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
2305.10366	Set-Membership Filtering-Based Cooperative State Estimation for Multi-Agent Systems	In this article, we focus on the cooperative state estimation problem of a multi-agent system. Each agent is equipped with absolute and relative measurements. The purpose of this research is to make each agent generate its own state estimation with only local measurement information and local communication with neighbo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	365,022
2404.15296	Maximum Discrepancy Generative Regularization and Non-Negative Matrix Factorization for Single Channel Source Separation	The idea of adversarial learning of regularization functionals has recently been introduced in the wider context of inverse problems. The intuition behind this method is the realization that it is not only necessary to learn the basic features that make up a class of signals one wants to represent, but also, or even mo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	449,031
1807.08087	Capacity Analysis for Full Duplex Self-backhauled Small Cells	Full duplex (FD) communication enables simultaneous transmission and reception on the same frequency band. Though it has the potential of doubling the throughput on isolated links, in reality, higher interference and asymmetric traffic demands in the uplink and downlink could significantly reduce the gains of FD operat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	103,450
2402.05876	Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices	Offline reinforcement learning (RL), which seeks to learn an optimal policy using offline data, has garnered significant interest due to its potential in critical applications where online data collection is infeasible or expensive. This work explores the benefit of federated learning for offline RL, aiming at collabor...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	428,041
2203.13692	Bisimulations for Verifying Strategic Abilities with an Application to the ThreeBallot Voting Protocol	We propose a notion of alternating bisimulation for strategic abilities under imperfect information. The bisimulation preserves formulas of ATL$^*$ for both the {\em objective} and {\em subjective} variants of the state-based semantics with imperfect information, which are commonly used in the modeling and verification...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	287,728
2210.02862	Causal Inference for Chatting Handoff	Aiming to ensure chatbot quality by predicting chatbot failure and enabling human-agent collaboration, Machine-Human Chatting Handoff (MHCH) has attracted lots of attention from both industry and academia in recent years. However, most existing methods mainly focus on the dialogue context or assist with global satisfac...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	321,805
2207.06814	BERTIN: Efficient Pre-Training of a Spanish Language Model using Perplexity Sampling	The pre-training of large language models usually requires massive amounts of resources, both in terms of computation and data. Frequently used web sources such as Common Crawl might contain enough noise to make this pre-training sub-optimal. In this work, we experiment with different sampling methods from the Spanish ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	308,001
2411.01019	A lightweight Convolutional Neural Network based on U shape structure and Attention Mechanism for Anterior Mediastinum Segmentation	To automatically detect Anterior Mediastinum Lesions (AMLs) in the Anterior Mediastinum (AM), the primary requirement will be an automatic segmentation model specifically designed for the AM. The prevalence of AML is extremely low, making it challenging to conduct screening research similar to lung cancer screening. Re...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	504,876
1909.03965	Evaluating Long-form Text-to-Speech: Comparing the Ratings of Sentences and Paragraphs	Text-to-speech systems are typically evaluated on single sentences. When long-form content, such as data consisting of full paragraphs or dialogues is considered, evaluating sentences in isolation is not always appropriate as the context in which the sentences are synthesized is missing. In this paper, we investigate t...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	144,657
2202.02796	GLPanoDepth: Global-to-Local Panoramic Depth Estimation	In this paper, we propose a learning-based method for predicting dense depth values of a scene from a monocular omnidirectional image. An omnidirectional image has a full field-of-view, providing much more complete descriptions of the scene than perspective images. However, fully-convolutional networks that most curren...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,948
2209.14064	A mass-conserving sparse grid combination technique with biorthogonal hierarchical basis functions for kinetic simulations	The exact numerical simulation of plasma turbulence is one of the assets and challenges in fusion research. For grid-based solvers, sufficiently fine resolutions are often unattainable due to the curse of dimensionality. The sparse grid combination technique provides the means to alleviate the curse of dimensionality f...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	320,125
2412.12448	Task-Parameter Nexus: Task-Specific Parameter Learning for Model-Based Control	This paper presents the Task-Parameter Nexus (TPN), a learning-based approach for online determination of the (near-)optimal control parameters of model-based controllers (MBCs) for tracking tasks. In TPN, a deep neural network is introduced to predict the control parameters for any given tracking task at runtime, espe...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	517,869
