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
1707.06315	FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference	A classical problem in causal inference is that of matching, where treatment units need to be matched to control units based on covariate information. In this work, we propose a method that computes high quality almost-exact matches for high-dimensional categorical datasets. This method, called FLAME (Fast Large-scale ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	77,393
1908.08486	Dialogue Coherence Assessment Without Explicit Dialogue Act Labels	Recent dialogue coherence models use the coherence features designed for monologue texts, e.g. nominal entities, to represent utterances and then explicitly augment them with dialogue-relevant features, e.g., dialogue act labels. It indicates two drawbacks, (a) semantics of utterances is limited to entity mentions, and...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	142,564
0804.3825	On the inner and outer bounds for 2-receiver discrete memoryless broadcast channels	We study the best known general inner bound[MAR '79] and outer bound[N-EG'07] for the capacity region of the two user discrete memory less channel. We prove that a seemingly stronger outer bound is identical to a weaker form of the outer bound that was also presented in [N-EG'07]. We are able to further express the bes...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,625
0806.2726	L2 Orthogonal Space Time Code for Continuous Phase Modulation	To combine the high power efficiency of Continuous Phase Modulation (CPM) with either high spectral efficiency or enhanced performance in low Signal to Noise conditions, some authors have proposed to introduce CPM in a MIMO frame, by using Space Time Codes (STC). In this paper, we address the code design problem of Spa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,929
2109.12081	Deep Social Force	The Social Force model introduced by Helbing and Molnar in 1995 is a cornerstone of pedestrian simulation. This paper introduces a differentiable simulation of the Social Force model where the assumptions on the shapes of interaction potentials are relaxed with the use of universal function approximators in the form of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,155
2411.17722	When IoT Meet LLMs: Applications and Challenges	Recent advances in Large Language Models (LLMs) have positively and efficiently transformed workflows in many domains. One such domain with significant potential for LLM integration is the Internet of Things (IoT), where this integration brings new opportunities for improved decision making and system interaction. In t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	511,568
2310.10299	Forking Uncertainties: Reliable Prediction and Model Predictive Control with Sequence Models via Conformal Risk Control	In many real-world problems, predictions are leveraged to monitor and control cyber-physical systems, demanding guarantees on the satisfaction of reliability and safety requirements. However, predictions are inherently uncertain, and managing prediction uncertainty presents significant challenges in environments charac...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	400,164
1801.06845	Time series kernel similarities for predicting Paroxysmal Atrial Fibrillation from ECGs	We tackle the problem of classifying Electrocardiography (ECG) signals with the aim of predicting the onset of Paroxysmal Atrial Fibrillation (PAF). Atrial fibrillation is the most common type of arrhythmia, but in many cases PAF episodes are asymptomatic. Therefore, in order to help diagnosing PAF, it is important to ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	88,689
2103.01087	Stochastic Model Predictive Control for tracking of distributed linear systems with additive uncertainty	In this paper, we propose a chance constrained stochastic model predictive control scheme for reference tracking of distributed linear time-invariant systems with additive stochastic uncertainty. The chance constraints are reformulated analytically based on mean-variance information, where we design suitable Probabilis...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	222,509
1411.7282	Successive Cancellation List Polar Decoder using Log-likelihood Ratios	Successive cancellation list (SCL) decoding algorithm is a powerful method that can help polar codes achieve excellent error-correcting performance. However, the current SCL algorithm and decoders are based on likelihood or log-likelihood forms, which render high hardware complexity. In this paper, we propose a log-lik...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	37,906
1712.00843	Large-scale analysis of disease pathways in the human interactome	Discovering disease pathways, which can be defined as sets of proteins associated with a given disease, is an important problem that has the potential to provide clinically actionable insights for disease diagnosis, prognosis, and treatment. Computational methods aid the discovery by relying on protein-protein interact...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	85,993
1810.09995	Deep Graph Convolutional Encoders for Structured Data to Text Generation	Most previous work on neural text generation from graph-structured data relies on standard sequence-to-sequence methods. These approaches linearise the input graph to be fed to a recurrent neural network. In this paper, we propose an alternative encoder based on graph convolutional networks that directly exploits the i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	111,174
2006.16569	Forced-exploration free Strategies for Unimodal Bandits	We consider a multi-armed bandit problem specified by a set of Gaussian or Bernoulli distributions endowed with a unimodal structure. Although this problem has been addressed in the literature (Combes and Proutiere, 2014), the state-of-the-art algorithms for such structure make appear a forced-exploration mechanism. We...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	184,848
