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
19,078	4	Title: Geometric Stability Estimates For 3D-Object Encryption Through Permutations and Rotations Abstract: We compute precise estimates for dimensions of 3D-encryption techniques of 3D-point clouds which use permutations and rigid body motion, in which geometric stability is to be guaranteed. Few attempts are made in t...	[]	Validation
19,079	16	Title: BPJDet: Extended Object Representation for Generic Body-Part Joint Detection Abstract: Detection of human body and its parts (e.g., head or hands) has been intensively studied. However, most of these CNNs-based detectors are trained independently, making it difficult to associate detected parts with body. In thi...	[ 33218, 45333 ]	Train
19,080	24	Title: Towards Efficient Modeling and Inference in Multi-Dimensional Gaussian Process State-Space Models Abstract: The Gaussian process state-space model (GPSSM) has attracted extensive attention for modeling complex nonlinear dynamical systems. However, the existing GPSSM employs separate Gaussian processes (GPs) for ...	[ 10121, 35731 ]	Train
19,081	5	Title: Speedup of Distributed Algorithms for Power Graphs in the CONGEST Model Abstract: We obtain improved distributed algorithms in the CONGEST message-passing setting for problems on power graphs of an input graph $G$. This includes Coloring, Maximal Independent Set, and related problems. We develop a general determ...	[ 13379, 31076 ]	Train
19,082	10	Title: Heckerthoughts Abstract: This manuscript is technical memoir about my work at Stanford and Microsoft Research. Included are fundamental concepts central to machine learning and artificial intelligence, applications of these concepts, and stories behind their creation.	[]	Train
19,083	30	Title: MEGA: Multilingual Evaluation of Generative AI Abstract: Generative AI models have impressive performance on many Natural Language Processing tasks such as language understanding, reasoning and language generation. One of the most important questions that is being asked by the AI community today is about the cap...	[ 13189, 44441, 23452, 6173, 1572, 7339, 22832, 43569, 34099, 13495, 12602, 20802, 41795, 38218, 2764, 29396, 26974, 37215, 44776, 31219, 8436, 26357, 21494, 35580, 34942 ]	Train
19,084	31	Title: Large Language Models are Competitive Near Cold-start Recommenders for Language- and Item-based Preferences Abstract: Traditional recommender systems leverage users’ item preference history to recommend novel content that users may like. However, modern dialog interfaces that allow users to express language-base...	[ 4610, 452, 40453, 45898, 24503, 34874 ]	Train
19,085	10	Title: Long Short-Term Memory Neural Network for Temperature Prediction in Laser Powder Bed Additive Manufacturing Abstract: nan	[]	Validation
19,086	24	Title: Optimization of body configuration and joint-driven attitude stabilization for transformable spacecrafts under solar radiation pressure Abstract: A solar sail is one of the most promising space exploration system because of its theoretically infinite specific impulse using solar radiation pressure (SRP). Recentl...	[]	Validation
19,087	16	Title: Delving into Ipsilateral Mammogram Assessment under Multi-View Network Abstract: In many recent years, multi-view mammogram analysis has been focused widely on AI-based cancer assessment. In this work, we aim to explore diverse fusion strategies (average and concatenate) and examine the model's learning behavior...	[ 46172 ]	Validation
19,088	30	Title: Hierarchical Prompting Assists Large Language Model on Web Navigation Abstract: Large language models (LLMs) struggle on processing complicated observations in interactive decision making. To alleviate this issue, we propose a simple hierarchical prompting approach. Diverging from previous prompting approaches t...	[ 41336, 37252, 22286 ]	Test
19,089	30	Title: Can Contextual Biasing Remain Effective with Whisper and GPT-2? Abstract: End-to-end automatic speech recognition (ASR) and large language models, such as Whisper and GPT-2, have recently been scaled to use vast amounts of training data. Despite the large amount of training data, infrequent content words that oc...	[ 37177, 45914 ]	Test