1403.0284	Bayes Merging of Multiple Vocabularies for Scalable Image Retrieval	The Bag-of-Words (BoW) representation is well applied to recent state-of-the-art image retrieval works. Typically, multiple vocabularies are generated to correct quantization artifacts and improve recall. However, this routine is corrupted by vocabulary correlation, i.e., overlapping among different vocabularies. Vocab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	31,280
1703.10730	Unsupervised Holistic Image Generation from Key Local Patches	We introduce a new problem of generating an image based on a small number of key local patches without any geometric prior. In this work, key local patches are defined as informative regions of the target object or scene. This is a challenging problem since it requires generating realistic images and predicting locatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,966
1905.05006	Time-Series Event Prediction with Evolutionary State Graph	The accurate and interpretable prediction of future events in time-series data often requires the capturing of representative patterns (or referred to as states) underpinning the observed data. To this end, most existing studies focus on the representation and recognition of states, but ignore the changing transitional...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,618
2111.09496	Developing a Machine Learning Algorithm-Based Classification Models for the Detection of High-Energy Gamma Particles	Cherenkov gamma telescope observes high energy gamma rays, taking advantage of the radiation emitted by charged particles produced inside the electromagnetic showers initiated by the gammas, and developing in the atmosphere. The detector records and allows for the reconstruction of the shower parameters. The reconstruc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,034
2307.10915	Revisiting Fine-Tuning Strategies for Self-supervised Medical Imaging Analysis	Despite the rapid progress in self-supervised learning (SSL), end-to-end fine-tuning still remains the dominant fine-tuning strategy for medical imaging analysis. However, it remains unclear whether this approach is truly optimal for effectively utilizing the pre-trained knowledge, especially considering the diverse ca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,735
2407.04737	Hierarchical Decoupling Capacitor Optimization for Power Distribution Network of 2.5D ICs with Co-Analysis of Frequency and Time Domains Based on Deep Reinforcement Learning	With the growing need for higher memory bandwidth and computation density, 2.5D design, which involves integrating multiple chiplets onto an interposer, emerges as a promising solution. However, this integration introduces significant challenges due to increasing data rates and a large number of I/Os, necessitating adv...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	470,684
2210.12352	NeuPhysics: Editable Neural Geometry and Physics from Monocular Videos	We present a method for learning 3D geometry and physics parameters of a dynamic scene from only a monocular RGB video input. To decouple the learning of underlying scene geometry from dynamic motion, we represent the scene as a time-invariant signed distance function (SDF) which serves as a reference frame, along with...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	325,699
2210.07661	CAB: Comprehensive Attention Benchmarking on Long Sequence Modeling	Transformer has achieved remarkable success in language, image, and speech processing. Recently, various efficient attention architectures have been proposed to improve transformer's efficiency while largely preserving its efficacy, especially in modeling long sequences. A widely-used benchmark to test these efficient ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	323,816
1801.03623	Optimal locally repairable codes of distance $3$ and $4$ via cyclic codes	Like classical block codes, a locally repairable code also obeys the Singleton-type bound (we call a locally repairable code {\it optimal} if it achieves the Singleton-type bound). In the breakthrough work of \cite{TB14}, several classes of optimal locally repairable codes were constructed via subcodes of Reed-Solomon ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	88,133
2403.13551	Ground-A-Score: Scaling Up the Score Distillation for Multi-Attribute Editing	Despite recent advancements in text-to-image diffusion models facilitating various image editing techniques, complex text prompts often lead to an oversight of some requests due to a bottleneck in processing text information. To tackle this challenge, we present Ground-A-Score, a simple yet powerful model-agnostic imag...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	439,678
cs/0203021	NetNeg: A Connectionist-Agent Integrated System for Representing Musical Knowledge	The system presented here shows the feasibility of modeling the knowledge involved in a complex musical activity by integrating sub-symbolic and symbolic processes. This research focuses on the question of whether there is any advantage in integrating a neural network together with a distributed artificial intelligence...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	537,527
2412.11815	ColorFlow: Retrieval-Augmented Image Sequence Colorization	Automatic black-and-white image sequence colorization while preserving character and object identity (ID) is a complex task with significant market demand, such as in cartoon or comic series colorization. Despite advancements in visual colorization using large-scale generative models like diffusion models, challenges w...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	517,596
