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
42,078	16	Title: DiffBlender: Scalable and Composable Multimodal Text-to-Image Diffusion Models Abstract: The recent progress in diffusion-based text-to-image generation models has significantly expanded generative capabilities via conditioning the text descriptions. However, since relying solely on text prompts is still restric...	[ 34074, 11820, 15983, 34009, 41146 ]	Train
42,079	23	Title: TestLab: An Intelligent Automated Software Testing Framework Abstract: The prevalence of software systems has become an integral part of modern-day living. Software usage has increased significantly, leading to its growth in both size and complexity. Consequently, software development is becoming a more time-con...	[ 29858 ]	Train
42,080	16	Title: Skinned Motion Retargeting with Residual Perception of Motion Semantics & Geometry Abstract: A good motion retargeting cannot be reached without reasonable consideration of source-target differences on both the skeleton and shape geometry levels. In this work, we propose a novel Residual RETargeting network (R2E...	[]	Train
42,081	36	Title: Base Fee Manipulation In Ethereum's EIP-1559 Transaction Fee Mechanism Abstract: In 2021 Ethereum adjusted the transaction pricing mechanism by implementing EIP-1559, which introduces the base fee - a network fee that is burned and dynamically adjusts to the network demand. The authors of the Ethereum Improvemen...	[ 22655 ]	Train
42,082	16	Title: HST-MRF: Heterogeneous Swin Transformer with Multi-Receptive Field for Medical Image Segmentation Abstract: The Transformer has been successfully used in medical image segmentation due to its excellent long-range modeling capabilities. However, patch segmentation is necessary when building a Transformer class mo...	[]	Validation
42,083	30	Title: Perturbation-based QE: An Explainable, Unsupervised Word-level Quality Estimation Method for Blackbox Machine Translation Abstract: Quality Estimation (QE) is the task of predicting the quality of Machine Translation (MT) system output, without using any gold-standard translation references. State-of-the-art QE ...	[ 27340, 24150 ]	Test
42,084	27	Title: Probabilistic Uncertainty Quantification of Prediction Models with Application to Visual Localization Abstract: The uncertainty quantification of prediction models (e.g., neural networks) is crucial for their adoption in many robotics applications. This is arguably as important as making accurate predictions, es...	[]	Test
42,085	24	Title: Framework for Certification of AI-Based Systems Abstract: The current certification process for aerospace software is not adapted to"AI-based"algorithms such as deep neural networks. Unlike traditional aerospace software, the precise parameters optimized during neural network training are as important as (or mor...	[]	Train
42,086	30	Title: Transformed Protoform Reconstruction Abstract: Protoform reconstruction is the task of inferring what morphemes or words appeared like in the ancestral languages of a set of daughter languages. Meloni et al (2021) achieved the state-of-the-art on Latin protoform reconstruction with an RNN-based encoder-decoder w...	[]	Test
42,087	24	Title: Benign Overfitting in Deep Neural Networks under Lazy Training Abstract: This paper focuses on over-parameterized deep neural networks (DNNs) with ReLU activation functions and proves that when the data distribution is well-separated, DNNs can achieve Bayes-optimal test error for classification while obtaining (...	[]	Train
42,088	16	Title: MetaHead: An Engine to Create Realistic Digital Head Abstract: Collecting and labeling training data is one important step for learning-based methods because the process is time-consuming and biased. For face analysis tasks, although some generative models can be used to generate face data, they can only achieve...	[]	Train
42,089	30	Title: An Overview on Language Models: Recent Developments and Outlook Abstract: Language modeling studies the probability distributions over strings of texts. It is one of the most fundamental tasks in natural language processing (NLP). It has been widely used in text generation, speech recognition, machine translatio...	[ 17248, 12001, 40135, 12013, 11190, 26974 ]	Train