19,090	24	Title: Steering Graph Neural Networks with Pinning Control Abstract: In the semi-supervised setting where labeled data are largely limited, it remains to be a big challenge for message passing based graph neural networks (GNNs) to learn feature representations for the nodes with the same class label that is distributed...	[]	Test
19,091	6	Title: Experiments on Generative AI-Powered Parametric Modeling and BIM for Architectural Design Abstract: This paper introduces a new architectural design framework that utilizes generative AI tools including ChatGPT and Veras with parametric modeling and Building Information Modeling (BIM) to enhance the design proce...	[ 6942 ]	Validation
19,092	24	Title: On the Dynamics of Learning Time-Aware Behavior with Recurrent Neural Networks Abstract: Recurrent Neural Networks (RNNs) have shown great success in modeling time-dependent patterns, but there is limited research on their learned representations of latent temporal features and the emergence of these representat...	[]	Train
19,093	24	Title: Uncertainty-Aware Off-Policy Learning Abstract: Off-policy learning, referring to the procedure of policy optimization with access only to logged feedback data, has shown importance in various real-world applications, such as search engines, recommender systems, and etc. While the ground-truth logging policy, wh...	[]	Train
19,094	30	Title: COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective Abstract: Detecting commonsense causal relations (causation) between events has long been an essential yet challenging task. Given that events are complicated, an event may have different causes under various contexts. Thus, ...	[ 34892, 16766 ]	Train
19,095	30	Title: Computational Language Acquisition with Theory of Mind Abstract: Unlike current state-of-the-art language models, young children actively acquire language through interactions with their surrounding environment and caretakers. One mechanism that has been argued to be critical to language learning is the ability ...	[ 16429 ]	Test
19,096	24	Title: S-REINFORCE: A Neuro-Symbolic Policy Gradient Approach for Interpretable Reinforcement Learning Abstract: This paper presents a novel RL algorithm, S-REINFORCE, which is designed to generate interpretable policies for dynamic decision-making tasks. The proposed algorithm leverages two types of function approxima...	[]	Train
19,097	28	Title: Technology Trends for Massive MIMO towards 6G Abstract: At the dawn of the next-generation wireless systems and networks, massive multiple-input multiple-output (MIMO) in combination with leading-edge technologies, methodologies, and architectures are poised to be a cornerstone technology. Capitalizing on its su...	[ 33183 ]	Train
19,098	16	Title: PRSeg: A Lightweight Patch Rotate MLP Decoder for Semantic Segmentation Abstract: The lightweight MLP-based decoder has become increasingly promising for semantic segmentation. However, the channel-wise MLP cannot expand the receptive fields, lacking the context modeling capacity, which is critical to semantic s...	[ 22181 ]	Validation
19,099	20	Title: On Minimizing the Energy of a Spherical Graph Representation Abstract: Graph representations are the generalization of geometric graph drawings from the plane to higher dimensions. A method introduced by Tutte to optimize properties of graph drawings is to minimize their energy. We explore this minimization for ...	[]	Test
19,100	8	Title: On the Role of Preemption for Timing Metrics in Coded Multipath Communication Abstract: Recent trends in communication networks have focused on Quality of Service (QoS) requirements expressed through timing metrics such as latency or Age of Information (AoI). A possible way to achieve this is coded multipath com...	[]	Train
19,101	16	Title: Frequency-domain Learning for Volumetric-based 3D Data Perception Abstract: Frequency-domain learning draws attention due to its superior tradeoff between inference accuracy and input data size. Frequency-domain learning in 2D computer vision tasks has shown that 2D convolutional neural networks (CNN) have a sta...	[]	Train
19,102	27	Title: The effect of tail stiffness on a sprawling quadruped locomotion Abstract: A distinctive feature of quadrupeds that is integral to their locomotion is the tail. Tails serve many purposes in biological systems, including propulsion, counterbalance, and stabilization while walking, running, climbing, or jumping. S...	[]	Train