2404.09696	Are Large Language Models Reliable Argument Quality Annotators?	Evaluating the quality of arguments is a crucial aspect of any system leveraging argument mining. However, it is a challenge to obtain reliable and consistent annotations regarding argument quality, as this usually requires domain-specific expertise of the annotators. Even among experts, the assessment of argument qual...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	446,797
2409.13286	Generative Learning Powered Probing Beam Optimization for Cell-Free Hybrid Beamforming	Probing beam measurement (PBM)-based hybrid beamforming provides a feasible solution for cell-free MIMO. In this letter, we propose a novel probing beam optimization framework where three collaborative modules respectively realize PBM augmentation, sum-rate prediction and probing beam optimization. Specifically, the PB...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	489,929
1803.04813	Artificial neural network based modelling approach for municipal solid waste gasification in a fluidized bed reactor	In this paper, multi-layer feed forward neural networks are used to predict the lower heating value of gas (LHV), lower heating value of gasification products including tars and entrained char (LHVp) and syngas yield during gasification of municipal solid waste (MSW) during gasification in a fluidized bed reactor. Thes...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	92,521
2011.07584	Pix2Streams: Dynamic Hydrology Maps from Satellite-LiDAR Fusion	Where are the Earth's streams flowing right now? Inland surface waters expand with floods and contract with droughts, so there is no one map of our streams. Current satellite approaches are limited to monthly observations that map only the widest streams. These are fed by smaller tributaries that make up much of the de...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	206,603
1811.08840	Integrating Reinforcement Learning to Self Training for Pulmonary Nodule Segmentation in Chest X-rays	Machine learning applications in medical imaging are frequently limited by the lack of quality labeled data. In this paper, we explore the self training method, a form of semi-supervised learning, to address the labeling burden. By integrating reinforcement learning, we were able to expand the application of self train...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	114,137
2105.02573	Assessing Dialogue Systems with Distribution Distances	An important aspect of developing dialogue systems is how to evaluate and compare the performance of different systems. Existing automatic evaluation metrics are based on turn-level quality evaluation and use average scores for system-level comparison. In this paper, we propose to measure the performance of a dialogue ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	233,859
2111.09076	To Trust or Not To Trust Prediction Scores for Membership Inference Attacks	Membership inference attacks (MIAs) aim to determine whether a specific sample was used to train a predictive model. Knowing this may indeed lead to a privacy breach. Most MIAs, however, make use of the model's prediction scores - the probability of each output given some input - following the intuition that the traine...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	266,899
2101.07517	FUBOCO: Structure Synthesis of Basic Op-Amps by FUnctional BlOck COmposition	This paper presents a method to automatically synthesize the structure of an operational amplifier. It is positioned between approaches with fixed design plans and a small search space of structures and approaches with generic structural production rules and a large search space with technically impractical structures....	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	216,054
1907.10559	QRMODA and BRMODA: Novel Models for Face Recognition Accuracy in Computer Vision Systems with Adapted Video Streams	A major challenge facing Computer Vision systems is providing the ability to accurately detect threats and recognize subjects and/or objects under dynamically changing network conditions. We propose two novel models that characterize the face recognition accuracy in terms of video encoding parameters. Specifically, we ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	139,653
2410.01100	Unlocking Korean Verbs: A User-Friendly Exploration into the Verb Lexicon	The Sejong dictionary dataset offers a valuable resource, providing extensive coverage of morphology, syntax, and semantic representation. This dataset can be utilized to explore linguistic information in greater depth. The labeled linguistic structures within this dataset form the basis for uncovering relationships be...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	493,609
2105.09279	Unsupervised Discriminative Learning of Sounds for Audio Event Classification	Recent progress in network-based audio event classification has shown the benefit of pre-training models on visual data such as ImageNet. While this process allows knowledge transfer across different domains, training a model on large-scale visual datasets is time consuming. On several audio event classification benchm...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	236,019
2110.10030	Accelerating Framework of Transformer by Hardware Design and Model Compression Co-Optimization	State-of-the-art Transformer-based models, with gigantic parameters, are difficult to be accommodated on resource constrained embedded devices. Moreover, with the development of technology, more and more embedded devices are available to run a Transformer model. For a Transformer model with different constraints (tight...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,013
2304.00387	HaLP: Hallucinating Latent Positives for Skeleton-based Self-Supervised Learning of Actions	Supervised learning of skeleton sequence encoders for action recognition has received significant attention in recent times. However, learning such encoders without labels continues to be a challenging problem. While prior works have shown promising results by applying contrastive learning to pose sequences, the qualit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	355,664
