node_id int64 0 76.9k | label int64 0 39 | text stringlengths 13 124k | neighbors listlengths 0 3.32k | mask stringclasses 4
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|---|---|---|---|---|
17,778 | 24 | Title: Single-model uncertainty quantification in neural network potentials does not consistently outperform model ensembles
Abstract: Neural networks (NNs) often assign high confidence to their predictions, even for points far out-of-distribution, making uncertainty quantification (UQ) a challenge. When they are emplo... | [] | Train |
17,779 | 30 | Title: Memory Augmented Lookup Dictionary based Language Modeling for Automatic Speech Recognition
Abstract: Recent studies have shown that using an external Language Model (LM) benefits the end-to-end Automatic Speech Recognition (ASR). However, predicting tokens that appear less frequently in the training set is stil... | [] | Test |
17,780 | 24 | Title: FairAdaBN: Mitigating unfairness with adaptive batch normalization and its application to dermatological disease classification
Abstract: Deep learning is becoming increasingly ubiquitous in medical research and applications while involving sensitive information and even critical diagnosis decisions. Researchers... | [
3029
] | Train |
17,781 | 30 | Title: CommonAccent: Exploring Large Acoustic Pretrained Models for Accent Classification Based on Common Voice
Abstract: Despite the recent advancements in Automatic Speech Recognition (ASR), the recognition of accented speech still remains a dominant problem. In order to create more inclusive ASR systems, research ha... | [] | Test |
17,782 | 28 | Title: New Results for the Pointing Errors Model in Two Asymptotic Cases
Abstract: Several precise and computationally efficient results for pointing errors models in two asymptotic cases are derived in this paper. The normalized mean-squared error (NMSE) performance metric is employed to quantify the accuracy of diffe... | [] | Train |
17,783 | 24 | Title: Local Message Passing on Frustrated Systems
Abstract: Message passing on factor graphs is a powerful framework for probabilistic inference, which finds important applications in various scientific domains. The most wide-spread message passing scheme is the sum-product algorithm (SPA) which gives exact results on... | [] | Validation |
17,784 | 2 | Title: Symbolic Analysis and Parameter Synthesis for Time Petri Nets Using Maude and SMT Solving
Abstract: Parametric time Petri nets with inhibitor arcs (PITPNs) support flexibility for timed systems by allowing parameters in firing bounds. In this paper we present and prove correct a concrete and a symbolic rewriting... | [] | Train |
17,785 | 24 | Title: A general Markov decision process formalism for action-state entropy-regularized reward maximization
Abstract: Previous work has separately addressed different forms of action, state and action-state entropy regularization, pure exploration and space occupation. These problems have become extremely relevant for ... | [] | Train |
17,786 | 24 | Title: Adaptive Aggregation for Safety-Critical Control
Abstract: Safety has been recognized as the central obstacle to preventing the use of reinforcement learning (RL) for real-world applications. Different methods have been developed to deal with safety concerns in RL. However, learning reliable RL-based solutions u... | [] | Validation |
17,787 | 10 | Title: Real-Time Network-Level Traffic Signal Control: An Explicit Multiagent Coordination Method
Abstract: Efficient traffic signal control (TSC) has been one of the most useful ways for reducing urban road congestion. Key to the challenge of TSC includes 1) the essential of real-time signal decision, 2) the complexit... | [] | Train |
17,788 | 16 | Title: Dense Multitask Learning to Reconfigure Comics
Abstract: In this paper, we develop a MultiTask Learning (MTL) model to achieve dense predictions for comics panels to, in turn, facilitate the transfer of comics from one publication channel to another by assisting authors in the task of reconfiguring their narrati... | [] | Test |
17,789 | 30 | Title: Self-Refine: Iterative Refinement with Self-Feedback
Abstract: Like humans, large language models (LLMs) do not always generate the best output on their first try. Motivated by how humans refine their written text, we introduce Self-Refine, an approach for improving initial outputs from LLMs through iterative fe... | [
514,
27138,
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19472,
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26210,
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3181,
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23159,
43641,
12411,
