node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
values |
|---|---|---|---|---|
26,778 | 4 | Title: Decentralized Inverse Transparency With Blockchain
Abstract:
Employee data can be used to facilitate work, but their misusage may pose risks for individuals.
Inverse transparency
therefore aims to track all usages of personal data, allowing individuals to monitor them to ensure accountability for potential m... | [
41035,
21946,
4859
] | Train |
26,779 | 23 | Title: Automated Machine Learning in the smart construction era: Significance and accessibility for industrial classification and regression tasks
Abstract: This paper explores the application of automated machine learning (AutoML) techniques to the construction industry, a sector vital to the global economy. Tradition... | [] | Train |
26,780 | 24 | Title: Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges
Abstract: Deep reinforcement learning (DRL), leveraging Deep Learning (DL) in reinforcement learning, has shown significant potential in achieving human-level autonomy in a wide range of domains, including robotics, computer vision, and comp... | [] | Train |
26,781 | 24 | Title: "Can We Detect Substance Use Disorder?": Knowledge and Time Aware Classification on Social Media from Darkweb
Abstract: Opioid and substance misuse is rampant in the United States today, with the phenomenon known as the"opioid crisis". The relationship between substance use and mental health has been extensively... | [] | Train |
26,782 | 16 | Title: Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion
Abstract: A typical monocular depth estimator is trained for a single camera, so its performance drops severely on images taken with different cameras. To address this issue, we propose a v... | [] | Test |
26,783 | 5 | Title: From Kubernetes to Knactor: A State-Centric Rethink of Service Integration
Abstract: Microservices are increasingly used in modern applications, leading to a growing need for effective service integration solutions. However, we argue that traditional API-centric integration mechanisms (e.g., RPC, REST, and Pub/S... | [
9637
] | Train |
26,784 | 24 | Title: The Behavior and Convergence of Local Bayesian Optimization
Abstract: A recent development in Bayesian optimization is the use of local optimization strategies, which can deliver strong empirical performance on high-dimensional problems compared to traditional global strategies. The"folk wisdom"in the literature... | [] | Test |
26,785 | 16 | Title: One-to-Few Label Assignment for End-to-End Dense Detection
Abstract: One-to-one (o2o) label assignment plays a key role for transformer based end-to-end detection, and it has been recently introduced in fully convolutional detectors for end-to-end dense detection. However, o2o can degrade the feature learning ef... | [
9138
] | Test |
26,786 | 27 | Title: USA-Net: Unified Semantic and Affordance Representations for Robot Memory
Abstract: In order for robots to follow open-ended instructions like"go open the brown cabinet over the sink", they require an understanding of both the scene geometry and the semantics of their environment. Robotic systems often handle th... | [
7419,
28557,
22222
] | Validation |
26,787 | 36 | Title: The Shapley-Hodge Associated Game
Abstract: In cooperative game theory, associated games allow for providing meaningful characterizations of solution concepts. Moreover, generalized values allow computing an influence or power index of each coalition in a game. In this paper, we view associated games through the... | [] | Train |
26,788 | 24 | Title: Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping
Abstract: Long-term time series forecasting has gained significant attention in recent years. While there are various specialized designs for capturing temporal dependency, previous studies have demonstrated that a single linear lay... | [
16576,
9764,
40397,
23527
] | Train |
26,789 | 24 | Title: Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Abstract: The general sequential decision-making problem, which includes Markov decision processes (MDPs) and partially observable MDPs (POMDPs) as special cases, aims at maximizing a cumulative reward by making a sequence of de... | [
26407
] | Validation |
26,790 | 5 | Title: Auditable data structures: theory and applications
Abstract: Every digital process needs to consume some data in order to work properly. It is very common for applications to use some external data in their processes, getting them by sources such as external APIs. Therefore, trusting the received data becomes cr... | [
2516
] | Validation |