2004.01113	ProxyNCA++: Revisiting and Revitalizing Proxy Neighborhood Component Analysis	We consider the problem of distance metric learning (DML), where the task is to learn an effective similarity measure between images. We revisit ProxyNCA and incorporate several enhancements. We find that low temperature scaling is a performance-critical component and explain why it works. Besides, we also discover tha...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	170,819
2405.12421	A Unified Linear Programming Framework for Offline Reward Learning from Human Demonstrations and Feedback	Inverse Reinforcement Learning (IRL) and Reinforcement Learning from Human Feedback (RLHF) are pivotal methodologies in reward learning, which involve inferring and shaping the underlying reward function of sequential decision-making problems based on observed human demonstrations and feedback. Most prior work in rewar...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	455,512
2203.08731	Tangles and Hierarchical Clustering	We establish a connection between tangles, a concept from structural graph theory that plays a central role in Robertson and Seymour's graph minor project, and hierarchical clustering. Tangles cannot only be defined for graphs, but in fact for arbitrary connectivity functions, which are functions defined on the subsets...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	285,893
2311.07166	NDDepth: Normal-Distance Assisted Monocular Depth Estimation and Completion	Over the past few years, monocular depth estimation and completion have been paid more and more attention from the computer vision community because of their widespread applications. In this paper, we introduce novel physics (geometry)-driven deep learning frameworks for these two tasks by assuming that 3D scenes are c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	407,225
1512.01725	The Evolution of Wikipedia's Norm Network	Social norms have traditionally been difficult to quantify. In any particular society, their sheer number and complex interdependencies often limit a system-level analysis. One exception is that of the network of norms that sustain the online Wikipedia community. We study the fifteen-year evolution of this network usin...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	49,850
2408.11266	Practical Aspects on Solving Differential Equations Using Deep Learning: A Primer	Deep learning has become a popular tool across many scientific fields, including the study of differential equations, particularly partial differential equations. This work introduces the basic principles of deep learning and the Deep Galerkin method, which uses deep neural networks to solve differential equations. Thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	482,205
1711.07893	Effective Strategies in Zero-Shot Neural Machine Translation	In this paper, we proposed two strategies which can be applied to a multilingual neural machine translation system in order to better tackle zero-shot scenarios despite not having any parallel corpus. The experiments show that they are effective in terms of both performance and computing resources, especially in multil...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	85,092
2206.05478	Monitoring and Proactive Management of QoS Levels in Pervasive Applications	The advent of Edge Computing (EC) as a promising paradigm that provides multiple computation and analytics capabilities close to data sources opens new pathways for novel applications. Nonetheless, the limited computational capabilities of EC nodes and the expectation of ensuring high levels of QoS during tasks executi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	302,018
2206.04003	Patch-based Object-centric Transformers for Efficient Video Generation	In this work, we present Patch-based Object-centric Video Transformer (POVT), a novel region-based video generation architecture that leverages object-centric information to efficiently model temporal dynamics in videos. We build upon prior work in video prediction via an autoregressive transformer over the discrete la...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	301,480
2207.09682	Quantized Training of Gradient Boosting Decision Trees	Recent years have witnessed significant success in Gradient Boosting Decision Trees (GBDT) for a wide range of machine learning applications. Generally, a consensus about GBDT's training algorithms is gradients and statistics are computed based on high-precision floating points. In this paper, we investigate an essenti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	308,983
1704.04313	CBinfer: Change-Based Inference for Convolutional Neural Networks on Video Data	Extracting per-frame features using convolutional neural networks for real-time processing of video data is currently mainly performed on powerful GPU-accelerated workstations and compute clusters. However, there are many applications such as smart surveillance cameras that require or would benefit from on-site process...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	71,787
1903.02313	Learning from Higher-Layer Feature Visualizations	Driven by the goal to enable sleep apnea monitoring and machine learning-based detection at home with small mobile devices, we investigate whether interpretation-based indirect knowledge transfer can be used to create classifiers with acceptable performance. Interpretation-based indirect knowledge transfer means that a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,479
