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
23,578	24	Title: Physics-informed Spectral Learning: the Discrete Helmholtz-Hodge Decomposition Abstract: In this work, we further develop the Physics-informed Spectral Learning (PiSL) by Espath et al. \cite{Esp21} based on a discrete $L^2$ projection to solve the discrete Hodge--Helmholtz decomposition from sparse data. Within ...	[]	Train
23,579	16	Title: HICO-DET-SG and V-COCO-SG: New Data Splits for Evaluating the Systematic Generalization Performance of Human-Object Interaction Detection Models Abstract: Human-Object Interaction (HOI) detection is a task to localize humans and objects in an image and predict the interactions in human-object pairs. In real-worl...	[ 16778 ]	Train
23,580	30	Title: Prompting Multilingual Large Language Models to Generate Code-Mixed Texts: The Case of South East Asian Languages Abstract: While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for natural language processing (NLP) ...	[ 39392, 19460, 6535, 28903, 11918, 14133, 23898, 35580, 6173, 11262 ]	Validation
23,581	24	Title: Exploiting Counter-Examples for Active Learning with Partial labels Abstract: This paper studies a new problem, \emph{active learning with partial labels} (ALPL). In this setting, an oracle annotates the query samples with partial labels, relaxing the oracle from the demanding accurate labeling process. To addre...	[]	Train
23,582	27	Title: Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) for comfortable and safe autonomous driving Abstract: This paper presents a Predictive Maneuver Planning with Deep Reinforcement Learning (PMP-DRL) model for maneuver planning. Traditional rule-based maneuver planning approaches often have t...	[]	Train
23,583	16	Title: CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition Abstract: We present CrossLoc3D, a novel 3D place recognition method that solves a large-scale point matching problem in a cross-source setting. Cross-source point cloud data corresponds to point sets captured by depth sensors with different accuracies ...	[]	Test
23,584	16	Title: Unsupervised haze removal from underwater images Abstract: Several supervised networks exist that remove haze information from underwater images using paired datasets and pixel-wise loss functions. However, training these networks requires large amounts of paired data which is cumbersome, complex and time-consum...	[]	Validation
23,585	26	Title: Popularity Ratio Maximization: Surpassing Competitors through Influence Propagation Abstract: In this paper, we present an algorithmic study on how to surpass competitors in popularity by strategic promotions in social networks. We first propose a novel model, in which we integrate the Preferential Attachment (P...	[]	Train
23,586	24	Title: Rethinking Warm-Starts with Predictions: Learning Predictions Close to Sets of Optimal Solutions for Faster L-/L♮-Convex Function Minimization Abstract: An emerging line of work has shown that machine-learned predictions are useful to warm-start algorithms for discrete optimization problems, such as bipartite ma...	[ 43872 ]	Train
23,587	24	Title: Inductive detection of Influence Operations via Graph Learning Abstract: Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies may enable novel operations which evade cur...	[ 42841 ]	Validation
23,588	24	Title: Graph Enabled Cross-Domain Knowledge Transfer Abstract: To leverage machine learning in any decision-making process, one must convert the given knowledge (for example, natural language, unstructured text) into representation vectors that can be understood and processed by machine learning model in their compatib...	[ 34472 ]	Validation
23,589	28	Title: RSMA for Overloaded MIMO Networks: Low-Complexity Design for Max-Min Fairness Abstract: Rate-Splitting Multiple Access (RSMA) is a robust multiple access scheme for multi-antenna wireless networks. In this work, we study the performance of RSMA in downlink overloaded networks, where the number of transmit antenn...	[ 18208, 33770 ]	Validation
23,590	26	Title: Encapsulation Structure and Dynamics in Hypergraphs Abstract: Hypergraphs have emerged as a powerful modeling framework to represent systems with multiway interactions, that is systems where interactions may involve an arbitrary number of agents. Here we explore the properties of real-world hypergraphs, focusing...	[ 45834 ]	Train
