node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
16,978 | 37 | Title: Finding Favourite Tuples on Data Streams with Provably Few Comparisons
Abstract: One of the most fundamental tasks in data science is to assist a user with unknown preferences in finding high-utility tuples within a large database. To accurately elicit the unknown user preferences, a widely-adopted way is by ask... | [] | Test |
16,979 | 2 | Title: Proceedings Fifth International Conference on Applied Category Theory
Abstract: The Fifth International Conference on Applied Category Theory took place at the University of Strathclyde in Glasgow, Scotland on 18-22 July 2022. This conference follows the previous meetings at Leiden (2018), Oxford (2019), MIT (20... | [] | Test |
16,980 | 27 | Title: Diagnosing and Augmenting Feature Representations in Correctional Inverse Reinforcement Learning
Abstract: Robots have been increasingly better at doing tasks for humans by learning from their feedback, but still often suffer from model misalignment due to missing or incorrectly learned features. When the featur... | [] | Train |
16,981 | 4 | Title: You Can Backdoor Personalized Federated Learning
Abstract: Existing research primarily focuses on backdoor attacks and defenses within the generic federated learning scenario, where all clients collaborate to train a single global model. A recent study conducted by Qin et al. (2023) marks the initial exploration... | [
7409,
29989
] | Train |
16,982 | 16 | Title: Polygonizer: An auto-regressive building delineator
Abstract: In geospatial planning, it is often essential to represent objects in a vectorized format, as this format easily translates to downstream tasks such as web development, graphics, or design. While these problems are frequently addressed using semantic ... | [] | Train |
16,983 | 5 | Title: MaGNAS: A Mapping-Aware Graph Neural Architecture Search Framework for Heterogeneous MPSoC Deployment
Abstract: Graph Neural Networks (GNNs) are becoming increasingly popular for vision-based applications due to their intrinsic capacity in modeling structural and contextual relations between various parts of an ... | [
41401,
39308,
39950
] | Train |
16,984 | 29 | Title: RAID Organizations for Improved Reliability and Performance: A Not Entirely Unbiased Tutorial
Abstract: This is a followup to the 1994 tutorial by Berkeley RAID researchers whose 1988 RAID paper foresaw a revolutionary change in storage industry based on advances in magnetic disk technology, i.e., replacement of... | [] | Validation |
16,985 | 26 | Title: Predicting the Popularity of Information on Social Platforms without Underlying Network Structure
Abstract: The ability to predict the size of information cascades in online social networks is crucial for various applications, including decision-making and viral marketing. However, traditional methods either rel... | [] | Validation |
16,986 | 4 | Title: Split-State Non-Malleable Codes and Secret Sharing Schemes for Quantum Messages
Abstract: Non-malleable codes are fundamental objects at the intersection of cryptography and coding theory. These codes provide security guarantees even in settings where error correction and detection are impossible, and have found... | [
42439
] | Test |
16,987 | 23 | Title: Refining ChatGPT-Generated Code: Characterizing and Mitigating Code Quality Issues
Abstract: In this paper, we systematically study the quality of 4,066 ChatGPT-generated code implemented in two popular programming languages, i.e., Java and Python, for 2,033 programming tasks. The goal of this work is three fold... | [
18984,
21873,
39466,
42735
] | Validation |
16,988 | 5 | Title: On the Regret of Online Edge Service Hosting
Abstract: We consider the problem of service hosting where a service provider can dynamically rent edge resources via short term contracts to ensure better quality of service to its customers. The service can also be partially hosted at the edge, in which case, custom... | [] | Train |
16,989 | 30 | Title: Improving Reading Comprehension Question Generation with Data Augmentation and Overgenerate-and-rank
Abstract: Reading comprehension is a crucial skill in many aspects of education, including language learning, cognitive development, and fostering early literacy skills in children. Automated answer-aware reading... | [
27669
] | Train |
16,990 | 32 | Title: Symbolic-Numeric Parameter Estimation Software Package in Julia