26,791 | 4 | Title: Covert D2D Communication Underlaying Cellular Network: A System-Level Security Perspective
Abstract: In this paper, we aim to secure the D2D communication of the D2D-underlaid cellular network by leveraging covert communication to hide its presence from the vigilant adversary. In particular, there are adversarie... | [] | Validation |
26,792 | 10 | Title: Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Abstract: Ensuring alignment, which refers to making models behave in accordance with human intentions [1,2], has become a critical task before deploying large language models (LLMs) in real-world applications. For instance,... | [
23425,
29825,
40586,
38157,
44173,
16401,
38801,
21921,
40610,
44323,
2855,
13224,
2988,
22444,
25772,
27439,
31794,
27059,
40504,
20794,
37947,
45242,
35580,
22476,
26317,
32206,
44623,
6353,
12896,
11745,
36196,
4071,
32618,
33132,
37360,
19315... | Test |
26,793 | 23 | Title: A3Test: Assertion-Augmented Automated Test Case Generation
Abstract: Test case generation is an important activity, yet a time-consuming and laborious task. Recently, AthenaTest -- a deep learning approach for generating unit test cases -- is proposed. However, AthenaTest can generate less than one-fifth of the ... | [
22097,
7043,
9635
] | Validation |
26,794 | 6 | Title: Context, Utility and Influence of an Explanation
Abstract: Contextual utility theory integrates context-sensitive factors into utility-based decision-making models. It stresses the importance of understanding individual decision-makers' preferences, values, and beliefs and the situational factors that affect the... | [] | Test |
26,795 | 4 | Title: Network Agnostic MPC with Statistical Security
Abstract: We initiate the study of the network agnostic MPC protocols with statistical security. Network agnostic protocols give the best possible security guarantees irrespective of the underlying network type. We consider the general-adversary model, where the adv... | [] | Validation |
26,796 | 16 | Title: IPCC-TP: Utilizing Incremental Pearson Correlation Coefficient for Joint Multi-Agent Trajectory Prediction
Abstract: Reliable multi-agent trajectory prediction is crucial for the safe planning and control of autonomous systems. Compared with single-agent cases, the major challenge in simultaneously processing mu... | [
18283
] | Test |
26,797 | 30 | Title: Bipol: A Novel Multi-Axes Bias Evaluation Metric with Explainability for NLP
Abstract: We introduce bipol, a new metric with explainability, for estimating social bias in text data. Harmful bias is prevalent in many online sources of data that are used for training machine learning (ML) models. In a step to addr... | [
27208
] | Train |
26,798 | 16 | Title: Vote2Cap-DETR++: Decoupling Localization and Describing for End-to-End 3D Dense Captioning
Abstract: 3D dense captioning requires a model to translate its understanding of an input 3D scene into several captions associated with different object regions. Existing methods adopt a sophisticated"detect-then-describe... | [
968,
18776,
10624,
14926
] | Train |
26,799 | 16 | Title: ConTEXTual Net: A Multimodal Vision-Language Model for Segmentation of Pneumothorax
Abstract: Radiology narrative reports often describe characteristics of a patient's disease, including its location, size, and shape. Motivated by the recent success of multimodal learning, we hypothesized that this descriptive t... | [] | Test |
26,800 | 5 | Title: Automated service monitoring in the deployment of ARCHER2
Abstract: The ARCHER2 service, a CPU based HPE Cray EX system with 750,080 cores (5860 nodes), has been deployed throughout 2020 and 2021, going into full service in December of 2021. A key part of the work during this deployment was the integration of AR... | [] | Train |
26,801 | 2 | Title: Finitely accessible arboreal adjunctions and Hintikka formulae
Abstract: Arboreal categories provide an axiomatic framework in which abstract notions of bisimilarity and back-and-forth games can be defined. They act on extensional categories, typically consisting of relational structures, via arboreal adjunction... | [] | Train |
26,802 | 30 | Title: DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
Abstract: Learning from noisy labels is a challenge that arises in many real-world applications where training data can contain incorrect or corrupted labels. When fine-tuning language models with noisy labels, models can easily overfit ... | [
19288,
24217
] | Train |
26,803 | 24 | Title: When Source-Free Domain Adaptation Meets Learning with Noisy Labels