23,591	16	Title: Unsupervised Style-based Explicit 3D Face Reconstruction from Single Image Abstract: Inferring 3D object structures from a single image is an ill-posed task due to depth ambiguity and occlusion. Typical resolutions in the literature include leveraging 2D or 3D ground truth for supervised learning, as well as imp...	[]	Train
23,592	10	Title: Analyzing the Contextual Shortcomings of Artificial General Intelligence Abstract: Even in the most cutting-edge Artificial General Intelligence (AGI) endeavors, the disparity between humans and artificial systems is extremely apparent. Although this difference fundamentally divides the capabilities of each, hum...	[]	Train
23,593	16	Title: AvatarBooth: High-Quality and Customizable 3D Human Avatar Generation Abstract: We introduce AvatarBooth, a novel method for generating high-quality 3D avatars using text prompts or specific images. Unlike previous approaches that can only synthesize avatars based on simple text descriptions, our method enables ...	[ 32384, 6145, 27688, 26216, 34074, 2005, 34167, 13498 ]	Train
23,594	30	Title: Word-Graph2vec: An efficient word embedding approach on word co-occurrence graph using random walk sampling Abstract: Word embedding has become ubiquitous and is widely used in various text mining and natural language processing (NLP) tasks, such as information retrieval, semantic analysis, and machine translati...	[]	Train
23,595	16	Title: Contrastive Predictive Autoencoders for Dynamic Point Cloud Self-Supervised Learning Abstract: We present a new self-supervised paradigm on point cloud sequence understanding. Inspired by the discriminative and generative self-supervised methods, we design two tasks, namely point cloud sequence based Contrastive...	[ 22048, 10043 ]	Validation
23,596	16	Title: ShaRPy: Shape Reconstruction and Hand Pose Estimation from RGB-D with Uncertainty Abstract: Despite their potential, markerless hand tracking technologies are not yet applied in practice to the diagnosis or monitoring of the activity in inflammatory musculoskeletal diseases. One reason is that the focus of most ...	[]	Train
23,597	16	Title: AirBirds: A Large-scale Challenging Dataset for Bird Strike Prevention in Real-world Airports Abstract: nan	[ 7865 ]	Train
23,598	30	Title: ChatGPT MT: Competitive for High- (but not Low-) Resource Languages Abstract: Large language models (LLMs) implicitly learn to perform a range of language tasks, including machine translation (MT). Previous studies explore aspects of LLMs' MT capabilities. However, there exist a wide variety of languages for whi...	[ 14368, 13189, 26068, 44441, 35580, 1789, 15358 ]	Train
23,599	16	Title: SCENE: Reasoning About Traffic Scenes Using Heterogeneous Graph Neural Networks Abstract: Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to encode diverse traffic scenes in heterogeneous ...	[ 21194, 39445, 39026 ]	Train
23,600	16	Title: Instance-Conditioned GAN Data Augmentation for Representation Learning Abstract: Data augmentation has become a crucial component to train state-of-the-art visual representation models. However, handcrafting combinations of transformations that lead to improved performances is a laborious task, which can result ...	[]	Test
23,601	23	Title: EdgeFL: A Lightweight Decentralized Federated Learning Framework Abstract: Federated Learning (FL) has emerged as a promising approach for collaborative machine learning, addressing data privacy concerns. However, existing FL platforms and frameworks often present challenges for software engineers in terms of co...	[]	Test
23,602	30	Title: Journey to the Center of the Knowledge Neurons: Discoveries of Language-Independent Knowledge Neurons and Degenerate Knowledge Neurons Abstract: Pre-trained language models (PLMs) contain vast amounts of factual knowledge, but how the knowledge is stored in the parameters remains unclear. This paper delves into ...	[ 40192, 33220, 33933, 38801, 18105, 2390, 43641, 6942 ]	Train
23,603	23	Title: Comparing Mobile Testing Tools Using Documentary Analysis Abstract: Due to the high demand for mobile applications, given the exponential growth of users of this type of technology, testing professionals are frequently required to invest time in studying testing tools, in particular, because nowadays, several di...	[]	Validation
