Split (2)

train · 433k rows

id stringlengths 9 16	title stringlengths 4 278	abstract stringlengths 3 4.08k	cs.HC bool 2 classes	cs.CE bool 2 classes	cs.SD bool 2 classes	cs.SI bool 2 classes	cs.AI bool 2 classes	cs.IR bool 2 classes	cs.LG bool 2 classes	cs.RO bool 2 classes	cs.CL bool 2 classes	cs.IT bool 2 classes	cs.SY bool 2 classes	cs.CV bool 2 classes	cs.CR bool 2 classes	cs.CY bool 2 classes	cs.MA bool 2 classes	cs.NE bool 2 classes	cs.DB bool 2 classes	Other bool 2 classes	__index_level_0__ int64 0 541k
2110.09374	Ortho-Shot: Low Displacement Rank Regularization with Data Augmentation for Few-Shot Learning	In few-shot classification, the primary goal is to learn representations from a few samples that generalize well for novel classes. In this paper, we propose an efficient low displacement rank (LDR) regularization strategy termed Ortho-Shot; a technique that imposes orthogonal regularization on the convolutional layers...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	261,788
2304.01902	Affective Robotics For Wellbeing: A Scoping Review	Affective robotics research aims to better understand human social and emotional signals to improve human-robot interaction (HRI), and has been widely used during the last decade in multiple application fields. Past works have demonstrated, indeed, the potential of using affective robots (i.e., that can recognize, or i...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	356,249
2106.07627	Toward Automatic Interpretation of 3D Plots	This paper explores the challenge of teaching a machine how to reverse-engineer the grid-marked surfaces used to represent data in 3D surface plots of two-variable functions. These are common in scientific and economic publications; and humans can often interpret them with ease, quickly gleaning general shape and curva...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	240,997
1811.01715	Multi-armed Bandits with Compensation	We propose and study the known-compensation multi-arm bandit (KCMAB) problem, where a system controller offers a set of arms to many short-term players for $T$ steps. In each step, one short-term player arrives to the system. Upon arrival, the player aims to select an arm with the current best average reward and receiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,431
2501.14452	On the Rate-Exponent Region of Integrated Sensing and Communications With Variable-Length Coding	This paper considers the achievable rate-exponent region of integrated sensing and communication systems in the presence of variable-length coding with feedback. This scheme is fundamentally different from earlier studies, as the coding methods that utilize feedback impose different constraints on the codewords. The fo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	527,123
2206.06520	Memory-Based Model Editing at Scale	Even the largest neural networks make errors, and once-correct predictions can become invalid as the world changes. Model editors make local updates to the behavior of base (pre-trained) models to inject updated knowledge or correct undesirable behaviors. Existing model editors have shown promise, but also suffer from ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	302,402
2304.13302	HiQ -- A Declarative, Non-intrusive, Dynamic and Transparent Observability and Optimization System	This paper proposes a non-intrusive, declarative, dynamic and transparent system called `HiQ` to track Python program runtime information without compromising on the run-time system performance and losing insight. HiQ can be used for monolithic and distributed systems, offline and online applications. HiQ is developed ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	360,535
1711.08155	A Face Fairness Framework for 3D Meshes	In this paper, we present a face fairness framework for 3D meshes that preserves the regular shape of faces and is applicable to a variety of 3D mesh restoration tasks. Specifically, we present a number of desirable properties for any mesh restoration method and show that our framework satisfies them. We then apply our...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,146
1706.03791	Significantly Improving Lossy Compression for Scientific Data Sets Based on Multidimensional Prediction and Error-Controlled Quantization	Today's HPC applications are producing extremely large amounts of data, such that data storage and analysis are becoming more challenging for scientific research. In this work, we design a new error-controlled lossy compression algorithm for large-scale scientific data. Our key contribution is significantly improving t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	75,223
2404.14808	Visual-Augmented Dynamic Semantic Prototype for Generative Zero-Shot Learning	Generative Zero-shot learning (ZSL) learns a generator to synthesize visual samples for unseen classes, which is an effective way to advance ZSL. However, existing generative methods rely on the conditions of Gaussian noise and the predefined semantic prototype, which limit the generator only optimized on specific seen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	448,826
2409.12257	MQA-KEAL: Multi-hop Question Answering under Knowledge Editing for Arabic Language	Large Language Models (LLMs) have demonstrated significant capabilities across numerous application domains. A key challenge is to keep these models updated with latest available information, which limits the true potential of these models for the end-applications. Although, there have been numerous attempts for LLMs K...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	489,502