2104.12259	User Preference-aware Fake News Detection	Disinformation and fake news have posed detrimental effects on individuals and society in recent years, attracting broad attention to fake news detection. The majority of existing fake news detection algorithms focus on mining news content and/or the surrounding exogenous context for discovering deceptive signals; whil...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	232,155
1901.08159	Meta-Learning for Contextual Bandit Exploration	We describe MELEE, a meta-learning algorithm for learning a good exploration policy in the interactive contextual bandit setting. Here, an algorithm must take actions based on contexts, and learn based only on a reward signal from the action taken, thereby generating an exploration/exploitation trade-off. MELEE address...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	119,394
2010.13574	Modeling and Simulation of a Point to Point Spherical Articulated Manipulator using Optimal Control	This paper aims to design an optimal stability controller for a point to point trajectory tracking 3 degree of freedom articulated manipulator. The DH convention is used to obtain the forward and inverse kinematics of the manipulator. The manipulator dynamics are formulated using the Lagrange Euler method to obtain a n...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	203,182
2303.07000	Predicting Density of States via Multi-modal Transformer	The density of states (DOS) is a spectral property of materials, which provides fundamental insights on various characteristics of materials. In this paper, we propose a model to predict the DOS by reflecting the nature of DOS: DOS determines the general distribution of states as a function of energy. Specifically, we ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,076
2411.11451	Robust Markov Decision Processes: A Place Where AI and Formal Methods Meet	Markov decision processes (MDPs) are a standard model for sequential decision-making problems and are widely used across many scientific areas, including formal methods and artificial intelligence (AI). MDPs do, however, come with the restrictive assumption that the transition probabilities need to be precisely known. ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	509,053
2502.13142	Pre-training Auto-regressive Robotic Models with 4D Representations	Foundation models pre-trained on massive unlabeled datasets have revolutionized natural language and computer vision, exhibiting remarkable generalization capabilities, thus highlighting the importance of pre-training. Yet, efforts in robotics have struggled to achieve similar success, limited by either the need for co...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	535,227
1904.02101	The Landscape of R Packages for Automated Exploratory Data Analysis	The increasing availability of large but noisy data sets with a large number of heterogeneous variables leads to the increasing interest in the automation of common tasks for data analysis. The most time-consuming part of this process is the Exploratory Data Analysis, crucial for better domain understanding, data clean...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,331
2312.02501	Inspecting Model Fairness in Ultrasound Segmentation Tasks	With the rapid expansion of machine learning and deep learning (DL), researchers are increasingly employing learning-based algorithms to alleviate diagnostic challenges across diverse medical tasks and applications. While advancements in diagnostic precision are notable, some researchers have identified a concerning tr...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	412,894
2310.10310	Investigating Bias in Multilingual Language Models: Cross-Lingual Transfer of Debiasing Techniques	This paper investigates the transferability of debiasing techniques across different languages within multilingual models. We examine the applicability of these techniques in English, French, German, and Dutch. Using multilingual BERT (mBERT), we demonstrate that cross-lingual transfer of debiasing techniques is not on...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	400,169
1904.12780	A Simple Derivation of the Refined Sphere Packing Bound Under Certain Symmetry Hypotheses	A judicious application of the Berry-Esseen theorem via suitable Augustin information measures is demonstrated to be sufficient for deriving the sphere packing bound with a prefactor that is $\mathit{\Omega}\left(n^{-0.5(1-E_{sp}'(R))}\right)$ for all codes on certain families of channels -- including the Gaussian chan...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	129,224
2201.09871	On Evaluation Metrics for Graph Generative Models	In image generation, generative models can be evaluated naturally by visually inspecting model outputs. However, this is not always the case for graph generative models (GGMs), making their evaluation challenging. Currently, the standard process for evaluating GGMs suffers from three critical limitations: i) it does no...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	276,804
2011.04446	Bangla Text Classification using Transformers	Text classification has been one of the earliest problems in NLP. Over time the scope of application areas has broadened and the difficulty of dealing with new areas (e.g., noisy social media content) has increased. The problem-solving strategy switched from classical machine learning to deep learning algorithms. One o...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	205,587
