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
32,078	16	Title: Multi-view knowledge distillation transformer for human action recognition Abstract: Recently, Transformer-based methods have been utilized to improve the performance of human action recognition. However, most of these studies assume that multi-view data is complete, which may not always be the case in real-worl...	[]	Validation
32,079	31	Title: HAMUR: Hyper Adapter for Multi-Domain Recommendation Abstract: Multi-Domain Recommendation (MDR) has gained significant attention in recent years, which leverages data from multiple domains to enhance their performance concurrently.However, current MDR models are confronted with two limitations. Firstly, the maj...	[ 37200, 2212, 40743 ]	Train
32,080	30	Title: Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing Abstract: Interactive semantic parsing based on natural language (NL) feedback, where users provide feedback to correct the parser mistakes, has emerged as a more practical scenario than the traditional one-shot semantic parsing. How...	[ 1401, 22578, 37411, 17789 ]	Train
32,081	5	Title: A Case for Planetary Computing Abstract: We make a case for planetary computing: accessible, interoperable and extensible end-to-end systems infrastructure to process petabytes of global remote-sensing data for the scientific analysis of environmental action. We discuss some pressing scientific scenarios, survey...	[]	Test
32,082	16	Title: Spritz-PS: Validation of Synthetic Face Images Using a Large Dataset of Printed Documents Abstract: The capability of doing effective forensic analysis on printed and scanned (PS) images is essential in many applications. PS documents may be used to conceal the artifacts of images which is due to the synthetic n...	[]	Train
32,083	16	Title: Learning to Select Camera Views: Efficient Multiview Understanding at Few Glances Abstract: Multiview camera setups have proven useful in many computer vision applications for reducing ambiguities, mitigating occlusions, and increasing field-of-view coverage. However, the high computational cost associated with ...	[]	Train
32,084	30	Title: Distinguish Sense from Nonsense: Out-of-Scope Detection for Virtual Assistants Abstract: Out of Scope (OOS) detection in Conversational AI solutions enables a chatbot to handle a conversation gracefully when it is unable to make sense of the end-user query. Accurately tagging a query as out-of-domain is particul...	[ 24467 ]	Test
32,085	16	Title: Enhancing image quality prediction with self-supervised visual masking Abstract: Full-reference image quality metrics (FR-IQMs) aim to measure the visual differences between a pair of reference and distorted images, with the goal of accurately predicting human judgments. However, existing FR-IQMs, including trad...	[]	Test
32,086	27	Title: Online Estimation of Self-Body Deflection With Various Sensor Data Based on Directional Statistics Abstract: In this paper, we propose a method for online estimation of the robot's posture. Our method uses von Mises and Bingham distributions as probability distributions of joint angles and 3D orientation, which ...	[]	Validation
32,087	27	Title: A Legendre-Gauss Pseudospectral Collocation Method for Trajectory Optimization in Second Order Systems Abstract: Pseudospectral collocation methods have proven to be powerful tools to solve optimal control problems. While these methods generally assume the dynamics is given in the first order form $x$ = f(x, u, ...	[ 22022 ]	Train
32,088	24	Title: schlably: A Python Framework for Deep Reinforcement Learning Based Scheduling Experiments Abstract: Research on deep reinforcement learning (DRL) based production scheduling (PS) has gained a lot of attention in recent years, primarily due to the high demand for optimizing scheduling problems in diverse industry...	[]	Train
32,089	16	Title: Instance-based Max-margin for Practical Few-shot Recognition Abstract: In order to mimic the human few-shot learning (FSL) ability better and to make FSL closer to real-world applications, this paper proposes a practical FSL (pFSL) setting. pFSL is based on unsupervised pretrained models (analogous to human prio...	[]	Train
32,090	27	Title: A Multi-robot Coverage Path Planning Algorithm Based on Improved DARP Algorithm Abstract: The research on multi-robot coverage path planning (CPP) has been attracting more and more attention. In order to achieve efficient coverage, this paper proposes an improved DARP coverage algorithm. The improved DARP algori...	[]	Train
32,091	27	Title: Sim2Real2: Actively Building Explicit Physics Model for Precise Articulated Object Manipulation Abstract: Accurately manipulating articulated objects is a challenging yet important task for real robot applications. In this paper, we present a novel framework called Sim2Real2 to enable the robot to manipulate an ...	[ 21518 ]	Validation