34953,
34956,
17040,
30366,
40610,
15527,
7339,
39602,
5816,
... | Validation |
17,790 | 24 | Title: Machine Learning Methods for Cancer Classification Using Gene Expression Data: A Review
Abstract: Cancer is a term that denotes a group of diseases caused by the abnormal growth of cells that can spread in different parts of the body. According to the World Health Organization (WHO), cancer is the second major c... | [] | Test |
17,791 | 3 | Title: Digital Engineering Transformation with Trustworthy AI towards Industry 4.0: Emerging Paradigm Shifts
Abstract: Digital engineering transformation is a crucial process for the engineering paradigm shifts in the fourth industrial revolution (4IR), and artificial intelligence (AI) is a critical enabling technology... | [] | Train |
17,792 | 24 | Title: Classification-Aware Neural Topic Model Combined With Interpretable Analysis - For Conflict Classification
Abstract: A large number of conflict events are affecting the world all the time. In order to analyse such conflict events effectively, this paper presents a Classification-Aware Neural Topic Model (CANTM-I... | [] | Train |
17,793 | 16 | Title: RidgeBase: A Cross-Sensor Multi-Finger Contactless Fingerprint Dataset
Abstract: Contactless fingerprint matching using smartphone cameras can alleviate major challenges of traditional fingerprint systems including hygienic acquisition, portability and presentation attacks. However, development of practical and ... | [
34033
] | Train |
17,794 | 16 | Title: Semantic Counting from Self-Collages
Abstract: While recent supervised methods for reference-based object counting continue to improve the performance on benchmark datasets, they have to rely on small datasets due to the cost associated with manually annotating dozens of objects in images. We propose Unsupervise... | [
4643
] | Train |
17,795 | 27 | Title: REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction
Abstract: The ability to detect and analyze failed executions automatically is crucial for an explainable and robust robotic system. Recently, Large Language Models (LLMs) have demonstrated strong reasoning abilities on textual inputs.... | [
10624,
13700,
19492,
13510,
7657,
11658,
20169
] | Validation |
17,796 | 24 | Title: Provable Data Subset Selection For Efficient Neural Network Training
Abstract: Radial basis function neural networks (\emph{RBFNN}) are {well-known} for their capability to approximate any continuous function on a closed bounded set with arbitrary precision given enough hidden neurons. In this paper, we introduc... | [
17475,
11435,
23874
] | Test |
17,797 | 4 | Title: A Comparative Analysis on Volatility and Scalability Properties of Blockchain Compression Protocols
Abstract: Increasing popularity of trading digital assets can lead to significant delays in Blockchain networks when processing transactions. When transaction fees become miners' primary revenue, an imbalance in r... | [] | Validation |
17,798 | 36 | Title: Strategy-proof Budgeting via a VCG-like Mechanism
Abstract: We present a strategy-proof public goods budgeting mechanism where agents determine both the total volume of expanses and the specific allocation. It is constructed as a modification of VCG to a less typical environment, namely where we do not assume qu... | [] | Validation |
17,799 | 5 | Title: WHYPE: A Scale-Out Architecture With Wireless Over-the-Air Majority for Scalable In-Memory Hyperdimensional Computing
Abstract: Hyperdimensional computing (HDC) is an emerging computing paradigm that represents, manipulates, and communicates data using long random vectors known as hypervectors. Among different h... | [
636
] | Train |
17,800 | 4 | Title: DiSPEL: Distributed Security Policy Enforcement for Bus-based SoC
Abstract: The current zero trust model adopted in System-on-Chip (SoC) design is vulnerable to various malicious entities, and modern SoC designs must incorporate various security policies to protect sensitive assets from unauthorized access. Thes... | [
44381
] | Test |
17,801 | 30 | Title: PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Abstract: In recent years, the transition to cloud-based platforms in the IT sector has emphasized the significance of cloud incident root cause analysis to ensure service reliability and mai... | [
9184,
12896,
8677,
38697,
44176,
24760,
37947,
28862
] | Validation |
17,802 | 24 | Title: A review of clustering models in educational data science towards fairness-aware learning
Abstract: nan | [] | Train |
17,803 | 16 | Title: OnlineRefer: A Simple Online Baseline for Referring Video Object Segmentation