1604.01151	Use of Non-Orthogonal Multiple Access in Dual-hop relaying	To improve the sum-rate (SR) of the dual-hop relay system, a novel two-stage power allocation scheme with non-orthogonal multiple access (NOMA) is proposed. In this scheme, after the reception of the superposition coded symbol with a power allocation from the source, the relay node forwards a new superposition coded sy...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	54,152
2502.08818	Lexical Manifold Reconfiguration in Large Language Models: A Novel Architectural Approach for Contextual Modulation	Contextual adaptation in token embeddings plays a central role in determining how well language models maintain coherence and retain semantic relationships over extended text sequences. Static embeddings often impose constraints on lexical flexibility, leading to suboptimal performance when faced with complex sentence ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	533,177
2404.00604	Extensive Self-Contrast Enables Feedback-Free Language Model Alignment	Reinforcement learning from human feedback (RLHF) has been a central technique for recent large language model (LLM) alignment. However, its heavy dependence on costly human or LLM-as-Judge preference feedback could stymie its wider applications. In this work, we introduce Self-Contrast, a feedback-free large language ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	443,020
1408.4587	EURETILE D7.3 - Dynamic DAL benchmark coding, measurements on MPI version of DPSNN-STDP (distributed plastic spiking neural net) and improvements to other DAL codes	The EURETILE project required the selection and coding of a set of dedicated benchmarks. The project is about the software and hardware architecture of future many-tile distributed fault-tolerant systems. We focus on dynamic workloads characterised by heavy numerical processing requirements. The ambition is to identify...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	35,471
2106.07455	Resilient and Distributed Discrete Optimal Transport with Deceptive Adversary: A Game-Theoretic Approach	Optimal transport (OT) is a framework that can be used to guide the optimal allocation of a limited amount of resources. The classical OT paradigm does not consider malicious attacks in its formulation and thus the designed transport plan lacks resiliency to an adversary. To address this concern, we establish an OT fra...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	240,931
2106.03315	Semantic and Syntactic Enhanced Aspect Sentiment Triplet Extraction	Aspect Sentiment Triplet Extraction (ASTE) aims to extract triplets from sentences, where each triplet includes an entity, its associated sentiment, and the opinion span explaining the reason for the sentiment. Most existing research addresses this problem in a multi-stage pipeline manner, which neglects the mutual inf...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	239,266
2112.08827	Distributed event-triggered flocking control of Lagrangian systems	In this paper, an event-triggered control protocol is developed to investigate flocking control of Lagrangian systems, where event-triggering conditions are proposed to determine when the velocities of the agents are transmitted to their neighbours. In particular, the proposed controller is distributed, since it only d...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	271,951
2302.09693	mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization	Modern deep learning models are over-parameterized, where different optima can result in widely varying generalization performance. The Sharpness-Aware Minimization (SAM) technique modifies the fundamental loss function that steers gradient descent methods toward flatter minima, which are believed to exhibit enhanced g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,527
1709.10204	A Neural Comprehensive Ranker (NCR) for Open-Domain Question Answering	This paper proposes a novel neural machine reading model for open-domain question answering at scale. Existing machine comprehension models typically assume that a short piece of relevant text containing answers is already identified and given to the models, from which the models are designed to extract answers. This a...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	true	false	false	81,743
1401.3488	Content Modeling Using Latent Permutations	We present a novel Bayesian topic model for learning discourse-level document structure. Our model leverages insights from discourse theory to constrain latent topic assignments in a way that reflects the underlying organization of document topics. We propose a global model in which both topic selection and ordering ar...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	29,892
1101.0350	Graffiti Networks: A Subversive, Internet-Scale File Sharing Model	The proliferation of peer-to-peer (P2P) file sharing protocols is due to their efficient and scalable methods for data dissemination to numerous users. But many of these networks have no provisions to provide users with long term access to files after the initial interest has diminished, nor are they able to guarantee ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	8,706
2108.02174	Knowledge-Grounded Dialogue Flow Management for Social Robots and Conversational Agents	The article proposes a system for knowledge-based conversation designed for Social Robots and other conversational agents. The proposed system relies on an Ontology for the description of all concepts that may be relevant conversation topics, as well as their mutual relationships. The article focuses on the algorithm f...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	249,241
2305.08776	Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models	Foundation models have achieved remarkable results in 2D and language tasks like image segmentation, object detection, and visual-language understanding. However, their potential to enrich 3D scene representation learning is largely untapped due to the existence of the domain gap. In this work, we propose an innovative...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	364,402