42,090	10	Title: Minimizing Return Gaps with Discrete Communications in Decentralized POMDP Abstract: Communication is crucial for solving cooperative Multi-Agent Reinforcement Learning tasks in Partially-Observable Markov Decision Processes. Existing works often rely on black-box methods to encode local information/features int...	[ 13714, 16084, 4525 ]	Train
42,091	24	Title: Catapults in SGD: spikes in the training loss and their impact on generalization through feature learning Abstract: In this paper, we first present an explanation regarding the common occurrence of spikes in the training loss when neural networks are trained with stochastic gradient descent (SGD). We provide evi...	[]	Train
42,092	34	Title: Differentially Private Continual Releases of Streaming Frequency Moment Estimations Abstract: The streaming model of computation is a popular approach for working with large-scale data. In this setting, there is a stream of items and the goal is to compute the desired quantities (usually data statistics) while m...	[ 11074, 34404, 9000, 6740, 16373, 11128 ]	Validation
42,093	16	Title: Backdoor Defense via Adaptively Splitting Poisoned Dataset Abstract: Backdoor defenses have been studied to alleviate the threat of deep neural networks (DNNs) being backdoor attacked and thus maliciously altered. Since DNNs usually adopt some external training data from an untrusted third party, a robust backdo...	[ 1569, 26251, 28441 ]	Train
42,094	16	Title: Learning Cross Space Mapping via DNN Using Large Scale Click-Through Logs Abstract: The gap between low-level visual signals and high-level semantics has been progressively bridged by continuous development of deep neural network (DNN). With recent progress of DNN, almost all image classification tasks have achi...	[]	Test
42,095	16	Title: ConvFormer: Parameter Reduction in Transformer Models for 3D Human Pose Estimation by Leveraging Dynamic Multi-Headed Convolutional Attention Abstract: Recently, fully-transformer architectures have replaced the defacto convolutional architecture for the 3D human pose estimation task. In this paper we propose \t...	[]	Train
42,096	24	Title: Goal-oriented inference of environment from redundant observations Abstract: The agent learns to organize decision behavior to achieve a behavioral goal, such as reward maximization, and reinforcement learning is often used for this optimization. Learning an optimal behavioral strategy is difficult under the unc...	[]	Train
42,097	24	Title: Systematic analysis of the impact of label noise correction on ML Fairness Abstract: Arbitrary, inconsistent, or faulty decision-making raises serious concerns, and preventing unfair models is an increasingly important challenge in Machine Learning. Data often reflect past discriminatory behavior, and models tra...	[]	Test
42,098	24	Title: GraphSHA: Synthesizing Harder Samples for Class-Imbalanced Node Classification Abstract: Class imbalance is the phenomenon that some classes have much fewer instances than others, which is ubiquitous in real-world graph-structured scenarios. Recent studies find that off-the-shelf Graph Neural Networks (GNNs) wou...	[]	Test
42,099	16	Title: Towards Precision in Appearance-based Gaze Estimation in the Wild Abstract: Appearance-based gaze estimation systems have shown great progress recently, yet the performance of these techniques depend on the datasets used for training. Most of the existing gaze estimation datasets setup in interactive settings we...	[]	Validation
42,100	16	Title: DDRF: Denoising Diffusion Model for Remote Sensing Image Fusion Abstract: Denosing diffusion model, as a generative model, has received a lot of attention in the field of image generation recently, thanks to its powerful generation capability. However, diffusion models have not yet received sufficient research i...	[ 8234, 42221, 34227, 32314, 34356, 43478, 34074 ]	Train
42,101	5	Title: When Edge Meets FaaS: Opportunities and Challenges Abstract: The proliferation of edge devices and the rapid growth of IoT data have called forth the edge computing paradigm. Function-as-a-service (FaaS) is a promising computing paradigm to realize edge computing. This paper explores the feasibility and advantag...	[]	Validation
42,102	27	Title: Co-manipulation of soft-materials estimating deformation from depth images Abstract: Human-robot co-manipulation of soft materials, such as fabrics, composites, and sheets of paper/cardboard, is a challenging operation that presents several relevant industrial applications. Estimating the deformation state of th...	[]	Validation