Abstract: Referring video object segmentation (RVOS) aims at segmenting an object in a video following human instruction. Current state-of-the-art methods fall into an offline pattern, in which each clip independently interacts with te... | [
32674,
34532,
25222,
5143
] | Test |
17,804 | 23 | Title: CBIM: object-level cloud collaboration platform for supporting across-domain asynchronous design
Abstract: The conventional approach of designing BIM projects requires packaging of building information as files to exchange designs. This study develops a series of components to implement a previously established ... | [
27989
] | Train |
17,805 | 30 | Title: Turning Flowchart into Dialog: Plan-based Data Augmentation for Low-Resource Flowchart-grounded Troubleshooting Dialogs
Abstract: Flowchart-grounded troubleshooting dialogue (FTD) systems, which follow the instructions of a flowchart to diagnose users' problems in specific domains (eg., vehicle, laptop), have be... | [] | Train |
17,806 | 24 | Title: Unimodal Distributions for Ordinal Regression
Abstract: In many real-world prediction tasks, class labels contain information about the relative order between labels that are not captured by commonly used loss functions such as multicategory cross-entropy. Recently, the preference for unimodal distributions in t... | [] | Train |
17,807 | 13 | Title: Understanding and Improving Optimization in Predictive Coding Networks
Abstract: Backpropagation (BP), the standard learning algorithm for artificial neural networks, is often considered biologically implausible. In contrast, the standard learning algorithm for predictive coding (PC) models in neuroscience, know... | [] | Train |
17,808 | 24 | Title: Transferable Adversarial Robustness for Categorical Data via Universal Robust Embeddings
Abstract: Research on adversarial robustness is primarily focused on image and text data. Yet, many scenarios in which lack of robustness can result in serious risks, such as fraud detection, medical diagnosis, or recommende... | [] | Train |
17,809 | 4 | Title: Adversarial Evasion Attacks Practicality in Networks: Testing the Impact of Dynamic Learning
Abstract: Machine Learning (ML) has become ubiquitous, and its deployment in Network Intrusion Detection Systems (NIDS) is inevitable due to its automated nature and high accuracy in processing and classifying large volu... | [] | Train |
17,810 | 31 | Title: A Lightweight Method for Modeling Confidence in Recommendations with Learned Beta Distributions
Abstract: Most recommender systems (RecSys) do not provide an indication of confidence in their decisions. Therefore, they do not distinguish between recommendations of which they are certain, and those where they are... | [] | Train |
17,811 | 16 | Title: CIFF-Net: Contextual Image Feature Fusion for Melanoma Diagnosis
Abstract: Melanoma is considered to be the deadliest variant of skin cancer causing around 75\% of total skin cancer deaths. To diagnose Melanoma, clinicians assess and compare multiple skin lesions of the same patient concurrently to gather contex... | [] | Train |
17,812 | 16 | Title: Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transforms
Abstract: By integrating the self-attention capability and the biological properties of Spiking Neural Networks (SNNs), Spikformer applies the flourishing Transformer architecture to SNNs design. It introduces a Spiking Self-Attentio... | [
39312,
13962,
43109
] | Train |
17,813 | 24 | Title: Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction
Abstract: Despite impressive performance on a wide variety of tasks, deep neural networks require significant memory and computation costs, prohibiting their application in resource-constrained scenarios. Sparse training is one of ... | [
28090,
24391
] | Test |
17,814 | 28 | Title: Codes Correcting a Single Long Duplication Error
Abstract: We consider the problem of constructing a code capable of correcting a single long tandem duplication error of variable length. As the main contribution of this paper, we present an efficiently encodable code of length n + 1 and redundancy 1 that can cor... | [] | Train |
17,815 | 30 | Title: Exploring Chain-of-Thought Style Prompting for Text-to-SQL
Abstract: Conventional supervised approaches for text-to-SQL parsing often require large amounts of annotated data, which is costly to obtain in practice. Recently, in-context learning with large language models (LLMs) has caught increasing attention due... | [
24948,
39773,
1326,
4351
] | Train |
17,816 | 31 | Title: Pareto Invariant Representation Learning for Multimedia Recommendation
Abstract: Multimedia recommendation involves personalized ranking tasks, where multimedia content is usually represented using a generic encoder. However, these generic representations introduce spurious correlations that fail to reveal users... | [