32,092	4	Title: IoT Botnet Detection Using an Economic Deep Learning Model Abstract: The rapid progress in technology innovation usage and distribution has increased in the last decade. The rapid growth of the Internet of Things (IoT) systems worldwide has increased network security challenges created by malicious third parties...	[]	Train
32,093	24	Title: Learning Stochastic Dynamical System via Flow Map Operator Abstract: We present a numerical framework for learning unknown stochastic dynamical systems using measurement data. Termed stochastic flow map learning (sFML), the new framework is an extension of flow map learning (FML) that was developed for learning ...	[ 38863 ]	Train
32,094	24	Title: Optimal Rates for Bandit Nonstochastic Control Abstract: Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) control are foundational and extensively researched problems in optimal control. We investigate LQR and LQG problems with semi-adversarial perturbations and time-varying adversarial bandi...	[ 7145, 42572 ]	Validation
32,095	30	Title: A Topic-aware Summarization Framework with Different Modal Side Information Abstract: Automatic summarization plays an important role in the exponential document growth on the Web. On content websites such as CNN.com and WikiHow.com, there often exist various kinds of side information along with the main documen...	[]	Train
32,096	6	Title: Investigating the use of ChatGPT for the scheduling of construction projects Abstract: Generative Pre-Trained Transformer (GPT) language models such as ChatGPT have the potential to revolutionize the construction industry by automating repetitive and time-consuming tasks. This paper presents a study in which Cha...	[ 11273, 1899, 12013, 31922, 28339, 25821, 3518 ]	Test
32,097	30	Title: Revisiting Event Argument Extraction: Can EAE Models Learn Better When Being Aware of Event Co-occurrences? Abstract: Event co-occurrences have been proved effective for event extraction (EE) in previous studies, but have not been considered for event argument extraction (EAE) recently. In this paper, we try to ...	[ 36545 ]	Train
32,098	15	Title: ECHOES: a 200 GOPS/W Frequency Domain SoC with FFT Processor and I2S DSP for Flexible Data Acquisition from Microphone Arrays Abstract: Emerging applications in the IoT domain require ultra-low-power and high-performance end-nodes to deal with complex near-sensor-data analytics. Domains such as audio, radar, and...	[]	Train
32,099	16	Title: Lifelong Change Detection: Continuous Domain Adaptation for Small Object Change Detection in Everyday Robot Navigation Abstract: The recently emerging research area in robotics, ground view change detection, suffers from its ill-posed-ness because of visual uncertainty combined with complex nonlinear perspective...	[]	Validation
32,100	31	Title: Disentangled Representation for Diversified Recommendations Abstract: Accuracy and diversity have long been considered to be two conflicting goals for recommendations. We point out, however, that as the diversity is typically measured by certain pre-selected item attributes, e.g., category as the most popularly ...	[ 34434 ]	Validation
32,101	34	Title: Fully-Dynamic Approximate Decision Trees With Worst-Case Update Time Guarantees Abstract: We give the first algorithm that maintains an approximate decision tree over an arbitrary sequence of insertions and deletions of labeled examples, with strong guarantees on the worst-case running time per update request. F...	[]	Train
32,102	30	Title: Measuring and Modifying Factual Knowledge in Large Language Models Abstract: Large Language Models (LLMs) store an extensive amount of factual knowledge obtained from vast collections of text. To effectively utilize these models for downstream tasks, it is crucial to have reliable methods for measuring their kno...	[ 33220, 13700, 9518, 38102, 12602 ]	Test
32,103	24	Title: Pattern Mining for Anomaly Detection in Graphs: Application to Fraud in Public Procurement Abstract: In the context of public procurement, several indicators called red flags are used to estimate fraud risk. They are computed according to certain contract attributes and are therefore dependent on the proper fill...	[]	Test
32,104	24	Title: Physics Symbolic Learner for Discovering Ground-Motion Models Via NGA-West2 Database Abstract: Ground-motion model (GMM) is the basis of many earthquake engineering studies. In this study, a novel physics-informed symbolic learner (PISL) method based on the Nest Generation Attenuation-West2 database is proposed ...	[]	Train
32,105	16	Title: CTG-Net: An Efficient Cascaded Framework Driven by Terminal Guidance Mechanism for Dilated Pancreatic Duct Segmentation Abstract: Pancreatic duct dilation indicates a high risk of various pancreatic diseases. Segmentation for dilated pancreatic duct (DPD) on computed tomography (CT) image shows the potential to ...	[]	Train