42,103	30	Title: Vistaar: Diverse Benchmarks and Training Sets for Indian Language ASR Abstract: Improving ASR systems is necessary to make new LLM-based use-cases accessible to people across the globe. In this paper, we focus on Indian languages, and make the case that diverse benchmarks are required to evaluate and improve ASR...	[ 33537 ]	Train
42,104	16	Title: PhotoVerse: Tuning-Free Image Customization with Text-to-Image Diffusion Models Abstract: Personalized text-to-image generation has emerged as a powerful and sought-after tool, empowering users to create customized images based on their specific concepts and prompts. However, existing approaches to personalizati...	[ 7458, 30402, 42149, 20687, 17647, 4084, 28532, 26809, 34074, 18205 ]	Train
42,105	24	Title: Learning from Power Signals: An Automated Approach to Electrical Disturbance Identification Within a Power Transmission System Abstract: As power quality becomes a higher priority in the electric utility industry, the amount of disturbance event data continues to grow. Utilities do not have the required personne...	[]	Train
42,106	10	Title: An End-to-End Approach for Online Decision Mining and Decision Drift Analysis in Process-Aware Information Systems: Extended Version Abstract: Decision mining enables the discovery of decision rules from event logs or streams, and constitutes an important part of in-depth analysis and optimisation of business pr...	[]	Validation
42,107	16	Title: Learning Differentially Private Probabilistic Models for Privacy-Preserving Image Generation Abstract: A number of deep models trained on high-quality and valuable images have been deployed in practical applications, which may pose a leakage risk of data privacy. Learning differentially private generative models...	[]	Validation
42,108	24	Title: K-SpecPart: Supervised embedding algorithms and cut overlay for improved hypergraph partitioning Abstract: State-of-the-art hypergraph partitioners follow the multilevel paradigm that constructs multiple levels of progressively coarser hypergraphs that are used to drive cut refinement on each level of the hierar...	[]	Train
42,109	16	Title: Improving the Transferability of Adversarial Examples via Direction Tuning Abstract: In the transfer-based adversarial attacks, adversarial examples are only generated by the surrogate models and achieve effective perturbation in the victim models. Although considerable efforts have been developed on improving t...	[ 4052, 21661 ]	Train
42,110	16	Title: Frequency-Based Vulnerability Analysis of Deep Learning Models against Image Corruptions Abstract: Deep learning models often face challenges when handling real-world image corruptions. In response, researchers have developed image corruption datasets to evaluate the performance of deep neural networks in handli...	[ 4643 ]	Train
42,111	10	Title: Self-consistency for open-ended generations Abstract: Large Language Models (LLMs) can exhibit considerable variation in the quality of their sampled outputs. Reranking and selecting the best generation from the sampled set is a popular way of obtaining strong gains in generation quality. In this paper, we prese...	[ 38575, 12741, 25751 ]	Test
42,112	8	Title: Fine-grained Spatio-Temporal Distribution Prediction of Mobile Content Delivery in 5G Ultra-Dense Networks Abstract: The 5G networks have extensively promoted the growth of mobile users and novel applications, and with the skyrocketing user requests for a large amount of popular content, the consequent content d...	[ 30925 ]	Train
42,113	30	Title: CollabKG: A Learnable Human-Machine-Cooperative Information Extraction Toolkit for (Event) Knowledge Graph Construction Abstract: In order to construct or extend entity-centric and event-centric knowledge graphs (KG and EKG), the information extraction (IE) annotation toolkit is essential. However, existing IE t...	[ 31189 ]	Test
42,114	24	Title: Who You Play Affects How You Play: Predicting Sports Performance Using Graph Attention Networks With Temporal Convolution Abstract: This study presents a novel deep learning method, called GATv2-GCN, for predicting player performance in sports. To construct a dynamic player interaction graph, we leverage player ...	[ 32869 ]	Validation
