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
17,678	30	Title: Low-Rank Prune-And-Factorize for Language Model Compression Abstract: The components underpinning PLMs -- large weight matrices -- were shown to bear considerable redundancy. Matrix factorization, a well-established technique from matrix theory, has been utilized to reduce the number of parameters in PLM. Howeve...	[]	Train
17,679	24	Title: BSSAD: Towards A Novel Bayesian State-Space Approach for Anomaly Detection in Multivariate Time Series Abstract: —Detecting anomalies in multivariate time series (MTS) data plays an important role in many domains. The abnormal values could indicate events, medical abnormalities, cyber-attacks, or faulty devices ...	[ 39411 ]	Train
17,680	16	Title: Rethinking Rotation Invariance with Point Cloud Registration Abstract: Recent investigations on rotation invariance for 3D point clouds have been devoted to devising rotation-invariant feature descriptors or learning canonical spaces where objects are semantically aligned. Examinations of learning frameworks for...	[]	Train
17,681	30	Title: Exploring the Grounding Issues in Image Caption Abstract: This paper explores the grounding issue concerning multimodal semantic representation from a computational cognitive-linguistic view. Five perceptual properties of groundedness are annotated and analyzed: Affordance, Perceptual salience, Object number, Ga...	[ 10624 ]	Validation
17,682	31	Title: Fast Approximate Nearest Neighbor Search with a Dynamic Exploration Graph using Continuous Refinement Abstract: For approximate nearest neighbor search, graph-based algorithms have shown to offer the best trade-off between accuracy and search time. We propose the Dynamic Exploration Graph (DEG) which significant...	[]	Validation
17,683	16	Title: A Study on the Impact of Face Image Quality on Face Recognition in the Wild Abstract: Deep learning has received increasing interests in face recognition recently. Large quantities of deep learning methods have been proposed to handle various problems appeared in face recognition. Quite a lot deep methods claime...	[]	Train
17,684	3	Title: A Review of and Roadmap for Data Science and Machine Learning for the Neuropsychiatric Phenotype of Autism Abstract: Autism spectrum disorder (autism) is a neurodevelopmental delay that affects at least 1 in 44 children. Like many neurological disorder phenotypes, the diagnostic features are observable, can be t...	[ 13504, 15557, 29483, 36045, 13234 ]	Train
17,685	22	Title: Multi-graded Featherweight Java Abstract: Resource-aware type systems statically approximate not only the expected result type of a program, but also the way external resources are used, e.g., how many times the value of a variable is needed. We extend the type system of Featherweight Java to be resource-aware, ...	[]	Test
17,686	30	Title: More than Classification: A Unified Framework for Event Temporal Relation Extraction Abstract: Event temporal relation extraction (ETRE) is usually formulated as a multi-label classification task, where each type of relation is simply treated as a one-hot label. This formulation ignores the meaning of relations ...	[]	Train
17,687	23	Title: Using a Nearest-Neighbour, BERT-Based Approach for Scalable Clone Detection Abstract: Code clones can detrimentally impact software maintenance and manually detecting them in very large code-bases is impractical. Additionally, automated approaches find detection of Type 3 and Type 4 (inexact) clones very challen...	[ 21303 ]	Train
17,688	6	Title: CollabCoder: A GPT-Powered Workflow for Collaborative Qualitative Analysis Abstract: The Collaborative Qualitative Analysis (CQA) process can be time-consuming and resource-intensive, requiring multiple discussions among team members to refine codes and ideas before reaching a consensus. To address these challen...	[ 11882, 2493, 11190, 3599 ]	Validation
17,689	16	Title: Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study Abstract: Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of microsatellite ...	[ 15257, 39199, 27951 ]	Validation
17,690	27	Title: MIMONet: Multi-Input Multi-Output On-Device Deep Learning Abstract: Future intelligent robots are expected to process multiple inputs simultaneously (such as image and audio data) and generate multiple outputs accordingly (such as gender and emotion), similar to humans. Recent research has shown that multi-input...	[ 22122, 34731 ]	Train