32,106	30	Title: Characterizing Learning Curves During Language Model Pre-Training: Learning, Forgetting, and Stability Abstract: How do language models learn to make predictions during pre-training? To study this question, we extract learning curves from five autoregressive English language model pre-training runs, for 1M token...	[ 19720, 13715, 29396, 29375 ]	Test
32,107	24	Title: Variance-Covariance Regularization Improves Representation Learning Abstract: Transfer learning has emerged as a key approach in the machine learning domain, enabling the application of knowledge derived from one domain to improve performance on subsequent tasks. Given the often limited information about these s...	[ 27622, 4063 ]	Train
32,108	24	Title: DPOK: Reinforcement Learning for Fine-tuning Text-to-Image Diffusion Models Abstract: Learning from human feedback has been shown to improve text-to-image models. These techniques first learn a reward function that captures what humans care about in the task and then improve the models based on the learned rewar...	[ 37152, 6145, 8994, 18022, 9384, 33608, 18220, 26673, 6962, 36084 ]	Train
32,109	16	Title: An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification Abstract: Wearable sensors such as Inertial Measurement Units (IMUs) are often used to assess the performance of human exercise. Common approaches use handcrafted features based on domain expertise or automatically extrac...	[]	Test
32,110	24	Title: Model Extraction Attacks on Split Federated Learning Abstract: Federated Learning (FL) is a popular collaborative learning scheme involving multiple clients and a server. FL focuses on protecting clients' data but turns out to be highly vulnerable to Intellectual Property (IP) threats. Since FL periodically coll...	[ 24951 ]	Train
32,111	28	Title: Achievable Rate Analysis of the STAR-RIS Aided NOMA Uplink in the Face of Imperfect CSI and Hardware Impairments Abstract: Reconfigurable intelligent surfaces (RIS) are capable of beneficially ameliorating the propagation environment by appropriately controlling the passive reflecting elements. To extend the cov...	[ 24888, 42043 ]	Train
32,112	8	Title: Implementation of a Channel Model for Non-Terrestrial Networks in ns-3 Abstract: While the 5th generation (5G) of mobile networks has landed in the commercial area, the research community is exploring new functionalities for 6th generation (6G) networks, for example non-terrestrial networks (NTNs) via space/air ...	[ 21061 ]	Train
32,113	8	Title: Policy Reuse for Communication Load Balancing in Unseen Traffic Scenarios Abstract: With the continuous growth in communication network complexity and traffic volume, communication load balancing solutions are receiving increasing attention. Specifically, reinforcement learning (RL)-based methods have shown impr...	[]	Validation
32,114	30	Title: MuLER: Detailed and Scalable Reference-based Evaluation Abstract: We propose a novel methodology (namely, MuLER) that transforms any reference-based evaluation metric for text generation, such as machine translation (MT) into a fine-grained analysis tool. Given a system and a metric, MuLER quantifies how much th...	[]	Validation
32,115	24	Title: Reinforced Labels: Multi-Agent Deep Reinforcement Learning for Point-feature Label Placement Abstract: Over the recent years, Reinforcement Learning combined with Deep Learning techniques has successfully proven to solve complex problems in various domains, including robotics, self-driving cars, and finance. In ...	[]	Train
32,116	16	Title: Deep learning-based stereo camera multi-video synchronization Abstract: Stereo vision is essential for many applications. Currently, the synchronization of the streams coming from two cameras is done using mostly hardware. A software-based synchronization method would reduce the cost, weight and size of the enti...	[]	Train
32,117	24	Title: Federated Neural Compression Under Heterogeneous Data Abstract: We discuss a federated learned compression problem, where the goal is to learn a compressor from real-world data which is scattered across clients and may be statistically heterogeneous, yet share a common underlying representation. We propose a dis...	[]	Validation
32,118	27	Title: Switching Head-Tail Funnel UNITER for Dual Referring Expression Comprehension with Fetch-and-Carry Tasks Abstract: This paper describes a domestic service robot (DSR) that fetches everyday objects and carries them to specified destinations according to free-form natural language instructions. Given an instructio...	[]	Train
32,119	16	Title: Blind Face Restoration for Under-Display Camera via Dictionary Guided Transformer Abstract: By hiding the front-facing camera below the display panel, Under-Display Camera (UDC) provides users with a full-screen experience. However, due to the characteristics of the display, images taken by UDC suffer from signi...	[ 16345 ]	Train
