Split (1)

train · 203k rows

node_id int64 0 76.9k	label int64 0 39	text stringlengths 13 124k	neighbors listlengths 0 3.32k	mask stringclasses 4 values
16,878	30	Title: SEED-Bench: Benchmarking Multimodal LLMs with Generative Comprehension Abstract: Based on powerful Large Language Models (LLMs), recent generative Multimodal Large Language Models (MLLMs) have gained prominence as a pivotal research area, exhibiting remarkable capability for both comprehension and generation. In...	[ 10624, 13700, 5, 37765, 26380, 41104, 4251, 14126, 40883, 15413, 8509, 27454, 8903, 38858, 14923, 7384, 11745, 37987, 36966, 11628, 12527, 29559, 32247, 19578 ]	Test
16,879	27	Title: Design and Control of a Ballbot Drivetrain with High Agility, Minimal Footprint, and High Payload Abstract: This paper presents the design and control of a ballbot drivetrain that aims to achieve high agility, minimal footprint, and high payload capacity while maintaining dynamic stability. Two hardware platform...	[]	Validation
16,880	30	Title: Evaluation of Social Biases in Recent Large Pre-Trained Models Abstract: Large pre-trained language models are widely used in the community. These models are usually trained on unmoderated and unfiltered data from open sources like the Internet. Due to this, biases that we see in platforms online which are a ref...	[]	Validation
16,881	27	Title: Penalty-Based Imitation Learning With Cross Semantics Generation Sensor Fusion for Autonomous Driving Abstract: In recent times, there has been a growing focus on end-to-end autonomous driving technologies. This technology involves the replacement of the entire driving pipeline with a single neural network, whic...	[]	Test
16,882	24	Title: Pure Exploration in Bandits with Linear Constraints Abstract: We address the problem of identifying the optimal policy with a fixed confidence level in a multi-armed bandit setup, when \emph{the arms are subject to linear constraints}. Unlike the standard best-arm identification problem which is well studied, th...	[]	Train
16,883	23	Title: An Effective Data-Driven Approach for Localizing Deep Learning Faults Abstract: Deep Learning (DL) applications are being used to solve problems in critical domains (e.g., autonomous driving or medical diagnosis systems). Thus, developers need to debug their systems to ensure that the expected behavior is delive...	[]	Train
16,884	8	Title: Machine Learning for Relaying Topology: Optimization of IoT Networks With Energy Harvesting Abstract: In this paper, we examine Internet of Things (IoT) systems related to smart cities, smart factories, connected cars, etc. To support such systems in a wide area with low power consumption, energy harvesting tech...	[]	Validation
16,885	16	Title: Tracker Meets Night: A Transformer Enhancer for UAV Tracking Abstract: Most previous progress in object tracking is realized in daytime scenes with favorable illumination. State-of-the-arts can hardly carry on their superiority at night so far, thereby considerably blocking the broadening of visual tracking-rela...	[ 14051 ]	Validation
16,886	24	Title: FedPIDAvg: A PID controller inspired aggregation method for Federated Learning Abstract: This paper presents FedPIDAvg, the winning submission to the Federated Tumor Segmentation Challenge 2022 (FETS22). Inspired by FedCostWAvg, our winning contribution to FETS21, we contribute an improved aggregation strategy f...	[]	Train
16,887	9	Title: Distribution-Free Proofs of Proximity Abstract: Motivated by the fact that input distributions are often unknown in advance, distribution-free property testing considers a setting in which the algorithmic task is to accept functions $f : [n] \to \{0,1\}$ having a certain property $\Pi$ and reject functions that ...	[]	Train
16,888	24	Title: Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization Abstract: Out-of-distribution (OOD) graph generalization are critical for many real-world applications. Existing methods neglect to discard spurious or noisy features of inputs, which are irrelevant to the label. Besid...	[]	Validation
16,889	23	Title: What Practitioners Really Think About Continuous Software Engineering: A Taxonomy of Challenges Abstract: The Continuous software engineering is a collaborative software development environment which offers the continues development and deployment of quality software project within short time. The Continuous sof...	[]	Test