1434,
1059,
36660,
27018
] | Validation |
17,817 | 24 | Title: Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback
Abstract: Exploration and reward specification are fundamental and intertwined challenges for reinforcement learning. Solving sequential decision-making tasks requiring expansive exploration requires either careful design of re... | [] | Validation |
17,818 | 30 | Title: Inter-connection: Effective Connection between Pre-trained Encoder and Decoder for Speech Translation
Abstract: In end-to-end speech translation, speech and text pre-trained models improve translation quality. Recently proposed models simply connect the pre-trained models of speech and text as encoder and decode... | [
16873
] | Train |
17,819 | 16 | Title: Building Coverage Estimation with Low-resolution Remote Sensing Imagery
Abstract: Building coverage statistics provide crucial insights into the urbanization, infrastructure, and poverty level of a region, facilitating efforts towards alleviating poverty, building sustainable cities, and allocating infrastructur... | [] | Train |
17,820 | 24 | Title: Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
Abstract: The explicit incorporation of task-specific inductive biases through symmetry has emerged as a general design precept in the development of high-performance machine learning models. For example, group equivariant neural netw... | [
20543
] | Validation |
17,821 | 27 | Title: Towards Discovering Erratic Behavior in Robotic Process Automation with Statistical Process Control
Abstract: Companies that use robotic process automation very often deal with problems maintaining the bots in their RPA portfolio. Current key performance indicators do not track the behavior of RPA bots or proces... | [] | Train |
17,822 | 24 | Title: Encoder-Decoder Networks for Self-Supervised Pretraining and Downstream Signal Bandwidth Regression on Digital Antenna Arrays
Abstract: This work presents the first applications of self-supervised learning applied to data from digital antenna arrays. Encoder-decoder networks are pretrained on digital array data ... | [] | Train |
17,823 | 24 | Title: Fair Column Subset Selection
Abstract: We consider the problem of fair column subset selection. In particular, we assume that two groups are present in the data, and the chosen column subset must provide a good approximation for both, relative to their respective best rank-k approximations. We show that this fai... | [] | Test |
17,824 | 7 | Title: Boundary integrated neural networks (BINNs) for 2D elastostatic and piezoelectric problems: Theory and MATLAB code
Abstract: In this paper, we make the first attempt to apply the boundary integrated neural networks (BINNs) for the numerical solution of two-dimensional (2D) elastostatic and piezoelectric problems... | [] | Train |
17,825 | 31 | Title: Compressed Interaction Graph based Framework for Multi-behavior Recommendation
Abstract: Multi-types of user behavior data (e.g., clicking, adding to cart, and purchasing) are recorded in most real-world recommendation scenarios, which can help to learn users’ multi-faceted preferences. However, it is challengin... | [
17731,
13475
] | Test |
17,826 | 16 | Title: Customizing Synthetic Data for Data-Free Student Learning
Abstract: Data-free knowledge distillation (DFKD) aims to obtain a lightweight student model without original training data. Existing works generally synthesize data from the pretrained teacher model to replace the original training data for student learn... | [
22921
] | Train |
17,827 | 7 | Title: Solving the Discretised Boltzmann Transport Equations using Neural Networks: Applications in Neutron Transport
Abstract: In this paper we solve the Boltzmann transport equation using AI libraries. The reason why this is attractive is because it enables one to use the highly optimised software within AI libraries... | [
28969
] | Train |
17,828 | 24 | Title: Sy-CON: Symmetric Contrastive Loss for Continual Self-Supervised Representation Learning
Abstract: We introduce a novel and general loss function, called Symmetric Contrastive (Sy-CON) loss, for effective continual self-supervised learning (CSSL). We first argue that the conventional loss form of continual learn... | [
10783
] | Test |
17,829 | 24 | Title: Graph-based Knowledge Distillation: A survey and experimental evaluation
Abstract: Graph, such as citation networks, social networks, and transportation networks, are prevalent in the real world. Graph Neural Networks (GNNs) have gained widespread attention for their robust expressiveness and exceptional perform... | [] | Train |