17,691	37	Title: JSONoid: Monoid-based Enrichment for Configurable and Scalable Data-Driven Schema Discovery Abstract: Schema discovery is an important aspect to working with data in formats such as JSON. Unlike relational databases, JSON data sets often do not have associated structural information. Consumers of such datasets a...	[]	Test
17,692	4	Title: PECAN: A Deterministic Certified Defense Against Backdoor Attacks Abstract: Neural networks are vulnerable to backdoor poisoning attacks, where the attackers maliciously poison the training set and insert triggers into the test input to change the prediction of the victim model. Existing defenses for backdoor at...	[ 24245 ]	Train
17,693	39	Title: Perfect Roman Domination and Unique Response Roman Domination Abstract: The idea of enumeration algorithms with polynomial delay is to polynomially bound the running time between any two subsequent solutions output by the enumeration algorithm. While it is open for more than four decades if all minimal dominatin...	[ 12131 ]	Train
17,694	4	Title: Measuring Website Password Creation Policies At Scale Abstract: Researchers have extensively explored how password creation policies influence the security and usability of user-chosen passwords, producing evidence-based policy guidelines. However, for web authentication to improve in practice, websites must act...	[]	Train
17,695	24	Title: Dynamic Mixed Membership Stochastic Block Model for Weighted Labeled Networks Abstract: Most real-world networks evolve over time. Existing literature proposes models for dynamic networks that are either unlabeled or assumed to have a single membership structure. On the other hand, a new family of Mixed Membersh...	[]	Train
17,696	4	Title: Fuzzified advanced robust hashes for identification of digital and physical objects Abstract: With the rising numbers for IoT objects, it is becoming easier to penetrate counterfeit objects into the mainstream market by adversaries. Such infiltration of bogus products can be addressed with third-party-verifiable...	[]	Validation
17,697	16	Title: Guided Attention for Next Active Object @ EGO4D STA Challenge Abstract: In this technical report, we describe the Guided-Attention mechanism based solution for the short-term anticipation (STA) challenge for the EGO4D challenge. It combines the object detections, and the spatiotemporal features extracted from vi...	[ 10385, 7981, 43991 ]	Validation
17,698	10	Title: From Robustness to Explainability and Back Again Abstract: In contrast with ad-hoc methods for eXplainable Artificial Intelligence (XAI), formal explainability offers important guarantees of rigor. However, formal explainability is hindered by poor scalability for some families of classifiers, the most significa...	[ 21129 ]	Test
17,699	24	Title: On Sequential Bayesian Inference for Continual Learning Abstract: Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks. We revisit sequential Bayesian inference and assess whether using the previ...	[ 36894 ]	Train
17,700	16	Title: 3D Open-vocabulary Segmentation with Foundation Models Abstract: Open-vocabulary segmentation of 3D scenes is a fundamental function of human perception and thus a crucial objective in computer vision research. However, this task is heavily impeded by the lack of large-scale and diverse 3D open-vocabulary segmen...	[ 4643, 33220, 37254, 25383, 22222, 19630, 22767, 24399, 41400, 6942 ]	Test
17,701	27	Title: Deep Reinforcement Learning Based on Local GNN for Goal-Conditioned Deformable Object Rearranging Abstract: Object rearranging is one of the most common deformable manipulation tasks, where the robot needs to rearrange a deformable object into a goal configuration. Previous studies focus on designing an expert s...	[ 16816, 32520, 37685 ]	Train
17,702	4	Title: Towards adversarial realism and robust learning for IoT intrusion detection and classification Abstract: nan	[ 29858, 38282, 6083, 35459 ]	Validation
17,703	16	Title: Balanced Classification: A Unified Framework for Long-Tailed Object Detection Abstract: Conventional detectors suffer from performance degradation when dealing with long-tailed data due to a classification bias towards the majority head categories. In this paper, we contend that the learning bias originates from...	[]	Train