Abstract: We present our Julia software package ParameterEstimation.jl, which estimates parameter values in parametric ODE models, using measured data. Our approach, unlike most other approaches, is not based on optimization. Instead, it is based on... | [] | Train |
16,991 | 24 | Title: Reducing Air Pollution through Machine Learning
Abstract: This paper presents a data-driven approach to mitigate the effects of air pollution from industrial plants on nearby cities by linking operational decisions with weather conditions. Our method combines predictive and prescriptive machine learning models t... | [
33306
] | Train |
16,992 | 25 | Title: Incorporating Total Variation Regularization in the design of an intelligent Query by Humming system
Abstract: A Query-By-Humming (QBH) system constitutes a particular case of music information retrieval where the input is a user-hummed melody and the output is the original song which contains that melody. A typ... | [] | Validation |
16,993 | 8 | Title: DBO: Response Time Fairness for Cloud-Hosted Financial Exchanges
Abstract: In this paper, we consider the problem of hosting financial exchanges in the cloud. Financial exchanges require predictable, equal latency to all market participants to ensure fairness for various tasks, such as high speed trading. Howeve... | [] | Train |
16,994 | 27 | Title: Time-Optimal Path Tracking with ISO Safety Guarantees
Abstract: One way of ensuring operator's safety during human-robot collaboration is through Speed and Separation Monitoring (SSM), as defined in ISO standard ISO/TS 15066. In general, it is impossible to avoid all human-robot collisions: consider for instance... | [] | Train |
16,995 | 4 | Title: Forensic Log Based Detection For Keystroke Injection "BadUsb" Attacks
Abstract: This document describes an experiment with main purpose to detect BadUSB attacks that utilize external Human Interaction Device hardware gadgets to inject keystrokes and acquire remote code execution. One of the main goals, is to det... | [] | Train |
16,996 | 24 | Title: Machine learning in and out of equilibrium
Abstract: The algorithms used to train neural networks, like stochastic gradient descent (SGD), have close parallels to natural processes that navigate a high-dimensional parameter space -- for example protein folding or evolution. Our study uses a Fokker-Planck approac... | [] | Train |
16,997 | 24 | Title: SWAMP: Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
Abstract: Given the ever-increasing size of modern neural networks, the significance of sparse architectures has surged due to their accelerated inference speeds and minimal memory demands. When it comes to global pruning tech... | [] | Train |
16,998 | 6 | Title: Human-AI Collaboration: The Effect of AI Delegation on Human Task Performance and Task Satisfaction
Abstract: Recent work has proposed artificial intelligence (AI) models that can learn to decide whether to make a prediction for an instance of a task or to delegate it to a human by considering both parties’ capa... | [
10621
] | Train |
16,999 | 31 | Title: Discrete Prompt Optimization via Constrained Generation for Zero-shot Re-ranker
Abstract: Re-rankers, which order retrieved documents with respect to the relevance score on the given query, have gained attention for the information retrieval (IR) task. Rather than fine-tuning the pre-trained language model (PLM)... | [
397
] | Test |
17,000 | 25 | Title: Face: Fast, Accurate and Context-Aware Audio Annotation and Classification
Abstract: This paper presents a context-aware framework for feature selection and classification procedures to realize a fast and accurate audio event annotation and classification. The context-aware design starts with exploring feature e... | [] | Train |
17,001 | 24 | Title: Spectral Augmentations for Graph Contrastive Learning
Abstract: Contrastive learning has emerged as a premier method for learning representations with or without supervision. Recent studies have shown its utility in graph representation learning for pre-training. Despite successes, the understanding of how to de... | [] | Train |
17,002 | 16 | Title: A Recipe for Efficient SBIR Models: Combining Relative Triplet Loss with Batch Normalization and Knowledge Distillation
Abstract: Sketch-Based Image Retrieval (SBIR) is a crucial task in multimedia retrieval, where the goal is to retrieve a set of images that match a given sketch query. Researchers have already ... | [] | Validation |