2404.15704	Efficient Multi-Model Fusion with Adversarial Complementary Representation Learning	Single-model systems often suffer from deficiencies in tasks such as speaker verification (SV) and image classification, relying heavily on partial prior knowledge during decision-making, resulting in suboptimal performance. Although multi-model fusion (MMF) can mitigate some of these issues, redundancy in learned repr...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	449,204
2303.13110	OCELOT: Overlapped Cell on Tissue Dataset for Histopathology	Cell detection is a fundamental task in computational pathology that can be used for extracting high-level medical information from whole-slide images. For accurate cell detection, pathologists often zoom out to understand the tissue-level structures and zoom in to classify cells based on their morphology and the surro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,550
1106.1631	The combined effect of connectivity and dependency links on percolation of networks	Percolation theory is extensively studied in statistical physics and mathematics with applications in diverse fields. However, the research is focused on systems with only one type of links, connectivity links. We review a recently developed mathematical framework for analyzing percolation properties of realistic scena...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	10,767
1908.10731	DeepCopy: Grounded Response Generation with Hierarchical Pointer Networks	Recent advances in neural sequence-to-sequence models have led to promising results for several language generation-based tasks, including dialogue response generation, summarization, and machine translation. However, these models are known to have several problems, especially in the context of chit-chat based dialogue...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	143,197
2412.06212	A Self-guided Multimodal Approach to Enhancing Graph Representation Learning for Alzheimer's Diseases	Graph neural networks (GNNs) are powerful machine learning models designed to handle irregularly structured data. However, their generic design often proves inadequate for analyzing brain connectomes in Alzheimer's Disease (AD), highlighting the need to incorporate domain knowledge for optimal performance. Infusing AD-...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	515,155
2209.10668	Data-driven, metaheuristic-based off-grid microgrid capacity planning optimisation and scenario analysis: Insights from a case study of Aotea-Great Barrier Island	Small privately-purchased off-grid renewable energy systems (RESs) are increasingly used for energy generation in remote areas. However, such privately-purchased stand-alone RESs are often unaffordable for households with lower incomes. While considerable attention has been devoted to a range of off-grid microgrid sizi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	318,933
2501.00201	Hierarchical Functionality Prioritization in Multicast ISAC: Optimal Admission Control and Discrete-Phase Beamforming	We investigate the joint admission control and discrete-phase multicast beamforming design for integrated sensing and communications (ISAC) systems, where sensing and communications functionalities have different hierarchies. Specifically, the ISAC system first allocates resources to the higher-hierarchy functionality ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	521,572
2401.10474	LDReg: Local Dimensionality Regularized Self-Supervised Learning	Representations learned via self-supervised learning (SSL) can be susceptible to dimensional collapse, where the learned representation subspace is of extremely low dimensionality and thus fails to represent the full data distribution and modalities. Dimensional collapse also known as the "underfilling" phenomenon is o...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	422,652
2406.15529	Supersonic OT: Fast Unconditionally Secure Oblivious Transfer	Oblivious Transfer (OT) is a fundamental cryptographic protocol with applications in secure Multi-Party Computation, Federated Learning, and Private Set Intersection. With the advent of quantum computing, it is crucial to develop unconditionally secure core primitives like OT to ensure their continued security in the p...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	true	false	466,767
2112.01025	A Mixture of Expert Based Deep Neural Network for Improved ASR	This paper presents a novel deep learning architecture for acoustic model in the context of Automatic Speech Recognition (ASR), termed as MixNet. Besides the conventional layers, such as fully connected layers in DNN-HMM and memory cells in LSTM-HMM, the model uses two additional layers based on Mixture of Experts (MoE...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	269,341
2107.11945	A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation	Cross-contrast image translation is an important task for completing missing contrasts in clinical diagnosis. However, most existing methods learn separate translator for each pair of contrasts, which is inefficient due to many possible contrast pairs in real scenarios. In this work, we propose a unified Hyper-GAN mode...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	247,748
1402.1454	An Autoencoder Approach to Learning Bilingual Word Representations	Cross-language learning allows us to use training data from one language to build models for a different language. Many approaches to bilingual learning require that we have word-level alignment of sentences from parallel corpora. In this work we explore the use of autoencoder-based methods for cross-language learning ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	30,671