Abstract: Recent state-of-the-art source-free domain adaptation (SFDA) methods have focused on learning meaningful cluster structures in the feature space, which have succeeded in adapting the knowledge from source domain to unlabeled target dom... | [
29025,
31596,
28176,
43608,
4412
] | Train |
26,804 | 16 | Title: Multi-task 3D building understanding with multi-modal pretraining
Abstract: This paper explores various learning strategies for 3D building type classification and part segmentation on the BuildingNet dataset. ULIP with PointNeXt and PointNeXt segmentation are extended for the classification and segmentation tas... | [
17583
] | Validation |
26,805 | 28 | Title: Age of Information of CSMA/CA Based Wireless Networks
Abstract: We consider a wireless network where $N$ nodes compete for a shared channel over the CSMA/CA protocol to deliver observed updates to a common remote monitor. For this network, we rate the information freshness of the CSMA/CA based network using the ... | [] | Validation |
26,806 | 16 | Title: EAML: ensemble self-attention-based mutual learning network for document image classification
Abstract: nan | [] | Train |
26,807 | 16 | Title: Learning with Noisy labels via Self-supervised Adversarial Noisy Masking
Abstract: Collecting large-scale datasets is crucial for training deep models, annotating the data, however, inevitably yields noisy labels, which poses challenges to deep learning algorithms. Previous efforts tend to mitigate this problem ... | [
11712,
10715
] | Train |
26,808 | 6 | Title: Inform the Uninformed: Improving Online Informed Consent Reading with an AI-Powered Chatbot
Abstract: Informed consent is a core cornerstone of ethics in human subject research. Through the informed consent process, participants learn about the study procedure, benefits, risks, and more to make an informed decis... | [
31391
] | Test |
26,809 | 16 | Title: ELITE: Encoding Visual Concepts into Textual Embeddings for Customized Text-to-Image Generation
Abstract: In addition to the unprecedented ability in imaginary creation, large text-to-image models are expected to take customized concepts in image generation. Existing works generally learn such concepts in an opt... | [
37126,
43911,
25739,
14361,
18205,
7458,
44197,
31913,
37930,
18731,
35499,
305,
24763,
20687,
20435,
12116,
3031,
14047,
33261,
4084,
28532,
42104
] | Train |
26,810 | 30 | Title: FaNS: a Facet-based Narrative Similarity Metric
Abstract: Similar Narrative Retrieval is a crucial task since narratives are essential for explaining and understanding events, and multiple related narratives often help to create a holistic view of the event of interest. To accurately identify semantically simila... | [
38208,
28151,
35545,
39451,
35388,
24479
] | Validation |
26,811 | 28 | Title: Do not Interfere but Cooperate: A Fully Learnable Code Design for Multi-Access Channels with Feedback
Abstract: Data-driven deep learning based code designs, including low-complexity neural decoders for existing codes, or end-to-end trainable auto-encoders have exhibited impressive results, particularly in scena... | [] | Train |
26,812 | 24 | Title: Pretraining task diversity and the emergence of non-Bayesian in-context learning for regression
Abstract: Pretrained transformers exhibit the remarkable ability of in-context learning (ICL): they can learn tasks from just a few examples provided in the prompt without updating any weights. This raises a foundatio... | [
25833,
26578,
3795,
25892
] | Train |
26,813 | 30 | Title: S2abEL: A Dataset for Entity Linking from Scientific Tables
Abstract: Entity linking (EL) is the task of linking a textual mention to its corresponding entry in a knowledge base, and is critical for many knowledge-intensive NLP applications. When applied to tables in scientific papers, EL is a step toward large-... | [
35944,
28576
] | Test |
26,814 | 30 | Title: Learn What Is Possible, Then Choose What Is Best: Disentangling One-To-Many Relations in Language Through Text-based Games
Abstract: Language models pre-trained on large self-supervised corpora, followed by task-specific fine-tuning has become the dominant paradigm in NLP. These pre-training datasets often have ... | [] | Train |
26,815 | 30 | Title: A Study on Robustness and Reliability of Large Language Model Code Generation
Abstract: Recently, the large language models (LLMs) have shown extraordinary ability in understanding natural language and generating programming code. It has been a common practice of software engineers to consult LLMs when encounter... | [
2980,
33220,
31145,
29396,
38615,
43641,
13278
] | Train |
26,816 | 16 | Title: Towards L-System Captioning for Tree Reconstruction