17,003 | 16 | Title: Spherical Feature Pyramid Networks For Semantic Segmentation
Abstract: Semantic segmentation for spherical data is a challenging problem in machine learning since conventional planar approaches require projecting the spherical image to the Euclidean plane. Representing the signal on a fundamentally different top... | [] | Train |
17,004 | 16 | Title: PVD-AL: Progressive Volume Distillation with Active Learning for Efficient Conversion Between Different NeRF Architectures
Abstract: Neural Radiance Fields (NeRF) have been widely adopted as practical and versatile representations for 3D scenes, facilitating various downstream tasks. However, different architect... | [
5779
] | Train |
17,005 | 34 | Title: Local Lipschitz Filters for Bounded-Range Functions
Abstract: We study local filters for the Lipschitz property of real-valued functions $f: V \to [0,r]$, where the Lipschitz property is defined with respect to an arbitrary undirected graph $G=(V,E)$. We give nearly optimal local Lipschitz filters both with resp... | [] | Train |
17,006 | 36 | Title: Conditional dominance in games with unawareness
Abstract: Heifetz, Meier, and Schipper (2013) introduced dynamic game with unawareness consisting of a partially ordered set of games in extensive form. Here, we study the normal form of dynamic games with unawareness. The generalized normal form associated with a ... | [] | Train |
17,007 | 16 | Title: Dual Adaptive Representation Alignment for Cross-Domain Few-Shot Learning
Abstract: Few-shot learning aims to recognize novel queries with limited support samples by learning from base knowledge. Recent progress in this setting assumes that the base knowledge and novel query samples are distributed in the same d... | [] | Validation |
17,008 | 24 | Title: Detecting and Ranking Causal Anomalies in End-to-End Complex System
Abstract: With the rapid development of technology, the automated monitoring systems of large-scale factories are becoming more and more important. By collecting a large amount of machine sensor data, we can have many ways to find anomalies. We ... | [] | Train |
17,009 | 27 | Title: Toward Globally Optimal State Estimation Using Automatically Tightened Semidefinite Relaxations
Abstract: In recent years, semidefinite relaxations of common optimization problems in robotics have attracted growing attention due to their ability to provide globally optimal solutions. In many cases, it was shown ... | [
3809,
36231,
32729,
21595,
22431
] | Train |
17,010 | 32 | Title: Massively Distributed Finite-Volume Flux Computation
Abstract: Designing large-scale geological carbon capture and storage projects and ensuring safe long-term CO2 containment - as a climate change mitigation strategy - requires fast and accurate numerical simulations. These simulations involve solving complex P... | [
29339
] | Test |
17,011 | 27 | Title: A Lightweight and Transferable Design for Robust LEGO Manipulation
Abstract: LEGO is a well-known platform for prototyping pixelized objects. However, robotic LEGO prototyping (i.e. manipulating LEGO bricks) is challenging due to the tight connections and accuracy requirement. This paper investigates safe and ef... | [] | Validation |
17,012 | 16 | Title: Underwater Camouflage Object Detection Dataset
Abstract: We have made a dataset of camouflage object detection mainly for complex seabed scenes, and named it UnderWater RGB&Sonar,or UW-RS for short. The UW-RS dataset contains a total of 1972 image data. The dataset mainly consists of two parts, namely underwater... | [] | Train |
17,013 | 8 | Title: Optimal Mobility Aware Wireless Edge Cloud Support for the Metaverse
Abstract: Mobile-augmented-reality (MAR) applications extended into the metaverse could provide mixed and immersive experiences by amalgamating the virtual and physical worlds. However, the consideration of joining MAR and the metaverse require... | [] | Validation |
17,014 | 24 | Title: Linear Spaces of Meanings: Compositional Structures in Vision-Language Models
Abstract: We investigate compositional structures in data embeddings from pre-trained vision-language models (VLMs). Traditionally, compositionality has been associated with algebraic operations on embeddings of words from a pre-existi... | [
7538,
39509
] | Validation |
17,015 | 10 | Title: Fast Knowledge Graph Completion using Graphics Processing Units