16,890	30	Title: RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback Abstract: Reinforcement learning from human feedback (RLHF) is effective at aligning large language models (LLMs) to human preferences, but gathering high quality human preference labels is a key bottleneck. We conduct a head-to-head comp...	[ 17153, 45923, 40804, 41029, 25734, 29396, 41782, 39642, 17789 ]	Test
16,891	30	Title: Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models Abstract: Language models have been shown to exhibit positive scaling, where performance improves as models are scaled up in terms of size, compute, or data. In this work, we introduce NeQA, a dataset consisting of questions with neg...	[ 27880, 34178, 975 ]	Train
16,892	8	Title: A Vision and An Evolutionary Framework for 6G: Scenarios, Capabilities and Enablers Abstract: With the standardization and commercialization completed at an unforeseen pace for the 5th generation (5G) wireless networks, researchers, engineers and executives from the academia and industry have turned their attent...	[ 31920, 6713, 41323 ]	Train
16,893	24	Title: Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems Abstract: Learning high-quality feature embeddings efficiently and effectively is critical for the performance of web-scale machine learning systems. A typical model ingests hundreds of features with vocabularies on the order of mi...	[ 9610, 13510, 6918 ]	Train
16,894	28	Title: Five infinite families of binary cyclic codes and their related codes with good parameters Abstract: Cyclic codes are an interesting type of linear codes and have wide applications in communication and storage systems due to their efficient encoding and decoding algorithms. Inspired by the recent work on binary ...	[ 26033, 19415 ]	Train
16,895	2	Title: Layered Modal Type Theories Abstract: We introduce layers to modal type theories, which subsequently enables type theories for pattern matching on code in meta-programming and clean and straightforward semantics.	[]	Train
16,896	30	Title: Approximating CKY with Transformers Abstract: We investigate the ability of transformer models to approximate the CKY algorithm, using them to directly predict a parse and thus avoid the CKY algorithm's cubic dependence on sentence length. We find that on standard constituency parsing benchmarks this approach ac...	[]	Test
16,897	10	Title: Risk-Aware Distributed Multi-Agent Reinforcement Learning Abstract: Autonomous cyber and cyber-physical systems need to perform decision-making, learning, and control in unknown environments. Such decision-making can be sensitive to multiple factors, including modeling errors, changes in costs, and impacts of ev...	[]	Train
16,898	24	Title: Balancing Exploration and Exploitation: Disentangled β-CVAE in De Novo Drug Design Abstract: Deep generative models have recently emerged as a promising de novo drug design method. In this respect, deep generative conditional variational autoencoder (CVAE) models are a powerful approach for generating novel mole...	[]	Test
16,899	30	Title: Cross-lingual Knowledge Transfer and Iterative Pseudo-labeling for Low-Resource Speech Recognition with Transducers Abstract: Voice technology has become ubiquitous recently. However, the accuracy, and hence experience, in different languages varies significantly, which makes the technology not equally inclusive...	[]	Train
16,900	16	Title: PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations Abstract: Learning a generalizable object manipulation policy is vital for an embodied agent to work in complex real-world scenes. Parts, as the shared components in different object categories, have the poten...	[ 21518, 34000, 12051, 8983, 45977 ]	Test
16,901	27	Title: Value of Assistance for Mobile Agents Abstract: Mobile robotic agents often suffer from localization uncertainty which grows with time and with the agents' movement. This can hinder their ability to accomplish their task. In some settings, it may be possible to perform assistive actions that reduce uncertainty a...	[]	Train
16,902	22	Title: P4R-Type: a Verified API for P4 Control Plane Programs (Technical Report) Abstract: Software-Defined Networking (SDN) significantly simplifies programming, reconfiguring, and optimizing network devices, such as switches and routers. The de facto standard for programmming SDN devices is the P4 language. However, ...	[]	Validation