Abstract: This work proposes a novel concept for tree and plant reconstruction by directly inferring a Lindenmayer-System (L-System) word representation from image data in an image captioning approach. We train a model end-to-end which is able to translate give... | [] | Validation |
26,817 | 5 | Title: Cloud Render Farm Services Discovery Using NLP And Ontology Based Knowledge Graph
Abstract: Cloud render farm services are the animation domain specific cloud services Platform-as-a-Service (PaaS) type of cloud services that provides a complete platform to render the animation files. However, identifying the ren... | [] | Validation |
26,818 | 16 | Title: Evolutionary Computation in Action: Hyperdimensional Deep Embedding Spaces of Gigapixel Pathology Images
Abstract: One of the main obstacles of adopting digital pathology is the challenge of efficient processing of hyperdimensional digitized biopsy samples, called whole slide images (WSIs). Exploiting deep learn... | [] | Train |
26,819 | 8 | Title: Dynamic Regret of Randomized Online Service Caching in Edge Computing
Abstract: This paper studies an online service caching problem, where an edge server, equipped with a prediction window of future service request arrivals, needs to decide which services to host locally subject to limited storage capacity. The... | [
9716
] | Train |
26,820 | 25 | Title: Auditory Attention Decoding with Task-Related Multi-View Contrastive Learning
Abstract: The human brain can easily focus on one speaker and suppress others in scenarios such as a cocktail party. Recently, researchers found that auditory attention can be decoded from the electroencephalogram (EEG) data. However, ... | [] | Train |
26,821 | 27 | Title: Design and Control of a Novel Variable Stiffness Series Elastic Actuator
Abstract: This article expounds the design and control of a new variable stiffness series elastic actuator (VSSEA). It is established by employing a modular mechanical design approach that allows us to effectively optimize the stiffness mod... | [
30945
] | Validation |
26,822 | 22 | Title: Clustered Relational Thread-Modular Abstract Interpretation with Local Traces
Abstract: We construct novel thread-modular analyses that track relational information for potentially overlapping clusters of global variables - given that they are protected by common mutexes. We provide a framework to systematically... | [] | Train |
26,823 | 30 | Title: Enhancing Biomedical Text Summarization and Question-Answering: On the Utility of Domain-Specific Pre-Training
Abstract: Biomedical summarization requires large datasets to train for text generation. We show that while transfer learning offers a viable option for addressing this challenge, an in-domain pre-train... | [
4108
] | Train |
26,824 | 16 | Title: Robust T-Loss for Medical Image Segmentation
Abstract: This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution and can effectively handle outliers in the data by controlling its sensitivity... | [] | Train |
26,825 | 24 | Title: A survey of Generative AI Applications
Abstract: Generative AI has experienced remarkable growth in recent years, leading to a wide array of applications across diverse domains. In this paper, we present a comprehensive survey of more than 350 generative AI applications, providing a structured taxonomy and conci... | [
40192,
26625,
13186,
4996,
28932,
25368,
30243,
11175,
39466,
42032,
44726,
7993,
37177,
41146,
39613,
22334,
14530,
9924,
30026,
351,
27232,
38368,
13029,
30566,
42597,
1011,
28532,
6648,
13564
] | Train |
26,826 | 27 | Title: Learning Rewards and Skills to Follow Commands with A Data Efficient Visual-Audio Representation
Abstract: Based on the recent advancements in representation learning, we propose a novel framework for command-following robots with raw sensor inputs. Previous RL-based methods are either difficult to continuously ... | [] | Train |
26,827 | 24 | Title: Stochastic Multi-Level Compositional Optimization Algorithms over Networks with Level-Independent Convergence Rate
Abstract: Stochastic multi-level compositional optimization problems cover many new machine learning paradigms, e.g., multi-step model-agnostic meta-learning, which require efficient optimization al... | [] | Test |
26,828 | 16 | Title: Faster Learning of Temporal Action Proposal via Sparse Multilevel Boundary Generator
Abstract: Temporal action localization in videos presents significant challenges in the field of computer vision. While the boundary-sensitive method has been widely adopted, its limitations include incomplete use of intermediat... | [] | Train |
26,829 | 24 | Title: Are uGLAD? Time will tell!
