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
2112.14209	Joint Activity and Blind Information Detection for UAV-Assisted Massive IoT Access	Grant-free non-coherent index-modulation (NC-IM) has been recently considered as an efficient massive access scheme for enabling cost- and energy-limited Internet-of-Things (IoT) devices that transmit small data packets. This paper investigates the grant-free NC-IM scheme combined with orthogonal frequency division mul...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	273,468
2110.01500	Factorized Neural Transducer for Efficient Language Model Adaptation	In recent years, end-to-end (E2E) based automatic speech recognition (ASR) systems have achieved great success due to their simplicity and promising performance. Neural Transducer based models are increasingly popular in streaming E2E based ASR systems and have been reported to outperform the traditional hybrid system ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	258,791
2009.07971	A Network-Based High-Level Data Classification Algorithm Using Betweenness Centrality	Data classification is a major machine learning paradigm, which has been widely applied to solve a large number of real-world problems. Traditional data classification techniques consider only physical features (e.g., distance, similarity, or distribution) of the input data. For this reason, those are called \textit{lo...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	196,087
1905.08853	Efficient Plane-Based Optimization of Geometry and Texture for Indoor RGB-D Reconstruction	We propose a novel approach to reconstruct RGB-D indoor scene based on plane primitives. Our approach takes as input a RGB-D sequence and a dense coarse mesh reconstructed from it, and generates a lightweight, low-polygonal mesh with clear face textures and sharp features without losing geometry details from the origin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	131,585
2305.03881	Fairness in Image Search: A Study of Occupational Stereotyping in Image Retrieval and its Debiasing	Multi-modal search engines have experienced significant growth and widespread use in recent years, making them the second most common internet use. While search engine systems offer a range of services, the image search field has recently become a focal point in the information retrieval community, as the adage goes, "...	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	362,547
2406.00438	Stein Random Feature Regression	In large-scale regression problems, random Fourier features (RFFs) have significantly enhanced the computational scalability and flexibility of Gaussian processes (GPs) by defining kernels through their spectral density, from which a finite set of Monte Carlo samples can be used to form an approximate low-rank GP. Howe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	459,853
2403.03488	Fast, nonlocal and neural: a lightweight high quality solution to image denoising	With the widespread application of convolutional neural networks (CNNs), the traditional model based denoising algorithms are now outperformed. However, CNNs face two problems. First, they are computationally demanding, which makes their deployment especially difficult for mobile terminals. Second, experimental evidenc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,215
1511.02259	Deterministic Annealing Based Optimization for Zero-Delay Source-Channel Coding in Networks	This paper studies the problem of global optimization of zero-delay source-channel codes that map between the source space and the channel space, under a given transmission power constraint and for the mean square error distortion. Particularly, we focus on two well known network settings: the Wyner-Ziv setting where o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	48,603
2110.02096	Top-N: Equivariant set and graph generation without exchangeability	This work addresses one-shot set and graph generation, and, more specifically, the parametrization of probabilistic decoders that map a vector-shaped prior to a distribution over sets or graphs. Sets and graphs are most commonly generated by first sampling points i.i.d. from a normal distribution, and then processing t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,005
2412.06279	Reconfigurable Holographic Surface-aided Distributed MIMO Radar Systems	Distributed phased Multiple-Input Multiple-Output (phased-MIMO) radar systems have attracted wide attention in target detection and tracking. However, the phase-shifting circuits in phased subarrays contribute to high power consumption and hardware cost. To address this issue, an energy-efficient and cost-efficient met...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	515,186
2310.19491	Generator Identification for Linear SDEs with Additive and Multiplicative Noise	In this paper, we present conditions for identifying the generator of a linear stochastic differential equation (SDE) from the distribution of its solution process with a given fixed initial state. These identifiability conditions are crucial in causal inference using linear SDEs as they enable the identification of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	404,011
1801.01531	Slugbot: An Application of a Novel and Scalable Open Domain Socialbot Framework	In this paper we introduce a novel, open domain socialbot for the Amazon Alexa Prize competition, aimed at carrying on friendly conversations with users on a variety of topics. We present our modular system, highlighting our different data sources and how we use the human mind as a model for data management. Additional...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	87,743