23,604	17	Title: On procedural urban digital twin generation and visualization of large scale data Abstract: The desired outcome for urban digital twins is an automatically generated detailed 3D model of a building from aerial imagery, footprints, LiDAR, or a fusion of these. Such 3D models have applications in architecture, civ...	[]	Train
23,605	16	Title: EDAPS: Enhanced Domain-Adaptive Panoptic Segmentation Abstract: With autonomous industries on the rise, domain adaptation of the visual perception stack is an important research direction due to the cost savings promise. Much prior art was dedicated to domain-adaptive semantic segmentation in the synthetic-to-re...	[]	Test
23,606	33	Title: Data-Flow-Based Normalization Generation Algorithm of R1CS for Zero-Knowledge Proof Abstract: The communities of blockchains and distributed ledgers have been stirred up by the introduction of zero-knowledge proofs (ZKPs). Originally designed to solve privacy issues, ZKPs have now evolved into an effective remed...	[]	Train
23,607	31	Title: Challenging the Myth of Graph Collaborative Filtering: a Reasoned and Reproducibility-driven Analysis Abstract: The success of graph neural network-based models (GNNs) has significantly advanced recommender systems by effectively modeling users and items as a bipartite, undirected graph. However, many original g...	[ 34128, 9150 ]	Train
23,608	30	Title: LAGAN: Deep Semi-Supervised Linguistic-Anthropology Classification with Conditional Generative Adversarial Neural Network Abstract: Education is a right of all, however, every individual is different than others. Teachers in post-communism era discover inherent individualism to equally train all towards job mark...	[]	Train
23,609	16	Title: Direct Superpoints Matching for Fast and Robust Point Cloud Registration Abstract: Although deep neural networks endow the downsampled superpoints with discriminative feature representations, directly matching them is usually not used alone in state-of-the-art methods, mainly for two reasons. First, the correspo...	[]	Train
23,610	5	Title: POLCA: Power Oversubscription in LLM Cloud Providers Abstract: Recent innovation in large language models (LLMs), and their myriad use-cases have rapidly driven up the compute capacity demand for datacenter GPUs. Several cloud providers and other enterprises have made substantial plans of growth in their datacen...	[]	Test
23,611	16	Title: Embedded Feature Similarity Optimization with Specific Parameter Initialization for 2D/3D Medical Image Registration Abstract: We present a novel deep learning-based framework: Embedded Feature Similarity Optimization with Specific Parameter Initialization (SOPI) for 2D/3D medical image registration which is a m...	[]	Train
23,612	5	Title: A Simple Python Testbed for Federated Learning Algorithms Abstract: Nowadays many researchers are developing various distributed and decentralized frameworks for federated learning algorithms. However, development of such a framework targeting smart Internet of Things in edge systems is still an open challenge. ...	[ 12458 ]	Train
23,613	5	Title: JOSS: Joint Exploration of CPU-Memory DVFS and Task Scheduling for Energy Efficiency Abstract: Energy-efficient execution of task-based parallel applications is crucial as tasking is a widely supported feature in many parallel programming libraries and runtimes. Currently, state-of-the-art proposals primarily re...	[]	Train
23,614	24	Title: Variations and Relaxations of Normalizing Flows Abstract: Normalizing Flows (NFs) describe a class of models that express a complex target distribution as the composition of a series of bijective transformations over a simpler base distribution. By limiting the space of candidate transformations to diffeomorphis...	[]	Train
23,615	30	Title: MasakhaNEWS: News Topic Classification for African languages Abstract: African languages are severely under-represented in NLP research due to lack of datasets covering several NLP tasks. While there are individual language specific datasets that are being expanded to different tasks, only a handful of NLP tasks...	[ 17952, 20226, 18324, 5717, 39291 ]	Train