16,903	27	Title: Robofriend: An Adpative Storytelling Robotic Teddy Bear - Technical Report Abstract: In this paper we describe Robofriend, a robotic teddy bear for telling stories to young children. Robofriend adapts its behavior to keep the childrens' attention using reinforcement learning.	[]	Train
16,904	28	Title: Maximum Match Subsequence Alignment Algorithm Finely Grained (MMSAA FG) Abstract: Sequence alignment is common nowadays as it is used in many fields to determine how closely two sequences are related and at times to see how little they differ. In computational biology / Bioinformatics, there are many algorithms ...	[]	Test
16,905	6	Title: Avatar-centred AR Collaborative Mobile Interaction Abstract: —Interaction with the physical environment and different users is essential to foster a collaborative experience. For this, we propose an interaction based on a central point represented by an Augmented Reality marker in which several users can capture...	[]	Train
16,906	24	Title: Achieving a Better Stability-Plasticity Trade-off via Auxiliary Networks in Continual Learning Abstract: In contrast to the natural capabilities of humans to learn new tasks in a sequential fashion, neural networks are known to suffer from catastrophic forgetting, where the model's performances on old tasks drop...	[ 26074, 36894 ]	Train
16,907	8	Title: Quid pro Quo in Streaming Services: Algorithms for Cooperative Recommendations Abstract: Recommendations are employed by Content Providers (CPs) of streaming services in order to boost user engagement and their revenues. Recent works suggest that nudging recommendations towards cached items can reduce operationa...	[]	Train
16,908	2	Title: Symmetric Ternary Logic and Its Systematic Logic Composition Methodology Abstract: Ternary logic is expected to increase the area efficiency of VLSI due to its expressiveness compared to the traditional binary logic. This paper proposes a new symmetric ternary logic and a systematic logic composition methodology...	[]	Validation
16,909	30	Title: AdaPlanner: Adaptive Planning from Feedback with Language Models Abstract: Large language models (LLMs) have recently demonstrated the potential in acting as autonomous agents for sequential decision-making tasks. However, most existing methods either take actions greedily without planning or rely on static plan...	[ 34178, 19492, 35950, 41425, 6963, 9812, 1401, 634 ]	Train
16,910	24	Title: Towards Better Evaluation of GNN Expressiveness with BREC Dataset Abstract: Research on the theoretical expressiveness of Graph Neural Networks (GNNs) has developed rapidly, and many methods have been proposed to enhance the expressiveness. However, most methods do not have a uniform expressiveness measure excep...	[ 8660 ]	Train
16,911	30	Title: Scaling Data-Constrained Language Models Abstract: The current trend of scaling language models involves increasing both parameter count and training dataset size. Extrapolating this trend suggests that training dataset size may soon be limited by the amount of text data available on the internet. Motivated by t...	[ 14592, 40192, 13700, 33809, 34963, 14869, 34208, 25892, 26282, 25522, 36406, 6328, 25021, 29375, 32450, 21190, 9804, 37070, 42192, 12628, 2776, 23898, 7131, 17382, 8939, 109, 17517, 3696 ]	Train
16,912	30	Title: Multi-Party Chat: Conversational Agents in Group Settings with Humans and Models Abstract: Current dialogue research primarily studies pairwise (two-party) conversations, and does not address the everyday setting where more than two speakers converse together. In this work, we both collect and evaluate multi-par...	[ 14145, 770, 33477, 36563, 22485, 12411 ]	Train
16,913	28	Title: An Elementary Proof of the First LP Bound on the Rate of Binary Codes Abstract: The asymptotic rate vs. distance problem is a long-standing fundamental problem in coding theory. The best upper bound to date was given in 1977 and has received since then numerous proofs and interpretations. Here we provide a new, ...	[ 5035 ]	Train
16,914	6	Title: Why Are Conversational Assistants Still Black Boxes? The Case For Transparency Abstract: Much has been written about privacy in the context of conversational and voice assistants. Yet, there have been remarkably few developments in terms of the actual privacy offered by these devices. But how much of this is due...	[]	Train