1311.6023	Third Order Intermodulation Power Estimation for N Sinusoidal Channels	In this paper analysis is given to find the third order intermodulation power given sinusoids are fed into a nonlinear device. A simple expression of the third order intermodulation power is given for the case that the center frequencies of the input sinusoids are equally spaced. Further, if the powers of the signals a...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	28,612
2011.04883	Determining Question-Answer Plausibility in Crowdsourced Datasets Using Multi-Task Learning	Datasets extracted from social networks and online forums are often prone to the pitfalls of natural language, namely the presence of unstructured and noisy data. In this work, we seek to enable the collection of high-quality question-answer datasets from social media by proposing a novel task for automated quality ana...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	205,729
1511.01238	The wisdom of networks: A general adaptation and learning mechanism of complex systems: The network core triggers fast responses to known stimuli; innovations require the slow network periphery and are encoded by core-remodeling	I hypothesize that re-occurring prior experience of complex systems mobilizes a fast response, whose attractor is encoded by their strongly connected network core. In contrast, responses to novel stimuli are often slow and require the weakly connected network periphery. Upon repeated stimulus, peripheral network nodes ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,481
cs/0206015	Japanese/English Cross-Language Information Retrieval: Exploration of Query Translation and Transliteration	Cross-language information retrieval (CLIR), where queries and documents are in different languages, has of late become one of the major topics within the information retrieval community. This paper proposes a Japanese/English CLIR system, where we combine a query translation and retrieval modules. We currently target ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,608
2405.03151	Time Series Stock Price Forecasting Based on Genetic Algorithm (GA)-Long Short-Term Memory Network (LSTM) Optimization	In this paper, a time series algorithm based on Genetic Algorithm (GA) and Long Short-Term Memory Network (LSTM) optimization is used to forecast stock prices effectively, taking into account the trend of the big data era. The data are first analyzed by descriptive statistics, and then the model is built and trained an...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	452,072
2408.10609	PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis	We present a comprehensive framework for predicting the effects of perturbations in single cells, designed to standardize benchmarking in this rapidly evolving field. Our framework, PerturBench, includes a user-friendly platform, diverse datasets, metrics for fair model comparison, and detailed performance analysis. Ex...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	481,936
2309.01706	On the Robustness of Post-hoc GNN Explainers to Label Noise	Proposed as a solution to the inherent black-box limitations of graph neural networks (GNNs), post-hoc GNN explainers aim to provide precise and insightful explanations of the behaviours exhibited by trained GNNs. Despite their recent notable advancements in academic and industrial contexts, the robustness of post-hoc ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	389,777
2103.11882	Generating Adversarial Computer Programs using Optimized Obfuscations	Machine learning (ML) models that learn and predict properties of computer programs are increasingly being adopted and deployed. These models have demonstrated success in applications such as auto-completing code, summarizing large programs, and detecting bugs and malware in programs. In this work, we investigate princ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	225,985
1706.08259	Relational Algebra for In-Database Process Mining	The execution logs that are used for process mining in practice are often obtained by querying an operational database and storing the result in a flat file. Consequently, the data processing power of the database system cannot be used anymore for this information, leading to constrained flexibility in the definition o...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	75,969
1711.02741	Recurrent Autoregressive Networks for Online Multi-Object Tracking	The main challenge of online multi-object tracking is to reliably associate object trajectories with detections in each video frame based on their tracking history. In this work, we propose the Recurrent Autoregressive Network (RAN), a temporal generative modeling framework to characterize the appearance and motion dyn...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	84,104
2306.08952	Towards Benchmarking and Improving the Temporal Reasoning Capability of Large Language Models	Reasoning about time is of fundamental importance. Many facts are time-dependent. For example, athletes change teams from time to time, and different government officials are elected periodically. Previous time-dependent question answering (QA) datasets tend to be biased in either their coverage of time spans or questi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	373,617
2304.13705	Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware	Fine manipulation tasks, such as threading cable ties or slotting a battery, are notoriously difficult for robots because they require precision, careful coordination of contact forces, and closed-loop visual feedback. Performing these tasks typically requires high-end robots, accurate sensors, or careful calibration, ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	360,675
2008.05084	Self-supervised Light Field View Synthesis Using Cycle Consistency	High angular resolution is advantageous for practical applications of light fields. In order to enhance the angular resolution of light fields, view synthesis methods can be utilized to generate dense intermediate views from sparse light field input. Most successful view synthesis methods are learning-based approaches ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	191,405