17,830 | 23 | Title: Prism: Revealing Hidden Functional Clusters from Massive Instances in Cloud Systems
Abstract: Ensuring the reliability of cloud systems is critical for both cloud vendors and customers. Cloud systems often rely on virtualization techniques to create instances of hardware resources, such as virtual machines. Howe... | [
11112
] | Train |
17,831 | 23 | Title: Architecture Smells vs. Concurrency Bugs: an Exploratory Study and Negative Results
Abstract: Technical debt occurs in many different forms across software artifacts. One such form is connected to software architectures where debt emerges in the form of structural anti-patterns across architecture elements, name... | [] | Train |
17,832 | 6 | Title: Design Patterns for Situated Visualization in Augmented Reality
Abstract: Situated visualization has become an increasingly popular research area in the visualization community, fueled by advancements in augmented reality (AR) technology and immersive analytics. Visualizing data in spatial proximity to their phy... | [
2995,
18975
] | Test |
17,833 | 23 | Title: A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms
Abstract: The accuracy reported for code smell-detecting tools varies depending on the dataset used to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a dataset for detecting smells highly dep... | [
21303
] | Train |
17,834 | 6 | Title: Vis-SPLIT: Interactive Hierarchical Modeling for mRNA Expression Classification
Abstract: We propose an interactive visual analytics tool, Vis-SPLIT, for partitioning a population of individuals into groups with similar gene signatures. Vis-SPLIT allows users to interactively explore a dataset and exploit visual... | [] | Test |
17,835 | 30 | Title: Generating High-Quality Emotion Arcs For Low-Resource Languages Using Emotion Lexicons
Abstract: Automatically generated emotion arcs -- that capture how an individual or a population feels over time -- are widely used in industry and research. However, there is little work on evaluating the generated arcs in En... | [
24954,
31133
] | Train |
17,836 | 28 | Title: Optimizing Reconfigurable Intelligent Surfaces for Small Data Packets: A Subarray Approach
Abstract: In this paper, we examine the energy consumption of a user equipment (UE) when it transmits a finite-sized data packet. The receiving base station (BS) controls a reconfigurable intelligent surface (RIS) that can... | [
28906
] | Train |
17,837 | 30 | Title: Improved Compositional Generalization by Generating Demonstrations for Meta-Learning
Abstract: Meta-learning and few-shot prompting are viable methods to induce certain types of compositional behaviour. However, these methods can be very sensitive to the choice of support examples used. Choosing good supports fr... | [] | Train |
17,838 | 16 | Title: Preventing Dimensional Collapse of Incomplete Multi-View Clustering via Direct Contrastive Learning
Abstract: Incomplete multi-view clustering (IMVC) is an unsupervised approach, among which IMVC via contrastive learning has received attention due to its excellent performance. The previous methods have the follo... | [] | Validation |
17,839 | 16 | Title: FlowText: Synthesizing Realistic Scene Text Video with Optical Flow Estimation
Abstract: Current video text spotting methods can achieve preferable performance, powered with sufficient labeled training data. However, labeling data manually is time-consuming and labor-intensive. To overcome this, using low-cost s... | [
945,
12177,
30922,
42221
] | Test |
17,840 | 24 | Title: Conservative Prediction via Data-Driven Confidence Minimization
Abstract: Errors of machine learning models are costly, especially in safety-critical domains such as healthcare, where such mistakes can prevent the deployment of machine learning altogether. In these settings, conservative models -- models which c... | [
947
] | Train |
17,841 | 2 | Title: Completeness Thresholds for Memory Safety of Array Traversing Programs
Abstract: We report on intermediate results of -- to the best of our knowledge -- the first study of completeness thresholds for (partially) bounded memory safety proofs. Specifically, we consider heap-manipulating programs that iterate over ... | [] | Train |
17,842 | 30 | Title: Self-supervised Meta-Prompt Learning with Meta-Gradient Regularization for Few-shot Generalization
Abstract: Prompt tuning is a parameter-efficient method, which learns soft prompts and conditions frozen language models to perform specific downstream tasks. Though effective, prompt tuning under few-shot settings... | [] | Validation |