42,115	16	Title: CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation Abstract: Semi-supervised domain adaptation (SSDA) adapts a learner to a new domain by effectively utilizing source domain data and a few labeled target samples. It is a practical yet under-investigated research topic. In this pa...	[ 14560 ]	Train
42,116	13	Title: Sparse Mutation Decompositions: Fine Tuning Deep Neural Networks with Subspace Evolution Abstract: Neuroevolution is a promising area of research that combines evolutionary algorithms and neural networks. A popular subclass of neuroevolutionary methods, called evolution strategies, rely on dense noise perturbati...	[]	Train
42,117	30	Title: Gradient Sparsification For Masked Fine-Tuning of Transformers Abstract: Fine-tuning pretrained self-supervised language models is widely adopted for transfer learning to downstream tasks. Fine-tuning can be achieved by freezing gradients of the pretrained network and only updating gradients of a newly added cla...	[]	Train
42,118	24	Title: Bayesian Optimisation of Functions on Graphs Abstract: The increasing availability of graph-structured data motivates the task of optimising over functions defined on the node set of graphs. Traditional graph search algorithms can be applied in this case, but they may be sample-inefficient and do not make use of...	[ 10106 ]	Train
42,119	27	Title: Spatio-Temporal Transformer-Based Reinforcement Learning for Robot Crowd Navigation Abstract: The social robot navigation is an open and challenging problem. In existing work, separate modules are used to capture spatial and temporal features, respectively. However, such methods lead to extra difficulties in imp...	[]	Validation
42,120	30	Title: LexGPT 0.1: pre-trained GPT-J models with Pile of Law Abstract: This research aims to build generative language models specialized for the legal domain. The manuscript presents the development of LexGPT models based on GPT-J models and pre-trained with Pile of Law. The foundation model built in this manuscript i...	[ 38424, 8498 ]	Train
42,121	37	Title: PG-Triggers: Triggers for Property Graphs Abstract: Graph databases are emerging as the leading data management technology for storing large knowledge graphs; significant efforts are ongoing to produce new standards (such as the Graph Query Language, GQL), as well as enrich them with properties, types, schemas, ...	[]	Validation
42,122	16	Title: How far Generated Data Can Impact Neural Networks Performance? Abstract: The success of deep learning models depends on the size and quality of the dataset to solve certain tasks. Here, we explore how far generated data can aid real data in improving the performance of Neural Networks. In this work, we consider ...	[]	Validation
42,123	4	Title: A Survey of Security Concerns and Countermeasures in Modern Micro-architectures with Transient Execution Abstract: nan	[]	Train
42,124	10	Title: The Structure and Dynamics of Knowledge Graphs, with Superficiality Abstract: Large knowledge graphs combine human knowledge garnered from projects ranging from academia and institutions to enterprises and crowdsourcing. Within such graphs, each relationship between two nodes represents a basic fact involving th...	[]	Train
42,125	16	Title: GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting Abstract: Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community. However, catastrophic forgetting caused by data heterogenei...	[ 14618, 12027 ]	Train
42,126	27	Title: LLM-BRAIn: AI-driven Fast Generation of Robot Behaviour Tree based on Large Language Model Abstract: This paper presents a novel approach in autonomous robot control, named LLM-BRAIn, that makes possible robot behavior generation, based on operator's commands. LLM-BRAIn is a transformer-based Large Language Mode...	[ 17508, 13700, 22150, 10163, 13564 ]	Test
42,127	24	Title: A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition Abstract: Recently, physiological data such as electroencephalography (EEG) signals have attracted significant attention in affective computing. In this context, the main goal is to design an automa...	[]	Validation