1911.06155	RNN-Test: Towards Adversarial Testing for Recurrent Neural Network Systems	While massive efforts have been investigated in adversarial testing of convolutional neural networks (CNN), testing for recurrent neural networks (RNN) is still limited and leaves threats for vast sequential application domains. In this paper, we propose an adversarial testing framework RNN-Test for RNN systems, focusi...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	153,463
2309.13047	NeuroCADR: Drug Repurposing to Reveal Novel Anti-Epileptic Drug Candidates Through an Integrated Computational Approach	Drug repurposing is an emerging approach for drug discovery involving the reassignment of existing drugs for novel purposes. An alternative to the traditional de novo process of drug development, repurposed drugs are faster, cheaper, and less failure prone than drugs developed from traditional methods. Recently, drug r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	394,025
2302.06354	Less is More: Selective Layer Finetuning with SubTuning	Finetuning a pretrained model has become a standard approach for training neural networks on novel tasks, resulting in fast convergence and improved performance. In this work, we study an alternative finetuning method, where instead of finetuning all the weights of the network, we only train a carefully chosen subset o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	345,370
2008.13585	At Your Service: Coffee Beans Recommendation From a Robot Assistant	With advances in the field of machine learning, precisely algorithms for recommendation systems, robot assistants are envisioned to become more present in the hospitality industry. Additionally, the COVID-19 pandemic has also highlighted the need to have more service robots in our everyday lives, to minimise the risk o...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	193,889
1707.02733	Synthesis-based Robust Low Resolution Face Recognition	Recognition of low resolution face images is a challenging problem in many practical face recognition systems. Methods have been proposed in the face recognition literature for the problem which assume that the probe is low resolution, but a high resolution gallery is available for recognition. These attempts have been...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,748
1511.07953	Exploring Correlation between Labels to improve Multi-Label Classification	This paper attempts multi-label classification by extending the idea of independent binary classification models for each output label, and exploring how the inherent correlation between output labels can be used to improve predictions. Logistic Regression, Naive Bayes, Random Forest, and SVM models were constructed, w...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	49,489
2409.14639	Impedance Control for Manipulators Handling Heavy Payloads	Attaching a heavy payload to the wrist force/moment (F/M) sensor of a manipulator can cause conventional impedance controllers to fail in establishing the desired impedance due to the presence of non-contact forces; namely, the inertial and gravitational forces of the payload. This paper presents an impedance control s...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	490,564
2206.06712	Visual Radial Basis Q-Network	While reinforcement learning (RL) from raw images has been largely investigated in the last decade, existing approaches still suffer from a number of constraints. The high input dimension is often handled using either expert knowledge to extract handcrafted features or environment encoding through convolutional network...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	302,470
2207.05064	Adaptive Graph Spatial-Temporal Transformer Network for Traffic Flow Forecasting	Traffic flow forecasting on graphs has real-world applications in many fields, such as transportation system and computer networks. Traffic forecasting can be highly challenging due to complex spatial-temporal correlations and non-linear traffic patterns. Existing works mostly model such spatial-temporal dependencies b...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	307,411
2411.14972	Open-Amp: Synthetic Data Framework for Audio Effect Foundation Models	This paper introduces Open-Amp, a synthetic data framework for generating large-scale and diverse audio effects data. Audio effects are relevant to many musical audio processing and Music Information Retrieval (MIR) tasks, such as modelling of analog audio effects, automatic mixing, tone matching and transcription. Exi...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	510,390
2307.11684	Minibatching Offers Improved Generalization Performance for Second Order Optimizers	Training deep neural networks (DNNs) used in modern machine learning is computationally expensive. Machine learning scientists, therefore, rely on stochastic first-order methods for training, coupled with significant hand-tuning, to obtain good performance. To better understand performance variability of different stoc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	380,990
1608.03639	Faster Training of Very Deep Networks Via p-Norm Gates	A major contributing factor to the recent advances in deep neural networks is structural units that let sensory information and gradients to propagate easily. Gating is one such structure that acts as a flow control. Gates are employed in many recent state-of-the-art recurrent models such as LSTM and GRU, and feedforwa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	59,697
2411.10632	Quantifying community evolution in temporal networks	When we detect communities in temporal networks it is important to ask questions about how they change in time. Normalised Mutual Information (NMI) has been used to measure the similarity of communities when the nodes on a network do not change. We propose two extensions namely Union-Normalised Mutual Information (UNMI...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	508,724