17,704	24	Title: Resource-Efficient Federated Learning for Heterogenous and Resource-Constrained Environments Abstract: Federated Learning (FL) is a privacy-enforcing sub-domain of machine learning that brings the model to the user's device for training, avoiding the need to share personal data with a central server. While exist...	[]	Validation
17,705	28	Title: The Kraft-Barmpalias-Lewis-Pye lemma revisited Abstract: This note provides a simplified exposition of the proof of hierarchical Kraft lemma proven by Barmpalias and Lewis-Pye and its consequences for the oracle use in the Ku\v{c}era--G\'acs theorem (saying that every sequence is Turing reducible to a random one...	[]	Test
17,706	13	Title: Temporally Layered Architecture for Adaptive, Distributed and Continuous Control Abstract: We present temporally layered architecture (TLA), a biologically inspired system for temporally adaptive distributed control. TLA layers a fast and a slow controller together to achieve temporal abstraction that allows eac...	[]	Train
17,707	5	Title: Towards Cooperative Federated Learning over Heterogeneous Edge/Fog Networks Abstract: Federated learning (FL) has been promoted as a popular technique for training machine learning (ML) models over edge/fog networks. Traditional implementations of FL have largely neglected the potential for inter-network coopera...	[ 10123, 8412, 9519 ]	Train
17,708	30	Title: Generative Sentiment Transfer via Adaptive Masking Abstract: Sentiment transfer aims at revising the input text to satisfy a given sentiment polarity while retaining the original semantic content. The nucleus of sentiment transfer lies in precisely separating the sentiment information from the content informatio...	[]	Test
17,709	25	Title: Capturing Spectral and Long-term Contextual Information for Speech Emotion Recognition Using Deep Learning Techniques Abstract: Traditional approaches in speech emotion recognition, such as LSTM, CNN, RNN, SVM, and MLP, have limitations such as difficulty capturing long-term dependencies in sequential data, capt...	[]	Test
17,710	27	Title: CTopPRM: Clustering Topological PRM for Planning Multiple Distinct Paths in 3D Environments Abstract: In this paper, we propose a new method called Clustering Topological PRM (CTopPRM) for finding multiple homotopically distinct paths in 3D cluttered environments. Finding such distinct paths, e.g., going around ...	[ 21218 ]	Train
17,711	6	Title: Towards Ubiquitous Semantic Metaverse: Challenges, Approaches, and Opportunities Abstract: In recent years, ubiquitous semantic Metaverse has been studied to revolutionize immersive cyber-virtual experiences for augmented reality (AR) and virtual reality (VR) users, which leverages advanced semantic understandin...	[ 32714, 37430 ]	Train
17,712	31	Title: Hierarchical Multi-Task Learning Framework for Session-based Recommendations Abstract: While session-based recommender systems (SBRSs) have shown superior recommendation performance, multi-task learning (MTL) has been adopted by SBRSs to enhance their prediction accuracy and generalizability further. Hierarchica...	[]	Train
17,713	24	Title: A Neural Emulator for Uncertainty Estimation of Fire Propagation Abstract: Wildfire propagation is a highly stochastic process where small changes in environmental conditions (such as wind speed and direction) can lead to large changes in observed behaviour. A traditional approach to quantify uncertainty in fire...	[]	Test
17,714	31	Title: GRAFS: Graphical Faceted Search System to Support Conceptual Understanding in Exploratory Search Abstract: When people search for information about a new topic within large document collections, they implicitly construct a mental model of the unfamiliar information space to represent what they currently know and...	[]	Train
17,715	10	Title: Measuring Faithfulness in Chain-of-Thought Reasoning Abstract: Large language models (LLMs) perform better when they produce step-by-step,"Chain-of-Thought"(CoT) reasoning before answering a question, but it is unclear if the stated reasoning is a faithful explanation of the model's actual reasoning (i.e., its p...	[ 8225, 40610, 5700, 8580, 2506, 975, 9907, 10165, 35927, 18041, 20794 ]	Validation