23,616	17	Title: Reprogramming Audio-driven Talking Face Synthesis into Text-driven Abstract: In this paper, we propose a method to reprogram pre-trained audio-driven talking face synthesis models to be able to operate with text inputs. As the audio-driven talking face synthesis model takes speech audio as inputs, in order to ge...	[ 11037 ]	Test
23,617	16	Title: Mask-Attention-Free Transformer for 3D Instance Segmentation Abstract: Recently, transformer-based methods have dominated 3D instance segmentation, where mask attention is commonly involved. Specifically, object queries are guided by the initial instance masks in the first cross-attention, and then iteratively r...	[ 35754, 5766, 36551 ]	Train
23,618	16	Title: S4M: Generating Radiology Reports by A Single Model for Multiple Body Parts Abstract: In this paper, we seek to design a report generation model that is able to generate reasonable reports even given different images of various body parts. We start by directly merging multiple datasets and training a single repo...	[ 10624, 37496, 44384 ]	Train
23,619	16	Title: Exploring Transformers for Open-world Instance Segmentation Abstract: Open-world instance segmentation is a rising task, which aims to segment all objects in the image by learning from a limited number of base-category objects. This task is challenging, as the number of unseen categories could be hundreds of tim...	[ 23570, 8957, 11999 ]	Validation
23,620	39	Title: Hypergraph Horn functions Abstract: Horn functions form a subclass of Boolean functions possessing interesting structural and computational properties. These functions play a fundamental role in algebra, artiﬁcial intelligence, combinatorics, computer science, database theory, and logic. In the present paper, we...	[]	Validation
23,621	24	Title: Automated classification of pre-defined movement patterns: A comparison between GNSS and UWB technology Abstract: Advanced real-time location systems (RTLS) allow for collecting spatio-temporal data from human movement behaviours. Tracking individuals in small areas such as schoolyards or nursing homes might imp...	[]	Train
23,622	30	Title: Characterizing Political Bias in Automatic Summaries: A Case Study of Trump and Biden Abstract: Growing literature has shown that powerful NLP systems may encode social biases; however, the political bias of summarization models remains relatively unknown. In this work, we use an entity replacement method to inv...	[]	Train
23,623	30	Title: On the Efficacy of Sampling Adapters Abstract: Sampling-based decoding strategies are widely employed for generating text from probabilistic models, yet standard ancestral sampling often results in text that is degenerate or incoherent. To alleviate this issue, various modifications to a model’s sampling distrib...	[ 33220 ]	Validation
23,624	3	Title: Equitable Network-Aware Decarbonization of Residential Heating at City Scale Abstract: Residential heating, primarily powered by natural gas, accounts for a significant portion of residential sector energy use and carbon emissions in many parts of the world. Hence, there is a push towards decarbonizing residenti...	[]	Train
23,625	30	Title: Does Vision Accelerate Hierarchical Generalization of Neural Language Learners? Abstract: Neural language models (LMs) are arguably less data-efficient than humans -- why does this gap occur? In this study, we hypothesize that this gap stems from the learners' accessibility to modalities other than text, specifi...	[]	Train
23,626	24	Title: Pre-Training Protein Encoder via Siamese Sequence-Structure Diffusion Trajectory Prediction Abstract: Self-supervised pre-training methods on proteins have recently gained attention, with most approaches focusing on either protein sequences or structures, neglecting the exploration of their joint distribution, w...	[]	Train
23,627	16	Title: ABAW: Valence-Arousal Estimation, Expression Recognition, Action Unit Detection & Emotional Reaction Intensity Estimation Challenges Abstract: The 5th ABAW Competition is part of the respective Workshop held in conjunction with IEEE CVPR 2023 and is a continuation of the Competitions held at ECCV 2022, IEEE CVPR...	[ 38944, 15426, 23458, 1574, 39782, 32166, 17321, 16586, 13419, 41354, 13234, 2323, 41556, 24856, 1305, 33403, 26844, 34718 ]	Train