1605.06409	R-FCN: Object Detection via Region-based Fully Convolutional Networks	We present region-based, fully convolutional networks for accurate and efficient object detection. In contrast to previous region-based detectors such as Fast/Faster R-CNN that apply a costly per-region subnetwork hundreds of times, our region-based detector is fully convolutional with almost all computation shared on ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	56,131
2105.07645	Leveraging EfficientNet and Contrastive Learning for Accurate Global-scale Location Estimation	In this paper, we address the problem of global-scale image geolocation, proposing a mixed classification-retrieval scheme. Unlike other methods that strictly tackle the problem as a classification or retrieval task, we combine the two practices in a unified solution leveraging the advantages of each approach with two ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,509
2409.01087	Pre-Trained Language Models for Keyphrase Prediction: A Review	Keyphrase Prediction (KP) is essential for identifying keyphrases in a document that can summarize its content. However, recent Natural Language Processing (NLP) advances have developed more efficient KP models using deep learning techniques. The limitation of a comprehensive exploration jointly both keyphrase extracti...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	485,204
2110.08393	A Bayesian Approach for Medical Inquiry and Disease Inference in Automated Differential Diagnosis	We propose a Bayesian approach for both medical inquiry and disease inference, the two major phases in differential diagnosis. Unlike previous work that simulates data from given probabilities and uses ML algorithms on them, we directly use the Quick Medical Reference (QMR) belief network, and apply Bayesian inference ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	261,373
1911.11451	Optimization of Chance-Constrained Submodular Functions	Submodular optimization plays a key role in many real-world problems. In many real-world scenarios, it is also necessary to handle uncertainty, and potentially disruptive events that violate constraints in stochastic settings need to be avoided. In this paper, we investigate submodular optimization problems with chance...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,133
2011.04797	Attentive Social Recommendation: Towards User And Item Diversities	Social recommendation system is to predict unobserved user-item rating values by taking advantage of user-user social relation and user-item ratings. However, user/item diversities in social recommendations are not well utilized in the literature. Especially, inter-factor (social and rating factors) relations and disti...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	205,692
1604.04383	Composition of Deep and Spiking Neural Networks for Very Low Bit Rate Speech Coding	Most current very low bit rate (VLBR) speech coding systems use hidden Markov model (HMM) based speech recognition/synthesis techniques. This allows transmission of information (such as phonemes) segment by segment that decreases the bit rate. However, the encoder based on a phoneme speech recognition may create bursts...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	54,639
2408.13271	Survey Paper on Control Barrier Functions	Control Barrier Functions (CBFs) have emerged as a powerful paradigm in control theory, providing a principled approach to enforcing safety-critical constraints in dynamic systems. This survey paper comprehensively explores the foundational principles of CBFs, delves into the complexities of High Order Control Barrier ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	483,080
2406.10280	Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries	This study investigates the privacy risks associated with text embeddings, focusing on the scenario where attackers cannot access the original embedding model. Contrary to previous research requiring direct model access, we explore a more realistic threat model by developing a transfer attack method. This approach uses...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	464,332
1702.08021	Friends and Enemies of Clinton and Trump: Using Context for Detecting Stance in Political Tweets	Stance detection, the task of identifying the speaker's opinion towards a particular target, has attracted the attention of researchers. This paper describes a novel approach for detecting stance in Twitter. We define a set of features in order to consider the context surrounding a target of interest with the final aim...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	68,898
1508.05034	Opinion Dynamics in Social Networks with Hostile Camps: Consensus vs. Polarization	Most of the distributed protocols for multi-agent consensus assume that the agents are mutually cooperative and "trustful," and so the couplings among the agents bring the values of their states closer. Opinion dynamics in social groups, however, require beyond these conventional models due to ubiquitous competition an...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	46,192
1806.03743	Are All Languages Equally Hard to Language-Model?	For general modeling methods applied to diverse languages, a natural question is: how well should we expect our models to work on languages with differing typological profiles? In this work, we develop an evaluation framework for fair cross-linguistic comparison of language models, using translated text so that all mod...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	100,074
2105.02960	A Deep Transfer Learning-based Edge Computing Method for Home Health Monitoring	The health-care gets huge stress in a pandemic or epidemic situation. Some diseases such as COVID-19 that causes a pandemic is highly spreadable from an infected person to others. Therefore, providing health services at home for non-critical infected patients with isolation shall assist to mitigate this kind of stress....	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,986