17,716	17	Title: Random-Access Neural Compression of Material Textures Abstract: The continuous advancement of photorealism in rendering is accompanied by a growth in texture data and, consequently, increasing storage and memory demands. To address this issue, we propose a novel neural compression technique specifically designed...	[ 37714, 11843 ]	Validation
17,717	16	Title: EVE: Efficient Vision-Language Pre-training with Masked Prediction and Modality-Aware MoE Abstract: Building scalable vision-language models to learn from diverse, multimodal data remains an open challenge. In this paper, we introduce an Efficient Vision-languagE foundation model, namely EVE, which is one unifie...	[ 39613 ]	Train
17,718	15	Title: On-Chip Sensors Data Collection and Analysis for SoC Health Management Abstract: Data produced by on-chip sensors in modern SoCs contains a large amount of information such as occurring faults, aging status, accumulated radiation dose, performance characteristics, environmental and other operational parameters. ...	[]	Train
17,719	24	Title: FMGNN: Fused Manifold Graph Neural Network Abstract: Graph representation learning has been widely studied and demonstrated effectiveness in various graph tasks. Most existing works embed graph data in the Euclidean space, while recent works extend the embedding models to hyperbolic or spherical spaces to achiev...	[ 43901 ]	Train
17,720	24	Title: Smart Home Energy Management: VAE-GAN synthetic dataset generator and Q-learning Abstract: Recent years have noticed an increasing interest among academia and industry towards analyzing the electrical consumption of residential buildings and employing smart home energy management systems (HEMS) to reduce househo...	[]	Validation
17,721	16	Title: Learning to Compress Unmanned Aerial Vehicle (UAV) Captured Video: Benchmark and Analysis Abstract: In this paper, we propose to build a novel benchmark and neural video coding task named learning based Unmanned Aerial Vehicle (UAV) video coding. We collect the UAV videos with different content variations, inclu...	[ 8882 ]	Train
17,722	16	Title: POSTER V2: A simpler and stronger facial expression recognition network Abstract: Facial expression recognition (FER) plays an important role in a variety of real-world applications such as human-computer interaction. POSTER achieves the state-of-the-art (SOTA) performance in FER by effectively combining facial ...	[ 1574, 17321, 16586, 34867, 33403 ]	Train
17,723	4	Title: On the Sensitivity of Deep Load Disaggregation to Adversarial Attacks Abstract: Non-intrusive Load Monitoring (NILM) algorithms, commonly referred to as load disaggregation algorithms, are fundamental tools for effective energy management. Despite the success of deep models in load disaggregation, they face vari...	[]	Validation
17,724	30	Title: Continual Pre-training of Language Models Abstract: Language models (LMs) have been instrumental for the rapid advance of natural language processing. This paper studies continual pre-training of LMs, in particular, continual domain-adaptive pre-training (or continual DAP-training). Existing research has shown t...	[ 8139, 42509, 27766, 23655 ]	Train
17,725	24	Title: Minimalist Traffic Prediction: Linear Layer Is All You Need Abstract: Traffic prediction is essential for the progression of Intelligent Transportation Systems (ITS) and the vision of smart cities. While Spatial-Temporal Graph Neural Networks (STGNNs) have shown promise in this domain by leveraging Graph Neural ...	[ 16576, 39898, 10642 ]	Test
17,726	30	Title: Contrasting Linguistic Patterns in Human and LLM-Generated Text Abstract: We conduct a quantitative analysis contrasting human-written English news text with comparable large language model (LLM) output from 4 LLMs from the LLaMa family. Our analysis spans several measurable linguistic dimensions, including morp...	[ 13700, 17061, 37100, 21485, 846, 22286 ]	Train
17,727	28	Title: A Cooperative NOMA User Pairing in UAV-Based Wireless Networks Abstract: NOMA (non-orthogonal multiple access) will be seen as a promising technology for enhancing spectrum efficiency in future cellular networks. The use of unmanned aerial vehicle (UAV) Amplify-and-Forward (AF) relaying as a moving access point ...	[]	Train