23,628	30	Title: Leveraging Synthetic Targets for Machine Translation Abstract: In this work, we provide a recipe for training machine translation models in a limited resource setting by leveraging synthetic target data generated using a large pre-trained model. We show that consistently across different benchmarks in bilingual,...	[]	Train
23,629	31	Title: Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting Abstract: Ranking documents using Large Language Models (LLMs) by directly feeding the query and candidate documents into the prompt is an interesting and practical problem. However, there has been limited success so far, as researc...	[ 67, 39, 29223, 13225, 18635, 33676, 397, 4270, 7344, 9012, 1909, 29205, 24503, 29753, 45181, 23102 ]	Train
23,630	24	Title: Balancing Explainability-Accuracy of Complex Models Abstract: Explainability of AI models is an important topic that can have a significant impact in all domains and applications from autonomous driving to healthcare. The existing approaches to explainable AI (XAI) are mainly limited to simple machine learning a...	[]	Train
23,631	30	Title: Better Zero-Shot Reasoning with Self-Adaptive Prompting Abstract: Modern large language models (LLMs) have demonstrated impressive capabilities at sophisticated tasks, often through step-by-step reasoning similar to humans. This is made possible by their strong few and zero-shot abilities -- they can effectively...	[ 39439, 7127 ]	Train
23,632	16	Title: Virtual Sparse Convolution for Multimodal 3D Object Detection Abstract: Recently, virtuall pseudo-point-based 3D object detection that seamlessly fuses RGB images and LiDAR data by depth completion has gained great attention. However, virtual points generated from an image are very dense, introducing a huge amou...	[ 15120, 9126 ]	Validation
23,633	16	Title: PSLT: A Light-Weight Vision Transformer With Ladder Self-Attention and Progressive Shift Abstract: Vision Transformer (ViT) has shown great potential for various visual tasks due to its ability to model long-range dependency. However, ViT requires a large amount of computing resource to compute the global self-a...	[]	Test
23,634	8	Title: Multipower‐level Q‐learning algorithm for random access in nonorthogonal multiple access massive machine‐type communications systems Abstract: The massive machine‐type communications (mMTC) service will be part of new services planned to integrate the beyond fifth generation of wireless communication. In mMTC, t...	[]	Train
23,635	4	Title: From Lemons to Peaches: Improving Security ROI through Security Chaos Engineering Abstract: Traditional information security presents a poor ROI: payoffs only manifest when attacks are successfully prevented. In a reality where attacks are inevitable, subpar returns are therefore inevitable. The emerging paradig...	[]	Train
23,636	15	Title: Harvesting L2 Caches in Server Processors Abstract: We make three observations in modern processors: (1) LLC capacity is getting larger (up to 1GB); (2) core counts are increasing (up to 128 cores), accumulating a more significant amount of private L2 cache capacity on the chip; and (3) overall processor utiliza...	[]	Train
23,637	16	Title: Image Vectorization: a Review Abstract: Nowadays, there are many diffusion and autoregressive models that show impressive results for generating images from text and other input domains. However, these methods are not intended for ultra-high-resolution image synthesis. Vector graphics are devoid of this disadvan...	[ 15133 ]	Train
23,638	16	Title: A Hierarchical Representation Network for Accurate and Detailed Face Reconstruction from In-The-Wild Images Abstract: Limited by the nature of the low-dimensional representational capacity of 3DMM, most of the 3DMM-based face reconstruction (FR) methods fail to recover high-frequency facial details, such as wrin...	[ 43781, 37670, 39339, 23468, 25838, 21630 ]	Validation
23,639	20	Title: New Approximation Algorithms for Touring Regions Abstract: We analyze the touring regions problem: find a ($1+\epsilon$)-approximate Euclidean shortest path in $d$-dimensional space that starts at a given starting point, ends at a given ending point, and visits given regions $R_1, R_2, R_3, \dots, R_n$ in that o...	[]	Train
23,640	25	Title: HierVST: Hierarchical Adaptive Zero-shot Voice Style Transfer Abstract: Despite rapid progress in the voice style transfer (VST) field, recent zero-shot VST systems still lack the ability to transfer the voice style of a novel speaker. In this paper, we present HierVST, a hierarchical adaptive end-to-end zero-sh...	[]	Train