32,120	24	Title: Reasoning with Latent Diffusion in Offline Reinforcement Learning Abstract: Offline reinforcement learning (RL) holds promise as a means to learn high-reward policies from a static dataset, without the need for further environment interactions. However, a key challenge in offline RL lies in effectively stitching...	[ 21152, 42666, 12515, 34215 ]	Train
32,121	28	Title: Common Information Dimension Abstract: The exact common information between a set of random variables X1,…, Xn is defined as the minimum entropy of a shared random variable that allows for the exact distributive simulation of X1,…, Xn. It has been established that, in certain instances, infinite entropy is requi...	[]	Validation
32,122	16	Title: Towards General and Fast Video Derain via Knowledge Distillation Abstract: As a common natural weather condition, rain can obscure video frames and thus affect the performance of the visual system, so video derain receives a lot of attention. In natural environments, rain has a wide variety of streak types, whic...	[]	Test
32,123	2	Title: Extracting total Amb programs from proofs Abstract: nan	[ 13386 ]	Train
32,124	6	Title: From User Perceptions to Technical Improvement: Enabling People Who Stutter to Better Use Speech Recognition Abstract: Consumer speech recognition systems do not work as well for many people with speech differences, such as stuttering, relative to the rest of the general population. However, what is not clear is...	[]	Validation
32,125	16	Title: Automating Style Analysis and Visualization With Explainable AI - Case Studies on Brand Recognition Abstract: Incorporating style-related objectives into shape design has been centrally important to maximize product appeal. However, stylistic features such as aesthetics and semantic attributes are hard to codify...	[]	Train
32,126	30	Title: Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training Abstract: We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users during inference. Our method incor...	[]	Validation
32,127	24	Title: Counting Carbon: A Survey of Factors Influencing the Emissions of Machine Learning Abstract: Machine learning (ML) requires using energy to carry out computations during the model training process. The generation of this energy comes with an environmental cost in terms of greenhouse gas emissions, depending on q...	[ 43424, 35006, 27926, 22847 ]	Train
32,128	16	Title: Heterogeneous graphs model spatial relationships between biological entities for breast cancer diagnosis Abstract: The heterogeneity of breast cancer presents considerable challenges for its early detection, prognosis, and treatment selection. Convolutional neural networks often neglect the spatial relationships...	[]	Train
32,129	2	Title: Leveraging polyhedral reductions for solving Petri net reachability problems Abstract: nan	[ 32200 ]	Train
32,130	27	Title: The Sum of Its Parts: Visual Part Segmentation for Inertial Parameter Identification of Manipulated Objects Abstract: To operate safely and efficiently alongside human workers, collaborative robots (cobots) require the ability to quickly understand the dynamics of manipulated objects. However, traditional method...	[]	Train
32,131	16	Title: Decomposed Guided Dynamic Filters for Efficient RGB-Guided Depth Completion Abstract: RGB-guided depth completion aims at predicting dense depth maps from sparse depth measurements and corresponding RGB images, where how to effectively and efficiently exploit the multi-modal information is a key issue. Guided dy...	[]	Train
32,132	28	Title: Self-Interference Cancellation for Full-Duplex Massive MIMO OFDM With Single RF Chain Abstract: In this letter, the digital self-intereference (SI) canellation in a single radio frequency (RF) chain massive multi-input multi-output (MIMO) full-duplex (FD) orthogonal frequency division multiplexing (OFDM) system ...	[]	Train
32,133	30	Title: Tuning Traditional Language Processing Approaches for Pashto Text Classification Abstract: Nowadays, text classification for different purposes becomes a basic task for concerned people. Hence, much research has been done to develop automatic text classification for the majority of national and international lan...	[]	Test
32,134	30	Title: Does mBERT understand Romansh? Evaluating word embeddings using word alignment Abstract: We test similarity-based word alignment models (SimAlign and awesome-align) in combination with word embeddings from mBERT and XLM-R on parallel sentences in German and Romansh. Since Romansh is an unseen language, we are de...	[]	Train
32,135	24	Title: DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record Abstract: Abstract Objective Heatlhcare institutions are establishing frameworks to govern and promote the implementation of accurate, actionable, and reliable machine learning models that int...	[ 29603 ]	Train