42,128	16	Title: Swin3D: A Pretrained Transformer Backbone for 3D Indoor Scene Understanding Abstract: The use of pretrained backbones with fine-tuning has been successful for 2D vision and natural language processing tasks, showing advantages over task-specific networks. In this work, we introduce a pretrained 3D backbone, call...	[ 13664, 7690, 26380, 5878 ]	Test
42,129	30	Title: Can Programming Languages Boost Each Other via Instruction Tuning? Abstract: When human programmers have mastered a programming language, it would be easier when they learn a new programming language. In this report, we focus on exploring whether programming languages can boost each other during the instruction ...	[ 14592, 2980, 31145, 15952, 33490, 14869 ]	Train
42,130	27	Title: Upper-limb Geometric MyoPassivity Map for Physical Human-Robot Interaction Abstract: The intrinsic biomechanical characteristic of the human upper limb plays a central role in absorbing the interactive energy during physical human-robot interaction (pHRI). We have recently shown that based on the concept of “Exc...	[]	Train
42,131	24	Title: Optimal Transport Model Distributional Robustness Abstract: Distributional robustness is a promising framework for training deep learning models that are less vulnerable to adversarial examples and data distribution shifts. Previous works have mainly focused on exploiting distributional robustness in data space....	[]	Train
42,132	24	Title: Sampling from Gaussian Process Posteriors using Stochastic Gradient Descent Abstract: Gaussian processes are a powerful framework for quantifying uncertainty and for sequential decision-making but are limited by the requirement of solving linear systems. In general, this has a cubic cost in dataset size and is s...	[ 1961 ]	Train
42,133	10	Title: Emergent collective intelligence from massive-agent cooperation and competition Abstract: Inspired by organisms evolving through cooperation and competition between different populations on Earth, we study the emergence of artificial collective intelligence through massive-agent reinforcement learning. To this e...	[ 23218 ]	Train
42,134	24	Title: Effective Bilevel Optimization via Minimax Reformulation Abstract: Bilevel optimization has found successful applications in various machine learning problems, including hyper-parameter optimization, data cleaning, and meta-learning. However, its huge computational cost presents a significant challenge for its u...	[ 13700 ]	Train
42,135	10	Title: Beneficent Intelligence: A Capability Approach to Modeling Benefit, Assistance, and Associated Moral Failures through AI Systems Abstract: The prevailing discourse around AI ethics lacks the language and formalism necessary to capture the diverse ethical concerns that emerge when AI systems interact with individ...	[]	Test
42,136	24	Title: Scalability of Message Encoding Techniques for Continuous Communication Learned with Multi-Agent Reinforcement Learning Abstract: Many multi-agent systems require inter-agent communication to properly achieve their goal. By learning the communication protocol alongside the action protocol using multi-agent reinf...	[]	Train
42,137	16	Title: Cocktail: Mixing Multi-Modality Controls for Text-Conditional Image Generation Abstract: Text-conditional diffusion models are able to generate high-fidelity images with diverse contents. However, linguistic representations frequently exhibit ambiguous descriptions of the envisioned objective imagery, requiring ...	[ 37152, 44711, 36168, 41146, 11820, 15983, 5583, 34074, 3067 ]	Train
42,138	11	Title: Cooperative Filtering with Range Measurements: A Distributed Constrained Zonotopic Method Abstract: This article studies the distributed estimation problem of a multi-agent system with bounded absolute and relative range measurements. Parts of the agents are with high-accuracy absolute measurements, which are co...	[ 19016, 22167 ]	Train
42,139	30	Title: Serial Contrastive Knowledge Distillation for Continual Few-shot Relation Extraction Abstract: Continual few-shot relation extraction (RE) aims to continuously train a model for new relations with few labeled training data, of which the major challenges are the catastrophic forgetting of old relations and the ov...	[]	Test
42,140	24	Title: Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model Abstract: Cutting planes (cuts) are important for solving mixed-integer linear programs (MILPs), which formulate a wide range of important real-world applications. Cut selection -- which aims to select a proper subset of ...	[ 22256, 23807 ]	Train