Abstract: We frequently encounter multiple series that are temporally correlated in our surroundings, such as EEG data to examine alterations in brain activity or sensors to monitor body movements. Segmentation of multivariate time series data is a technique for identifying meaningful ... | [
18278
] | Train |
26,830 | 27 | Title: Reasoning about the Unseen for Efficient Outdoor Object Navigation
Abstract: Robots should exist anywhere humans do: indoors, outdoors, and even unmapped environments. In contrast, the focus of recent advancements in Object Goal Navigation(OGN) has targeted navigating in indoor environments by leveraging spatial... | [
40610,
3333,
10502,
19719,
27454,
27440,
39089,
9907,
20469,
12606,
41247
] | Train |
26,831 | 24 | Title: Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
Abstract: A large-scale deep model pre-trained on massive labeled or unlabeled data transfers well to downstream tasks. Linear evaluation freezes parameters in the pre-trained model and trains a linear classifier separately, which is e... | [
15228,
17959,
17756
] | Train |
26,832 | 2 | Title: Bounded Model Checking for Asynchronous Hyperproperties
Abstract: Many types of attacks on confidentiality stem from the nondeterministic nature of the environment that computer programs operate in (e.g., schedulers and asynchronous communication channels). In this paper, we focus on verification of confidential... | [
33033
] | Train |
26,833 | 30 | Title: TrueTeacher: Learning Factual Consistency Evaluation with Large Language Models
Abstract: Factual consistency evaluation is often conducted using Natural Language Inference (NLI) models, yet these models exhibit limited success in evaluating summaries. Previous work improved such models with synthetic training d... | [
41667,
18564,
25830,
17447,
35545,
12602,
39451,
23359
] | Validation |
26,834 | 16 | Title: TbExplain: A Text-based Explanation Method for Scene Classification Models with the Statistical Prediction Correction
Abstract: The field of Explainable Artificial Intelligence (XAI) aims to improve the interpretability of black-box machine learning models. Building a heatmap based on the importance value of inp... | [
45721
] | Train |
26,835 | 34 | Title: Sumplete is Hard, Even with Two Different Numbers
Abstract: Sumplete is a logic puzzle famous for being developed by ChatGPT. The puzzle consists of a rectangular grid, with each cell containing a number. The player has to cross out some numbers such that the sum of uncrossed numbers in each row and column is eq... | [] | Test |
26,836 | 5 | Title: A Robust Adaptive Workload Orchestration in Pure Edge Computing
Abstract: Pure Edge computing (PEC) aims to bring cloud applications and services to the edge of the network to support the growing user demand for time-sensitive applications and data-driven computing. However, mobility and limited computational ca... | [] | Train |
26,837 | 30 | Title: “Why is this misleading?”: Detecting News Headline Hallucinations with Explanations
Abstract: Automatic headline generation enables users to comprehend ongoing news events promptly and has recently become an important task in web mining and natural language processing. With the growing need for news headline gen... | [
38102
] | Train |
26,838 | 10 | Title: Explaining with Attribute-based and Relational Near Misses: An Interpretable Approach to Distinguishing Facial Expressions of Pain and Disgust
Abstract: Explaining concepts by contrasting examples is an efficient and convenient way of giving insights into the reasons behind a classification decision. This is of ... | [] | Test |
26,839 | 16 | Title: Incorporating Pre-training Data Matters in Unsupervised Domain Adaptation
Abstract: Unsupervised domain adaptation(UDA) and Source-free UDA(SFUDA) methods formulate the problem involving two domains: source and target. They typically employ a standard training approach that begins with models pre-trained on larg... | [] | Train |
26,840 | 16 | Title: Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble
Abstract: Multi-organ segmentation, which identifies and separates different organs in medical images, is a fundamental task in medical image analysis. Recently, the immense success of deep learning motivated its wide adoption in multi-organ se... | [
30829
] | Train |
26,841 | 30 | Title: Flacuna: Unleashing the Problem Solving Power of Vicuna using FLAN Fine-Tuning