23,641	10	Title: Adaptive ResNet Architecture for Distributed Inference in Resource-Constrained IoT Systems Abstract: As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. Therefore, the concept of distributed inference is essential to ...	[]	Validation
23,642	24	Title: Designing Optimal Behavioral Experiments Using Machine Learning Abstract: Computational models are powerful tools for understanding human cognition and behavior. They let us express our theories clearly and precisely, and offer predictions that can be subtle and often counter-intuitive. However, this same richne...	[ 8914 ]	Validation
23,643	2	Title: Polynomial Time and Dependent Types Abstract: We combine dependent types with linear type systems that soundly and completely capture polynomial time computation. We explore two systems for capturing polynomial time: one system that disallows construction of iterable data, and one, based on the LFPL system of Ma...	[]	Train
23,644	23	Title: NeuroCodeBench: a plain C neural network benchmark for software verification Abstract: Safety-critical systems with neural network components require strong guarantees. While existing neural network verification techniques have shown great progress towards this goal, they cannot prove the absence of software fau...	[ 18194 ]	Train
23,645	24	Title: Distributed Variational Inference for Online Supervised Learning Abstract: Developing efficient solutions for inference problems in intelligent sensor networks is crucial for the next generation of location, tracking, and mapping services. This paper develops a scalable distributed probabilistic inference algori...	[]	Train
23,646	24	Title: Weakly Supervised Anomaly Detection: A Survey Abstract: Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news. However, obtaining complete, accurate, and precise labels for AD tasks can be...	[ 43488, 45814, 21654, 7351, 4698 ]	Validation
23,647	16	Title: Lossy and Lossless (L2) Post-training Model Size Compression Abstract: Deep neural networks have delivered remarkable performance and have been widely used in various visual tasks. However, their huge size causes significant inconvenience for transmission and storage. Many previous studies have explored model si...	[ 923 ]	Test
23,648	31	Title: Fairness-aware Cross-Domain Recommendation Abstract: Cross-Domain Recommendation (CDR) is an effective way to alleviate the cold-start problem. However, previous work severely ignores fairness and bias when learning the mapping function, which is used to obtain the representations for fresh users in the target d...	[]	Train
23,649	16	Title: LLA-FLOW: A Lightweight Local Aggregation on Cost Volume for Optical Flow Estimation Abstract: Lack of texture often causes ambiguity in matching, and handling this issue is an important challenge in optical flow estimation. Some methods insert stacked transformer modules that allow the network to use global inf...	[]	Train
23,650	24	Title: Explainable, Interpretable & Trustworthy AI for Intelligent Digital Twin: Case Study on Remaining Useful Life Abstract: Machine learning (ML) and Artificial Intelligence (AI) are increasingly used in energy and engineering systems, but these models must be fair, unbiased, and explainable. It is critical to have ...	[ 19136 ]	Train
23,651	24	Title: Learning representations by forward-propagating errors Abstract: Back-propagation (BP) is widely used learning algorithm for neural network optimization. However, BP requires enormous computation cost and is too slow to train in central processing unit (CPU). Therefore current neural network optimizaiton is perf...	[]	Test
23,652	24	Title: A Probabilistic Approach to Self-Supervised Learning using Cyclical Stochastic Gradient MCMC Abstract: In this paper we present a practical Bayesian self-supervised learning method with Cyclical Stochastic Gradient Hamiltonian Monte Carlo (cSGHMC). Within this framework, we place a prior over the parameters of a...	[]	Test
23,653	3	Title: Ghosting the Machine: Judicial Resistance to a Recidivism Risk Assessment Instrument Abstract: Recidivism risk assessment instruments are presented as an ‘evidence-based’ strategy for criminal justice reform – a way of increasing consistency in sentencing, replacing cash bail, and reducing mass incarceration. In...	[]	Validation