2104.12311	Stochastic Recurrent Neural Network for Multistep Time Series Forecasting	Time series forecasting based on deep architectures has been gaining popularity in recent years due to their ability to model complex non-linear temporal dynamics. The recurrent neural network is one such model capable of handling variable-length input and output. In this paper, we leverage recent advances in deep gene...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	232,174
2501.05501	Strategy Masking: A Method for Guardrails in Value-based Reinforcement Learning Agents	The use of reward functions to structure AI learning and decision making is core to the current reinforcement learning paradigm; however, without careful design of reward functions, agents can learn to solve problems in ways that may be considered "undesirable" or "unethical." Without thorough understanding of the ince...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	523,627
1211.7052	Quantifying the effect of temporal resolution on time-varying networks	Time-varying networks describe a wide array of systems whose constituents and interactions evolve over time. They are defined by an ordered stream of interactions between nodes, yet they are often represented in terms of a sequence of static networks, each aggregating all edges and nodes present in a time interval of s...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	20,025
1706.09737	Indoor UAV scheduling with Restful Task Assignment Algorithm	Research in UAV scheduling has obtained an emerging interest from scientists in the optimization field. When the scheduling itself has established a strong root since the 19th century, works on UAV scheduling in indoor environment has come forth in the latest decade. Several works on scheduling UAV operations in indoor...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	76,186
2009.04350	Reinforcement Learning in Non-Stationary Discrete-Time Linear-Quadratic Mean-Field Games	In this paper, we study large population multi-agent reinforcement learning (RL) in the context of discrete-time linear-quadratic mean-field games (LQ-MFGs). Our setting differs from most existing work on RL for MFGs, in that we consider a non-stationary MFG over an infinite horizon. We propose an actor-critic algorith...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	195,018
2012.04553	Pattern Morphing for Efficient Graph Mining	Graph mining applications analyze the structural properties of large graphs, and they do so by finding subgraph isomorphisms, which makes them computationally intensive. Existing graph mining techniques including both custom graph mining applications and general-purpose graph mining systems, develop efficient execution...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	210,490
2010.11841	When Does it Pay Off to Learn a New Skill? Revealing the Complementary Benefit of Cross-Skilling	This work examines the economic benefits of learning a new skill from a different domain: cross-skilling. To assess this, a network of skills from the job profiles of 14,790 online freelancers is constructed. Based on this skill network, relationships between 3,480 different skills are revealed and marginal effects of ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	202,446
2406.10417	Enhanced Intrusion Detection System for Multiclass Classification in UAV Networks	Unmanned Aerial Vehicles (UAVs) have become increasingly popular in various applications, especially with the emergence of 6G systems and networks. However, their widespread adoption has also led to concerns regarding security vulnerabilities, making the development of reliable intrusion detection systems (IDS) essenti...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	464,391
1701.08374	Feature base fusion for splicing forgery detection based on neuro fuzzy	Most of researches on image forensics have been mainly focused on detection of artifacts introduced by a single processing tool. They lead in the development of many specialized algorithms looking for one or more particular footprints under specific settings. Naturally, the performance of such algorithms are not perfec...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	67,458
2212.13408	NEEDED: Introducing Hierarchical Transformer to Eye Diseases Diagnosis	With the development of natural language processing techniques(NLP), automatic diagnosis of eye diseases using ophthalmology electronic medical records (OEMR) has become possible. It aims to evaluate the condition of both eyes of a patient respectively, and we formulate it as a particular multi-label classification tas...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	338,296
1607.02232	A Formal Framework for Modeling Trust and Reputation in Collective Adaptive Systems	Trust and reputation models for distributed, collaborative systems have been studied and applied in several domains, in order to stimulate cooperation while preventing selfish and malicious behaviors. Nonetheless, such models have received less attention in the process of specifying and analyzing formally the functiona...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	58,316
1201.5689	An Efficient Construction of Self-Dual Codes	We complete the building-up construction for self-dual codes by resolving the open cases over $GF(q)$ with $q \equiv 3 \pmod 4$, and over $\Z_{p^m}$ and Galois rings $\GR(p^m,r)$ with an odd prime $p$ satisfying $p \equiv 3 \pmod 4$ with $r$ odd. We also extend the building-up construction for self-dual codes to finite...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	13,969