19,103	25	Title: Progressive Sub-Graph Clustering Algorithm for Semi-Supervised Domain Adaptation Speaker Verification Abstract: Utilizing the large-scale unlabeled data from the target domain via pseudo-label clustering algorithms is an important approach for addressing domain adaptation problems in speaker verification tasks. ...	[]	Test
19,104	31	Title: Improving Implicit Feedback-Based Recommendation through Multi-Behavior Alignment Abstract: Recommender systems that learn from implicit feedback often use large volumes of a single type of implicit user feedback, such as clicks, to enhance the prediction of sparse target behavior such as purchases. Using multip...	[ 20665 ]	Train
19,105	16	Title: Omnidirectional Information Gathering for Knowledge Transfer-based Audio-Visual Navigation Abstract: Audio-visual navigation is an audio-targeted wayfinding task where a robot agent is entailed to travel a never-before-seen 3D environment towards the sounding source. In this article, we present ORAN, an omnidire...	[]	Test
19,106	33	Title: Freezing 1-Tag Systems with States Abstract: We study 1-tag systems with states obeying the freezing property that only allows constant bounded number of rewrites of symbols. We look at examples of languages accepted by such systems, the accepting power of the model, as well as certain closure properties and dec...	[]	Train
19,107	24	Title: Characterizing the load profile in power grids by Koopman mode decomposition of interconnected dynamics Abstract: Electricity load forecasting is crucial for effectively managing and optimizing power grids. Over the past few decades, various statistical and deep learning approaches have been used to develop load...	[]	Train
19,108	24	Title: Selective Sampling and Imitation Learning via Online Regression Abstract: We consider the problem of Imitation Learning (IL) by actively querying noisy expert for feedback. While imitation learning has been empirically successful, much of prior work assumes access to noiseless expert feedback which is not practi...	[]	Train
19,109	16	Title: Arbitrary point cloud upsampling via Dual Back-Projection Network Abstract: Point clouds acquired from 3D sensors are usually sparse and noisy. Point cloud upsampling is an approach to increase the density of the point cloud so that detailed geometric information can be restored. In this paper, we propose a Dual...	[]	Train
19,110	3	Title: Exploring Xenophobic Events through GDELT Data Analysis Abstract: This study explores xenophobic events related to refugees and migration using the GDELT 2.0 database and APIs through visualizations. We conducted two case studies -- the first being an analysis of refugee-related news following the death of a two...	[]	Validation
19,111	6	Title: The CUFF, Clenching Upper-limb Force Feedback wearable device: design, characterization and validation Abstract: This paper presents the design, characterization and validation of a wearable haptic device able to convey skin stretch, force feedback, and a combination of both, to the user's arm. In this work, we ...	[]	Train
19,112	26	Title: Detecting Pump&Dump Stock Market Manipulation from Online Forums Abstract: The intersection of social media, low-cost trading platforms, and naive investors has created an ideal situation for information-based market manipulations, especially pump&dumps. Manipulators accumulate small-cap stocks, disseminate fals...	[]	Validation
19,113	11	Title: A Variational Approach to Mutual Information-Based Coordination for Multi-Agent Reinforcement Learning Abstract: In this paper, we propose a new mutual information framework for multi-agent reinforcement learning to enable multiple agents to learn coordinated behaviors by regularizing the accumulated return with...	[ 10274 ]	Train
19,114	30	Title: Parallel Sentence-Level Explanation Generation for Real-World Low-Resource Scenarios Abstract: In order to reveal the rationale behind model predictions, many works have exploited providing explanations in various forms. Recently, to further guarantee readability, more and more works turn to generate sentence-le...	[ 38544, 18889, 1895 ]	Validation
19,115	28	Title: Blind Beamforming for Intelligent Reflecting Surface in Fading Channels without CSI Abstract: This paper discusses how to optimize the phase shifts of intelligent reflecting surface (IRS) to combat channel fading without any channel state information (CSI), namely blind beamforming. Differing from most previous ...	[ 22548 ]	Validation