2303.04557	Scene Matters: Model-based Deep Video Compression	Video compression has always been a popular research area, where many traditional and deep video compression methods have been proposed. These methods typically rely on signal prediction theory to enhance compression performance by designing high efficient intra and inter prediction strategies and compressing video fra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,133
2001.04652	A deep machine learning algorithm for construction of the Kolmogorov-Arnold representation	The Kolmogorov-Arnold representation is a proven adequate replacement of a continuous multivariate function by an hierarchical structure of multiple functions of one variable. The proven existence of such representation inspired many researchers to search for a practical way of its construction, since such model answer...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	160,312
1905.03219	Evaluating the Stability of Recurrent Neural Models during Training with Eigenvalue Spectra Analysis	We analyze the stability of recurrent networks, specifically, reservoir computing models during training by evaluating the eigenvalue spectra of the reservoir dynamics. To circumvent the instability arising in examining a closed loop reservoir system with feedback, we propose to break the closed loop system. Essentiall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	130,152
2105.12332	SimNet: Learning Reactive Self-driving Simulations from Real-world Observations	In this work, we present a simple end-to-end trainable machine learning system capable of realistically simulating driving experiences. This can be used for the verification of self-driving system performance without relying on expensive and time-consuming road testing. In particular, we frame the simulation problem as...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	236,976
2409.05872	CSRec: Rethinking Sequential Recommendation from A Causal Perspective	The essence of sequential recommender systems (RecSys) lies in understanding how users make decisions. Most existing approaches frame the task as sequential prediction based on users' historical purchase records. While effective in capturing users' natural preferences, this formulation falls short in accurately modelin...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	486,921
2105.05237	Freshness Based Cache Updating in Parallel Relay Networks	We consider a system consisting of a server, which receives updates for $N$ files according to independent Poisson processes. The goal of the server is to deliver the latest version of the files to the user through a parallel network of $K$ caches. We consider an update received by the user successful, if the user rece...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	234,759
2106.10165	The Principles of Deep Learning Theory	This book develops an effective theory approach to understanding deep neural networks of practical relevance. Beginning from a first-principles component-level picture of networks, we explain how to determine an accurate description of the output of trained networks by solving layer-to-layer iteration equations and non...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	241,922
2308.08213	MEDOE: A Multi-Expert Decoder and Output Ensemble Framework for Long-tailed Semantic Segmentation	Long-tailed distribution of semantic categories, which has been often ignored in conventional methods, causes unsatisfactory performance in semantic segmentation on tail categories. In this paper, we focus on the problem of long-tailed semantic segmentation. Although some long-tailed recognition methods (e.g., re-sampl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,816
1511.06072	Mediated Experts for Deep Convolutional Networks	We present a new supervised architecture termed Mediated Mixture-of-Experts (MMoE) that allows us to improve classification accuracy of Deep Convolutional Networks (DCN). Our architecture achieves this with the help of expert networks: A network is trained on a disjoint subset of a given dataset and then run in paralle...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	49,154
2206.03066	Recent Advances for Quantum Neural Networks in Generative Learning	Quantum computers are next-generation devices that hold promise to perform calculations beyond the reach of classical computers. A leading method towards achieving this goal is through quantum machine learning, especially quantum generative learning. Due to the intrinsic probabilistic nature of quantum mechanics, it is...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	301,137
2108.09048	A Contactless Fingerprint Recognition System	Fingerprints are one of the most widely explored biometric traits. Specifically, contact-based fingerprint recognition systems reign supreme due to their robustness, portability and the extensive research work done in the field. However, these systems suffer from issues such as hygiene, sensor degradation due to consta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	251,479
2101.07124	Tip of the Tongue Known-Item Retrieval: A Case Study in Movie Identification	While current information retrieval systems are effective for known-item retrieval where the searcher provides a precise name or identifier for the item being sought, systems tend to be much less effective for cases where the searcher is unable to express a precise name or identifier. We refer to this as tip of the ton...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	215,941