Abstract: Recently, the release of INSTRUCTEVAL has provided valuable insights into the performance of large language models (LLMs) that utilize encoder-decoder or decoder-only architecture. Interestingly, despite being introduced fou... | [
34208,
13700,
25892,
9012,
2197,
4635,
9403
] | Train |
26,842 | 24 | Title: Interpretable machine learning-accelerated seed treatment by nanomaterials for environmental stress alleviation
Abstract: Crops are constantly challenged by different environmental conditions. Seed treatment using nanomaterials is a cost-effective and environmentally friendly solution for environmental stress mi... | [] | Train |
26,843 | 30 | Title: Knowledge of cultural moral norms in large language models
Abstract: Moral norms vary across cultures. A recent line of work suggests that English large language models contain human-like moral biases, but these studies typically do not examine moral variation in a diverse cultural setting. We investigate the ex... | [
12424,
23559,
13495
] | Validation |
26,844 | 16 | Title: Multi Modal Facial Expression Recognition with Transformer-Based Fusion Networks and Dynamic Sampling
Abstract: Facial expression recognition is an essential task for various applications, including emotion detection, mental health analysis, and human-machine interactions. In this paper, we propose a multi-modal... | [
23627,
32166
] | Train |
26,845 | 16 | Title: Towards Robust Prompts on Vision-Language Models
Abstract: With the advent of vision-language models (VLMs) that can perform in-context and prompt-based learning, how can we design prompting approaches that robustly generalize to distribution shift and can be used on novel classes outside the support set of the ... | [
6393,
24083,
28729
] | Train |
26,846 | 15 | Title: eFAT: Improving the Effectiveness of Fault-Aware Training for Mitigating Permanent Faults in DNN Hardware Accelerators
Abstract: Fault-Aware Training (FAT) has emerged as a highly effective technique for addressing permanent faults in DNN accelerators, as it offers fault mitigation without significant performanc... | [] | Train |
26,847 | 10 | Title: InfeRE: Step-by-Step Regex Generation via Chain of Inference
Abstract: Automatically generating regular expressions (abbrev. regexes) from natural language description (NL2RE) has been an emerging research area. Prior studies treat regex as a linear sequence of tokens and generate the final expressions autoregre... | [
19250
] | Train |
26,848 | 16 | Title: LightGlue: Local Feature Matching at Light Speed
Abstract: We introduce LightGlue, a deep neural network that learns to match local features across images. We revisit multiple design decisions of SuperGlue, the state of the art in sparse matching, and derive simple but effective improvements. Cumulatively, they ... | [
19738,
42522
] | Train |
26,849 | 24 | Title: ADRMX: Additive Disentanglement of Domain Features with Remix Loss
Abstract: The common assumption that train and test sets follow similar distributions is often violated in deployment settings. Given multiple source domains, domain generalization aims to create robust models capable of generalizing to new unsee... | [] | Train |
26,850 | 4 | Title: SPGNN-API: A Transferable Graph Neural Network for Attack Paths Identification and Autonomous Mitigation
Abstract: Attack paths are the potential chain of malicious activities an attacker performs to compromise network assets and acquire privileges through exploiting network vulnerabilities. Attack path analysis... | [] | Train |
26,851 | 16 | Title: Out-of-Distribution Detection for Monocular Depth Estimation
Abstract: In monocular depth estimation, uncertainty estimation approaches mainly target the data uncertainty introduced by image noise. In contrast to prior work, we address the uncertainty due to lack of knowledge, which is relevant for the detection... | [] | Test |
26,852 | 6 | Title: An EEG-based Experiment on VR Sickness and Postural Instability While Walking in Virtual Environments
Abstract: Previous studies showed that natural walking reduces the susceptibility to VR sickness. However, many users still experience VR sickness when wearing VR headsets that allow free walking in room-scale s... | [
8005
] | Train |
26,853 | 31 | Title: Adversarial Learning Data Augmentation for Graph Contrastive Learning in Recommendation