19,116	30	Title: Detecting and Reasoning of Deleted Tweets before they are Posted Abstract: Social media platforms empower us in several ways, from information dissemination to consumption. While these platforms are useful in promoting citizen journalism, public awareness etc., they have misuse potentials. Malicious users use th...	[]	Train
19,117	10	Title: Redes Generativas Adversarias (GAN) Fundamentos Teóricos y Aplicaciones Abstract: Generative adversarial networks (GANs) are a method based on the training of two neural networks, one called generator and the other discriminator, competing with each other to generate new instances that resemble those of the prob...	[]	Test
19,118	17	Title: Dynamic Mesh-Aware Radiance Fields Abstract: Embedding polygonal mesh assets within photorealistic Neural Radience Fields (NeRF) volumes, such that they can be rendered and their dynamics simulated in a physically consistent manner with the NeRF, is under-explored from the system perspective of integrating NeRF ...	[ 7068, 31586, 5820, 11206 ]	Train
19,119	3	Title: Food Choice Mimicry on a Large University Campus Abstract: Social influence is a strong determinant of food consumption, which in turn influences health. Although consistent observations have been made on the role of social factors in driving similarities in food consumption, much less is known about the precise...	[]	Test
19,120	6	Title: Insights into Cognitive Engagement: Comparing the Effectiveness of Game-Based and Video-Based Learning Abstract: The analysis of brain signals holds considerable importance in enhancing our comprehension of diverse learning techniques and cognitive mechanisms. Game-based learning is increasingly being recognized...	[]	Train
19,121	16	Title: Efficient solutions to the relative pose of three calibrated cameras from four points using virtual correspondences Abstract: We study the challenging problem of estimating the relative pose of three calibrated cameras. We propose two novel solutions to the notoriously difficult configuration of four points in t...	[]	Validation
19,122	16	Title: Memory-and-Anticipation Transformer for Online Action Understanding Abstract: Most existing forecasting systems are memory-based methods, which attempt to mimic human forecasting ability by employing various memory mechanisms and have progressed in temporal modeling for memory dependency. Nevertheless, an obviou...	[ 20588, 45452, 17484 ]	Validation
19,123	1	Title: Visual Captioning at Will: Describing Images and Videos Guided by a Few Stylized Sentences Abstract: Stylized visual captioning aims to generate image or video descriptions with specific styles, making them more attractive and emotionally appropriate. One major challenge with this task is the lack of paired styl...	[ 34286, 36382 ]	Test
19,124	24	Title: Interpretable System Identification and Long-term Prediction on Time-Series Data Abstract: Time-series prediction has drawn considerable attention during the past decades fueled by the emerging advances of deep learning methods. However, most neural network based methods lack interpretability and fail in extract...	[]	Train
19,125	16	Title: Representation Learning for Tablet and Paper Domain Adaptation in Favor of Online Handwriting Recognition Abstract: The performance of a machine learning model degrades when it is applied to data from a similar but different domain than the data it has initially been trained on. The goal of domain adaptation (DA...	[]	Test
19,126	7	Title: Progress Towards the Calculation of Time-Dependent, Viscous, Compressible Flows using Active Flux Scheme Abstract: The Active Flux scheme is a Finite Volume scheme with additional degrees of freedom. It makes use of a continuous reconstruction and does not require a Riemann solver. An evolution operator is used ...	[]	Test
19,127	30	Title: FrameBERT: Conceptual Metaphor Detection with Frame Embedding Learning Abstract: In this paper, we propose FrameBERT, a BERT-based model that can explicitly learn and incorporate FrameNet Embeddings for concept-level metaphor detection. FrameBERT not only achieves better or comparable performance to the state-of...	[ 10801, 28158, 45595, 13790 ]	Train