2403.19651	MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions	Image retrieval, i.e., finding desired images given a reference image, inherently encompasses rich, multi-faceted search intents that are difficult to capture solely using image-based measures. Recent works leverage text instructions to allow users to more freely express their search intents. However, they primarily fo...	false	false	false	false	true	true	false	false	true	false	false	true	false	false	false	false	false	true	442,433
cond-mat/0109121	Coordination of Decisions in a Spatial Agent Model	For a binary choice problem, the spatial coordination of decisions in an agent community is investigated both analytically and by means of stochastic computer simulations. The individual decisions are based on different local information generated by the agents with a finite lifetime and disseminated in the system with...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	536,933
1603.06407	The mathematics of non-linear metrics for nested networks	Numerical analysis of data from international trade and ecological networks has shown that the non-linear fitness-complexity metric is the best candidate to rank nodes by importance in bipartite networks that exhibit a nested structure. Despite its relevance for real networks, the mathematical properties of the metric ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	53,492
cs/0307001	Serving Database Information Using a Flexible Server in a Three Tier Architecture	The D0 experiment at Fermilab relies on a central Oracle database for storing all detector calibration information. Access to this data is needed by hundreds of physics applications distributed worldwide. In order to meet the demands of these applications from scarce resources, we have created a distributed system that...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	537,904
2302.14401	GLM-Dialog: Noise-tolerant Pre-training for Knowledge-grounded Dialogue Generation	We present GLM-Dialog, a large-scale language model (LLM) with 10B parameters capable of knowledge-grounded conversation in Chinese using a search engine to access the Internet knowledge. GLM-Dialog offers a series of applicable techniques for exploiting various external knowledge including both helpful and noisy knowl...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	348,280
1001.2447	PPM demodulation: On approaching fundamental limits of optical communications	We consider the problem of demodulating M-ary optical PPM (pulse-position modulation) waveforms, and propose a structured receiver whose mean probability of symbol error is smaller than all known receivers, and approaches the quantum limit. The receiver uses photodetection coupled with optimized phase-coherent optical ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,390
2204.07679	DialAug: Mixing up Dialogue Contexts in Contrastive Learning for Robust Conversational Modeling	Retrieval-based conversational systems learn to rank response candidates for a given dialogue context by computing the similarity between their vector representations. However, training on a single textual form of the multi-turn context limits the ability of a model to learn representations that generalize to natural p...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	291,796
2109.04260	Online Enhanced Semantic Hashing: Towards Effective and Efficient Retrieval for Streaming Multi-Modal Data	With the vigorous development of multimedia equipment and applications, efficient retrieval of large-scale multi-modal data has become a trendy research topic. Thereinto, hashing has become a prevalent choice due to its retrieval efficiency and low storage cost. Although multi-modal hashing has drawn lots of attention ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	254,334
1904.03475	Utilizing Bluetooth Low Energy to recognize proximity, touch and humans	Interacting with humans is one of the main challenges for mobile robots in a human inhabited environment. To enable adaptive behavior, a robot needs to recognize touch gestures and/or the proximity to interacting individuals. Moreover, a robot interacting with two or more humans usually needs to distinguish between the...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	126,734
2205.09433	CAMEO: Curiosity Augmented Metropolis for Exploratory Optimal Policies	Reinforcement Learning has drawn huge interest as a tool for solving optimal control problems. Solving a given problem (task or environment) involves converging towards an optimal policy. However, there might exist multiple optimal policies that can dramatically differ in their behaviour; for example, some may be faste...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	297,270
2009.09399	DVG-Face: Dual Variational Generation for Heterogeneous Face Recognition	Heterogeneous Face Recognition (HFR) refers to matching cross-domain faces and plays a crucial role in public security. Nevertheless, HFR is confronted with challenges from large domain discrepancy and insufficient heterogeneous data. In this paper, we formulate HFR as a dual generation problem, and tackle it via a nov...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	196,571
2010.11642	The Role of Mutual Information in Variational Classifiers	Overfitting data is a well-known phenomenon related with the generation of a model that mimics too closely (or exactly) a particular instance of data, and may therefore fail to predict future observations reliably. In practice, this behaviour is controlled by various--sometimes heuristics--regularization techniques, wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,345