Abstract: Knowledge graphs can be used in many areas related to data semantics such as question-answering systems, knowledge based systems. However, the currently constructed knowledge graphs need to be complemented for better knowledge in terms of ... | [] | Test |
17,016 | 25 | Title: Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining
Abstract: Existing contrastive learning methods for anomalous sound detection refine the audio representation of each audio sample by using the contrast between the samples' augmentations (e.g., with time ... | [] | Validation |
17,017 | 16 | Title: Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomaly Detection
Abstract: Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the latent representations of normal motions t... | [
32737,
2310
] | Train |
17,018 | 31 | Title: DELTA: Dynamic Embedding Learning with Truncated Conscious Attention for CTR Prediction
Abstract: Click-Through Rate (CTR) prediction is a pivotal task in product and content recommendation, where learning effective feature embeddings is of great significance. However, traditional methods typically learn fixed f... | [
44289,
7134
] | Train |
17,019 | 16 | Title: FourLLIE: Boosting Low-Light Image Enhancement by Fourier Frequency Information
Abstract: Recently, Fourier frequency information has attracted much attention in Low-Light Image Enhancement (LLIE). Some researchers noticed that, in the Fourier space, the lightness degradation mainly exists in the amplitude compo... | [
10948,
32967
] | Train |
17,020 | 24 | Title: Ghost Noise for Regularizing Deep Neural Networks
Abstract: Batch Normalization (BN) is widely used to stabilize the optimization process and improve the test performance of deep neural networks. The regularization effect of BN depends on the batch size and explicitly using smaller batch sizes with Batch Normali... | [] | Train |
17,021 | 28 | Title: Successive Refinement of Shannon Cipher System Under Maximal Leakage
Abstract: We study the successive refinement problem of Shannon cipher system under maximal leakage for a discrete memoryless source with arbitrary bounded distortion measures. Specifically, we generalize the threat model described by Issa, Wag... | [] | Validation |
17,022 | 27 | Title: Design, Modeling and Control of a Top-Loading Fully-Actuated Cargo Transportation Multirotor
Abstract: Existing multirotor-based cargo transportation does not maintain a constant cargo attitude due to underactuation; however, fragile payloads may require a consistent posture. The conventional method is also cumb... | [] | Train |
17,023 | 24 | Title: The effect of network topologies on fully decentralized learning: a preliminary investigation
Abstract: In a decentralized machine learning system, data is typically partitioned among multiple devices or nodes, each of which trains a local model using its own data. These local models are then shared and combined... | [] | Train |
17,024 | 16 | Title: PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360°
Abstract: Synthesis and reconstruction of 3D human head has gained increasing interests in computer vision and computer graphics recently. Existing state-of-the-art 3D generative adversarial networks (GANs) for 3D human head synthesis are either limited to ... | [
41857,
25983
] | Train |
17,025 | 27 | Title: Learning Stabilization Control from Observations by Learning Lyapunov-like Proxy Models
Abstract: The deployment of Reinforcement Learning to robotics applications faces the difficulty of reward engineering. Therefore, approaches have focused on creating reward functions by Learning from Observations (LfO) which... | [] | Train |
17,026 | 25 | Title: Mispronunciation Detection of Basic Quranic Recitation Rules using Deep Learning
Abstract: In Islam, readers must apply a set of pronunciation rules called Tajweed rules to recite the Quran in the same way that the angel Jibrael taught the Prophet, Muhammad. The traditional process of learning the correct applic... | [] | Test |
17,027 | 22 | Title: Cutting the Cake: A Language for Fair Division
Abstract: The fair division literature in economics considers how to divide resources between multiple agents such that the allocation is envy-free: each agent receives their favorite piece. Researchers have developed a variety of fair division protocols for the mos... | [] | Train |
17,028 | 30 | Title: Exploring the Potential of Large Language models in Traditional Korean Medicine: A Foundation Model Approach to Culturally-Adapted Healthcare