19,128	8	Title: Metaverse for Wireless Systems: Architecture, Advances, Standardization, and Open Challenges Abstract: The growing landscape of emerging wireless applications is a key driver toward the development of novel wireless system designs. Such a design can be based on the metaverse that uses a virtual model of the phys...	[ 15446, 46055 ]	Train
19,129	37	Title: Free Join: Unifying Worst-Case Optimal and Traditional Joins Abstract: Over the last decade, worst-case optimal join (WCOJ) algorithms have emerged as a new paradigm for one of the most fundamental challenges in query processing: computing joins efficiently. Such an algorithm can be asymptotically faster than tr...	[ 17366 ]	Test
19,130	16	Title: SANDFORMER: CNN and Transformer under Gated Fusion for Sand Dust Image Restoration Abstract: Although Convolutional Neural Networks (CNN) have made good progress in image restoration, the intrinsic equivalence and locality of convolutions still constrain further improvements in image quality. Recent vision trans...	[]	Validation
19,131	4	Title: A Decentralized Authorization and Security Framework for Distributed Research Workflows* Abstract: Research challenges such as climate change and the search for habitable planets increasingly use academic and commercial computing resources distributed across different institutions and physical sites. Furthermore...	[]	Train
19,132	16	Title: BlobGAN-3D: A Spatially-Disentangled 3D-Aware Generative Model for Indoor Scenes Abstract: 3D-aware image synthesis has attracted increasing interest as it models the 3D nature of our real world. However, performing realistic object-level editing of the generated images in the multi-object scenario still remains...	[ 7076 ]	Test
19,133	27	Title: A Study in Zucker: Insights on Human-Robot Interactions Abstract: In recent years there has been a large focus on how robots can operate in human populated environments. In this paper, we focus on interactions between humans and small indoor robots and introduce a new human-robot interaction (HRI) dataset. The a...	[]	Validation
19,134	4	Title: Privacy Against Agnostic Inference Attack in Vertical Federated Learning Abstract: A novel form of inference attack in vertical federated learning (VFL) is proposed, where two parties collaborate in training a machine learning (ML) model. Logistic regression is considered for the VFL model. One party, referred t...	[]	Train
19,135	16	Title: Extreme Image Compression using Fine-tuned VQGAN Models Abstract: Recent advances in generative compression methods have demonstrated remarkable progress in enhancing the perceptual quality of compressed data, especially in scenarios with low bitrates. Nevertheless, their efficacy and applicability in achieving ...	[]	Train
19,136	24	Title: Operator Learning Framework for Digital Twin and Complex Engineering Systems Abstract: With modern computational advancements and statistical analysis methods, machine learning algorithms have become a vital part of engineering modeling. Neural Operator Networks (ONets) is an emerging machine learning algorithm ...	[ 23650 ]	Train
19,137	25	Title: Music Source Separation with Band-Split RoPE Transformer Abstract: Music source separation (MSS) aims to separate a music recording into multiple musically distinct stems, such as vocals, bass, drums, and more. Recently, deep learning approaches such as convolutional neural networks (CNNs) and recurrent neural n...	[ 14112, 42281 ]	Train
19,138	4	Title: Software-based security approach for networked embedded devices Abstract: As the Internet of Things (IoT) continues to expand, data security has become increasingly important for ensuring privacy and safety, especially given the sensitive and, sometimes, critical nature of the data handled by IoT devices. There ...	[]	Train
19,139	16	Title: Learning to Upsample by Learning to Sample Abstract: We present DySample, an ultra-lightweight and effective dynamic upsampler. While impressive performance gains have been witnessed from recent kernel-based dynamic upsamplers such as CARAFE, FADE, and SAPA, they introduce much workload, mostly due to the time-c...	[ 25481 ]	Train
19,140	30	Title: Japanese Lexical Complexity for Non-Native Readers: A New Dataset Abstract: Lexical complexity prediction (LCP) is the task of predicting the complexity of words in a text on a continuous scale. It plays a vital role in simplifying or annotating complex words to assist readers.To study lexical complexity in Japa...	[]	Train