17,843 | 24 | Title: On the Joint Interaction of Models, Data, and Features
Abstract: Learning features from data is one of the defining characteristics of deep learning, but our theoretical understanding of the role features play in deep learning is still rudimentary. To address this gap, we introduce a new tool, the interaction te... | [] | Test |
17,844 | 22 | Title: Data accounting and error counting
Abstract: Can we infer sources of errors from outputs of the complex data analytics software? Bidirectional programming promises that we can reverse flow of software, and translate corrections of output into corrections of either input or data analysis. This allows us to achiev... | [] | Train |
17,845 | 24 | Title: A hybrid machine learning framework for clad characteristics prediction in metal additive manufacturing
Abstract: During the past decade, metal additive manufacturing (MAM) has experienced significant developments and gained much attention due to its ability to fabricate complex parts, manufacture products with ... | [
41457,
20298
] | Validation |
17,846 | 25 | Title: Pre-Training Strategies Using Contrastive Learning and Playlist Information for Music Classification and Similarity
Abstract: In this work, we investigate an approach that relies on contrastive learning and music metadata as a weak source of supervision to train music representation models. Recent studies show t... | [] | Validation |
17,847 | 27 | Title: Rearrangement Planning for General Part Assembly
Abstract: Most successes in autonomous robotic assembly have been restricted to single target or category. We propose to investigate general part assembly, the task of creating novel target assemblies with unseen part shapes. As a fundamental step to a general par... | [] | Train |
17,848 | 28 | Title: Eigenvector prediction-based precoding for massive MIMO with mobility
Abstract: Eigenvector decomposition (EVD) is an inevitable operation to obtain the precoders in practical massive multiple-input multiple-output (MIMO) systems. Due to the large antenna size and at finite computation resources at the base stat... | [] | Train |
17,849 | 27 | Title: Balanced Line Coverage in Large-scale Urban Scene
Abstract: Line coverage is to cover linear infrastructure modeled as 1D segments by robots, which received attention in recent years. With the increasing urbanization, the area of the city and the density of infrastructure continues to increase, which brings two ... | [
38809,
19735
] | Test |
17,850 | 30 | Title: Exploring Linguistic Similarity and Zero-Shot Learning for Multilingual Translation of Dravidian Languages
Abstract: Current research in zero-shot translation is plagued by several issues such as high compute requirements, increased training time and off target translations. Proposed remedies often come at the c... | [] | Train |
17,851 | 16 | Title: Robust Classification via a Single Diffusion Model
Abstract: Recently, diffusion models have been successfully applied to improving adversarial robustness of image classifiers by purifying the adversarial noises or generating realistic data for adversarial training. However, the diffusion-based purification can ... | [
33414,
3015,
8234,
26517,
45080
] | Train |
17,852 | 10 | Title: Completeness, Recall, and Negation in Open-World Knowledge Bases: A Survey
Abstract: General-purpose knowledge bases (KBs) are a cornerstone of knowledge-centric AI. Many of them are constructed pragmatically from Web sources, and are thus far from complete. This poses challenges for the consumption as well as t... | [] | Validation |
17,853 | 5 | Title: Automated Translation and Accelerated Solving of Differential Equations on Multiple GPU Platforms
Abstract: We demonstrate a high-performance vendor-agnostic method for massively parallel solving of ensembles of ordinary differential equations (ODEs) and stochastic differential equations (SDEs) on GPUs. The meth... | [] | Train |
17,854 | 24 | Title: Spectral Clustering on Large Datasets: When Does it Work? Theory from Continuous Clustering and Density Cheeger-Buser
Abstract: Spectral clustering is one of the most popular clustering algorithms that has stood the test of time. It is simple to describe, can be implemented using standard linear algebra, and oft... | [] | Train |
17,855 | 4 | Title: Oracle Counterpoint: Relationships between On-chain and Off-chain Market Data
Abstract: We investigate the theoretical and empirical relationships between activity in on-chain markets and pricing in off-chain cryptocurrency markets (e.g., ETH/USD prices). The motivation is to develop methods for proxying off-cha... | [] | Train |
17,856 | 36 | Title: Are Equivariant Equilibrium Approximators Beneficial?