Abstract: Introduction: Traditional Korean medicine (TKM) emphasizes individualized diagnosis and treatment, making AI modeling difficult due to limited data and implicit ... | [
19758
] | Train |
17,029 | 16 | Title: DreamStone: Image as Stepping Stone for Text-Guided 3D Shape Generation
Abstract: In this paper, we present a new text-guided 3D shape generation approach DreamStone that uses images as a stepping stone to bridge the gap between text and shape modalities for generating 3D shapes without requiring paired text and... | [
26698,
24622,
44593,
16562,
15668,
33845,
15541,
33977,
18267,
28478
] | Validation |
17,030 | 4 | Title: White-box Inference Attacks against Centralized Machine Learning and Federated Learning
Abstract: With the development of information science and technology, various industries have generated massive amounts of data, and machine learning is widely used in the analysis of big data. However, if the privacy of mach... | [] | Train |
17,031 | 27 | Title: LiDAR-based drone navigation with reinforcement learning
Abstract: Reinforcement learning is of increasing importance in the field of robot control and simulation plays a~key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number of published scientific pape... | [] | Validation |
17,032 | 5 | Title: Efficient Multitask Learning on Resource-Constrained Systems
Abstract: We present Antler, which exploits the affinity between all pairs of tasks in a multitask inference system to construct a compact graph representation of the task set and finds an optimal order of execution of the tasks such that the end-to-en... | [
28172
] | Test |
17,033 | 23 | Title: On Refactoring Quantum Programs
Abstract: Refactoring is a crucial technique for improving the efficiency and maintainability of software by restructuring its internal design while preserving its external behavior. While classical programs have benefited from various refactoring methods, the field of quantum pro... | [] | Validation |
17,034 | 28 | Title: QoS-based Beamforming and Compression Design for Cooperative Cellular Networks via Lagrangian Duality
Abstract: This paper considers the quality-of-service (QoS)-based joint beamforming and compression design problem in the downlink cooperative cellular network, where multiple relay-like base stations (BSs), con... | [
6780
] | Test |
17,035 | 34 | Title: A simpler and parallelizable $O(\sqrt{\log n})$-approximation algorithm for Sparsest Cut
Abstract: Currently, the best known tradeoff between approximation ratio and complexity for the {\sc Sparsest Cut} problem is achieved by the algorithm in [Sherman, FOCS 2009]: it computes $O(\sqrt{(\log n)/\varepsilon})$-ap... | [
31178
] | Train |
17,036 | 16 | Title: HybridPoint: Point Cloud Registration Based on Hybrid Point Sampling and Matching
Abstract: Patch-to-point matching has become a robust way of point cloud registration. However, previous patch-matching methods employ superpoints with poor localization precision as nodes, which may lead to ambiguous patch partiti... | [] | Test |
17,037 | 24 | Title: Towards Modular Machine Learning Solution Development: Benefits and Trade-offs
Abstract: Machine learning technologies have demonstrated immense capabilities in various domains. They play a key role in the success of modern businesses. However, adoption of machine learning technologies has a lot of untouched pot... | [] | Train |
17,038 | 24 | Title: Selective Uncertainty Propagation in Offline RL
Abstract: We study the finite-horizon offline reinforcement learning (RL) problem. Since actions at any state can affect next-state distributions, the related distributional shift challenges can make this problem far more statistically complex than offline policy l... | [] | Train |
17,039 | 10 | Title: DREAM: Adaptive Reinforcement Learning based on Attention Mechanism for Temporal Knowledge Graph Reasoning
Abstract: Temporal knowledge graphs (TKGs) model the temporal evolution of events and have recently attracted increasing attention. Since TKGs are intrinsically incomplete, it is necessary to reason out mis... | [
20665,
16725
] | Train |
17,040 | 30 | Title: Inference-Time Policy Adapters (IPA): Tailoring Extreme-Scale LMs without Fine-tuning
Abstract: Large language models excel at a variety of language tasks when prompted with examples or instructions. Yet controlling these models through prompting alone is limited. Tailoring language models through fine-tuning (e... | [
39273,
4658,
33220,
17789
] | Validation |
17,041 | 36 | Title: Machine Learning-powered Combinatorial Clock Auction