19,141	37	Title: Approximating Clustering for Memory Management and request processing Abstract: Clustering is a crucial tool for analyzing data in virtually every scientific and engineering discipline. There are more scalable solutions framed to enable time and space clustering for the future large-scale data analyses. As a res...	[]	Train
19,142	16	Title: Learning Spatial Distribution of Long-Term Trackers Scores Abstract: Long-Term tracking is a hot topic in Computer Vision. In this context, competitive models are presented every year, showing a constant growth rate in performances, mainly measured in standardized protocols as Visual Object Tracking (VOT) and Ob...	[]	Train
19,143	10	Title: Jointly Learning Consistent Causal Abstractions Over Multiple Interventional Distributions Abstract: An abstraction can be used to relate two structural causal models representing the same system at different levels of resolution. Learning abstractions which guarantee consistency with respect to interventional d...	[ 39984 ]	Validation
19,144	18	Title: Tunable Synaptic Working Memory with Volatile Memristive Devices Abstract: Different real-world cognitive tasks evolve on different relevant timescales. Processing these tasks requires memory mechanisms able to match their specific time constants. In particular, the working memory utilizes mechanisms that span o...	[]	Validation
19,145	27	Title: Toward Wheeled Mobility on Vertically Challenging Terrain: Platforms, Datasets, and Algorithms Abstract: Most conventional wheeled robots can only move in flat environments and simply divide their planar workspaces into free spaces and obstacles. Deeming obstacles as non-traversable significantly limits wheeled ...	[ 6577, 44673 ]	Validation
19,146	30	Title: Authorship attribution for Differences between Literary Texts by Bilingual Russian-French and Non-Bilingual French Authors Abstract: Do bilingual Russian-French authors of the end of the twentieth century such as Andre\"i Makine, Val\'ery Afanassiev, Vladimir F\'edorovski, Iegor Gran, Luba Jurgenson have common ...	[]	Test
19,147	24	Title: Precision and Recall Reject Curves for Classification Abstract: For some classification scenarios, it is desirable to use only those classification instances that a trained model associates with a high certainty. To obtain such high-certainty instances, previous work has proposed accuracy-reject curves. Reject c...	[ 6670 ]	Train
19,148	32	Title: Collective-Optimized FFTs Abstract: This paper measures the impact of the various alltoallv methods. Results are analyzed within Beatnik, a Z-model solver that is bottlenecked by HeFFTe and representative of applications that rely on FFTs.	[ 36184 ]	Train
19,149	13	Title: Binary stochasticity enabled highly efficient neuromorphic deep learning achieves better-than-software accuracy Abstract: Deep learning needs high-precision handling of forwarding signals, backpropagating errors, and updating weights. This is inherently required by the learning algorithm since the gradient desce...	[]	Validation
19,150	24	Title: Weak-PDE-LEARN: A Weak Form Based Approach to Discovering PDEs From Noisy, Limited Data Abstract: We introduce Weak-PDE-LEARN, a Partial Differential Equation (PDE) discovery algorithm that can identify non-linear PDEs from noisy, limited measurements of their solutions. Weak-PDE-LEARN uses an adaptive loss func...	[]	Train
19,151	24	Title: Adaptive Strategies in Non-convex Optimization Abstract: An algorithm is said to be adaptive to a certain parameter (of the problem) if it does not need a priori knowledge of such a parameter but performs competitively to those that know it. This dissertation presents our work on adaptive algorithms in following...	[]	Train
19,152	30	Title: Disambiguation of Company names via Deep Recurrent Networks Abstract: Name Entity Disambiguation is the Natural Language Processing task of identifying textual records corresponding to the same Named Entity, i.e. real-world entities represented as a list of attributes (names, places, organisations, etc.). In thi...	[]	Train