42,141	24	Title: Are Defenses for Graph Neural Networks Robust? Abstract: A cursory reading of the literature suggests that we have made a lot of progress in designing effective adversarial defenses for Graph Neural Networks (GNNs). Yet, the standard methodology has a serious flaw - virtually all of the defenses are evaluated ag...	[ 1921, 35618, 3908, 20201, 31561, 25533, 13657, 39994, 38332, 6493 ]	Test
42,142	36	Title: Improving Approximation Guarantees for Maximin Share Abstract: We consider fair division of a set of indivisible goods among $n$ agents with additive valuations using the desirable fairness notion of maximin share (MMS). MMS is the most popular share-based notion, in which an agent finds an allocation fair to he...	[ 11338, 33924, 38845, 25118 ]	Train
42,143	24	Title: Achieving Sample and Computational Efficient Reinforcement Learning by Action Space Reduction via Grouping Abstract: Reinforcement learning often needs to deal with the exponential growth of states and actions when exploring optimal control in high-dimensional spaces (often known as the curse of dimensionality)....	[]	Train
42,144	24	Title: Hard Adversarial Example Mining for Improving Robust Fairness Abstract: Adversarial training (AT) is widely considered the state-of-the-art technique for improving the robustness of deep neural networks (DNNs) against adversarial examples (AE). Nevertheless, recent studies have revealed that adversarially traine...	[]	Validation
42,145	16	Title: SEGA: Instructing Diffusion using Semantic Dimensions Abstract: Text-to-image diffusion models have recently received a lot of interest for their astonishing ability to produce high-fidelity images from text only. However, achieving one-shot generation that aligns with the user's intent is nearly impossible, yet...	[ 15132, 37286, 39813, 45477, 13034, 32143, 10070, 40534, 16696, 9468, 15901, 7678 ]	Test
42,146	27	Title: SensorX2car: Sensors-to-car calibration for autonomous driving in road scenarios Abstract: Properly-calibrated sensors are the prerequisite for a dependable autonomous driving system. However, most prior methods focus on extrinsic calibration between sensors, and few focus on the misalignment between the sensors...	[]	Train
42,147	34	Title: Critical Relaxed Stable Matchings with Two-Sided Ties Abstract: We consider the stable marriage problem in the presence of ties in preferences and critical vertices. The input to our problem is a bipartite graph G = (A U B, E) where A and B denote sets of vertices which need to be matched. Each vertex has a pref...	[]	Train
42,148	28	Title: Robust Hybrid Transceiver Designs for Linear Decentralized Estimation in mmWave MIMO IoT Networks in the Face of Imperfect CSI Abstract: Hybrid transceivers are designed for linear decentralized estimation (LDE) in a mmWave multiple-input multiple-output (MIMO) IoT network (IoTNe). For a noiseless fusion center ...	[]	Validation
42,149	16	Title: Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models Abstract: Text-to-image personalization aims to teach a pre-trained diffusion model to reason about novel, user provided concepts, embedding them into new scenes guided by natural language prompts. However, current personalization appro...	[ 31109, 5223, 43911, 25739, 39340, 29389, 33261, 27059, 20852, 12116, 3031, 42104, 14047 ]	Validation
42,150	23	Title: What Happens When We Fuzz? Investigating OSS-Fuzz Bug History Abstract: BACKGROUND: Software engineers must be vigilant in preventing and correcting vulnerabilities and other critical bugs. In servicing this need, numerous tools and techniques have been developed to assist developers. Fuzzers, by autonomously ge...	[]	Train
42,151	24	Title: Towards Diverse and Coherent Augmentation for Time-Series Forecasting Abstract: Time-series data augmentation mitigates the issue of insufficient training data for deep learning models. Yet, existing augmentation methods are mainly designed for classification, where class labels can be preserved even if augmenta...	[]	Train
42,152	14	Title: Two Variants of Bézout Subresultants for Several Univariate Polynomials Abstract: nan	[]	Train