2305.13079	Robust dynamic operating envelopes for flexibility operation using only local voltage measurement	With growing intermittency and uncertainty in distribution networks around the world, ensuring operational integrity is becoming challenging. Recent use cases of dynamic operating envelopes (DOEs) indicate that they can be utilized for network awareness for autonomous operation of flexibility, maximizing distributed ge...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	366,336
2209.13515	Assessing Digital Language Support on a Global Scale	The users of endangered languages struggle to thrive in a digitally-mediated world. We have developed an automated method for assessing how well every language recognized by ISO 639 is faring in terms of digital language support. The assessment is based on scraping the names of supported languages from the websites of ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	319,925
2010.09121	Online-to-Offline Advertisements as Field Experiments	Online advertisements have become one of today's most widely used tools for enhancing businesses partly because of their compatibility with A/B testing. A/B testing allows sellers to find effective advertisement strategies such as ad creatives or segmentations. Even though several studies propose a technique to maximiz...	true	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	201,416
2410.23389	Continuous Evolution of Digital Twins using the DarTwin Notation	Despite best efforts, various challenges remain in the creation and maintenance processes of digital twins (DTs). One of those primary challenges is the constant, continuous and omnipresent evolution of systems, their user's needs and their environment, demanding the adaptation of the developed DT systems. DTs are deve...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	504,023
1303.1599	Efficient learning strategy of Chinese characters based on network approach	Based on network analysis of hierarchical structural relations among Chinese characters, we develop an efficient learning strategy of Chinese characters. We regard a more efficient learning method if one learns the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of ...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	22,736
2106.10138	Classical Planning as QBF without Grounding (extended version)	Most classical planners use grounding as a preprocessing step, essentially reducing planning to propositional logic. However, grounding involves instantiating all action rules with concrete object combinations, and results in large encodings for SAT/QBF-based planners. This severe cost in memory becomes a main bottlene...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	241,911
2404.15058	A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI	Recent generative AI systems have demonstrated more advanced persuasive capabilities and are increasingly permeating areas of life where they can influence decision-making. Generative AI presents a new risk profile of persuasion due the opportunity for reciprocal exchange and prolonged interactions. This has led to gro...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	448,929
1805.08345	Success Probability of Grant-Free Random Access with Massive MIMO	Massive MIMO opens up new avenues for enabling highly efficient random access (RA) by offering abundance of spatial degrees of freedom. In this paper, we investigate the grant-free RA with massive MIMO and derive the analytic expressions of success probability of the grant-free RA for conjugate beamforming and zero-for...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	98,113
2209.01534	Multi-modal Masked Autoencoders Learn Compositional Histopathological Representations	Self-supervised learning (SSL) enables learning useful inductive biases through utilizing pretext tasks that require no labels. The unlabeled nature of SSL makes it especially important for whole slide histopathological images (WSIs), where patch-level human annotation is difficult. Masked Autoencoders (MAE) is a recen...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	315,922
2312.01281	Mendata: A Framework to Purify Manipulated Training Data	Untrusted data used to train a model might have been manipulated to endow the learned model with hidden properties that the data contributor might later exploit. Data purification aims to remove such manipulations prior to training the model. We propose Mendata, a novel framework to purify manipulated training data. St...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	412,387
2110.00653	Sparse Deep Learning: A New Framework Immune to Local Traps and Miscalibration	Deep learning has powered recent successes of artificial intelligence (AI). However, the deep neural network, as the basic model of deep learning, has suffered from issues such as local traps and miscalibration. In this paper, we provide a new framework for sparse deep learning, which has the above issues addressed in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,474
2501.18294	A Comprehensive Analysis on Machine Learning based Methods for Lung Cancer Level Classification	Lung cancer is a major issue in worldwide public health, requiring early diagnosis using stable techniques. This work begins a thorough investigation of the use of machine learning (ML) methods for precise classification of lung cancer stages. A cautious analysis is performed to overcome overfitting issues in model per...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	528,647
1304.2351	Uncertainty Management for Fuzzy Decision Support Systems	A new approach for uncertainty management for fuzzy, rule based decision support systems is proposed: The domain expert's knowledge is expressed by a set of rules that frequently refer to vague and uncertain propositions. The certainty of propositions is represented using intervals [a, b] expressing that the propositio...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	23,659