2409.15882	Exploring VQ-VAE with Prosody Parameters for Speaker Anonymization	Human speech conveys prosody, linguistic content, and speaker identity. This article investigates a novel speaker anonymization approach using an end-to-end network based on a Vector-Quantized Variational Auto-Encoder (VQ-VAE) to deal with these speech components. This approach is designed to disentangle these componen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	491,108
2102.05547	Learning Equational Theorem Proving	We develop Stratified Shortest Solution Imitation Learning (3SIL) to learn equational theorem proving in a deep reinforcement learning (RL) setting. The self-trained models achieve state-of-the-art performance in proving problems generated by one of the top open conjectures in quasigroup theory, the Abelian Inner Mappi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	219,478
1608.00147	Attention Span For Personalisation	A click on an item is arguably the most widely used feature in recommender systems. However, a click is one out of 174 events a browser can trigger. This paper presents a framework to effectively collect and store data from event streams. A set of mining methods is provided to extract user engagement features such as: ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	59,231
2003.02943	A deep learning-facilitated radiomics solution for the prediction of lung lesion shrinkage in non-small cell lung cancer trials	Herein we propose a deep learning-based approach for the prediction of lung lesion response based on radiomic features extracted from clinical CT scans of patients in non-small cell lung cancer trials. The approach starts with the classification of lung lesions from the set of primary and metastatic lesions at various ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	167,075
2010.11793	Metapath- and Entity-aware Graph Neural Network for Recommendation	In graph neural networks (GNNs), message passing iteratively aggregates nodes' information from their direct neighbors while neglecting the sequential nature of multi-hop node connections. Such sequential node connections e.g., metapaths, capture critical insights for downstream tasks. Concretely, in recommender system...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	202,429
2110.04898	Response surface single loop reliability-based design optimization with higher-order reliability assessment	Reliability-based design optimization (RBDO) aims at determination of the optimal design in the presence of uncertainty. The available Single-Loop approaches for RBDO are based on the First-Order Reliability Method (FORM) for the computation of the probability of failure, along with different approximations in order to...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	260,076
1806.06336	Improving Network Availability of Ultra-Reliable and Low-Latency Communications with Multi-Connectivity	Ultra-reliable and low-latency communications (URLLC) have stringent requirements on quality-of-service and network availability. Due to path loss and shadowing, it is very challenging to guarantee the stringent requirements of URLLC with satisfactory communication range. In this paper, we first provide a quantitative ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	100,681
2405.19093	Multi-stage Retrieve and Re-rank Model for Automatic Medical Coding Recommendation	The International Classification of Diseases (ICD) serves as a definitive medical classification system encompassing a wide range of diseases and conditions. The primary objective of ICD indexing is to allocate a subset of ICD codes to a medical record, which facilitates standardized documentation and management of var...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	458,747
2410.22284	Embedding-based classifiers can detect prompt injection attacks	Large Language Models (LLMs) are seeing significant adoption in every type of organization due to their exceptional generative capabilities. However, LLMs are found to be vulnerable to various adversarial attacks, particularly prompt injection attacks, which trick them into producing harmful or inappropriate content. A...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	503,566
2407.07221	Tracing Back the Malicious Clients in Poisoning Attacks to Federated Learning	Poisoning attacks compromise the training phase of federated learning (FL) such that the learned global model misclassifies attacker-chosen inputs called target inputs. Existing defenses mainly focus on protecting the training phase of FL such that the learnt global model is poison free. However, these defenses often a...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	471,674
2001.01798	Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition	Teacher-student (T/S) has shown to be effective for domain adaptation of deep neural network acoustic models in hybrid speech recognition systems. In this work, we extend the T/S learning to large-scale unsupervised domain adaptation of an attention-based end-to-end (E2E) model through two levels of knowledge transfer:...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	159,575
2403.14713	Auditing Fairness under Unobserved Confounding	Many definitions of fairness or inequity involve unobservable causal quantities that cannot be directly estimated without strong assumptions. For instance, it is particularly difficult to estimate notions of fairness that rely on hard-to-measure concepts such as risk (e.g., quantifying whether patients at the same risk...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	440,221
2302.06683	Enhancing Multivariate Time Series Classifiers through Self-Attention and Relative Positioning Infusion	Time Series Classification (TSC) is an important and challenging task for many visual computing applications. Despite the extensive range of methods developed for TSC, relatively few utilized Deep Neural Networks (DNNs). In this paper, we propose two novel attention blocks (Global Temporal Attention and Temporal Pseudo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	345,494
