substantial parameter size and pre-training on ex... | [
13817,
1626,
12851,
12741
] | Validation |
36,677 | 24 | Title: The Expressive Power of Graph Neural Networks: A Survey
Abstract: Graph neural networks (GNNs) are effective machine learning models for many graph-related applications. Despite their empirical success, many research efforts focus on the theoretical limitations of GNNs, i.e., the GNNs expressive power. Early wor... | [
8660
] | Validation |
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