2301.05168	A Novel Modular, Reconfigurable Battery Energy Storage System: Design, Control, and Experimentation	This paper presents a novel modular, reconfigurable battery energy storage system. The proposed design is characterized by a tight integration of reconfigurable power switches and DC/DC converters. This characteristic enables isolation of faulty cells from the system and allows fine power control for individual cells t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	340,276
1805.05813	Experimental Demonstration of Geometrically-Shaped Constellations Tailored to the Nonlinear Fibre Channel	A geometrically-shaped 256-QAM constellation, tailored to the nonlinear optical fibre channel, is experimentally demonstrated. The proposed constellation outperforms both uniform and AWGN-tailored 256-QAM, as it is designed to optimise the trade-off between shaping gain, nonlinearity and transceiver impairments.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	97,491
1404.1006	Contrasting Effects of Strong Ties on SIR and SIS Processes in Temporal Networks	Most real networks are characterized by connectivity patterns that evolve in time following complex, non-Markovian, dynamics. Here we investigate the impact of this ubiquitous feature by studying the Susceptible-Infected-Recovered (SIR) and Susceptible-Infected-Susceptible (SIS) epidemic models on activity driven netwo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	32,070
1010.4690	A convex approximation approach to Weighted Sum Rate Maximization of Multiuser MISO Interference Channel under outage constraints	This paper considers weighted sum rate maximization of multiuser multiple-input single-output interference channel (MISO-IFC) under outage constraints. The outage-constrained weighted sum rate maximization problem is a nonconvex optimization problem and is difficult to solve. While it is possible to optimally deal with...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,988
2309.05914	Medical Image Segmentation with Belief Function Theory and Deep Learning	Deep learning has shown promising contributions in medical image segmentation with powerful learning and feature representation abilities. However, it has limitations for reasoning with and combining imperfect (imprecise, uncertain, and partial) information. In this thesis, we study medical image segmentation approache...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,238
1810.05841	Error estimation at the information reconciliation stage of quantum key distribution	Quantum key distribution (QKD) offers a practical solution for secure communication between two distinct parties via a quantum channel and an authentic public channel. In this work, we consider different approaches to the quantum bit error rate (QBER) estimation at the information reconciliation stage of the post-proce...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	110,326
2209.04595	OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue	This paper presents an ontology-aware pretrained language model (OPAL) for end-to-end task-oriented dialogue (TOD). Unlike chit-chat dialogue models, task-oriented dialogue models fulfill at least two task-specific modules: dialogue state tracker (DST) and response generator (RG). The dialogue state consists of the dom...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	316,824
2401.15717	Check News in One Click: NLP-Empowered Pro-Kremlin Propaganda Detection	Many European citizens become targets of the Kremlin propaganda campaigns, aiming to minimise public support for Ukraine, foster a climate of mistrust and disunity, and shape elections (Meister, 2022). To address this challenge, we developed ''Check News in 1 Click'', the first NLP-empowered pro-Kremlin propaganda dete...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	424,558
1810.03958	Deterministic Variational Inference for Robust Bayesian Neural Networks	Bayesian neural networks (BNNs) hold great promise as a flexible and principled solution to deal with uncertainty when learning from finite data. Among approaches to realize probabilistic inference in deep neural networks, variational Bayes (VB) is theoretically grounded, generally applicable, and computationally effic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,914
2410.05582	Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning	Autonomous driving necessitates the ability to reason about future interactions between traffic agents and to make informed evaluations for planning. This paper introduces the \textit{Gen-Drive} framework, which shifts from the traditional prediction and deterministic planning framework to a generation-then-evaluation ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	495,802
2011.03151	Efficient Hyperparameter Tuning with Dynamic Accuracy Derivative-Free Optimization	Many machine learning solutions are framed as optimization problems which rely on good hyperparameters. Algorithms for tuning these hyperparameters usually assume access to exact solutions to the underlying learning problem, which is typically not practical. Here, we apply a recent dynamic accuracy derivative-free opti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	205,150
2311.08740	AdVENTR: Autonomous Robot Navigation in Complex Outdoor Environments	We present a novel system, AdVENTR for autonomous robot navigation in unstructured outdoor environments that consist of uneven and vegetated terrains. Our approach is general and can enable both wheeled and legged robots to handle outdoor terrain complexity including unevenness, surface properties like poor traction, g...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	407,851