17,728	16	Title: One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian Manifolds Abstract: The processing, storage and transmission of large-scale point clouds is an ongoing challenge in the computer vision community which hinders progress in the application of 3D models to real-world setti...	[]	Train
17,729	24	Title: Balancing of competitive two-player Game Levels with Reinforcement Learning Abstract: The balancing process for game levels in a competitive two-player context involves a lot of manual work and testing, particularly in non-symmetrical game levels. In this paper, we propose an architecture for automated balancing...	[]	Test
17,730	30	Title: Pre-training for Speech Translation: CTC Meets Optimal Transport Abstract: The gap between speech and text modalities is a major challenge in speech-to-text translation (ST). Different methods have been proposed to reduce this gap, but most of them require architectural changes in ST training. In this work, we p...	[]	Train
17,731	31	Title: Parallel Knowledge Enhancement based Framework for Multi-behavior Recommendation Abstract: Multi-behavior recommendation algorithms aim to leverage the multiplex interactions between users and items to learn users' latent preferences. Recent multi-behavior recommendation frameworks contain two steps: fusion and ...	[ 17825 ]	Validation
17,732	24	Title: Adaptive Depth Graph Attention Networks Abstract: As one of the most popular GNN architectures, the graph attention networks (GAT) is considered the most advanced learning architecture for graph representation and has been widely used in various graph mining tasks with impressive results. However, since GAT was ...	[]	Validation
17,733	34	Title: In Which Graph Structures Can We Efficiently Find Temporally Disjoint Paths and Walks? Abstract: A temporal graph has an edge set that may change over discrete time steps, and a temporal path (or walk) must traverse edges that appear at increasing time steps. Accordingly, two temporal paths (or walks) are tempor...	[]	Train
17,734	4	Title: DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models Abstract: Recently, Generative Diffusion Models (GDMs) have showcased their remarkable capabilities in learning and generating images. A large community of GDMs has naturally emerged, further promoting the diversified appli...	[ 7586, 30376, 26158, 8308, 34074 ]	Test
17,735	24	Title: Discovery of sparse hysteresis models for piezoelectric materials Abstract: This article presents an approach for modeling hysteresis in piezoelectric materials that leverages recent advancements in machine learning, particularly in sparse-regression techniques. While sparse regression has previously been used t...	[ 7902 ]	Train
17,736	30	Title: Pre-training Language Model as a Multi-perspective Course Learner Abstract: ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing performance, ELECTRA still faces the challenges of monotonous tr...	[]	Train
17,737	24	Title: Speeding Up EfficientNet: Selecting Update Blocks of Convolutional Neural Networks using Genetic Algorithm in Transfer Learning Abstract: The performance of convolutional neural networks (CNN) depends heavily on their architectures. Transfer learning performance of a CNN relies quite strongly on selection of its...	[]	Train
17,738	31	Title: Annotating Data for Fine-Tuning a Neural Ranker? Current Active Learning Strategies are not Better than Random Selection Abstract: Search methods based on Pretrained Language Models (PLM) have demonstrated great effectiveness gains compared to statistical and early neural ranking models. However, fine-tuning PLM...	[]	Train
17,739	24	Title: Non-Asymptotic Performance of Social Machine Learning Under Limited Data Abstract: This paper studies the probability of error associated with the social machine learning framework, which involves an independent training phase followed by a cooperative decision-making phase over a graph. This framework addresses...	[]	Test
17,740	24	Title: A model is worth tens of thousands of examples Abstract: Traditional signal processing methods relying on mathematical data generation models have been cast aside in favour of deep neural networks, which require vast amounts of data. Since the theoretical sample complexity is nearly impossible to evaluate, these...	[ 31418 ]	Test