Abstract: Recently, Graph Neural Networks (GNNs) achieve remarkable success in Recommendation. To reduce the influence of data sparsity, Graph Contrastive Learning (GCL) is adopted in GNN-based CF methods for enhancing perfor... | [
31124
] | Validation |
26,854 | 16 | Title: Inst-Inpaint: Instructing to Remove Objects with Diffusion Models
Abstract: Image inpainting task refers to erasing unwanted pixels from images and filling them in a semantically consistent and realistic way. Traditionally, the pixels that are wished to be erased are defined with binary masks. From the applicati... | [
17968,
21324,
34239
] | Validation |
26,855 | 24 | Title: MixupExplainer: Generalizing Explanations for Graph Neural Networks with Data Augmentation
Abstract: Graph Neural Networks (GNNs) have received increasing attention due to their ability to learn from graph-structured data. However, their predictions are often not interpretable. Post-hoc instance-level explanatio... | [] | Train |
26,856 | 2 | Title: Soundness and Completeness of a Model-Checking Proof System for CTL
Abstract: We propose a local model-checking proof system for a fragment of CTL. The rules of the proof system are motivated by the well-known fixed-point characterisation of CTL based on unfolding of the temporal operators. To guarantee terminat... | [] | Test |
26,857 | 30 | Title: Boosting Norwegian Automatic Speech Recognition
Abstract: In this paper, we present several baselines for automatic speech recognition (ASR) models for the two official written languages in Norway: Bokmål and Nynorsk. We compare the performance of models of varying sizes and pre-training approaches on multiple N... | [] | Train |
26,858 | 24 | Title: Evaluation of Convolution Primitives for Embedded Neural Networks on 32-bit Microcontrollers
Abstract: Deploying neural networks on constrained hardware platforms such as 32-bit microcontrollers is a challenging task because of the large memory, computing and energy requirements of their inference process. To ta... | [] | Test |
26,859 | 8 | Title: Data Availability Sampling in Ethereum: Analysis of P2P Networking Requirements
Abstract: Despite their increasing popularity, blockchains still suffer from severe scalability limitations. Recently, Ethereum proposed a novel approach to block validation based on Data Availability Sampling (DAS), that has the pot... | [] | Train |
26,860 | 27 | Title: Simulating the Integration of Urban Air Mobility into Existing Transportation Systems: A Survey
Abstract: Urban air mobility (UAM) has the potential to revolutionize transportation in metropolitan areas, providing a new mode of transportation that could alleviate congestion and improve accessibility. However, th... | [] | Train |
26,861 | 7 | Title: A deep transfer learning network for structural condition identification with limited real-world training data
Abstract: Structural condition identification based on monitoring data is important for automatic civil infrastructure asset management. Nevertheless, the monitoring data are almost always insufficient ... | [] | Test |
26,862 | 2 | Title: Process Algebra with Imperfect Actions
Abstract: We discuss the deal of imperfectness of atomic actions in reality with the background of process algebras. And we show the applications of the imperfect actions in verification of computational systems. | [] | Train |
26,863 | 24 | Title: A Survey on Multi-Objective based Parameter Optimization for Deep Learning
Abstract: Deep learning models form one of the most powerful machine learning models for the extraction of important features. Most of the designs of deep neural models, i.e., the initialization of parameters, are still manually tuned. He... | [] | Test |
26,864 | 3 | Title: Navigating Surveillance Capitalism: A Critical Analysis through philosophical perspectives in Computer Ethics
Abstract: Surveillance capitalism is a concept that describes the practice of collecting and analyzing massive amounts of user data for the purpose of targeted advertising and other forms of monetization... | [] | Train |
26,865 | 24 | Title: Deep Generative Imputation Model for Missing Not At Random Data
Abstract: Data analysis usually suffers from the Missing Not At Random (MNAR) problem, where the cause of the value missing is not fully observed. Compared to the naive Missing Completely At Random (MCAR) problem, it is more in line with the realist... | [] | Test |