2104.12928	If your data distribution shifts, use self-learning	We demonstrate that self-learning techniques like entropy minimization and pseudo-labeling are simple and effective at improving performance of a deployed computer vision model under systematic domain shifts. We conduct a wide range of large-scale experiments and show consistent improvements irrespective of the model a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	232,359
2303.03019	NxPlain: Web-based Tool for Discovery of Latent Concepts	The proliferation of deep neural networks in various domains has seen an increased need for the interpretability of these models, especially in scenarios where fairness and trust are as important as model performance. A lot of independent work is being carried out to: i) analyze what linguistic and non-linguistic knowl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	349,576
2407.00737	LLM4GEN: Leveraging Semantic Representation of LLMs for Text-to-Image Generation	Diffusion models have exhibited substantial success in text-to-image generation. However, they often encounter challenges when dealing with complex and dense prompts involving multiple objects, attribute binding, and long descriptions. In this paper, we propose a novel framework called \textbf{LLM4GEN}, which enhances ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	468,988
2412.02192	Thallus: An RDMA-based Columnar Data Transport Protocol	The volume of data generated and stored in contemporary global data centers is experiencing exponential growth. This rapid data growth necessitates efficient processing and analysis to extract valuable business insights. In distributed data processing systems, data undergoes exchanges between the compute servers that c...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	513,426
2303.01734	AdvART: Adversarial Art for Camouflaged Object Detection Attacks	Physical adversarial attacks pose a significant practical threat as it deceives deep learning systems operating in the real world by producing prominent and maliciously designed physical perturbations. Emphasizing the evaluation of naturalness is crucial in such attacks, as humans can readily detect and eliminate unnat...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	349,085
2408.07978	Coupling without Communication and Drafter-Invariant Speculative Decoding	Suppose Alice has a distribution $P$ and Bob has a distribution $Q$. Alice wants to draw a sample $a\sim P$ and Bob a sample $b \sim Q$ such that $a = b$ with as high of probability as possible. It is well-known that, by sampling from an optimal coupling between the distributions, Alice and Bob can achieve $\Pr[a = b] ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	480,801
2210.13641	NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fields	We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-time scene reconstruction from monocular images. To achieve this, we leverage recent advances in dense monocular SLAM and real-time hierarchical volumetric neural radiance fields. Our insight is that dense monocular SLAM provides the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	326,240
0906.5034	Effective Focused Crawling Based on Content and Link Structure Analysis	A focused crawler traverses the web selecting out relevant pages to a predefined topic and neglecting those out of concern. While surfing the internet it is difficult to deal with irrelevant pages and to predict which links lead to quality pages. In this paper a technique of effective focused crawling is implemented to...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	3,984
1903.12561	Adversarial Robustness vs Model Compression, or Both?	It is well known that deep neural networks (DNNs) are vulnerable to adversarial attacks, which are implemented by adding crafted perturbations onto benign examples. Min-max robust optimization based adversarial training can provide a notion of security against adversarial attacks. However, adversarial robustness requir...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	125,762
2109.09961	Non-parametric Kernel-Based Estimation of Probability Distributions for Precipitation Modeling	The probability distribution of precipitation amount strongly depends on geography, climate zone, and time scale considered. Closed-form parametric probability distributions are not sufficiently flexible to provide accurate and universal models for precipitation amount over different time scales. In this paper we deriv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	256,462
1705.00630	Influence maximization by rumor spreading on correlated networks through community identification	The identification of the minimal set of nodes that maximizes the propagation of information is one of the most relevant problems in network science. In this paper, we introduce a new method to find the set of initial spreaders to maximize the information propagation in complex networks. We evaluate this method in asso...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	72,721
2410.00775	Decoding Hate: Exploring Language Models' Reactions to Hate Speech	Hate speech is a harmful form of online expression, often manifesting as derogatory posts. It is a significant risk in digital environments. With the rise of Large Language Models (LLMs), there is concern about their potential to replicate hate speech patterns, given their training on vast amounts of unmoderated intern...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	493,499
1003.0404	Exploration Of The Dendritic Cell Algorithm Using The Duration Calculus	As one of the newest members in Artificial Immune Systems (AIS), the Dendritic Cell Algorithm (DCA) has been applied to a range of problems. These applications mainly belong to the field of anomaly detection. However, real-time detection, a new challenge to anomaly detection, requires improvement on the real-time capab...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	5,817