1901.03729	Automated Rationale Generation: A Technique for Explainable AI and its Effects on Human Perceptions	Automated rationale generation is an approach for real-time explanation generation whereby a computational model learns to translate an autonomous agent's internal state and action data representations into natural language. Training on human explanation data can enable agents to learn to generate human-like explanatio...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	118,473
2406.14529	A Benchmarking Study of Kolmogorov-Arnold Networks on Tabular Data	Kolmogorov-Arnold Networks (KANs) have very recently been introduced into the world of machine learning, quickly capturing the attention of the entire community. However, KANs have mostly been tested for approximating complex functions or processing synthetic data, while a test on real-world tabular datasets is current...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	466,354
2109.14881	Extracting stochastic dynamical systems with $\alpha$-stable L\'evy noise from data	With the rapid increase of valuable observational, experimental and simulated data for complex systems, much efforts have been devoted to identifying governing laws underlying the evolution of these systems. Despite the wide applications of non-Gaussian fluctuations in numerous physical phenomena, the data-driven appro...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,103
2101.04051	Horizontal-to-Vertical Video Conversion	Alongside the prevalence of mobile videos, the general public leans towards consuming vertical videos on hand-held devices. To revitalize the exposure of horizontal contents, we hereby set forth the exploration of automated horizontal-to-vertical (abbreviated as H2V) video conversion with our proposed H2V framework, ac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,057
2310.11976	InfoDiffusion: Information Entropy Aware Diffusion Process for Non-Autoregressive Text Generation	Diffusion models have garnered considerable interest in the field of text generation. Several studies have explored text diffusion models with different structures and applied them to various tasks, including named entity recognition and summarization. However, there exists a notable disparity between the "easy-first" ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	400,856
0710.2889	An efficient reduction of ranking to classification	This paper describes an efficient reduction of the learning problem of ranking to binary classification. The reduction guarantees an average pairwise misranking regret of at most that of the binary classifier regret, improving a recent result of Balcan et al which only guarantees a factor of 2. Moreover, our reduction ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	789
1903.11626	Bridging Adversarial Robustness and Gradient Interpretability	Adversarial training is a training scheme designed to counter adversarial attacks by augmenting the training dataset with adversarial examples. Surprisingly, several studies have observed that loss gradients from adversarially trained DNNs are visually more interpretable than those from standard DNNs. Although this phe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	125,547
2001.10039	Prediction diversity and selective attention in the wisdom of crowds	The wisdom of crowds is the idea that the combination of independent estimates of the magnitude of some quantity yields a remarkably accurate prediction, which is always more accurate than the average individual estimate. In addition, it is largely believed that the accuracy of the crowd can be improved by increasing t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	161,719
2404.12447	AmbigDocs: Reasoning across Documents on Different Entities under the Same Name	Different entities with the same name can be difficult to distinguish. Handling confusing entity mentions is a crucial skill for language models (LMs). For example, given the question "Where was Michael Jordan educated?" and a set of documents discussing different people named Michael Jordan, can LMs distinguish entity...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	447,890
2011.08641	A Review of Generalized Zero-Shot Learning Methods	Generalized zero-shot learning (GZSL) aims to train a model for classifying data samples under the condition that some output classes are unknown during supervised learning. To address this challenging task, GZSL leverages semantic information of the seen (source) and unseen (target) classes to bridge the gap between b...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,941
2410.04925	Intent Classification for Bank Chatbots through LLM Fine-Tuning	This study evaluates the application of large language models (LLMs) for intent classification within a chatbot with predetermined responses designed for banking industry websites. Specifically, the research examines the effectiveness of fine-tuning SlovakBERT compared to employing multilingual generative models, such ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	495,497
1511.08476	Low-Complexity SINR Feasibility Checking and Joint Power and Admission Control in Prioritized Multi-tier Cellular Networks	Next generation cellular networks will consist of multiple tiers of cells and users associated with different network tiers may have different priorities (e.g., macrocell-picocell-femtocell networks with macro tier prioritized over pico tier, which is again prioritized over femto tier). Designing efficient joint power ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	49,543
2110.08756	Stability evaluation of the Russian sociologists online community: 2011-2018 years	This study deals with the stability evaluation of the online community of Russian sociologists. Based on the data from the Facebook group, which consists of 7 years of communication from 2011 till 2018, we constructed the networks based on commenting and reacting. The participants activity includes four main periods fo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	261,544