19,153	16	Title: One-class Damage Detector Using Deeper Fully Convolutional Data Descriptions for Civil Application Abstract: Infrastructure managers must maintain high standards to ensure user satisfaction during the lifecycle of infrastructures. Surveillance cameras and visual inspections have enabled progress in automating th...	[ 36772, 11324, 41798 ]	Train
19,154	16	Title: Seed Kernel Counting using Domain Randomization and Object Tracking Neural Networks Abstract: High-throughput phenotyping (HTP) of seeds, also known as seed phenotyping, is the comprehensive assessment of complex seed traits such as growth, development, tolerance, resistance, ecology, yield, and the measurement ...	[]	Train
19,155	6	Title: Prompt Middleware: Mapping Prompts for Large Language Models to UI Affordances Abstract: To help users do complex work, researchers have developed techniques to integrate AI and human intelligence into user interfaces (UIs). With the recent introduction of large language models (LLMs), which can generate text in...	[ 25291, 17341, 42405 ]	Validation
19,156	31	Title: On Modeling Long-Term User Engagement from Stochastic Feedback Abstract: An ultimate goal of recommender systems (RS) is to improve user engagement. Reinforcement learning (RL) is a promising paradigm for this goal, as it directly optimizes overall performance of sequential recommendation. However, many existing...	[]	Test
19,157	16	Title: Content-aware Token Sharing for Efficient Semantic Segmentation with Vision Transformers Abstract: This paper introduces Content-aware Token Sharing (CTS), a token reduction approach that improves the computational efficiency of semantic segmentation networks that use Vision Transformers (ViTs). Existing works h...	[]	Validation
19,158	25	Title: Language Models are Drummers: Drum Composition with Natural Language Pre-Training Abstract: Automatic music generation with artificial intelligence typically requires a large amount of data which is hard to obtain for many less common genres and musical instruments. To tackle this issue, we present ongoing work ...	[]	Train
19,159	31	Title: When Large Language Models Meet Personalization: Perspectives of Challenges and Opportunities Abstract: The advent of large language models marks a revolutionary breakthrough in artificial intelligence. With the unprecedented scale of training and model parameters, the capability of large language models has bee...	[ 7936, 40192, 4610, 24706, 13700, 28674, 27138, 44173, 27281, 5522, 3609, 12445, 40610, 19747, 13224, 45615, 39600, 9907, 16179, 2613, 30131, 5815, 4535, 24503, 20794, 3643, 9917, 22334, 4546, 452, 45898, 203, 34385, 31314, 2771, 10069, 12251, ...	Validation
19,160	16	Title: Diffusion Based Augmentation for Captioning and Retrieval in Cultural Heritage Abstract: Cultural heritage applications and advanced machine learning models are creating a fruitful synergy to provide effective and accessible ways of interacting with artworks. Smart audio-guides, personalized art-related content ...	[ 12764 ]	Test
19,161	24	Title: A Cubic-regularized Policy Newton Algorithm for Reinforcement Learning Abstract: We consider the problem of control in the setting of reinforcement learning (RL), where model information is not available. Policy gradient algorithms are a popular solution approach for this problem and are usually shown to converg...	[]	Train
19,162	34	Title: On Lifting Integrality Gaps to SSEH Hardness for Globally Constrained CSPs Abstract: A $\mu$-constrained Boolean Max-CSP$(\psi)$ instance is a Boolean Max-CSP instance on predicate $\psi:\{0,1\}^r \to \{0,1\}$ where the objective is to find a labeling of relative weight exactly $\mu$ that maximizes the fraction ...	[]	Train
19,163	24	Title: TensorKrowch: Smooth integration of tensor networks in machine learning Abstract: Tensor networks are factorizations of high-dimensional tensors into networks of smaller tensors. They have applications in physics and mathematics, and recently have been proposed as promising machine learning architectures. To eas...	[]	Test
19,164	31	Title: Semantic Equivalence of e-Commerce Queries Abstract: Search query variation poses a challenge in e-commerce search, as equivalent search intents can be expressed through different queries with surface-level differences. This paper introduces a framework to recognize and leverage query equivalence to enhance sear...	[]	Validation