2407.11078	Overcoming Catastrophic Forgetting in Federated Class-Incremental Learning via Federated Global Twin Generator	Federated Class-Incremental Learning (FCIL) increasingly becomes important in the decentralized setting, where it enables multiple participants to collaboratively train a global model to perform well on a sequence of tasks without sharing their private data. In FCIL, conventional Federated Learning algorithms such as F...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	473,292
2409.15126	UTrace: Poisoning Forensics for Private Collaborative Learning	Privacy-preserving machine learning (PPML) enables multiple data owners to contribute their data privately to a set of servers that run a secure multi-party computation (MPC) protocol to train a joint ML model. In these protocols, the input data remains private throughout the training process, and only the resulting mo...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	490,765
1812.00303	Multi-modal Capsule Routing for Actor and Action Video Segmentation Conditioned on Natural Language Queries	In this paper, we propose an end-to-end capsule network for pixel level localization of actors and actions present in a video. The localization is performed based on a natural language query through which an actor and action are specified. We propose to encode both the video as well as textual input in the form of caps...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	115,218
2411.17913	CrypQ: A Database Benchmark Based on Dynamic, Ever-Evolving Ethereum Data	Modern database systems are expected to handle dynamic data whose characteristics may evolve over time. Many popular database benchmarks are limited in their ability to evaluate this dynamic aspect of the database systems. Those that use synthetic data generators often fail to capture the complexity and unpredictable n...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	511,651
2312.13584	Wave Physics-informed Matrix Factorizations	With the recent success of representation learning methods, which includes deep learning as a special case, there has been considerable interest in developing techniques that incorporate known physical constraints into the learned representation. As one example, in many applications that involve a signal propagating th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	417,356
2312.04404	On the Impact of Multi-dimensional Local Differential Privacy on Fairness	Automated decision systems are increasingly used to make consequential decisions in people's lives. Due to the sensitivity of the manipulated data as well as the resulting decisions, several ethical concerns need to be addressed for the appropriate use of such technologies, in particular, fairness and privacy. Unlike p...	false	false	false	false	false	false	true	false	false	false	false	false	true	true	false	false	false	false	413,667
2307.09891	Amortised Design Optimization for Item Response Theory	Item Response Theory (IRT) is a well known method for assessing responses from humans in education and psychology. In education, IRT is used to infer student abilities and characteristics of test items from student responses. Interactions with students are expensive, calling for methods that efficiently gather informat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	380,339
1302.5696	Capacity Bounds for Wireless Ergodic Fading Broadcast Channels with Partial CSIT	The two-user wireless ergodic fading Broadcast Channel (BC) with partial Channel State Information at the Transmitter (CSIT) is considered. The CSIT is given by an arbitrary deterministic function of the channel state. This characteristic yields a full control over how much state information is available, from perfect ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,318
2407.02310	Evaluating the Ability of LLMs to Solve Semantics-Aware Process Mining Tasks	The process mining community has recently recognized the potential of large language models (LLMs) for tackling various process mining tasks. Initial studies report the capability of LLMs to support process analysis and even, to some extent, that they are able to reason about how processes work. This latter property su...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	469,672
2012.15019	Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients	As reinforcement learning techniques are increasingly applied to real-world decision problems, attention has turned to how these algorithms use potentially sensitive information. We consider the task of training a policy that maximizes reward while minimizing disclosure of certain sensitive state variables through the ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	213,669
2309.11107	Indoor Exploration and Simultaneous Trolley Collection Through Task-Oriented Environment Partitioning	In this paper, we present a simultaneous exploration and object search framework for the application of autonomous trolley collection. For environment representation, a task-oriented environment partitioning algorithm is presented to extract diverse information for each sub-task. First, LiDAR data is classified as pote...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	393,283
2304.10854	HabitatDyn Dataset: Dynamic Object Detection to Kinematics Estimation	The advancement of computer vision and machine learning has made datasets a crucial element for further research and applications. However, the creation and development of robots with advanced recognition capabilities are hindered by the lack of appropriate datasets. Existing image or video processing datasets are unab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,586
1112.4057	Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model	In this paper a method is proposed for performance evaluation of road traffic control systems. The method is designed to be implemented in an on-line simulation environment, which enables optimisation of adaptive traffic control strategies. Performance measures are computed using a fuzzy cellular traffic model, formula...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	13,499