26,866 | 16 | Title: Improving Diffusion-based Image Translation using Asymmetric Gradient Guidance
Abstract: Diffusion models have shown significant progress in image translation tasks recently. However, due to their stochastic nature, there's often a trade-off between style transformation and content preservation. Current strategi... | [
3690,
8308,
7390,
46135
] | Validation |
26,867 | 36 | Title: Partial Allocations in Budget-Feasible Mechanism Design: Bridging Multiple Levels of Service and Divisible Agents
Abstract: Budget-feasible procurement has been a major paradigm in mechanism design since its introduction by Singer (2010). An auctioneer (buyer) with a strict budget constraint is interested in buy... | [] | Train |
26,868 | 30 | Title: MaScQA: A Question Answering Dataset for Investigating Materials Science Knowledge of Large Language Models
Abstract: Information extraction and textual comprehension from materials literature are vital for developing an exhaustive knowledge base that enables accelerated materials discovery. Language models have... | [
13345,
13700,
17517,
43641,
23866
] | Test |
26,869 | 16 | Title: Minimalist and High-Quality Panoramic Imaging with PSF-aware Transformers
Abstract: High-quality panoramic images with a Field of View (FoV) of 360-degree are essential for contemporary panoramic computer vision tasks. However, conventional imaging systems come with sophisticated lens designs and heavy optical c... | [
20083,
33722,
18883
] | Train |
26,870 | 23 | Title: Understanding Container-based Services under Software Aging: Dependability and Performance Views
Abstract: Container technology, as the key enabler behind microservice architectures, is widely applied in Cloud and Edge Computing. A long and continuous running of operating system (OS) host-ing container-based ser... | [] | Train |
26,871 | 16 | Title: TBFormer: Two-Branch Transformer for Image Forgery Localization
Abstract: Image forgery localization aims to identify forged regions by capturing subtle traces from high-quality discriminative features. In this paper, we propose a Transformer-style network with two feature extraction branches for image forgery l... | [] | Train |
26,872 | 26 | Title: Prompt-Based Zero- and Few-Shot Node Classification: A Multimodal Approach
Abstract: Multimodal data empowers machine learning models to better understand the world from various perspectives. In this work, we study the combination of \emph{text and graph} modalities, a challenging but understudied combination wh... | [] | Test |
26,873 | 16 | Title: Boosting Visual-Language Models by Exploiting Hard Samples
Abstract: Large vision and language models, such as Contrastive Language-Image Pre-training (CLIP), are rapidly becoming the industry norm for matching images and texts. In order to improve its zero-shot recognition performance, current research either a... | [
1581,
7422
] | Train |
26,874 | 24 | Title: Best of Both Worlds Policy Optimization
Abstract: Policy optimization methods are popular reinforcement learning algorithms in practice. Recent works have built theoretical foundation for them by proving $\sqrt{T}$ regret bounds even when the losses are adversarial. Such bounds are tight in the worst case but of... | [] | Test |
26,875 | 16 | Title: Multi-source adversarial transfer learning based on similar source domains with local features
Abstract: Transfer learning leverages knowledge from other domains and has been successful in many applications. Transfer learning methods rely on the overall similarity of the source and target domains. However, in so... | [] | Train |
26,876 | 16 | Title: Factored-NeuS: Reconstructing Surfaces, Illumination, and Materials of Possibly Glossy Objects
Abstract: We develop a method that recovers the surface, materials, and illumination of a scene from its posed multi-view images. In contrast to prior work, it does not require any additional data and can handle glossy... | [
11874,
33187,
39012,
39653,
12078,
13232,
40503,
9599
] | Train |
26,877 | 18 | Title: A New Paradigm of Reservoir Computing Exploiting Hydrodynamics
Abstract: Nonlinear waves have played a significant role in the development of the science of complexity throughout history. More recently, they have also contributed to the emergence of a novel paradigm in reservoir computing called neuromorphic com... | [] | Train |
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