17,741	27	Title: Holistic Graph-based Motion Prediction Abstract: Motion prediction for automated vehicles in complex environments is a difficult task that is to be mastered when automated vehicles are to be used in arbitrary situations. Many factors influence the future motion of traffic participants starting with traffic rules...	[]	Train
17,742	4	Title: Systematic Evaluation of Geolocation Privacy Mechanisms Abstract: Location data privacy has become a serious concern for users as Location Based Services (LBSs) have become an important part of their life. It is possible for malicious parties having access to geolocation data to learn sensitive information about...	[]	Train
17,743	24	Title: Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence Abstract: This study probes the vulnerabilities of cooperative multi-agent reinforcement learning (c-MARL) under adversarial attacks, a critical determinant of c-MARL's worst-case performance prior to real-world implementa...	[ 25632, 14209, 13510, 32170, 16436 ]	Validation
17,744	30	Title: GenQ: Automated Question Generation to Support Caregivers While Reading Stories with Children Abstract: When caregivers ask open--ended questions to motivate dialogue with children, it facilitates the child's reading comprehension skills.Although there is scope for use of technological tools, referred here as"in...	[]	Train
17,745	34	Title: Distributed Construction of Near-Optimal Compact Routing Schemes for Planar Graphs Abstract: We consider the problem of computing compact routing tables for a (weighted) planar graph $G:= (V, E,w)$ in the PRAM, CONGEST, and the novel HYBRID communication model. We present algorithms with polylogarithmic work and...	[]	Test
17,746	24	Title: Accelerating Fair Federated Learning: Adaptive Federated Adam Abstract: Federated learning is a distributed and privacy-preserving approach to train a statistical model col-laboratively from decentralized data of different parties. However, when datasets of participants are not independent and identically distri...	[ 45124 ]	Train
17,747	24	Title: Mathematical analysis of singularities in the diffusion model under the submanifold assumption Abstract: This paper provide several mathematical analyses of the diffusion model in machine learning. The drift term of the backwards sampling process is represented as a conditional expectation involving the data dis...	[]	Train
17,748	24	Title: One-Shot Online Testing of Deep Neural Networks Based on Distribution Shift Detection Abstract: Neural networks (NNs) are capable of learning complex patterns and relationships in data to make predictions with high accuracy, making them useful for various tasks. However, NNs are both computation-intensive and me...	[]	Train
17,749	16	Title: Structure Embedded Nucleus Classification for Histopathology Images Abstract: Nuclei classification provides valuable information for histopathology image analysis. However, the large variations in the appearance of different nuclei types cause difficulties in identifying nuclei. Most neural network based method...	[]	Train
17,750	4	Title: TUSH-Key: Transferable User Secrets on Hardware Key Abstract: Passwordless authentication was first tested for seamless and secure merchant payments without the use of passwords or pins. It opened a whole new world of authentications giving up the former reliance on traditional passwords. It relied on the W3C We...	[]	Train
17,751	13	Title: Im2win: An Efficient Convolution Paradigm on GPU Abstract: Convolution is the most time-consuming operation in deep neural network operations, so its performance is critical to the overall performance of the neural network. The commonly used methods for convolution on GPU include the general matrix multiplicatio...	[]	Validation
17,752	14	Title: Data Augmentation for Mathematical Objects Abstract: This paper discusses and evaluates ideas of data balancing and data augmentation in the context of mathematical objects: an important topic for both the symbolic computation and satisfiability checking communities, when they are making use of machine learning ...	[ 45216, 45212 ]	Test