Abstract: Recently, remarkable progress has been made by approximating Nash equilibrium (NE), correlated equilibrium (CE), and coarse correlated equilibrium (CCE) through function approximation that trains a neural network to predict equilibria from game repr... | [
7945
] | Train |
17,857 | 24 | Title: A Generative Adversarial Network for Climate Tipping Point Discovery (TIP-GAN)
Abstract: We propose a new Tipping Point Generative Adversarial Network (TIP-GAN) for better characterizing potential climate tipping points in Earth system models. We describe an adversarial game to explore the parameter space of the... | [
11681,
34149,
42871
] | Validation |
17,858 | 34 | Title: Efficient Temporal Butterfly Counting and Enumeration on Temporal Bipartite Graphs
Abstract: Bipartite graphs model relationships between two different sets of entities, like actor-movie, user-item, and author-paper. The butterfly, a 4-vertices 4-edges $2\times 2$ bi-clique, is the simplest cohesive motif in a b... | [] | Train |
17,859 | 30 | Title: Beyond Arabic: Software for Perso-Arabic Script Manipulation
Abstract: This paper presents an open-source software library that provides a set of finite-state transducer (FST) components and corresponding utilities for manipulating the writing systems of languages that use the Perso-Arabic script. The operations... | [
38904,
1841
] | Train |
17,860 | 16 | Title: From Classification to Segmentation with Explainable AI: A Study on Crack Detection and Growth Monitoring
Abstract: Monitoring surface cracks in infrastructure is crucial for structural health monitoring. Automatic visual inspection offers an effective solution, especially in hard-to-reach areas. Machine learnin... | [] | Train |
17,861 | 24 | Title: A Tutorial Introduction to Reinforcement Learning
Abstract: In this paper, we present a brief survey of Reinforcement Learning (RL), with particular emphasis on Stochastic Approximation (SA) as a unifying theme. The scope of the paper includes Markov Reward Processes, Markov Decision Processes, Stochastic Approx... | [] | Validation |
17,862 | 16 | Title: Instructive Feature Enhancement for Dichotomous Medical Image Segmentation
Abstract: Deep neural networks have been widely applied in dichotomous medical image segmentation (DMIS) of many anatomical structures in several modalities, achieving promising performance. However, existing networks tend to struggle wit... | [] | Train |
17,863 | 24 | Title: Linking data separation, visual separation, and classifier performance using pseudo-labeling by contrastive learning
Abstract: Lacking supervised data is an issue while training deep neural networks (DNNs), mainly when considering medical and biological data where supervision is expensive. Recently, Embedded Pse... | [] | Train |
17,864 | 10 | Title: Machine Learning Approaches in Agile Manufacturing with Recycled Materials for Sustainability
Abstract: It is important to develop sustainable processes in materials science and manufacturing that are environmentally friendly. AI can play a significant role in decision support here as evident from our earlier re... | [] | Train |
17,865 | 22 | Title: Towards a Scalable Proof Engine: A Performant Prototype Rewriting Primitive for Coq
Abstract: We address the challenges of scaling verification efforts to match the increasing complexity and size of systems. We propose a research agenda aimed at building a performant proof engine by studying the asymptotic perfo... | [] | Validation |
17,866 | 16 | Title: Analysis of Sampling Strategies for Implicit 3D Reconstruction
Abstract: In the training process of the implicit 3D reconstruction network, the choice of spatial query points’ sampling strategy affects the final performance of the model. Different works have differences in the selection of sampling strategies, n... | [] | Train |
17,867 | 16 | Title: FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods
Abstract: The field of explainable artificial intelligence (XAI) aims to uncover the inner workings of complex deep neural models. While being crucial for safety-critical domains, XAI inherently lacks ground-truth explanat... | [] | Train |
17,868 | 16 | Title: 3D detection of roof sections from a single satellite image and application to LOD2-building reconstruction
Abstract: Reconstructing urban areas in 3D out of satellite raster images has been a long-standing and challenging goal of both academical and industrial research. The rare methods today achieving this obj... | [] | Validation |
17,869 | 16 | Title: Neural Network Training Strategy to Enhance Anomaly Detection Performance: A Perspective on Reconstruction Loss Amplification
Abstract: Unsupervised anomaly detection (UAD) is a widely adopted approach in industry due to rare anomaly occurrences and data imbalance. A desirable characteristic of an UAD model is c... | [
45938
] | Train |
17,870 | 26 | Title: Operationalizing content moderation "accuracy" in the Digital Services Act
Abstract: The Digital Services Act, recently adopted by the EU, requires social media platforms to report the ``accuracy'' of their automated content moderation systems. The colloquial term is vague, or open-textured -- on what data and g... | [] | Test |
17,871 | 16 | Title: CFI2P: Coarse-to-Fine Cross-Modal Correspondence Learning for Image-to-Point Cloud Registration
Abstract: In the context of image-to-point cloud registration, acquiring point-to-pixel correspondences presents a challenging task since the similarity between individual points and pixels is ambiguous due to the vis... | [] | Test |
17,872 | 24 | Title: A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Abstract: In recent years, contrastive learning achieves impressive results on self-supervised visual representation learning, but there still lacks a rigorous understanding of its learning dynamics. In this paper, we show that if we cast... | [
7968,
44266
] | Train |
17,873 | 36 | Title: When Bidders Are DAOs
Abstract: In a typical decentralized autonomous organization (DAO), people organize themselves into a group that is programmatically managed. DAOs can act as bidders in auctions, with a DAO's bid treated by the auctioneer as if it had been submitted by an individual, without regard to the i... | [] | Train |
17,874 | 16 | Title: MRGAN360: Multi-stage Recurrent Generative Adversarial Network for 360 Degree Image Saliency Prediction
Abstract: Thanks to the ability of providing an immersive and interactive experience, the uptake of 360 degree image content has been rapidly growing in consumer and industrial applications. Compared to planar... | [] | Train |
17,875 | 30 | Title: GesGPT: Speech Gesture Synthesis With Text Parsing from GPT
Abstract: Gesture synthesis has gained significant attention as a critical research area, focusing on producing contextually appropriate and natural gestures corresponding to speech or textual input. Although deep learning-based approaches have achieved... | [
41699,
295,
7198,
826,
40702
] | Train |
17,876 | 10 | Title: The Chai Platform's AI Safety Framework
Abstract: Chai empowers users to create and interact with customized chatbots, offering unique and engaging experiences. Despite the exciting prospects, the work recognizes the inherent challenges of a commitment to modern safety standards. Therefore, this paper presents t... | [
32550,
32263,
43608,
10716,
46173
] | Validation |
17,877 | 24 | Title: Optimal Stochastic Non-smooth Non-convex Optimization through Online-to-Non-convex Conversion
Abstract: We present new algorithms for optimizing non-smooth, non-convex stochastic objectives based on a novel analysis technique. This improves the current best-known complexity for finding a $(\delta,\epsilon)$-stat... | [] | Train |
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