Abstract: We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, several papers have recently proposed machine learning (ML)-based ... | [] | Validation |
17,042 | 24 | Title: Robust Lagrangian and Adversarial Policy Gradient for Robust Constrained Markov Decision Processes
Abstract: The robust constrained Markov decision process (RCMDP) is a recent task-modelling framework for reinforcement learning that incorporates behavioural constraints and that provides robustness to errors in t... | [
8490
] | Test |
17,043 | 6 | Title: Human-Centered Responsible Artificial Intelligence: Current & Future Trends
Abstract: In recent years, the CHI community has seen significant growth in research on Human-Centered Responsible Artificial Intelligence. While different research communities may use different terminology to discuss similar topics, all... | [
5778,
14750,
33967
] | Test |
17,044 | 16 | Title: UnitModule: A Lightweight Joint Image Enhancement Module for Underwater Object Detection
Abstract: Underwater object detection faces the problem of underwater image degradation, which affects the performance of the detector. Underwater object detection methods based on noise reduction and image enhancement usual... | [] | Train |
17,045 | 30 | Title: CREST: A Joint Framework for Rationalization and Counterfactual Text Generation
Abstract: Selective rationales and counterfactual examples have emerged as two effective, complementary classes of interpretability methods for analyzing and training NLP models. However, prior work has not explored how these methods... | [
40882
] | Train |
17,046 | 16 | Title: Zero-Shot 3D Shape Correspondence
Abstract: We propose a novel zero-shot approach to computing correspondences between 3D shapes. Existing approaches mainly focus on isometric and near-isometric shape pairs (e.g., human vs. human), but less attention has been given to strongly non-isometric and inter-class shape... | [
10624,
3012,
37517,
18447,
41104,
33875,
3609,
35263
] | Train |
17,047 | 6 | Title: Continuous Visual Feedback of Risk for Haptic Lateral Assistance
Abstract: Lateral assistance systems are a significant part of the currently existing Advanced Driving Assistance System (ADAS). In most cases, such systems provide intermittent audio and haptic feedback rather than continuous feedback, making it di... | [] | Train |
17,048 | 8 | Title: SCC5G: A PQC-based Architecture for Highly Secure Critical Communication over Cellular Network in Zero-Trust Environment
Abstract: 5G made a significant jump in cellular network security by offering enhanced subscriber identity protection and a user-network mutual authentication implementation. However, it still... | [] | Train |
17,049 | 30 | Title: PaniniQA: Enhancing Patient Education Through Interactive Question Answering
Abstract: Patient portal allows discharged patients to access their personalized discharge instructions in electronic health records (EHRs). However, many patients have difficulty understanding or memorizing their discharge instructions... | [
11425,
33220,
709,
25892,
39435,
22701,
39451
] | Train |
17,050 | 30 | Title: SlimFit: Memory-Efficient Fine-Tuning of Transformer-based Models Using Training Dynamics
Abstract: Transformer-based models, such as BERT and ViT, have achieved state-of-the-art results across different natural language processing (NLP) and computer vision (CV) tasks. However, these models are extremely memory ... | [] | Train |
17,051 | 10 | Title: Evolutionary approaches to explainable machine learning
Abstract: Machine learning models are increasingly being used in critical sectors, but their black-box nature has raised concerns about accountability and trust. The field of explainable artificial intelligence (XAI) or explainable machine learning (XML) ha... | [] | Train |
17,052 | 16 | Title: Semantic Neural Model Approach for Face Recognition from Sketch
Abstract: Face sketch synthesis and reputation have wide range of packages in law enforcement. Despite the amazing progresses had been made in faces cartoon and reputation, maximum current researches regard them as separate responsibilities. On this... | [] | Train |
17,053 | 16 | Title: HySpecNet-11k: A Large-Scale Hyperspectral Dataset for Benchmarking Learning-Based Hyperspectral Image Compression Methods
Abstract: The development of learning-based hyperspectral image compression methods has recently attracted great attention in remote sensing. Such methods require a high number of hyperspect... | [] | Train |