17,753	5	Title: Power Constrained Autotuning using Graph Neural Networks Abstract: Recent advances in multi and many-core processors have led to significant improvements in the performance of scientific computing applications. However, the addition of a large number of complex cores have also increased the overall power consump...	[ 18898 ]	Train
17,754	14	Title: On Rueppel's Linear Complexity Conjecture Abstract: Rueppel's conjecture on the linear complexity of the first $n$ terms of the sequence $(1,1,0,1,0^3,1,0^7,1,0^{15},\ldots)$ was first proved by Dai using the Euclidean algorithm. We have previously shown that we can attach a homogeneous (annihilator) ideal of $F...	[]	Train
17,755	39	Title: The Coxeter symmetries of high-level general sequential computation in the invertible-digital and quantum domains Abstract: The article investigates high-level general invertible-sequential processing in the digital and quantum domains. In particular it is shown that (i) invertible digital-sequential processes, ...	[]	Train
17,756	24	Title: Ranking with Abstention Abstract: We introduce a novel framework of ranking with abstention, where the learner can abstain from making prediction at some limited cost $c$. We present a extensive theoretical analysis of this framework including a series of $H$-consistency bounds for both the family of linear func...	[ 15228, 26831 ]	Test
17,757	24	Title: On information captured by neural networks: connections with memorization and generalization Abstract: Despite the popularity and success of deep learning, there is limited understanding of when, how, and why neural networks generalize to unseen examples. Since learning can be seen as extracting information from...	[]	Train
17,758	24	Title: Using Explainable AI to Cross-Validate Socio-economic Disparities Among Covid-19 Patient Mortality Abstract: This paper applies eXplainable Artificial Intelligence (XAI) methods to investigate the socioeconomic disparities in COVID-19 patient mortality. An Extreme Gradient Boosting (XGBoost) prediction model is ...	[]	Train
17,759	24	Title: Machine Fault Classification using Hamiltonian Neural Networks Abstract: A new approach is introduced to classify faults in rotating machinery based on the total energy signature estimated from sensor measurements. The overall goal is to go beyond using black-box models and incorporate additional physical constr...	[ 7165 ]	Train
17,760	6	Title: Modeling online adaptive navigation in virtual environments based on PID control Abstract: It is well known that locomotion-dominated navigation tasks may highly provoke cybersickness effects. Past research has proposed numerous approaches to tackle this issue based on offline considerations. In this work, a nov...	[]	Train
17,761	6	Title: Eleven Years of Gender Data Visualization: A Step Towards More Inclusive Gender Representation Abstract: We present an analysis of the representation of gender as a data dimension in data visualizations and propose a set of considerations around visual variables and annotations for gender-related data. Gender is...	[ 42383 ]	Train
17,762	24	Title: GFlowNet-EM for learning compositional latent variable models Abstract: Latent variable models (LVMs) with discrete compositional latents are an important but challenging setting due to a combinatorially large number of possible configurations of the latents. A key tradeoff in modeling the posteriors over latent...	[ 43749, 34630, 15438, 24784, 9778, 29267, 9686 ]	Train
17,763	23	Title: AutoRepair: Automated Repair for AI-Enabled Cyber-Physical Systems under Safety-Critical Conditions Abstract: Cyber-Physical Systems (CPS) have been widely deployed in safety-critical domains such as transportation, power and energy. Recently, there comes an increasing demand in employing deep neural networks (D...	[]	Train
17,764	6	Title: Investigating the Uncanny Valley Phenomenon Through the Temporal Dynamics of Neural Responses to Virtual Characters Abstract: The Uncanny Valley phenomenon refers to the feeling of unease that arises when interacting with characters that appear almost, but not quite, human-like. First theorised by Masahiro Mori ...	[]	Validation
17,765	30	Title: Exploring Speaker-Related Information in Spoken Language Understanding for Better Speaker Diarization Abstract: Speaker diarization(SD) is a classic task in speech processing and is crucial in multi-party scenarios such as meetings and conversations. Current mainstream speaker diarization approaches consider aco...	[]	Train