2009.07964	Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis	Aspect-based sentiment analysis (ABSA) aims to predict the sentiment towards a specific aspect in the text. However, existing ABSA test sets cannot be used to probe whether a model can distinguish the sentiment of the target aspect from the non-target aspects. To solve this problem, we develop a simple but effective ap...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	196,084
0805.0510	Iterative Hard Thresholding for Compressed Sensing	Compressed sensing is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper we present a theoretical analysis of the iterative hard thresholding algorithm when applied to the compressed sensing recovery problem. We show that the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	1,714
2107.03690	Proceedings of the First Workshop on Weakly Supervised Learning (WeaSuL)	Welcome to WeaSuL 2021, the First Workshop on Weakly Supervised Learning, co-located with ICLR 2021. In this workshop, we want to advance theory, methods and tools for allowing experts to express prior coded knowledge for automatic data annotations that can be used to train arbitrary deep neural networks for prediction...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,228
2104.09373	My Experience in Physical Layer Communications	I feel that I have been very lucky since I have experienced the most dynamic 30 years on electronics in the past. I think that the most visible change in our daily life over the past 30 years is communications. From computer modems, to internet, and to smart phones, people now feel much less lonely or bored since they ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	231,213
cond-mat/0202190	Threshold Disorder as a Source of Diverse and Complex Behavior in Random Nets	We study the diversity of complex spatio-temporal patterns in the behavior of random synchronous asymmetric neural networks (RSANNs). Special attention is given to the impact of disordered threshold values on limit-cycle diversity and limit-cycle complexity in RSANNs which have `normal' thresholds by default. Surprisin...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	536,937
2303.11117	EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation	Emotion Recognition in Conversation (ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies. In this paper, we propose an emotional inertia and contagion-driven dependency modeling approach (EmotionIC) for ERC task. Our EmotionIC c...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	352,711
2207.06757	Secure Network Function Computation for Linear Functions -- Part I: Source Security	In this paper, we put forward secure network function computation over a directed acyclic network. In such a network, a sink node is required to compute with zero error a target function of which the inputs are generated as source messages at multiple source nodes, while a wiretapper, who can access any one but not mor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	307,982
2101.02069	Model Extraction and Defenses on Generative Adversarial Networks	Model extraction attacks aim to duplicate a machine learning model through query access to a target model. Early studies mainly focus on discriminative models. Despite the success, model extraction attacks against generative models are less well explored. In this paper, we systematically study the feasibility of model ...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	214,518
2407.08073	NDST: Neural Driving Style Transfer for Human-Like Vision-Based Autonomous Driving	Autonomous Vehicles (AV) and Advanced Driver Assistant Systems (ADAS) prioritize safety over comfort. The intertwining factors of safety and comfort emerge as pivotal elements in ensuring the effectiveness of Autonomous Driving (AD). Users often experience discomfort when AV or ADAS drive the vehicle on their behalf. P...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	471,998
2305.12309	Uniform Pricing vs Pay as Bid in 100%-Renewables Electricity Markets: A Game-theoretical Analysis	This paper evaluates market equilibrium under different pricing mechanisms in a two-settlement 100%-renewables electricity market. Given general probability distributions of renewable energy, we establish game-theoretical models to analyze equilibrium bidding strategies, market prices, and profits under uniform pricing...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	365,938
1511.03690	Deep Multimodal Semantic Embeddings for Speech and Images	In this paper, we present a model which takes as input a corpus of images with relevant spoken captions and finds a correspondence between the two modalities. We employ a pair of convolutional neural networks to model visual objects and speech signals at the word level, and tie the networks together with an embedding a...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	48,785
1807.10562	Contributions to the development of the CRO-SL algorithm: Engineering applications problems	This Ph.D. thesis discusses advanced design issues of the evolutionary-based algorithm \textit{"Coral Reef Optimization"}, in its Substrate-Layer (CRO-SL) version, for optimization problems in Engineering Applications. The problems that can be tackled with meta-heuristic approaches is very wide and varied, and it is no...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	103,959
0801.4716	Methods to integrate a language model with semantic information for a word prediction component	Most current word prediction systems make use of n-gram language models (LM) to estimate the probability of the following word in a phrase. In the past years there have been many attempts to enrich such language models with further syntactic or semantic information. We want to explore the predictive powers of Latent Se...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	1,232