42,153	28	Title: Decentralized Caching under Nonuniform File Popularity and Size: Memory-Rate Tradeoff Characterization Abstract: This paper aims to characterize the memory-rate tradeoff for decentralized caching under nonuniform file popularity and size. We consider a recently proposed decentralized modified coded caching schem...	[]	Validation
42,154	16	Title: The Impact of Training Dataset Size and Ensemble Inference Strategies on Head and Neck Auto-Segmentation Abstract: Convolutional neural networks (CNNs) are increasingly being used to automate segmentation of organs-at-risk in radiotherapy. Since large sets of highly curated data are scarce, we investigated how m...	[]	Train
42,155	23	Title: Challenges of Producing Software Bill Of Materials for Java Abstract: Software bills of materials (SBOM) promise to become the backbone of software supply chain hardening. We deep-dive into 6 tools and the accuracy of the SBOMs they produce for complex open-source Java projects. Our novel insights reveal some ha...	[ 28536, 18146 ]	Train
42,156	3	Title: Algorithmic Unfairness through the Lens of EU Non-Discrimination Law: Or Why the Law is not a Decision Tree Abstract: Concerns regarding unfairness and discrimination in the context of artificial intelligence (AI) systems have recently received increased attention from both legal and computer science scholars. Y...	[]	Train
42,157	24	Title: Escaping the Sample Trap: Fast and Accurate Epistemic Uncertainty Estimation with Pairwise-Distance Estimators Abstract: This work introduces a novel approach for epistemic uncertainty estimation for ensemble models using pairwise-distance estimators (PaiDEs). These estimators utilize the pairwise-distance betwe...	[ 45272 ]	Validation
42,158	24	Title: eXplainable Artificial Intelligence on Medical Images: A Survey Abstract: Over the last few years, the number of works about deep learning applied to the medical field has increased enormously. The necessity of a rigorous assessment of these models is required to explain these results to all people involved in m...	[]	Validation
42,159	24	Title: T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification Abstract: Cancer is a complex disease characterized by uncontrolled cell growth and proliferation. T cell receptors (TCRs) are essential proteins for the adaptive immune system, and their specific recognition of antige...	[]	Validation
42,160	30	Title: The Extractive-Abstractive Axis: Measuring Content "Borrowing" in Generative Language Models Abstract: Generative language models produce highly abstractive outputs by design, in contrast to extractive responses in search engines. Given this characteristic of LLMs and the resulting implications for content Licen...	[ 5749, 13510, 22286 ]	Test
42,161	3	Title: More than programming? The impact of AI on work and skills Abstract: This chapter explores the ways in which organisational readiness and scientific advances in Artificial Intelligence have been affecting the demand for skills and their training in Australia and other nations leading in the promotion, use or dev...	[]	Test
42,162	16	Title: Relational Context Learning for Human-Object Interaction Detection Abstract: Recent state-of-the-art methods for HOI detection typically build on transformer architectures with two decoder branches, one for human-object pair detection and the other for interaction classification. Such disentangled transformers, ...	[]	Train
42,163	2	Title: Degrees of Second and Higher-Order Polynomials Abstract: Second-order polynomials generalize classical first-order ones in allowing for additional variables that range over functions rather than values. We are motivated by their applications in higher-order computational complexity theory, extending for example ...	[]	Validation
42,164	16	Title: Self-Training Guided Disentangled Adaptation for Cross-Domain Remote Sensing Image Semantic Segmentation Abstract: Deep convolutional neural networks (DCNNs) based remote sensing (RS) image semantic segmentation technology has achieved great success used in many real-world applications such as geographic element...	[]	Train
42,165	30	Title: Complex QA and language models hybrid architectures, Survey Abstract: This paper reviews the state-of-the-art of language models architectures and strategies for"complex"question-answering (QA, CQA, CPS) with a focus on hybridization. Large Language Models (LLM) are good at leveraging public data on standard pro...	[ 7936, 19720, 35595, 44173, 35607, 15004, 26673, 12851, 10165, 33464, 45242, 4027, 33220, 32966, 31431, 30026, 24275, 21461, 29419, 25847, 634, 21375 ]	Test