17,766	30	Title: Evaluating the Role of Target Arguments in Rumour Stance Classification Abstract: Considering a conversation thread, stance classification aims to identify the opinion (e.g. agree or disagree) of replies towards a given target. The target of the stance is expected to be an essential component in this task, being...	[]	Train
17,767	5	Title: Towards Confidential Computing: A Secure Cloud Architecture for Big Data Analytics and AI Abstract: Cloud computing provisions computer resources at a cost-effective way based on demand. Therefore it has become a viable solution for big data analytics and artificial intelligence which have been widely adopted in...	[]	Test
17,768	24	Title: Kernel Limit of Recurrent Neural Networks Trained on Ergodic Data Sequences Abstract: Mathematical methods are developed to characterize the asymptotics of recurrent neural networks (RNN) as the number of hidden units, data samples in the sequence, hidden state updates, and training steps simultaneously grow to ...	[]	Train
17,769	16	Title: RemoteTouch: Enhancing Immersive 3D Video Communication with Hand Touch Abstract: Recent research advance has significantly improved the visual real-ism of immersive 3D video communication. In this work we present a method to further enhance this immersive experience by adding the hand touch capability (“remote ...	[]	Validation
17,770	16	Title: Gender, Smoking History, and Age Prediction from Laryngeal Images Abstract: Flexible laryngoscopy is commonly performed by otolaryngologists to detect laryngeal diseases and to recognize potentially malignant lesions. Recently, researchers have introduced machine learning techniques to facilitate automated diagn...	[]	Train
17,771	24	Title: Reliable Gradient-free and Likelihood-free Prompt Tuning Abstract: Due to privacy or commercial constraints, large pre-trained language models (PLMs) are often offered as black-box APIs. Fine-tuning such models to downstream tasks is challenging because one can neither access the model’s internal representations...	[ 26441, 6538 ]	Train
17,772	34	Title: On the Maximal Independent Sets of k-mers with the Edit Distance Abstract: In computational biology, $k$-mers and edit distance are fundamental concepts. However, little is known about the metric space of all $k$-mers equipped with the edit distance. In this work, we explore the structure of the $k$-mer space by...	[]	Train
17,773	31	Title: InPars Toolkit: A Unified and Reproducible Synthetic Data Generation Pipeline for Neural Information Retrieval Abstract: Recent work has explored Large Language Models (LLMs) to overcome the lack of training data for Information Retrieval (IR) tasks. The generalization abilities of these models have enabled the ...	[ 39377, 7866 ]	Train
17,774	16	Title: Evolving Three Dimension (3D) Abstract Art: Fitting Concepts by Language Abstract: Computational creativity has contributed heavily to abstract art in modern era, allowing artists to create high quality, abstract two dimension (2D) arts with a high level of controllability and expressibility. However, even with ...	[]	Test
17,775	24	Title: Developmental Curiosity and Social Interaction in Virtual Agents Abstract: Infants explore their complex physical and social environment in an organized way. To gain insight into what intrinsic motivations may help structure this exploration, we create a virtual infant agent and place it in a developmentally-ins...	[]	Train
17,776	16	Title: Exploring Deep Models for Practical Gait Recognition Abstract: Gait recognition is a rapidly advancing vision technique for person identification from a distance. Prior studies predominantly employed relatively small and shallow neural networks to extract subtle gait features, achieving impressive successes in i...	[ 33208, 25171, 14596 ]	Train
17,777	30	Title: Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs Abstract: Large language models (LLMs), such as ChatGPT and GPT-4, are versatile and can solve different tasks due to their emergent ability and generalizability. However, LLMs sometimes lack domain-specific knowledge to perform...	[ 12128, 14368, 28151, 13700, 13029, 33220, 9518, 32213, 12087, 43641, 35580, 45695 ]	Validation

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.