16,915	24	Title: GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks Abstract: Graph structure learning is a well-established problem that aims at optimizing graph structures adaptive to specific graph datasets to help message passing neural networks (i.e., GNNs) to yield effective and robust node...	[ 44836, 4486, 31020, 22765, 1758 ]	Test
16,916	6	Title: Towards Building Child-Centered Machine Learning Pipelines: Use Cases from K-12 and Higher-Education Abstract: Researchers and policy-makers have started creating frameworks and guidelines for building machine-learning (ML) pipelines with a human-centered lens. Machine Learning pipelines stand for all the necess...	[ 32336 ]	Validation
16,917	30	Title: ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation Abstract: In this work, we make the first attempt to evaluate LLMs in a more challenging code generation scenario, i.e. class-level code generation. We first manually construct the first class-level code generation benchma...	[ 4610, 13700, 14229, 14869, 29215, 34208, 30243, 2980, 44452, 31145, 25522, 12602, 9403, 36159, 39873, 32450, 33220, 15952, 35427, 39908, 35580 ]	Validation
16,918	25	Title: Laughter Synthesis using Pseudo Phonetic Tokens with a Large-scale In-the-wild Laughter Corpus Abstract: We present a large-scale in-the-wild Japanese laughter corpus and a laughter synthesis method. Previous work on laughter synthesis lacks not only data but also proper ways to represent laughter. To solve thes...	[]	Validation
16,919	6	Title: SottoVoce: An Ultrasound Imaging-Based Silent Speech Interaction Using Deep Neural Networks Abstract: The availability of digital devices operated by voice is expanding rapidly. However, the applications of voice interfaces are still restricted. For example, speaking in public places becomes an annoyance to the ...	[ 13369, 34751 ]	Train
16,920	34	Title: A Simple 1.5-Approximation Algorithm for a Wide Range of Max-SMTI Problems Abstract: We give a simple approximation algorithm for a common generalization of many previously studied extensions of the stable matching problem with ties. These generalizations include the existence of critical vertices in the graph, ...	[]	Train
16,921	16	Title: Mining Conditional Part Semantics with Occluded Extrapolation for Human-Object Interaction Detection Abstract: Human-Object Interaction Detection is a crucial aspect of human-centric scene understanding, with important applications in various domains. Despite recent progress in this field, recognizing subtle and...	[]	Test
16,922	4	Title: Combining Blockchain and IOT for Decentralized Healthcare Data Management Abstract: The emergence of the Internet of Things (IoT) has resulted in a significant increase in research on e-health. As the amount of patient data grows, it has become increasingly challenging to protect patients' privacy. Patient data ...	[ 17996 ]	Train
16,923	24	Title: DSTCGCN: Learning Dynamic Spatial-Temporal Cross Dependencies for Traffic Forecasting Abstract: Traffic forecasting is essential to intelligent transportation systems, which is challenging due to the complicated spatial and temporal dependencies within a road network. Existing works usually learn spatial and tem...	[]	Test
16,924	16	Title: Making Vision Transformers Truly Shift-Equivariant Abstract: For computer vision tasks, Vision Transformers (ViTs) have become one of the go-to deep net architectures. Despite being inspired by Convolutional Neural Networks (CNNs), ViTs remain sensitive to small shifts in the input image. To address this, we int...	[ 1579 ]	Train
16,925	24	Title: Connecting Fairness in Machine Learning with Public Health Equity Abstract: Machine learning (ML) has become a critical tool in public health, offering the potential to improve population health, diagnosis, treatment selection, and health system efficiency. However, biases in data and model design can result in ...	[]	Train
16,926	16	Title: 3D-STMN: Dependency-Driven Superpoint-Text Matching Network for End-to-End 3D Referring Expression Segmentation Abstract: In 3D Referring Expression Segmentation (3D-RES), the earlier approach adopts a two-stage paradigm, extracting segmentation proposals and then matching them with referring expressions. Howeve...	[ 16755 ]	Train