17,054 | 23 | Title: TARGET: Traffic Rule-based Test Generation for Autonomous Driving Systems
Abstract: Recent accidents involving self-driving cars call for extensive testing efforts to improve the safety and robustness of autonomous driving. However, constructing test scenarios for autonomous driving is tedious and time-consuming... | [
22097
] | Test |
17,055 | 16 | Title: SC-NeuS: Consistent Neural Surface Reconstruction from Sparse and Noisy Views
Abstract: The recent neural surface reconstruction by volume rendering approaches have made much progress by achieving impressive surface reconstruction quality, but are still limited to dense and highly accurate posed views. To overco... | [] | Validation |
17,056 | 28 | Title: Octonion Phase Retrieval
Abstract: Signal processing over hypercomplex numbers arises in many optical imaging applications. In particular, spectral image or color stereo data are often processed using octonion algebra. Recently, the eight-band multispectral image phase recovery has gained salience, wherein it is... | [] | Test |
17,057 | 16 | Title: Group Activity Recognition in Computer Vision: A Comprehensive Review, Challenges, and Future Perspectives
Abstract: Group activity recognition is a hot topic in computer vision. Recognizing activities through group relationships plays a vital role in group activity recognition. It holds practical implications i... | [] | Train |
17,058 | 24 | Title: Large-scale gradient-based training of Mixtures of Factor Analyzers
Abstract: Gaussian Mixture Models (GMMs) are a standard tool in data analysis. However, they face problems when applied to high-dimensional data (e.g., images) due to the size of the required full covariance matrices (CMs), whereas the use of di... | [] | Test |
17,059 | 24 | Title: Adapting Neural Link Predictors for Data-Efficient Complex Query Answering
Abstract: Answering complex queries on incomplete knowledge graphs is a challenging task where a model needs to answer complex logical queries in the presence of missing knowledge. Prior work in the literature has proposed to address this... | [
15293
] | Train |
17,060 | 27 | Title: Efficient collision avoidance for autonomous vehicles in polygonal domains
Abstract: This research focuses on trajectory planning problems for autonomous vehicles utilizing numerical optimal control techniques. The study reformulates the constrained optimization problem into a nonlinear programming problem, inco... | [
32013
] | Test |
17,061 | 30 | Title: Can Large Language Models Be an Alternative to Human Evaluations?
Abstract: Human evaluation is indispensable and inevitable for assessing the quality of texts generated by machine learning models or written by humans. However, human evaluation is very difficult to reproduce and its quality is notoriously unstab... | [
45324,
19983,
29072,
14609,
33815,
35101,
29223,
15400,
7339,
41010,
16822,
13495,
10295,
29753,
2234,
9403,
45243,
17726,
2622,
22354,
35545,
39642,
1369,
16221,
43103,
20070,
17255,
25830,
38253,
17263
] | Train |
17,062 | 26 | Title: Metropolitan Scale and Longitudinal Dataset of Anonymized Human Mobility Trajectories
Abstract: Modeling and predicting human mobility trajectories in urban areas is an essential task for various applications. The recent availability of large-scale human movement data collected from mobile devices have enabled t... | [] | Train |
17,063 | 16 | Title: Class-Specific Variational Auto-Encoder for Content-Based Image Retrieval
Abstract: Using a discriminative representation obtained by supervised deep learning methods showed promising results on diverse Content-Based Image Retrieval (CBIR) problems. However, existing methods exploiting labels during training try... | [] | Train |
17,064 | 16 | Title: Robust Principles: Architectural Design Principles for Adversarially Robust CNNs
Abstract: Our research aims to unify existing works' diverging opinions on how architectural components affect the adversarial robustness of CNNs. To accomplish our goal, we synthesize a suite of three generalizable robust architect... | [
29873,
23357,
33414
] | Train |
17,065 | 9 | Title: On the Hardness of PosSLP
Abstract: The problem $\textrm{PosSLP}$ involves determining whether an integer computed by a given straight-line program is positive. This problem has attracted considerable attention within the field of computational complexity as it provides a complete characterization of the complex... | [] | Train |