23,654	30	Title: Should We Attend More or Less? Modulating Attention for Fairness Abstract: The abundance of annotated data in natural language processing (NLP) poses both opportunities and challenges. While it enables the development of high-performing models for a variety of tasks, it also poses the risk of models learning har...	[]	Train
23,655	30	Title: Adapting a Language Model While Preserving its General Knowledge Abstract: Domain-adaptive pre-training (or DA-training for short), also known as post-training, aimsto train a pre-trained general-purpose language model (LM) using an unlabeled corpus of aparticular domain to adapt the LM so that end-tasks in the ...	[ 17724, 42509, 21407 ]	Train
23,656	30	Title: Evaluating Transformer's Ability to Learn Mildly Context-Sensitive Languages Abstract: Despite that Transformers perform well in NLP tasks, recent studies suggest that self-attention is theoretically limited in learning even some regular and context-free languages. These findings motivated us to think about thei...	[ 27899 ]	Train
23,657	30	Title: Revisiting Automated Prompting: Are We Actually Doing Better? Abstract: Current literature demonstrates that Large Language Models (LLMs) are great few-shot learners, and prompting significantly increases their performance on a range of downstream tasks in a few-shot learning setting. An attempt to automate huma...	[]	Train
23,658	21	Title: Real-Time Adaptive Abstraction and Approximation Using Validity Frames - an Experience Report Abstract: Designing a Cyber-Physical System (CPS), including modeling the control components and services, is a challenging task. Using models and simulations during run-time is crucial for successfully implementing adv...	[]	Train
23,659	25	Title: Multi-Modality in Music: Predicting Emotion in Music from High-Level Audio Features and Lyrics Abstract: This paper aims to test whether a multi-modal approach for music emotion recognition (MER) performs better than a uni-modal one on high-level song features and lyrics. We use 11 song features retrieved from t...	[]	Test
23,660	30	Title: MTTN: Multi-Pair Text to Text Narratives for Prompt Generation Abstract: The increased interest in diffusion models has opened up opportunities for advancements in generative text modeling. These models can produce impressive images when given a well-crafted prompt, but creating a powerful or meaningful prompt c...	[]	Train
23,661	7	Title: Conditional variational autoencoder with Gaussian process regression recognition for parametric models Abstract: In this article, we present a data-driven method for parametric models with noisy observation data. Gaussian process regression based reduced order modeling (GPR-based ROM) can realize fast online pre...	[]	Train
23,662	36	Title: Efficient Last-iterate Convergence Algorithms in Solving Games Abstract: No-regret algorithms are popular for learning Nash equilibrium (NE) in two-player zero-sum normal-form games (NFGs) and extensive-form games (EFGs). Many recent works consider the last-iterate convergence no-regret algorithms. Among them, t...	[]	Train
23,663	16	Title: Improved Flood Insights: Diffusion-Based SAR to EO Image Translation Abstract: Driven by rapid climate change, the frequency and intensity of flood events are increasing. Electro-Optical (EO) satellite imagery is commonly utilized for rapid response. However, its utilities in flood situations are hampered by iss...	[ 8257 ]	Validation
23,664	10	Title: ExplainableFold: Understanding AlphaFold Prediction with Explainable AI Abstract: This paper presents ExplainableFold (xFold), which is an Explainable AI framework for protein structure prediction. Despite the success of AI-based methods such as AlphaFold (αFold) in this field, the underlying reasons for their p...	[ 28900 ]	Train
23,665	2	Title: On Statman's Finite Completeness Theorem Abstract: Abstract : We give a complete self-contained proof of Statman's finite completeness theorem and of a corollary of this theorem stating that the Lambda- definability conjecture implies the higher-order matching conjecture.	[ 44813 ]	Train