16,927	27	Title: RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation Abstract: For robots to be useful outside labs and specialized factories we need a way to teach them new useful behaviors quickly. Current approaches lack either the generality to onboard new tasks without task-specific engineering, or else lack th...	[ 22913, 16139, 8206 ]	Validation
16,928	4	Title: Multi-Granularity Detector for Vulnerability Fixes Abstract: With the increasing reliance on Open Source Software, users are exposed to third-party library vulnerabilities. Software Composition Analysis (SCA) tools have been created to alert users of such vulnerabilities. SCA requires the identification of vulne...	[ 1289, 37458, 10381, 6111 ]	Train
16,929	24	Title: Understanding the Role of Feedback in Online Learning with Switching Costs Abstract: In this paper, we study the role of feedback in online learning with switching costs. It has been shown that the minimax regret is $\widetilde{\Theta}(T^{2/3})$ under bandit feedback and improves to $\widetilde{\Theta}(\sqrt{T})...	[]	Train
16,930	25	Title: BLAT: Bootstrapping Language-Audio Pre-training based on AudioSet Tag-guided Synthetic Data Abstract: Compared with ample visual-text pre-training research, few works explore audio-text pre-training, mostly due to the lack of sufficient parallel audio-text data. Most existing methods incorporate the visual modal...	[]	Train
16,931	16	Title: Balanced Spherical Grid for Egocentric View Synthesis Abstract: We present EgoNeRF, a practical solution to reconstruct large-scale real-world environments for VR assets. Given a few seconds of casually captured 360 video, EgoNeRF can efficiently build neural radiance fields. Motivated by the recent acceleration...	[ 7076 ]	Train
16,932	24	Title: DiffDefense: Defending Against Adversarial Attacks via Diffusion Models Abstract: nan	[]	Train
16,933	16	Title: Deep Ensemble for Rotorcraft Attitude Prediction Abstract: Historically, the rotorcraft community has experienced a higher fatal accident rate than other aviation segments, including commercial and general aviation. To date, traditional methods applied to reduce incident rates have not proven hugely successful...	[ 32318 ]	Train
16,934	30	Title: Token-level Fitting Issues of Seq2seq Models Abstract: Sequence-to-sequence (seq2seq) models have been widely used for natural language processing, computer vision, and other deep learning tasks. We find that seq2seq models trained with early-stopping suffer from issues at the token level. In particular, while s...	[]	Train
16,935	31	Title: Entire Space Cascade Delayed Feedback Modeling for Effective Conversion Rate Prediction Abstract: Conversion rate (CVR) prediction is an essential task for large-scale e-commerce platforms. However, refund behaviors frequently occur after conversion in online shopping systems, which drives us to pay attention to...	[ 15417, 32494 ]	Train
16,936	30	Title: SemEval-2023 Task 10: Explainable Detection of Online Sexism Abstract: Online sexism is a widespread and harmful phenomenon. Automated tools can assist the detection of sexism at scale. Binary detection, however, disregards the diversity of sexist content, and fails to provide clear explanations for why somethin...	[ 27778, 10116, 22853, 28167, 35976, 39349, 30553, 2298, 19166, 32671 ]	Train
16,937	24	Title: DOS: Diverse Outlier Sampling for Out-of-Distribution Detection Abstract: Modern neural networks are known to give overconfident prediction for out-of-distribution inputs when deployed in the open world. It is common practice to leverage a surrogate outlier dataset to regularize the model during training, and re...	[]	Test
16,938	30	Title: HiPool: Modeling Long Documents Using Graph Neural Networks Abstract: Encoding long sequences in Natural Language Processing (NLP) is a challenging problem. Though recent pretraining language models achieve satisfying performances in many NLP tasks, they are still restricted by a pre-defined maximum length, maki...	[]	Train
16,939	16	Title: Multi-Granularity Archaeological Dating of Chinese Bronze Dings Based on a Knowledge-Guided Relation Graph Abstract: The archaeological dating of bronze dings has played a critical role in the study of ancient Chinese history. Current archaeology depends on trained experts to carry out bronze dating, which is ti...	[]	Train