2110.10972	Efficient Gradient Flows in Sliced-Wasserstein Space	Minimizing functionals in the space of probability distributions can be done with Wasserstein gradient flows. To solve them numerically, a possible approach is to rely on the Jordan-Kinderlehrer-Otto (JKO) scheme which is analogous to the proximal scheme in Euclidean spaces. However, it requires solving a nested optimi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,322
1504.01747	SCMA for Open-Loop Joint Transmission CoMP	Sparse Code Multiple Access (SCMA), a non-orthogonal multiple access scheme, has been introduced as a key 5G technology to improve spectral efficiency. In this work, we propose SCMA to enable open-loop coordinated multipoint (CoMP) joint transmission (JT). The scheme combines CoMP techniques with multi-user SCMA (MU-SC...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	41,849
1610.09756	Towards Deep Learning in Hindi NER: An approach to tackle the Labelled Data Scarcity	In this paper we describe an end to end Neural Model for Named Entity Recognition NER) which is based on Bi-Directional RNN-LSTM. Almost all NER systems for Hindi use Language Specific features and handcrafted rules with gazetteers. Our model is language independent and uses no domain specific features or any handcraft...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	63,109
1804.00211	Efficient Encodings of Conditional Cardinality Constraints	In the encoding of many real-world problems to propositional satisfiability, the cardinality constraint is a recurrent constraint that needs to be managed effectively. Several efficient encodings have been proposed while missing that such a constraint can be involved in a more general propositional formulation. To avoi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	93,962
1909.08153	CAMAL: Context-Aware Multi-layer Attention framework for Lightweight Environment Invariant Visual Place Recognition	In the last few years, Deep Convolutional Neural Networks (D-CNNs) have shown state-of-the-art (SOTA) performance for Visual Place Recognition (VPR), a pivotal component of long-term intelligent robotic vision (vision-aware localization and navigation systems). The prestigious generalization power of D-CNNs gained upon...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	145,879
2411.02404	Enhancing Retrieval Performance: An Ensemble Approach For Hard Negative Mining	Ranking consistently emerges as a primary focus in information retrieval research. Retrieval and ranking models serve as the foundation for numerous applications, including web search, open domain QA, enterprise domain QA, and text-based recommender systems. Typically, these models undergo training on triplets consisti...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	505,475
1905.13370	Rewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning	Our work involves enriching the Stack-LSTM transition-based AMR parser (Ballesteros and Al-Onaizan, 2017) by augmenting training with Policy Learning and rewarding the Smatch score of sampled graphs. In addition, we also combined several AMR-to-text alignments with an attention mechanism and we supplemented the parser ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	133,099
1805.10547	Using Syntax to Ground Referring Expressions in Natural Images	We introduce GroundNet, a neural network for referring expression recognition -- the task of localizing (or grounding) in an image the object referred to by a natural language expression. Our approach to this task is the first to rely on a syntactic analysis of the input referring expression in order to inform the stru...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	98,705
1612.05880	A Coordinate-Descent Framework to Design Low PSL/ISL Sequences	This paper is focused on the design of phase sequences with good (aperiodic) autocorrelation properties in terms of Peak Sidelobe Level (PSL) and Integrated Sidelobe Level (ISL). The problem is formulated as a bi-objective Pareto optimization forcing either a continuous or a discrete phase constraint at the design stag...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	65,738
2111.12122	Bounding Box-Free Instance Segmentation Using Semi-Supervised Learning for Generating a City-Scale Vehicle Dataset	Vehicle classification is a hot computer vision topic, with studies ranging from ground-view up to top-view imagery. In remote sensing, the usage of top-view images allows for understanding city patterns, vehicle concentration, traffic management, and others. However, there are some difficulties when aiming for pixel-w...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	true	false	267,868
2201.06645	Risk-aware Trajectory Sampling for Quadrotor Obstacle Avoidance in Dynamic Environments	Obstacle avoidance of quadrotors in dynamic environments is still a very open problem. Current works commonly leverage traditional static maps to represent static obstacles and the detection and tracking of moving objects (DATMO) method to model dynamic obstacles separately. The detection module requires pre-training, ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	275,782
2410.07220	Stock Price Prediction and Traditional Models: An Approach to Achieve Short-, Medium- and Long-Term Goals	A comparative analysis of deep learning models and traditional statistical methods for stock price prediction uses data from the Nigerian stock exchange. Historical data, including daily prices and trading volumes, are employed to implement models such as Long Short Term Memory (LSTM) networks, Gated Recurrent Units (G...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	496,547
1708.04811	Language Identification Using Deep Convolutional Recurrent Neural Networks	Language Identification (LID) systems are used to classify the spoken language from a given audio sample and are typically the first step for many spoken language processing tasks, such as Automatic Speech Recognition (ASR) systems. Without automatic language detection, speech utterances cannot be parsed correctly and ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	79,029