23,666	27	Title: A Vision-Based Algorithm for a Path Following Problem Abstract: A novel prize-winner algorithm designed for a path following problem within the Unmanned Aerial Vehicle (UAV) field is presented in this paper. The proposed approach exploits the advantages offered by the pure pursuing algorithm to set up an intuiti...	[ 23181, 19735 ]	Train
23,667	4	Title: Breaking Bad: Quantifying the Addiction of Web Elements to JavaScript Abstract: While JavaScript established itself as a cornerstone of the modern web, it also constitutes a major tracking and security vector, thus raising critical privacy and security concerns. In this context, some browser extensions propose t...	[]	Test
23,668	16	Title: Style-A-Video: Agile Diffusion for Arbitrary Text-based Video Style Transfer Abstract: Large-scale text-to-video diffusion models have demonstrated an exceptional ability to synthesize diverse videos. However, due to the lack of extensive text-to-video datasets and the necessary computational resources for train...	[ 20960, 42272 ]	Train
23,669	16	Title: Pix2Video: Video Editing using Image Diffusion Abstract: Image diffusion models, trained on massive image collections, have emerged as the most versatile image generator model in terms of quality and diversity. They support inverting real images and conditional (e.g., text) generation, making them attractive for...	[ 11655, 40979, 21014, 34074, 4765, 40606, 42272, 13474, 7078, 38696, 12841, 7993, 9276, 25666, 28482, 1860, 29527, 40671, 2528, 3680, 34534, 10216, 14956, 15983, 35326 ]	Train
23,670	37	Title: The LDBC Financial Benchmark Abstract: The Linked Data Benchmark Council's Financial Benchmark (LDBC FinBench) is a new effort that defines a graph database benchmark targeting financial scenarios such as anti-fraud and risk control. The benchmark has one workload, the Transaction Workload, currently. It capture...	[]	Train
23,671	30	Title: Participatory Research as a Path to Community-Informed, Gender-Fair Machine Translation Abstract: Recent years have seen a strongly increased visibility of non-binary people in public discourse. Accordingly, considerations of gender-fair language go beyond a binary conception of male/female. However, language te...	[]	Train
23,672	26	Title: Opinion Mining from YouTube Captions Using ChatGPT: A Case Study of Street Interviews Polling the 2023 Turkish Elections Abstract: Opinion mining plays a critical role in understanding public sentiment and preferences, particularly in the context of political elections. Traditional polling methods, while useful,...	[ 22976, 15049, 29072, 13654, 39642, 1789, 39834 ]	Test
23,673	24	Title: Directed Scattering for Knowledge Graph-based Cellular Signaling Analysis Abstract: Directed graphs are a natural model for many phenomena, in particular scientific knowledge graphs such as molecular interaction or chemical reaction networks that define cellular signaling relationships. In these situations, sour...	[]	Train
23,674	8	Title: 56 Gbps PCB Design Strategies for Clean, Low-Skew Channels Abstract: Although next generation (>28 Gbps) SerDes standards have been contemplated for several years, it has not been clear whether PCB structures supporting 56 Gbps NRZ will be feasible and practical. In this paper, we assess a number of specific PCB...	[ 38346 ]	Train
23,675	28	Title: Ordinary Differential Equation-based Sparse Signal Recovery Abstract: This study investigates the use of continuous-time dynamical systems for sparse signal recovery. The proposed dynamical system is in the form of a nonlinear ordinary differential equation (ODE) derived from the gradient flow of the Lasso objec...	[ 8807 ]	Validation
23,676	31	Title: Differentiable Retrieval Augmentation via Generative Language Modeling for E-commerce Query Intent Classification Abstract: Retrieval augmentation, which enhances downstream models by a knowledge retriever and an external corpus instead of by merely increasing the number of model parameters, has been successfull...	[ 15187 ]	Train
23,677	16	Title: Understanding the Latent Space of Diffusion Models through the Lens of Riemannian Geometry Abstract: Despite the success of diffusion models (DMs), we still lack a thorough understanding of their latent space. To understand the latent space $\mathbf{x}_t \in \mathcal{X}$, we analyze them from a geometrical persp...	[ 37254, 16103, 14490, 43867, 13310 ]	Validation

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