19,165	23	Title: Performance of Genetic Algorithms in the Context of Software Model Refactoring Abstract: Software systems continuously evolve due to new functionalities, requirements, or maintenance activities. In the context of software evolution, software refactoring has gained a strategic relevance. The space of possible sof...	[ 33432, 4353 ]	Validation
19,166	30	Title: IUST_NLP at SemEval-2023 Task 10: Explainable Detecting Sexism with Transformers and Task-adaptive Pretraining Abstract: This paper describes our system on SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). This work aims to design an automatic system for detecting and classifying sexist conten...	[ 16936 ]	Validation
19,167	28	Title: Cell-Edge Performance Booster in 6G: Cell-Free Massive MIMO vs. Reconfigurable Intelligent Surface Abstract: User experience in mobile communications is vulnerable to worse quality at the cell edge, which cannot be compensated by enjoying excellent service at the cell center, according to the principle of risk a...	[ 30010 ]	Train
19,168	16	Title: Controllable Mesh Generation Through Sparse Latent Point Diffusion Models Abstract: Mesh generation is of great value in various applications involving computer graphics and virtual content, yet designing generative models for meshes is challenging due to their irregular data structure and inconsistent topology ...	[ 33977, 39340, 21324 ]	Test
19,169	8	Title: Underwater 3D positioning on smart devices Abstract: The emergence of water-proof mobile and wearable devices (e.g., Garmin Descent and Apple Watch Ultra) designed for underwater activities like professional scuba diving, opens up opportunities for underwater networking and localization capabilities on these dev...	[]	Test
19,170	25	Title: A Review of Differentiable Digital Signal Processing for Music & Speech Synthesis Abstract: The term"differentiable digital signal processing"describes a family of techniques in which loss function gradients are backpropagated through digital signal processors, facilitating their integration into neural networks...	[ 3009, 23145, 1706, 26028, 23792, 43507, 20115, 40119 ]	Train
19,171	30	Title: Exploring the state of the art in legal QA systems Abstract: nan	[ 15104, 2417, 13700 ]	Validation
19,172	16	Title: Generating Visual Spatial Description via Holistic 3D Scene Understanding Abstract: Visual spatial description (VSD) aims to generate texts that describe the spatial relations of the given objects within images. Existing VSD work merely models the 2D geometrical vision features, thus inevitably falling prey to t...	[ 16130, 40258, 33932, 39919, 5107, 35220, 34358, 44828, 8509, 8895 ]	Test
19,173	16	Title: Masked Autoencoder for Unsupervised Video Summarization Abstract: Summarizing a video requires a diverse understanding of the video, ranging from recognizing scenes to evaluating how much each frame is essential enough to be selected as a summary. Self-supervised learning (SSL) is acknowledged for its robustness...	[]	Validation
19,174	24	Title: Multi-Domain Learning From Insufficient Annotations Abstract: Multi-domain learning (MDL) refers to simultaneously constructing a model or a set of models on datasets collected from different domains. Conventional approaches emphasize domain-shared information extraction and domain-private information preservati...	[ 12483, 6934 ]	Train
19,175	36	Title: Game-Theoretically Secure Protocols for the Ordinal Random Assignment Problem Abstract: We study game-theoretically secure protocols for the classical ordinal assignment problem (aka matching with one-sided preference), in which each player has a total preference order on items. To achieve the fairness notion of...	[]	Train
19,176	16	Title: Optimal Transport for Change Detection on LiDAR Point Clouds Abstract: Unsupervised change detection between airborne LiDAR data points, taken at separate times over the same location, can be difficult due to unmatching spatial support and noise from the acquisition system. Most current approaches to detect chan...	[ 45218 ]	Validation
19,177	16	Title: Mutual Exclusive Modulator for Long-Tailed Recognition Abstract: The long-tailed recognition (LTR) is the task of learning high-performance classifiers given extremely imbalanced training samples between categories. Most of the existing works address the problem by either enhancing the features of tail classes o...	[]	Validation

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