2211.02213	SSDA-YOLO: Semi-supervised Domain Adaptive YOLO for Cross-Domain Object Detection	Domain adaptive object detection (DAOD) aims to alleviate transfer performance degradation caused by the cross-domain discrepancy. However, most existing DAOD methods are dominated by outdated and computationally intensive two-stage Faster R-CNN, which is not the first choice for industrial applications. In this paper,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	328,507
2104.10956	FCOS3D: Fully Convolutional One-Stage Monocular 3D Object Detection	Monocular 3D object detection is an important task for autonomous driving considering its advantage of low cost. It is much more challenging than conventional 2D cases due to its inherent ill-posed property, which is mainly reflected in the lack of depth information. Recent progress on 2D detection offers opportunities...	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	false	false	false	231,771
1912.12635	\AE THEL: Automatically Extracted Typelogical Derivations for Dutch	We present {\AE}THEL, a semantic compositionality dataset for written Dutch. {\AE}THEL consists of two parts. First, it contains a lexicon of supertags for about 900 000 words in context. The supertags correspond to types of the simply typed linear lambda-calculus, enhanced with dependency decorations that capture gram...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	158,894
2203.02217	Quantification of emotions in decision making	The problem of quantification of emotions in the choice between alternatives is considered. The alternatives are evaluated in a dual manner. From one side, they are characterized by rational features defining the utility of each alternative. From the other side, the choice is affected by emotions labeling the alternati...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	283,686
2208.08226	Auto-segmentation of Hip Joints using MultiPlanar UNet with Transfer learning	Accurate geometry representation is essential in developing finite element models. Although generally good, deep-learning segmentation approaches with only few data have difficulties in accurately segmenting fine features, e.g., gaps and thin structures. Subsequently, segmented geometries need labor-intensive manual mo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	313,307
2103.16775	Attention, please! A survey of Neural Attention Models in Deep Learning	In humans, Attention is a core property of all perceptual and cognitive operations. Given our limited ability to process competing sources, attention mechanisms select, modulate, and focus on the information most relevant to behavior. For decades, concepts and functions of attention have been studied in philosophy, psy...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	227,699
2404.00261	A Simple Yet Effective Approach for Diversified Session-Based Recommendation	Session-based recommender systems (SBRSs) have become extremely popular in view of the core capability of capturing short-term and dynamic user preferences. However, most SBRSs primarily maximize recommendation accuracy but ignore user minor preferences, thus leading to filter bubbles in the long run. Only a handful of...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	442,838
1702.05272	Magnetic MIMO Signal Processing and Optimization for Wireless Power Transfer	In magnetic resonant coupling (MRC) enabled multiple-input multiple-output (MIMO) wireless power transfer (WPT) systems, multiple transmitters (TXs) each with one single coil are used to enhance the efficiency of simultaneous power transfer to multiple single-coil receivers (RXs) by constructively combining their induc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	68,375
1906.01241	Kinetic Market Model: An Evolutionary Algorithm	This research proposes the econophysics kinetic market model as an evolutionary algorithm's instance. The immediate results from this proposal is a new replacement rule for family competition genetic algorithms. It also represents a starting point to adding evolvable entities to kinetic market models.	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	133,651
1511.07917	Context-aware CNNs for person head detection	Person detection is a key problem for many computer vision tasks. While face detection has reached maturity, detecting people under a full variation of camera view-points, human poses, lighting conditions and occlusions is still a difficult challenge. In this work we focus on detecting human heads in natural scenes. St...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	49,482
2404.01958	MESEN: Exploit Multimodal Data to Design Unimodal Human Activity Recognition with Few Labels	Human activity recognition (HAR) will be an essential function of various emerging applications. However, HAR typically encounters challenges related to modality limitations and label scarcity, leading to an application gap between current solutions and real-world requirements. In this work, we propose MESEN, a multimo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	443,664
2402.08856	Approximation of relation functions and attention mechanisms	Inner products of neural network feature maps arise in a wide variety of machine learning frameworks as a method of modeling relations between inputs. This work studies the approximation properties of inner products of neural networks. It is shown that the inner product of a multi-layer perceptron with itself is a univ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,265