2203.00644	Tello Leg: The Study of Design Principles and Metrics for Dynamic Humanoid Robots	To be useful tools in real scenarios, humanoid robots must realize tasks dynamically. This means that they must be capable of applying substantial forces, rapidly swinging their limbs, and also mitigating impacts that may occur during the motion. Towards creating capable humanoids, this letter presents the leg of the r...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	283,074
1903.09870	Long Range Neural Navigation Policies for the Real World	Learned Neural Network based policies have shown promising results for robot navigation. However, most of these approaches fall short of being used on a real robot due to the extensive simulated training they require. These simulations lack the visuals and dynamics of the real world, which makes it infeasible to deploy...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	125,154
2106.09973	The Curse of Passive Data Collection in Batch Reinforcement Learning	In high stake applications, active experimentation may be considered too risky and thus data are often collected passively. While in simple cases, such as in bandits, passive and active data collection are similarly effective, the price of passive sampling can be much higher when collecting data from a system with cont...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	241,856
2409.18163	A Survey on Neural Architecture Search Based on Reinforcement Learning	The automation of feature extraction of machine learning has been successfully realized by the explosive development of deep learning. However, the structures and hyperparameters of deep neural network architectures also make huge difference on the performance in different tasks. The process of exploring optimal struct...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	492,130
2207.09884	Negative Samples are at Large: Leveraging Hard-distance Elastic Loss for Re-identification	We present a Momentum Re-identification (MoReID) framework that can leverage a very large number of negative samples in training for general re-identification task. The design of this framework is inspired by Momentum Contrast (MoCo), which uses a dictionary to store current and past batches to build a large set of enc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,061
2101.08669	Probabilistic Placement Optimization for Non-coherent and Coherent Joint Transmission in Cache-Enabled Cellular Networks	How to design proper content placement strategies is one of the major areas of interest in cache-enabled cellular networks. In this paper, we study the probabilistic content placement optimization of base station (BS) caching with cooperative transmission in the downlink of cellular networks. With placement probability...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	216,382
1712.04364	Agent Based Distributed Control of Islanded Microgrid - Real-Time Cyber-Physical Implementation	In the hierarchical control of an islanded microgrid, secondary control could be centralized or distributed. The former control strategy has several disadvantages, such as single point of failure at the level of the central controller as well as high investment of communication infrastructure. In this paper a three-lay...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	86,596
1812.01316	Numerical assessment of the percolation threshold using complement networks	Models of percolation processes on networks currently assume locally tree-like structures at low densities, and are derived exactly only in the thermodynamic limit. Finite size effects and the presence of short loops in real systems however cause a deviation between the empirical percolation threshold $p_c$ and its mod...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	115,498
2502.00826	Weak Supervision Dynamic KL-Weighted Diffusion Models Guided by Large Language Models	In this paper, we presents a novel method for improving text-to-image generation by combining Large Language Models (LLMs) with diffusion models, a hybrid approach aimed at achieving both higher quality and efficiency in image synthesis from text descriptions. Our approach introduces a new dynamic KL-weighting strategy...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	529,565
2312.08722	Quantifying Divergence for Human-AI Collaboration and Cognitive Trust	Predicting the collaboration likelihood and measuring cognitive trust to AI systems is more important than ever. To do that, previous research mostly focus solely on the model features (e.g., accuracy, confidence) and ignore the human factor. To address that, we propose several decision-making similarity measures based...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	415,419
1712.07143	Machine Learning for Vehicular Networks	The emerging vehicular networks are expected to make everyday vehicular operation safer, greener, and more efficient, and pave the path to autonomous driving in the advent of the fifth generation (5G) cellular system. Machine learning, as a major branch of artificial intelligence, has been recently applied to wireless ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	86,995
2007.06799	A Decentralized Approach to Bayesian Learning	Motivated by decentralized approaches to machine learning, we propose a collaborative Bayesian learning algorithm taking the form of decentralized Langevin dynamics in a non-convex setting. Our analysis show that the initial KL-divergence between the Markov Chain and the target posterior distribution is exponentially d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	187,130

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