16,940	16	Title: Towards Viewpoint Robustness in Bird's Eye View Segmentation Abstract: Autonomous vehicles (AV) require that neural networks used for perception be robust to different viewpoints if they are to be deployed across many types of vehicles without the repeated cost of data collection and labeling for each. AV compan...	[]	Train
16,941	10	Title: On the Expressivity of Multidimensional Markov Reward Abstract: We consider the expressivity of Markov rewards in sequential decision making under uncertainty. We view reward functions in Markov Decision Processes (MDPs) as a means to characterize desired behaviors of agents. Assuming desired behaviors are speci...	[]	Train
16,942	30	Title: Multimodal Deep Learning Abstract: This book is the result of a seminar in which we reviewed multimodal approaches and attempted to create a solid overview of the field, starting with the current state-of-the-art approaches in the two subfields of Deep Learning individually. Further, modeling frameworks are disc...	[]	Train
16,943	31	Title: Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation Abstract: Click-Through Rate (CTR) prediction plays a core role in recommender systems, serving as the final-stage filter to rank items for a user. The key to addressing the CTR task is learning feature interactions that are...	[ 16179, 18833, 1611 ]	Train
16,944	18	Title: Thermal Crosstalk Analysis in RRAM Passive Crossbar Arrays Abstract: As the packing density of resistive random access memory (RRAM) devices increases, the effect of thermal cross-talk across the devices in a crossbar array arrangement influences their overall operation significantly. The electro-thermal effects...	[]	Train
16,945	16	Title: Self-Supervised Learning for Group Equivariant Neural Networks Abstract: This paper proposes a method to construct pretext tasks for self-supervised learning on group equivariant neural networks. Group equivariant neural networks are the models whose structure is restricted to commute with the transformations on...	[]	Train
16,946	24	Title: Price-Aware Deep Learning for Electricity Markets Abstract: While deep learning gradually penetrates operational planning, its inherent prediction errors may significantly affect electricity prices. This letter examines how prediction errors propagate into electricity prices, revealing notable pricing errors and...	[]	Train
16,947	24	Title: Deception by Omission: Using Adversarial Missingness to Poison Causal Structure Learning Abstract: Causality-informed machine learning has been proposed as an avenue for achieving many of the goals of modern machine learning, from ensuring generalization under domain shifts to attaining fairness, robustness, and...	[]	Test
16,948	27	Title: Evolution of linkages for prototyping of linkage based robots Abstract: Prototyping robotic systems is a time consuming process. Computer aided design, however, might speed up the process significantly. Quality-diversity evolutionary approaches optimise for novelty as well as performance, and can be used to gene...	[]	Train
16,949	24	Title: Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification Abstract: Deep learning has been widely used in many fields, but the model training process usually consumes massive computational resources and time. Therefore, designing an efficient neural network training method with a provab...	[ 29089, 12898, 20449, 34404, 12966, 15561, 17354, 24635, 13100, 40301, 29006, 39573, 7767, 7643 ]	Train
16,950	8	Title: Towards a Real-Time IoT: Approaches for Incoming Packet Processing in Cyber-Physical Systems Abstract: nan	[]	Train
16,951	23	Title: CodeLens: An Interactive Tool for Visualizing Code Representations Abstract: Representing source code in a generic input format is crucial to automate software engineering tasks, e.g., applying machine learning algorithms to extract information. Visualizing code representations can further enable human experts t...	[]	Train
16,952	10	Title: MAILS - Meta AI Literacy Scale: Development and Testing of an AI Literacy Questionnaire Based on Well-Founded Competency Models and Psychological Change- and Meta-Competencies Abstract: The goal of the present paper is to develop and validate a questionnaire to assess AI literacy. In particular, the questionnair...	[]	Test