32,136	5	Title: Utility-Aware Load Shedding for Real-time Video Analytics at the Edge Abstract: Real-time video analytics typically require video frames to be processed by a query to identify objects or activities of interest while adhering to an end-to-end frame processing latency constraint. Such applications impose a continu...	[]	Validation
32,137	24	Title: GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Abstract: Given the growing concerns about fairness in machine learning and the impressive performance of Graph Neural Networks (GNNs) on graph data learning, algorithmic fairness in GNNs has attracted significant attention. Whi...	[ 263 ]	Train
32,138	16	Title: Dual Focal Loss for Calibration Abstract: The use of deep neural networks in real-world applications require well-calibrated networks with confidence scores that accurately reflect the actual probability. However, it has been found that these networks often provide over-confident predictions, which leads to poor...	[]	Train
32,139	31	Title: A Scalable Framework for Automatic Playlist Continuation on Music Streaming Services Abstract: Music streaming services often aim to recommend songs for users to extend the playlists they have created on these services. However, extending playlists while preserving their musical characteristics and matching user...	[ 41040 ]	Train
32,140	24	Title: PRECISION: Decentralized Constrained Min-Max Learning with Low Communication and Sample Complexities Abstract: Recently, min-max optimization problems have received increasing attention due to their wide range of applications in machine learning (ML). However, most existing min-max solution techniques are either...	[]	Train
32,141	26	Title: Stability and Efficiency of Personalised Cultural Markets Abstract: This work is concerned with the dynamics of online cultural markets, namely, attention allocation of many users on a set of digital goods with infinite supply. Such dynamics are important in shaping processes and outcomes in society, from trendi...	[]	Train
32,142	30	Title: Jambu: A historical linguistic database for South Asian languages Abstract: We introduce JAMBU, a cognate database of South Asian languages which unifies dozens of previous sources in a structured and accessible format. The database includes nearly 287k lemmata from 602 lects, grouped together in 23k sets of cog...	[]	Train
32,143	16	Title: Text-guided Eyeglasses Manipulation with Spatial Constraints Abstract: Virtual try-on of eyeglasses involves placing eyeglasses of different shapes and styles onto a face image without physically trying them on. While existing methods have shown impressive results, the variety of eyeglasses styles is limited and...	[ 16696, 42145, 17119 ]	Train
32,144	23	Title: CM-CASL: Comparison-based Performance Modeling of Software Systems via Collaborative Active and Semisupervised Learning Abstract: nan	[]	Train
32,145	6	Title: Critical Appraisal of Artificial Intelligence-Mediated Communication Abstract: Over the last two decades, technology use in language learning and teaching has significantly advanced and is now referred to as Computer-Assisted Language Learning (CALL). Recently, the integration of Artificial Intelligence (AI) int...	[]	Train
32,146	16	Title: A Semi-Paired Approach For Label-to-Image Translation Abstract: Data efficiency, or the ability to generalize from a few labeled data, remains a major challenge in deep learning. Semi-supervised learning has thrived in traditional recognition tasks alleviating the need for large amounts of labeled data, yet it r...	[ 35960, 30625, 35989 ]	Train
32,147	34	Title: Dynamic Compact Data Structure for Temporal Reachability with Unsorted Contact Insertions Abstract: Temporal graphs represent interactions between entities over time. Deciding whether entities can reach each other through temporal paths is useful for various applications such as in communication networks and epi...	[]	Train
32,148	16	Title: Scalable 3D Captioning with Pretrained Models Abstract: We introduce Cap3D, an automatic approach for generating descriptive text for 3D objects. This approach utilizes pretrained models from image captioning, image-text alignment, and LLM to consolidate captions from multiple views of a 3D asset, completely sid...	[ 10624, 22464, 27063, 5539, 19013, 11450, 42666, 34074, 21997, 17583, 16562, 25556, 17238, 11959, 14842, 18267, 40830 ]	Train
32,149	4	Title: Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning Abstract: Malicious server (MS) attacks have enabled the scaling of data stealing in federated learning to large batch sizes and secure aggregation, settings previously considered private. However, many concerns regarding client-side d...	[ 25090, 4579 ]	Train