1403.2024	Node Removal Vulnerability of the Largest Component of a Network	The connectivity structure of a network can be very sensitive to removal of certain nodes in the network. In this paper, we study the sensitivity of the largest component size to node removals. We prove that minimizing the largest component size is equivalent to solving a matrix one-norm minimization problem whose colu...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	31,454
2408.08544	Scaling up Multimodal Pre-training for Sign Language Understanding	Sign language serves as the primary meaning of communication for the deaf-mute community. Different from spoken language, it commonly conveys information by the collaboration of manual features, i.e., hand gestures and body movements, and non-manual features, i.e., facial expressions and mouth cues. To facilitate commu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	481,035
2309.01552	OutRank: Speeding up AutoML-based Model Search for Large Sparse Data sets with Cardinality-aware Feature Ranking	The design of modern recommender systems relies on understanding which parts of the feature space are relevant for solving a given recommendation task. However, real-world data sets in this domain are often characterized by their large size, sparsity, and noise, making it challenging to identify meaningful signals. Fea...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	389,723
1802.02605	Unsupervised word sense disambiguation in dynamic semantic spaces	In this paper, we are mainly concerned with the ability to quickly and automatically distinguish word senses in dynamic semantic spaces in which new terms and new senses appear frequently. Such spaces are built '"on the fly" from constantly evolving data sets such as Wikipedia, repositories of patent grants and applica...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	89,802
2107.10173	Assured Mission Adaptation of UAVs	The design of systems that can change their behaviour to account for scenarios that were not foreseen at design time remains an open challenge. In this paper we propose an approach for adaptation of mobile robot missions that is not constrained to a predefined set of mission evolutions. We propose applying the MORPH ad...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	247,234
2104.05082	The Core of Approval Participatory Budgeting with Uniform Costs (or with up to Four Projects) is Non-Empty	In the Approval Participatory Budgeting problem an agent prefers a set of projects $W'$ over $W$ if she approves strictly more projects in $W'$. A set of projects $W$ is in the core, if there is no other set of projects $W'$ and set of agents $K$ that both prefer $W'$ over $W$ and can fund $W'$. It is an open problem w...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	229,597
2410.01791	DreamGarden: A Designer Assistant for Growing Games from a Single Prompt	Coding assistants are increasingly leveraged in game design, both generating code and making high-level plans. To what degree can these tools align with developer workflows, and what new modes of human-computer interaction can emerge from their use? We present DreamGarden, an AI system capable of assisting with the dev...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	493,947
2410.23526	LEAF: Learning and Evaluation Augmented by Fact-Checking to Improve Factualness in Large Language Models	Large language models (LLMs) have shown remarkable capabilities in various natural language processing tasks, yet they often struggle with maintaining factual accuracy, particularly in knowledge-intensive domains like healthcare. This study introduces LEAF: Learning and Evaluation Augmented by Fact-Checking, a novel ap...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	504,072
2501.10401	Custom Loss Functions in Fuel Moisture Modeling	Fuel moisture content (FMC) is a key predictor for wildfire rate of spread (ROS). Machine learning models of FMC are being used more in recent years, augmenting or replacing traditional physics-based approaches. Wildfire rate of spread (ROS) has a highly nonlinear relationship with FMC, where small differences in dry f...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	525,505
2212.07611	Residual Policy Learning for Powertrain Control	Eco-driving strategies have been shown to provide significant reductions in fuel consumption. This paper outlines an active driver assistance approach that uses a residual policy learning (RPL) agent trained to provide residual actions to default power train controllers while balancing fuel consumption against other dr...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	336,460
2110.00415	Optimization Networks for Integrated Machine Learning	Optimization networks are a new methodology for holistically solving interrelated problems that have been developed with combinatorial optimization problems in mind. In this contribution we revisit the core principles of optimization networks and demonstrate their suitability for solving machine learning problems. We u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,377
2303.00934	Helpful, Misleading or Confusing: How Humans Perceive Fundamental Building Blocks of Artificial Intelligence Explanations	Explainable artificial intelligence techniques are developed at breakneck speed, but suitable evaluation approaches lag behind. With explainers becoming increasingly complex and a lack of consensus on how to assess their utility, it is challenging to judge the benefit and effectiveness of different explanations. To add...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	348,757