2301.12303	Presence of informal language, such as emoticons, hashtags, and slang, impact the performance of sentiment analysis models on social media text?	This study aimed to investigate the influence of the presence of informal language, such as emoticons and slang, on the performance of sentiment analysis models applied to social media text. A convolutional neural network (CNN) model was developed and trained on three datasets: a sarcasm dataset, a sentiment dataset, a...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	342,479
1209.0852	Automatic firewall rules generator for anomaly detection systems with Apriori algorithm	Network intrusion detection systems have become a crucial issue for computer systems security infrastructures. Different methods and algorithms are developed and proposed in recent years to improve intrusion detection systems. The most important issue in current systems is that they are poor at detecting novel anomaly ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	18,396
2401.07721	Graph Transformer GANs with Graph Masked Modeling for Architectural Layout Generation	We present a novel graph Transformer generative adversarial network (GTGAN) to learn effective graph node relations in an end-to-end fashion for challenging graph-constrained architectural layout generation tasks. The proposed graph-Transformer-based generator includes a novel graph Transformer encoder that combines gr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	421,634
2412.17303	When Focus Enhances Utility: Target Range LDP Frequency Estimation and Unknown Item Discovery	Local Differential Privacy (LDP) protocols enable the collection of randomized client messages for data analysis, without the necessity of a trusted data curator. Such protocols have been successfully deployed in real-world scenarios by major tech companies like Google, Apple, and Microsoft. In this paper, we propose a...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	519,916
1011.3400	Prize insights in probability, and one goat of a recycled error: Jason Rosenhouse's The Monty Hall Problem	The Monty Hall problem is the TV game scenario where you, the contestant, are presented with three doors, with a car hidden behind one and goats hidden behind the other two. After you select a door, the host (Monty Hall) opens a second door to reveal a goat. You are then invited to stay with your original choice of doo...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	8,241
0802.1258	Bayesian Nonlinear Principal Component Analysis Using Random Fields	We propose a novel model for nonlinear dimension reduction motivated by the probabilistic formulation of principal component analysis. Nonlinearity is achieved by specifying different transformation matrices at different locations of the latent space and smoothing the transformation using a Markov random field type pri...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	1,266
2502.08603	Scalable Thermodynamic Second-order Optimization	Many hardware proposals have aimed to accelerate inference in AI workloads. Less attention has been paid to hardware acceleration of training, despite the enormous societal impact of rapid training of AI models. Physics-based computers, such as thermodynamic computers, offer an efficient means to solve key primitives i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	533,076
2412.20725	Dialogue Director: Bridging the Gap in Dialogue Visualization for Multimodal Storytelling	Recent advances in AI-driven storytelling have enhanced video generation and story visualization. However, translating dialogue-centric scripts into coherent storyboards remains a significant challenge due to limited script detail, inadequate physical context understanding, and the complexity of integrating cinematic p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	521,331
2207.05462	Adaptive and Robust Cross-Voltage-Level Power Flow Control of Active Distribution Networks	The large-scale integration of Distributed Energy Resources (DERs) into the electric power system offers new opportunities to ensure stability. For example, Active Distribution Networks (ADNs) can be used in (sub-)transmission systems in the emergency state, as far as high robustness and performance of the ADN control ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	307,545
2411.00196	Whole-Herd Elephant Pose Estimation from Drone Data for Collective Behavior Analysis	This research represents a pioneering application of automated pose estimation from drone data to study elephant behavior in the wild, utilizing video footage captured from Samburu National Reserve, Kenya. The study evaluates two pose estimation workflows: DeepLabCut, known for its application in laboratory settings an...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	504,478
2502.04668	Machine-Learning Interatomic Potentials for Long-Range Systems	Machine-learning interatomic potentials have emerged as a revolutionary class of force-field models in molecular simulations, delivering quantum-mechanical accuracy at a fraction of the computational cost and enabling the simulation of large-scale systems over extended timescales. However, they often focus on modeling ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,265
2304.06626	Hebbian fast plasticity and working memory	Theories and models of working memory (WM) were at least since the mid-1990s dominated by the persistent activity hypothesis. The past decade has seen rising concerns about the shortcomings of sustained activity as the mechanism for short-term maintenance of WM information in the light of accumulating experimental evid...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	358,043
1811.06590	Reduced Order Model Predictive Control For Setpoint Tracking	Despite the success of model predictive control (MPC), its application to high-dimensional systems, such as flexible structures and coupled fluid/rigid-body systems, remains a largely open challenge due to excessive computational complexity. A promising solution approach is to leverage reduced order models for designin...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	113,557