2407.07683	The Language of Weather: Social Media Reactions to Weather Accounting for Climatic and Linguistic Baselines	This study explores how different weather conditions influence public sentiment on social media, focusing on Twitter data from the UK. By considering climate and linguistic baselines, we improve the accuracy of weather-related sentiment analysis. Our findings show that emotional responses to weather are complex, influe...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	471,857
2107.14370	Otimizacao de pesos e funcoes de ativacao de redes neurais aplicadas na previsao de series temporais	Neural Networks have been applied for time series prediction with good experimental results that indicate the high capacity to approximate functions with good precision. Most neural models used in these applications use activation functions with fixed parameters. However, it is known that the choice of activation funct...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,443
1209.0229	Efficiency-Risk Tradeoffs in Dynamic Oligopoly Markets - with application to electricity markets	In this paper, we examine in an abstract framework, how a tradeoff between efficiency and robustness arises in different dynamic oligopolistic market architectures. We consider a market in which there is a monopolistic resource provider and agents that enter and exit the market following a random process. Self-interest...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	18,351
2202.11087	Semi-Blind Joint Channel and Symbol Estimation in IRS-Assisted Multi-User MIMO Networks	Intelligent reflecting surface (IRS) is a promising technology for beyond 5th Generation of the wireless communications. In fully passive IRS-assisted systems, channel estimation is challenging and should be carried out only at the base station or at the terminals since the elements of the IRS are incapable of processi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	281,762
2310.03687	Probabilistic Generative Modeling for Procedural Roundabout Generation for Developing Countries	Due to limited resources and fast economic growth, designing optimal transportation road networks with traffic simulation and validation in a cost-effective manner is vital for developing countries, where extensive manual testing is expensive and often infeasible. Current rule-based road design generators lack diversit...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	397,376
2408.04649	Chain of Stance: Stance Detection with Large Language Models	Stance detection is an active task in natural language processing (NLP) that aims to identify the author's stance towards a particular target within a text. Given the remarkable language understanding capabilities and encyclopedic prior knowledge of large language models (LLMs), how to explore the potential of LLMs in ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	479,465
1911.12073	Property Invariant Embedding for Automated Reasoning	Automated reasoning and theorem proving have recently become major challenges for machine learning. In other domains, representations that are able to abstract over unimportant transformations, such as abstraction over translations and rotations in vision, are becoming more common. Standard methods of embedding mathema...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	155,309
2109.07865	OMPQ: Orthogonal Mixed Precision Quantization	To bridge the ever increasing gap between deep neural networks' complexity and hardware capability, network quantization has attracted more and more research attention. The latest trend of mixed precision quantization takes advantage of hardware's multiple bit-width arithmetic operations to unleash the full potential o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,682
1906.06582	A Computational-Hermeneutic Approach for Conceptual Explicitation	We present a computer-supported approach for the logical analysis and conceptual explicitation of argumentative discourse. Computational hermeneutics harnesses recent progresses in automated reasoning for higher-order logics and aims at formalizing natural-language argumentative discourse using flexible combinations of...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	135,344
1812.09912	Image-to-Image Translation via Group-wise Deep Whitening-and-Coloring Transformation	Recently, unsupervised exemplar-based image-to-image translation, conditioned on a given exemplar without the paired data, has accomplished substantial advancements. In order to transfer the information from an exemplar to an input image, existing methods often use a normalization technique, e.g., adaptive instance nor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	117,258
2208.01870	Joint Optimization for Secure and Reliable Communications in Finite Blocklength Regime	To realize ultra-reliable low latency communications with high spectral efficiency and security, we investigate a joint optimization problem for downlink communications with multiple users and eavesdroppers in the finite blocklength (FBL) regime. We formulate a multi-objective optimization problem to maximize a sum sec...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	311,301
2304.14365	Occ3D: A Large-Scale 3D Occupancy Prediction Benchmark for Autonomous Driving	Robotic perception requires the modeling of both 3D geometry and semantics. Existing methods typically focus on estimating 3D bounding boxes, neglecting finer geometric details and struggling to handle general, out-of-vocabulary objects. 3D occupancy prediction, which estimates the detailed occupancy states and semanti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	360,919