1309.3029	On the Chi square and higher-order Chi distances for approximating f-divergences	We report closed-form formula for calculating the Chi square and higher-order Chi distances between statistical distributions belonging to the same exponential family with affine natural space, and instantiate those formula for the Poisson and isotropic Gaussian families. We then describe an analytic formula for the $f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	26,991
2108.11674	Graph-guided random forest for gene set selection	Machine learning methods can detect complex relationships between variables, but usually do not exploit domain knowledge. This is a limitation because in many scientific disciplines, such as systems biology, domain knowledge is available in the form of graphs or networks, and its use can improve model performance. We n...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	252,249
2404.07445	Multi-view Aggregation Network for Dichotomous Image Segmentation	Dichotomous Image Segmentation (DIS) has recently emerged towards high-precision object segmentation from high-resolution natural images. When designing an effective DIS model, the main challenge is how to balance the semantic dispersion of high-resolution targets in the small receptive field and the loss of high-pre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,830
2310.16376	GADY: Unsupervised Anomaly Detection on Dynamic Graphs	Anomaly detection on dynamic graphs refers to detecting entities whose behaviors obviously deviate from the norms observed within graphs and their temporal information. This field has drawn increasing attention due to its application in finance, network security, social networks, and more. However, existing methods fac...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	402,702
1011.0298	Intuitionistic Fuzzy Ideal Extensions of {\Gamma}-Semigroups	In this paper the concept of the extensions of intuitionistic fuzzy ideals in a semigroup has been extended to a {\Gamma}-Semigroups. Among other results characterization of prime ideals in a {\Gamma}-Semigroups in terms of intuitionistic fuzzy ideal extension has been obtained.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,090
2404.18684	Work Smarter...Not Harder: Efficient Minimization of Dependency Length in SOV Languages	Dependency length minimization is a universally observed quantitative property of natural languages. However, the extent of dependency length minimization, and the cognitive mechanisms through which the language processor achieves this minimization remain unclear. This research offers mechanistic insights by postulatin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	450,353
2006.00885	CoAID: COVID-19 Healthcare Misinformation Dataset	As the COVID-19 virus quickly spreads around the world, unfortunately, misinformation related to COVID-19 also gets created and spreads like wild fire. Such misinformation has caused confusion among people, disruptions in society, and even deadly consequences in health problems. To be able to understand, detect, and mi...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,600
1610.00054	Outlier Detection from Network Data with Subnetwork Interpretation	Detecting a small number of outliers from a set of data observations is always challenging. This problem is more difficult in the setting of multiple network samples, where computing the anomalous degree of a network sample is generally not sufficient. In fact, explaining why the network is exceptional, expressed in th...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	61,785
1901.01479	Center of Gravity-based Approach for Modeling Dynamics of Multisection Continuum Arms	Multisection continuum arms offer complementary characteristics to those of traditional rigid-bodied robots. Inspired by biological appendages, such as elephant trunks and octopus arms, these robots trade rigidity for compliance, accuracy for safety, and therefore exhibit strong potential for applications in human-occu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	117,983
2008.01848	Forecasting AI Progress: A Research Agenda	Forecasting AI progress is essential to reducing uncertainty in order to appropriately plan for research efforts on AI safety and AI governance. While this is generally considered to be an important topic, little work has been conducted on it and there is no published document that gives and objective overview of the f...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	190,448
1207.2711	The Outage Probability of a Finite Ad Hoc Network in Nakagami Fading	An ad hoc network with a finite spatial extent and number of nodes or mobiles is analyzed. The mobile locations may be drawn from any spatial distribution, and interference-avoidance protocols or protection against physical collisions among the mobiles may be modeled by placing an exclusion zone around each radio. The ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	17,411
2403.07209	The entropic doubling constant and robustness of Gaussian codebooks for additive-noise channels	Entropy comparison inequalities are obtained for the differential entropy $h(X+Y)$ of the sum of two independent random vectors $X,Y$, when one is replaced by a Gaussian. For identically distributed random vectors $X,Y$, these are closely related to bounds on the entropic doubling constant, which quantifies the entropy...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	436,778
2201.01586	Learning True Rate-Distortion-Optimization for End-To-End Image Compression	Even though rate-distortion optimization is a crucial part of traditional image and video compression, not many approaches exist which transfer this concept to end-to-end-trained image compression. Most frameworks contain static compression and decompression models which are fixed after training, so efficient rate-dist...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	274,290

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