16,953	24	Title: Knowledge Distillation on Graphs: A Survey Abstract: Graph Neural Networks (GNNs) have attracted tremendous attention by demonstrating their capability to handle graph data. However, they are difficult to be deployed in resource-limited devices due to model sizes and scalability constraints imposed by the multi-...	[ 21769, 26268, 23805 ]	Train
16,954	16	Title: DORSal: Diffusion for Object-centric Representations of Scenes $\textit{et al.}$ Abstract: Recent progress in 3D scene understanding enables scalable learning of representations across large datasets of diverse scenes. As a consequence, generalization to unseen scenes and objects, rendering novel views from just...	[ 9610, 22480, 22010, 6488, 14842 ]	Train
16,955	24	Title: Adapting Machine Learning Diagnostic Models to New Populations Using a Small Amount of Data: Results from Clinical Neuroscience Abstract: Machine learning (ML) has shown great promise for revolutionizing a number of areas, including healthcare. However, it is also facing a reproducibility crisis, especially in m...	[ 1120 ]	Train
16,956	24	Title: Local Interpretability of Random Forests for Multi-Target Regression Abstract: Multi-target regression is useful in a plethora of applications. Although random forest models perform well in these tasks, they are often difficult to interpret. Interpretability is crucial in machine learning, especially when it can...	[]	Train
16,957	25	Title: Music Rearrangement Using Hierarchical Segmentation Abstract: Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a creative and time-consuming task commonly performed by an expert music e...	[]	Test
16,958	24	Title: MadSGM: Multivariate Anomaly Detection with Score-based Generative Models Abstract: The time-series anomaly detection is one of the most fundamental tasks for time-series. Unlike the time-series forecasting and classification, the time-series anomaly detection typically requires unsupervised (or self-supervised)...	[ 42339 ]	Train
16,959	11	Title: Coordinating Fully-Cooperative Agents Using Hierarchical Learning Anticipation Abstract: Learning anticipation is a reasoning paradigm in multi-agent reinforcement learning, where agents, during learning, consider the anticipated learning of other agents. There has been substantial research into the role of lear...	[ 10519 ]	Train
16,960	24	Title: Sparsity May Cry: Let Us Fail (Current) Sparse Neural Networks Together! Abstract: Sparse Neural Networks (SNNs) have received voluminous attention predominantly due to growing computational and memory footprints of consistently exploding parameter count in large-scale models. Similar to their dense counterparts...	[ 36557, 10038, 27583, 43452, 23007 ]	Validation
16,961	13	Title: On the Impact of Basic Mutation Operators and Populations within Evolutionary Algorithms for the Dynamic Weighted Traveling Salesperson Problem Abstract: Evolutionary algorithms have been shown to obtain good solutions for complex optimization problems in static and dynamic environments. It is important to under...	[]	Validation
16,962	16	Title: Efficient Multimodal Fusion via Interactive Prompting Abstract: Large-scale pre-training has brought unimodal fields such as computer vision and natural language processing to a new era. Following this trend, the size of multimodal learning models constantly increases, leading to an urgent need to reduce the mas...	[ 17375 ]	Validation
16,963	26	Title: Empowering Young Learners to Explore Blockchain with User-Friendly Tools: A Method Using Google Blockly and NFTs Abstract: As blockchain technology continues to gain attention, there is a growing need to make it more accessible to young learners in K-12 education. However, the technical complexity and lack of ac...	[ 33090 ]	Train
16,964	24	Title: Opportunistic Air Quality Monitoring and Forecasting with Expandable Graph Neural Networks Abstract: Air Quality Monitoring and Forecasting has been a popular research topic in recent years. Recently, data-driven approaches for air quality forecasting have garnered significant attention, owing to the availabilit...	[ 31309 ]	Validation
16,965	24	Title: Multivariate Time Series Anomaly Detection via Dynamic Graph Forecasting Abstract: Anomalies in univariate time series often refer to abnormal values and deviations from the temporal patterns from majority of historical observations. In multivariate time series, anomalies also refer to abnormal changes in the in...	[ 32869 ]	Train