17,066 | 30 | Title: Interpretability and Transparency-Driven Detection and Transformation of Textual Adversarial Examples (IT-DT)
Abstract: Transformer-based text classifiers like BERT, Roberta, T5, and GPT-3 have shown impressive performance in NLP. However, their vulnerability to adversarial examples poses a security risk. Existi... | [
21935
] | Test |
17,067 | 5 | Title: How Hard is Asynchronous Weight Reassignment? (Extended Version)
Abstract: The performance of distributed storage systems deployed on wide-area networks can be improved using weighted (majority) quorum systems instead of their regular variants due to the heterogeneous performance of the nodes. A significant limi... | [] | Test |
17,068 | 23 | Title: Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study
Abstract: [Context:] The quality of requirements engineering artifacts, e.g. requirements specifications, is acknowledged to be an important success factor for projects. Therefore, many companies spend significant amounts of m... | [
2647
] | Train |
17,069 | 4 | Title: NFT.mine: An xDeepFM-based Recommender System for Non-fungible Token (NFT) Buyers
Abstract: Non-fungible token (NFT) is a tradable unit of data stored on the blockchain which can be associated with some digital asset as a certification of ownership. The past several years have witnessed the exponential growth of... | [] | Train |
17,070 | 24 | Title: Training shallow ReLU networks on noisy data using hinge loss: when do we overfit and is it benign?
Abstract: We study benign overfitting in two-layer ReLU networks trained using gradient descent and hinge loss on noisy data for binary classification. In particular, we consider linearly separable data for which ... | [] | Train |
17,071 | 16 | Title: A Robust Negative Learning Approach to Partial Domain Adaptation Using Source Prototypes
Abstract: This work proposes a robust Partial Domain Adaptation (PDA) framework that mitigates the negative transfer problem by incorporating a robust target-supervision strategy. It leverages ensemble learning and includes ... | [] | Train |
17,072 | 24 | Title: Where We Have Arrived in Proving the Emergence of Sparse Symbolic Concepts in AI Models
Abstract: This paper aims to prove the emergence of symbolic concepts in well-trained AI models. We prove that if (1) the high-order derivatives of the model output w.r.t. the input variables are all zero, (2) the AI model ca... | [
4705,
10372,
13001,
25529,
5756
] | Train |
17,073 | 23 | Title: OrdinalFix: Fixing Compilation Errors via Shortest-Path CFL Reachability
Abstract: The development of correct and efficient software can be hindered by compilation errors, which must be fixed to ensure the code's syntactic correctness and program language constraints. Neural network-based approaches have been us... | [] | Train |
17,074 | 25 | Title: Deep Attention-Based Alignment Network for Melody Generation from Incomplete Lyrics
Abstract: We propose a deep attention-based alignment network, which aims to automatically predict lyrics and melody with given incomplete lyrics as input in a way similar to the music creation of humans. Most importantly, a deep... | [] | Test |
17,075 | 16 | Title: CeRF: Convolutional Neural Radiance Fields for New View Synthesis with Derivatives of Ray Modeling
Abstract: In recent years, novel view synthesis has gained popularity in generating high-fidelity images. While demonstrating superior performance in the task of synthesizing novel views, the majority of these meth... | [
33187,
11206,
18380,
27795,
20980,
21846,
42937,
37694
] | Train |
17,076 | 24 | Title: Efficient RLHF: Reducing the Memory Usage of PPO
Abstract: Reinforcement Learning with Human Feedback (RLHF) has revolutionized language modeling by aligning models with human preferences. However, the RL stage, Proximal Policy Optimization (PPO), requires over 3x the memory of Supervised Fine-Tuning (SFT), maki... | [
12128,
40192,
13700,
17508,
13510,
21190,
8106,
458,
25772,
17517,
27248,
26357,
39451,
22201,
17883,
24284
] | Train |
17,077 | 27 | Title: A Decision Tree-based Monitoring and Recovery Framework for Autonomous Robots with Decision Uncertainties
Abstract: Autonomous mobile robots (AMR) operating in the real world often need to make critical decisions that directly impact their own safety and the safety of their surroundings. Learning-based approache... | [] | Train |
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