32,150	24	Title: BALANCE: Bayesian Linear Attribution for Root Cause Localization Abstract: Root Cause Analysis (RCA) plays an indispensable role in distributed data system maintenance and operations, as it bridges the gap between fault detection and system recovery. Existing works mainly study multidimensional localization or g...	[]	Train
32,151	24	Title: End-to-End Augmentation Hyperparameter Tuning for Self-Supervised Anomaly Detection Abstract: Self-supervised learning (SSL) has emerged as a promising paradigm that presents self-generated supervisory signals to real-world problems, bypassing the extensive manual labeling burden. SSL is especially attractive fo...	[ 6942 ]	Train
32,152	24	Title: A Minimal Approach for Natural Language Action Space in Text-based Games Abstract: Text-based games (TGs) are language-based interactive environments for reinforcement learning. While language models (LMs) and knowledge graphs (KGs) are commonly used for handling large action space in TGs, it is unclear whether ...	[]	Validation
32,153	13	Title: Artificial to Spiking Neural Networks Conversion for Scientific Machine Learning Abstract: We introduce a method to convert Physics-Informed Neural Networks (PINNs), commonly used in scientific machine learning, to Spiking Neural Networks (SNNs), which are expected to have higher energy efficiency compared to tr...	[ 44354, 29379, 41711, 16186, 5085 ]	Validation
32,154	28	Title: Learning End-to-End Channel Coding with Diffusion Models Abstract: It is a known problem that deep-learning-based end-to-end (E2E) channel coding systems depend on a known and differentiable channel model, due to the learning process and based on the gradient-descent optimization methods. This places the challen...	[ 40649, 29187, 7550 ]	Validation
32,155	16	Title: A Dynamic Graph CNN with Cross-Representation Distillation for Event-Based Recognition Abstract: Recent advances in event-based research prioritize sparsity and temporal precision. Approaches using dense frame-based representations processed via well-pretrained CNNs are being replaced by the use of sparse point-...	[ 23280 ]	Test
32,156	30	Title: Lightweight Adaptation of Neural Language Models via Subspace Embedding Abstract: Traditional neural word embeddings are usually dependent on a richer diversity of vocabulary. However, the language models recline to cover major vocabularies via the word embedding parameters, in particular, for multilingual langu...	[]	Validation
32,157	27	Title: DriveAdapter: Breaking the Coupling Barrier of Perception and Planning in End-to-End Autonomous Driving Abstract: End-to-end autonomous driving aims to build a fully differentiable system that takes raw sensor data as inputs and directly outputs the planned trajectory or control signals of the ego vehicle. State...	[ 2756, 37832, 555, 13594, 22943 ]	Train
32,158	30	Title: Conformal Nucleus Sampling Abstract: Language models generate text based on successively sampling the next word. A decoding procedure based on nucleus (top-$p$) sampling chooses from the smallest possible set of words whose cumulative probability exceeds the probability $p$. In this work, we assess whether a top...	[ 10083, 4340, 33273, 35418, 10876 ]	Test
32,159	24	Title: Feasibility of Transfer Learning: A Mathematical Framework Abstract: Transfer learning is a popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. It has enjoyed numerous empirical successes and inspired a growing number of theoretical studies. This...	[]	Validation
32,160	23	Title: Smart Knowledge Transfer using Google-like Search Abstract: To address the issue of rising software maintenance cost due to program comprehension challenges, we propose SMARTKT (Smart Knowledge Transfer), a search framework, which extracts and integrates knowledge related to various aspects of an application in ...	[]	Train
32,161	3	Title: The role of online attention in the supply of disinformation in Wikipedia Abstract: Wikipedia and many User-Generated Content (UGC) communities are known for producing reliable, quality content, but also for being vulnerable to false or misleading information. Previous work has shown that many hoaxes on Wikipedi...	[ 39680 ]	Train
32,162	30	Title: The Stable Entropy Hypothesis and Entropy-Aware Decoding: An Analysis and Algorithm for Robust Natural Language Generation Abstract: State-of-the-art language generation models can degenerate when applied to open-ended generation problems such as text completion, story generation, or dialog modeling. This degene...	[]	Validation
32,163	28	Title: Sampling-Based Estimates of the Sizes of Constrained Subcodes of Reed-Muller Codes Abstract: This paper develops an algorithmic approach for obtaining approximate, numerical estimates of the sizes of subcodes of Reed-Muller (RM) codes, all of the codewords in which satisfy a given constraint. Our algorithm is ba...	[ 39102, 15310 ]	Test