16,966	24	Title: Fair Correlation Clustering in Forests Abstract: The study of algorithmic fairness received growing attention recently. This stems from the awareness that bias in the input data for machine learning systems may result in discriminatory outputs. For clustering tasks, one of the most central notions of fairness is...	[]	Train
16,967	16	Title: A Generative Model for Digital Camera Noise Synthesis Abstract: Noise synthesis is a challenging low-level vision task aiming to generate realistic noise given a clean image along with the camera settings. To this end, we propose an effective generative model which utilizes clean features as guidance followed by...	[ 304 ]	Test
16,968	1	Title: BOLA360: Near-optimal View and Bitrate Adaptation for 360-degree Video Streaming Abstract: Recent advances in omnidirectional cameras and AR/VR headsets have spurred the adoption of 360-degree videos that are widely believed to be the future of online video streaming. 360-degree videos allow users to wear a head...	[]	Train
16,969	6	Title: Augmented Math: Authoring AR-Based Explorable Explanations by Augmenting Static Math Textbooks Abstract: We introduce Augmented Math, a machine learning-based approach to authoring AR explorable explanations by augmenting static math textbooks without programming. To augment a static document, our system first e...	[ 18616 ]	Validation
16,970	34	Title: Shortest Odd Paths in Undirected Graphs with Conservative Weight Functions Abstract: We consider the Shortest Odd Path problem, where given an undirected graph $G$, a weight function on its edges, and two vertices $s$ and $t$ in $G$, the aim is to find an $(s,t)$-path with odd length and, among all such paths, o...	[ 2436 ]	Validation
16,971	16	Title: IndGIC: Supervised Action Recognition under Low Illumination Abstract: Technologies of human action recognition in the dark are gaining more and more attention as huge demand in surveillance, motion control and human-computer interaction. However, because of limitation in image enhancement method and low-lightin...	[]	Train
16,972	7	Title: Denture reinforcement via topology optimization Abstract: We present a computational design method that optimizes the reinforcement of dental prostheses and increases the durability and fracture resistance of dentures. Our approach optimally places reinforcement, which could be implemented by modern multi-materi...	[]	Train
16,973	6	Title: CrowDC: A Divide-and-Conquer Approach for Paired Comparisons in Crowdsourcing Abstract: Ranking a set of samples based on subjectivity, such as the experience quality of streaming video or the happiness of images, has been a typical crowdsourcing task. Numerous studies have employed paired comparison analysis to...	[ 45667 ]	Test
16,974	24	Title: FFPDG: Fast, Fair and Private Data Generation Abstract: Generative modeling has been used frequently in synthetic data generation. Fairness and privacy are two big concerns for synthetic data. Although Recent GAN [\cite{goodfellow2014generative}] based methods show good results in preserving privacy, the generat...	[]	Train
16,975	6	Title: LoopBoxes - Evaluation of a Collaborative Accessible Digital Musical Instrument Abstract: LoopBoxes is an accessible digital musical instrument designed to create an intuitive access to loop based music making for children with special educational needs (SEN). This paper describes the evaluation of the instrumen...	[]	Test
16,976	8	Title: CarFi: Rider Localization Using Wi-Fi CSI Abstract: With the rise of hailing services, people are increasingly relying on shared mobility (e.g., Uber, Lyft) drivers to pick up for transportation. However, such drivers and riders have difficulties finding each other in urban areas as GPS signals get blocked by sk...	[ 28172 ]	Train
16,977	16	Title: Confidence-aware 3D Gaze Estimation and Evaluation Metric Abstract: Deep learning appearance-based 3D gaze estimation is gaining popularity due to its minimal hardware requirements and being free of constraint. Unreliable and overconfident inferences, however, still limit the adoption of this gaze estimation met...	[]	Train

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