1910.08613	Poisson CNN: Convolutional neural networks for the solution of the Poisson equation on a Cartesian mesh	The Poisson equation is commonly encountered in engineering, for instance in computational fluid dynamics (CFD) where it is needed to compute corrections to the pressure field to ensure the incompressibility of the velocity field. In the present work, we propose a novel fully convolutional neural network (CNN) architec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,913
2205.16005	Neural Retriever and Go Beyond: A Thesis Proposal	Information Retriever (IR) aims to find the relevant documents (e.g. snippets, passages, and articles) to a given query at large scale. IR plays an important role in many tasks such as open domain question answering and dialogue systems, where external knowledge is needed. In the past, searching algorithms based on ter...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	299,952
2501.14877	DrawEduMath: Evaluating Vision Language Models with Expert-Annotated Students' Hand-Drawn Math Images	In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	527,305
2502.00706	Model Provenance Testing for Large Language Models	Large language models are increasingly customized through fine-tuning and other adaptations, creating challenges in enforcing licensing terms and managing downstream impacts. Tracking model origins is crucial both for protecting intellectual property and for identifying derived models when biases or vulnerabilities are...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	529,509
2205.08534	Vision Transformer Adapter for Dense Predictions	This work investigates a simple yet powerful dense prediction task adapter for Vision Transformer (ViT). Unlike recently advanced variants that incorporate vision-specific inductive biases into their architectures, the plain ViT suffers inferior performance on dense predictions due to weak prior assumptions. To address...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	296,972
1510.07954	Core-satellite Graphs. Clustering, Assortativity and Spectral Properties	Core-satellite graphs (sometimes referred to as generalized friendship graphs) are an interesting class of graphs that generalize many well known types of graphs. In this paper we show that two popular clustering measures, the average Watts-Strogatz clustering coefficient and the transitivity index, diverge when the gr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,247
1909.09006	APIR-Net: Autocalibrated Parallel Imaging Reconstruction using a Neural Network	Deep learning has been successfully demonstrated in MRI reconstruction of accelerated acquisitions. However, its dependence on representative training data limits the application across different contrasts, anatomies, or image sizes. To address this limitation, we propose an unsupervised, auto-calibrated k-space comple...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	146,120
2106.13415	Building Intelligent Autonomous Navigation Agents	Breakthroughs in machine learning in the last decade have led to `digital intelligence', i.e. machine learning models capable of learning from vast amounts of labeled data to perform several digital tasks such as speech recognition, face recognition, machine translation and so on. The goal of this thesis is to make pro...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	243,069
2204.08545	A Novel Region Duplication Detection Algorithm Based on Hybrid Approach	The digital images from various sources are ubiquitous due to easy availability of high bandwidth Internet. Digital images are easy to tamper with good or bad intentions. Non-availability of pre-embedded information in digital images makes the tampering detection process more difficult in case of digital forensics. Thu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	292,124
0801.0701	Adversarial Models and Resilient Schemes for Network Coding	In a recent paper, Jaggi et al. (INFOCOM 2007), presented a distributed polynomial-time rate-optimal network-coding scheme that works in the presence of Byzantine faults. We revisit their adversarial models and augment them with three, arguably realistic, models. In each of the models, we present a distributed scheme t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	1,120
2112.00443	TROLLMAGNIFIER: Detecting State-Sponsored Troll Accounts on Reddit	Growing evidence points to recurring influence campaigns on social media, often sponsored by state actors aiming to manipulate public opinion on sensitive political topics. Typically, campaigns are performed through instrumented accounts, known as troll accounts; despite their prominence, however, little work has been ...	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	269,140
2412.03304	Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation	Cultural biases in multilingual datasets pose significant challenges for their effectiveness as global benchmarks. These biases stem not only from differences in language but also from the cultural knowledge required to interpret questions, reducing the practical utility of translated datasets like MMLU. Furthermore, t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	513,908
2007.04574	Neural Video Coding using Multiscale Motion Compensation and Spatiotemporal Context Model	Over the past two decades, traditional block-based video coding has made remarkable progress and spawned a series of well-known standards such as MPEG-4, H.264/AVC and H.265/HEVC. On the other hand, deep neural networks (DNNs) have shown their powerful capacity for visual content understanding, feature extraction and c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,401

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