2410.20100	Latent Neural Operator Pretraining for Solving Time-Dependent PDEs	Pretraining methods gain increasing attraction recently for solving PDEs with neural operators. It alleviates the data scarcity problem encountered by neural operator learning when solving single PDE via training on large-scale datasets consisting of various PDEs and utilizing shared patterns among different PDEs to im...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	502,651
2305.17295	Rate-Distortion Theory in Coding for Machines and its Application	Recent years have seen a tremendous growth in both the capability and popularity of automatic machine analysis of images and video. As a result, a growing need for efficient compression methods optimized for machine vision, rather than human vision, has emerged. To meet this growing demand, several methods have been de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	368,505
2410.00848	An EM Gradient Algorithm for Mixture Models with Components Derived from the Manly Transformation	Zhu and Melnykov (2018) develop a model to fit mixture models when the components are derived from the Manly transformation. Their EM algorithm utilizes Nelder-Mead optimization in the M-step to update the skew parameter, $\boldsymbol{\lambda}_g$. An alternative EM gradient algorithm is proposed, using one step of Newt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,512
2501.09460	Normal-NeRF: Ambiguity-Robust Normal Estimation for Highly Reflective Scenes	Neural Radiance Fields (NeRF) often struggle with reconstructing and rendering highly reflective scenes. Recent advancements have developed various reflection-aware appearance models to enhance NeRF's capability to render specular reflections. However, the robust reconstruction of highly reflective scenes is still hind...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,151
2410.17494	Enhancing Multimodal Medical Image Classification using Cross-Graph Modal Contrastive Learning	The classification of medical images is a pivotal aspect of disease diagnosis, often enhanced by deep learning techniques. However, traditional approaches typically focus on unimodal medical image data, neglecting the integration of diverse non-image patient data. This paper proposes a novel Cross-Graph Modal Contrasti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	501,485
2502.06817	Diffusion-empowered AutoPrompt MedSAM	MedSAM, a medical foundation model derived from the SAM architecture, has demonstrated notable success across diverse medical domains. However, its clinical application faces two major challenges: the dependency on labor-intensive manual prompt generation, which imposes a significant burden on clinicians, and the absen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	532,263
2105.01331	BLM-17m: A Large-Scale Dataset for Black Lives Matter Topic Detection on Twitter	Protection of human rights is one of the most important problems of our world. In this paper, our aim is to provide a dataset which covers one of the most significant human rights contradiction in recent months affected the whole world, George Floyd incident. We propose a labeled dataset for topic detection that contai...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	233,494
2412.18090	Multi-Point Positional Insertion Tuning for Small Object Detection	Small object detection aims to localize and classify small objects within images. With recent advances in large-scale vision-language pretraining, finetuning pretrained object detection models has emerged as a promising approach. However, finetuning large models is computationally and memory expensive. To address this ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	520,249
1410.4218	Optimal Adaptive Random Multiaccess in Energy Harvesting Wireless Sensor Networks	Wireless sensors can integrate rechargeable batteries and energy-harvesting (EH) devices to enable long-term, autonomous operation, thus requiring intelligent energy management to limit the adverse impact of energy outages. This work considers a network of EH wireless sensors, which report packets with a random utility...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	36,776
1807.00431	Confounding variables can degrade generalization performance of radiological deep learning models	Early results in using convolutional neural networks (CNNs) on x-rays to diagnose disease have been promising, but it has not yet been shown that models trained on x-rays from one hospital or one group of hospitals will work equally well at different hospitals. Before these tools are used for computer-aided diagnosis i...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	101,831
2204.00879	Co-VQA : Answering by Interactive Sub Question Sequence	Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions and finally obtain the answer to the original question after answering the sub question sequence(SQS). By simulating the process, this paper...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,418
1905.01978	CraftAssist Instruction Parsing: Semantic Parsing for a Minecraft Assistant	We propose a large scale semantic parsing dataset focused on instruction-driven communication with an agent in Minecraft. We describe the data collection process which yields additional 35K human generated instructions with their semantic annotations. We report the performance of three baseline models and find that whi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	129,864
2212.12990	Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models	Diffusion Probabilistic Models (DPMs) have shown a powerful capacity of generating high-quality image samples. Recently, diffusion autoencoders (Diff-AE) have been proposed to explore DPMs for representation learning via autoencoding. Their key idea is to jointly train an encoder for discovering meaningful representati...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	338,192

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