42,166	23	Title: Deep Learning Based Code Generation Methods: A Literature Review Abstract: Code Generation aims at generating relevant code fragments according to given natural language descriptions. In the process of software development, there exist a large number of repetitive and low-tech code writing tasks, so code generat...	[]	Train
42,167	16	Title: Deep Neural Networks in Video Human Action Recognition: A Review Abstract: Currently, video behavior recognition is one of the most foundational tasks of computer vision. The 2D neural networks of deep learning are built for recognizing pixel-level information such as images with RGB, RGB-D, or optical flow form...	[ 13328 ]	Train
42,168	16	Title: Face Inverse Rendering via Hierarchical Decoupling Abstract: Previous face inverse rendering methods often require synthetic data with ground truth and/or professional equipment like a lighting stage. However, a model trained on synthetic data or using pre-defined lighting priors is typically unable to generaliz...	[]	Validation
42,169	24	Title: Prompt Evolution for Generative AI: A Classifier-Guided Approach Abstract: Synthesis of digital artifacts conditioned on user prompts has become an important paradigm facilitating an explosion of use cases with generative AI. However, such models often fail to connect the generated outputs and desired target con...	[ 33608, 40915 ]	Validation
42,170	37	Title: Differential Privacy for Protecting Private Patterns in Data Streams Abstract: Complex event processing (CEP) is a powerful and increasingly more important tool to analyse data streams for Internet of Things (IoT) applications. These data streams often contain private information that requires proper protection....	[ 21839 ]	Test
42,171	28	Title: Non-Integer-Oversampling Digital Signal Processing for Coherent Passive Optical Networks Abstract: Beyond 100G passive optical networks (PONs) will be required to meet the ever-increasing traffic demand in the future. Coherent optical technologies are the competitive solutions for the future beyond 100G PON but ...	[]	Train
42,172	27	Title: Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains Abstract: In this paper we study the problem of learning multi-step dynamics prediction models (jumpy models) from unlabeled experience and their utility for fast inference of (high-level) plans in downstream tasks. In particular we propos...	[ 25582 ]	Train
42,173	24	Title: Neural Task Synthesis for Visual Programming Abstract: Generative neural models hold great promise in enhancing programming education by synthesizing new content for students. We seek to design neural models that can automatically generate programming tasks for a given specification in the context of visual prog...	[ 6844, 35580, 5157, 40166, 20892 ]	Validation
42,174	27	Title: Homography matrix based trajectory planning method for robot uncalibrated visual servoing Abstract: In view of the classical visual servoing trajectory planning method which only considers the camera trajectory, this paper proposes one homography matrix based trajectory planning method for robot uncalibrated vis...	[]	Test
42,175	6	Title: Revealing the Hidden Effects of Phishing Emails: An Analysis of Eye and Mouse Movements in Email Sorting Tasks Abstract: Users are the last line of defense as phishing emails pass filter mechanisms. At the same time, phishing emails are designed so that they are challenging to identify by users. To this end, att...	[]	Train
42,176	16	Title: Interpretable Out-Of-Distribution Detection Using Pattern Identification Abstract: Out-of-distribution (OoD) detection for data-based programs is a goal of paramount importance. Common approaches in the literature tend to train detectors requiring inside-of-distribution (in-distribution, or IoD) and OoD validati...	[ 31248 ]	Train
42,177	34	Title: A simple division-free algorithm for computing Pfaffians Abstract: We present a very simple algorithm for computing Pfaffians which uses no division operations. Essentially, it amounts to iterating matrix multiplication and truncation. Its complexity, for a $2n\times 2n$ matrix, is $O(nM(n))$, where $M(n)$ is th...	[]	Train

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