32,164	2	Title: A Deforestation of Reducts: Refocusing Abstract: In a small-step semantics with a deterministic reduction strategy, refocusing is a transformation that connects a reduction-based normalization function (i.e., a normalization function that enumerates the successive terms in a reduction sequence -- the successive ...	[]	Validation
32,165	16	Title: Class-level Multiple Distributions Representation are Necessary for Semantic Segmentation Abstract: Existing approaches focus on using class-level features to improve semantic segmentation performance. How to characterize the relationships of intra-class pixels and inter-class pixels is the key to extract the di...	[]	Train
32,166	16	Title: Exploring Large-scale Unlabeled Faces to Enhance Facial Expression Recognition Abstract: Facial Expression Recognition (FER) is an important task in computer vision and has wide applications in many fields. In this paper, we introduce our approach to the fifth Affective Behavior Analysis in-the-wild (ABAW) Compe...	[ 39782, 16586, 23627, 16184, 26844 ]	Train
32,167	24	Title: Artificial Intelligence-Based Methods for Precision Medicine: Diabetes Risk Prediction Abstract: The rising prevalence of type 2 diabetes mellitus (T2DM) necessitates the development of predictive models for T2DM risk assessment. Artificial intelligence (AI) models are being extensively used for this purpose, bu...	[]	Train
32,168	4	Title: Utilization of Impedance Disparity Incurred from Switching Activities to Monitor and Characterize Firmware Activities Abstract: The massive trend toward embedded systems introduces new security threats to prevent. Malicious firmware makes it easier to launch cyberattacks against embedded systems. Systems infecte...	[ 36503 ]	Test
32,169	24	Title: Exploring the Vulnerabilities of Machine Learning and Quantum Machine Learning to Adversarial Attacks Using a Malware Dataset: A Comparative Analysis Abstract: The burgeoning fields of machine learning (ML) and quantum machine learning (QML) have shown remarkable potential in tackling complex problems across var...	[ 7801, 2354, 27670 ]	Train
32,170	4	Title: Isolation and Induction: Training Robust Deep Neural Networks against Model Stealing Attacks Abstract: Despite the broad application of Machine Learning models as a Service (MLaaS), they are vulnerable to model stealing attacks. These attacks can replicate the model functionality by using the black-box query pro...	[ 4544, 44201, 21478, 17743 ]	Validation
32,171	24	Title: Weight Compander: A Simple Weight Reparameterization for Regularization Abstract: Regularization is a set of techniques that are used to improve the generalization ability of deep neural networks. In this paper, we introduce weight compander (WC), a novel effective method to improve generalization by reparameter...	[]	Train
32,172	10	Title: Exploring Large Language Models for Ontology Alignment Abstract: This work investigates the applicability of recent generative Large Language Models (LLMs), such as the GPT series and Flan-T5, to ontology alignment for identifying concept equivalence mappings across ontologies. To test the zero-shot performance ...	[ 14985, 34329 ]	Train
32,173	30	Title: Rethinking Masked Language Modeling for Chinese Spelling Correction Abstract: In this paper, we study Chinese Spelling Correction (CSC) as a joint decision made by two separate models: a language model and an error model. Through empirical analysis, we find that fine-tuning BERT tends to over-fit the error model...	[ 43448, 17994 ]	Train
32,174	24	Title: Value Iteration Networks With Gated Summarization Module Abstract: In this paper, we address the challenges faced by Value Iteration Networks (VIN) in handling larger input maps and mitigating the impact of accumulated errors caused by increased iterations. We propose a novel approach, Value Iteration Networks w...	[]	Train
32,175	24	Title: A Bayesian Active Learning Approach to Comparative Judgement Abstract: Assessment is a crucial part of education. Traditional marking is a source of inconsistencies and unconscious bias, placing a high cognitive load on the assessors. An approach to address these issues is comparative judgement (CJ). In CJ, the ...	[]	Test
32,176	30	Title: PRISMA-DFLLM: An Extension of PRISMA for Systematic Literature Reviews using Domain-specific Finetuned Large Language Models Abstract: With the proliferation of open-sourced Large Language Models (LLMs) and efficient finetuning techniques, we are on the cusp of the emergence of numerous domain-specific LLMs that...	[ 13700, 13029, 23502, 24308, 36569, 5815, 18777, 42908, 37919 ]	Train
32,177	24	Title: One Explanation Does Not Fit XIL Abstract: Current machine learning models produce outstanding results in many areas but, at the same time, suffer from shortcut learning and spurious correlations. To address such flaws, the explanatory interactive machine learning (XIL) framework has been proposed to revise a mo...	[ 13034 ]	Validation

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