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
2202.08965	High-performance automatic categorization and attribution of inventory catalogs	Techniques of machine learning for automatic text categorization are applied and adapted for the problem of inventory catalog data attribution, with different approaches explored and optimal solution addressing the tradeoff between accuracy and performance is selected.	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	281,045
2111.10031	Novel Real-Time EMT-TS Modeling Architecture for Feeder Blackstart Simulations	This paper presents the development and benchmarking of a novel real-time electromagnetic-transient and transient-stability (EMT-TS) modeling architecture for distribution feeder restoration studies. The work presents for the first time in the literature a real-time EMT-TS testbed in which the grid-forming unit is simu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	267,184
2305.18421	HyperTime: Hyperparameter Optimization for Combating Temporal Distribution Shifts	In this work, we propose a hyperparameter optimization method named \emph{HyperTime} to find hyperparameters robust to potential temporal distribution shifts in the unseen test data. Our work is motivated by an important observation that it is, in many cases, possible to achieve temporally robust predictive performance...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	369,038
2311.06237	Summon a Demon and Bind it: A Grounded Theory of LLM Red Teaming	Engaging in the deliberate generation of abnormal outputs from Large Language Models (LLMs) by attacking them is a novel human activity. This paper presents a thorough exposition of how and why people perform such attacks, defining LLM red-teaming based on extensive and diverse evidence. Using a formal qualitative meth...	true	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	406,860
2105.09165	Evacuation Problem Under the Nuclear Leakage Accident	To handle the detrimental effects brought by leakage of radioactive gases at nuclear power station, we propose a bus based evacuation optimization problem. The proposed model incorporates the following four constraints, 1) the maximum dose of radiation per evacuee, 2) the limitation of bus capacity, 3) the number of ev...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	235,993
2105.03266	Comparison of Traditional and Hybrid Time Series Models for Forecasting COVID-19 Cases	Time series forecasting methods play critical role in estimating the spread of an epidemic. The coronavirus outbreak of December 2019 has already infected millions all over the world and continues to spread on. Just when the curve of the outbreak had started to flatten, many countries have again started to witness a ri...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	234,095
2405.09190	Advancing Explainable AI with Causal Analysis in Large-Scale Fuzzy Cognitive Maps	In the quest for accurate and interpretable AI models, eXplainable AI (XAI) has become crucial. Fuzzy Cognitive Maps (FCMs) stand out as an advanced XAI method because of their ability to synergistically combine and exploit both expert knowledge and data-driven insights, providing transparency and intrinsic interpretab...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	454,322
1909.04746	Tighter Theory for Local SGD on Identical and Heterogeneous Data	We provide a new analysis of local SGD, removing unnecessary assumptions and elaborating on the difference between two data regimes: identical and heterogeneous. In both cases, we improve the existing theory and provide values of the optimal stepsize and optimal number of local iterations. Our bounds are based on a new...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	144,879
2006.06497	A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons	Generalized linear models are one of the most efficient paradigms for predicting the correlated stochastic activity of neuronal networks in response to external stimuli, with applications in many brain areas. However, when dealing with complex stimuli, the inferred coupling parameters often do not generalize across dif...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,451
1901.00738	Resource-Scalable CNN Synthesis for IoT Applications	State-of-the-art image recognition systems use sophisticated Convolutional Neural Networks (CNNs) that are designed and trained to identify numerous object classes. Such networks are fairly resource intensive to compute, prohibiting their deployment on resource-constrained embedded platforms. On one hand, the ability t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	117,843
2311.05655	Fuzzy Ensembles of Reinforcement Learning Policies for Robotic Systems with Varied Parameters	Reinforcement Learning (RL) is an emerging approach to control many dynamical systems for which classical control approaches are not applicable or insufficient. However, the resultant policies may not generalize to variations in the parameters that the system may exhibit. This paper presents a powerful yet simple algor...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	406,658
2502.06163	Scalable k-Means Clustering for Large k via Seeded Approximate Nearest-Neighbor Search	For very large values of $k$, we consider methods for fast $k$-means clustering of massive datasets with $10^7\sim10^9$ points in high-dimensions ($d\geq100$). All current practical methods for this problem have runtimes at least $\Omega(k^2)$. We find that initialization routines are not a bottleneck for this case. In...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	531,959
2210.13690	Highly Efficient Real-Time Streaming and Fully On-Device Speaker Diarization with Multi-Stage Clustering	While recent research advances in speaker diarization mostly focus on improving the quality of diarization results, there is also an increasing interest in improving the efficiency of diarization systems. In this paper, we demonstrate that a multi-stage clustering strategy that uses different clustering algorithms for ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,260
2306.07126	Argumentative Characterizations of (Extended) Disjunctive Logic Programs	This paper continues an established line of research about the relations between argumentation theory, particularly assumption-based argumentation, and different kinds of logic programs. In particular, we extend known result of Caminada, Schultz and Toni by showing that assumption-based argumentation can represent not ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	372,893
2110.07253	Rethinking Point Cloud Filtering: A Non-Local Position Based Approach	Existing position based point cloud filtering methods can hardly preserve sharp geometric features. In this paper, we rethink point cloud filtering from a non-learning non-local non-normal perspective, and propose a novel position based approach for feature-preserving point cloud filtering. Unlike normal based techniqu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	260,918
2408.03874	Personalized Clinical Note Generation from Doctor-Patient Conversations	In this work, we present a novel technique to improve the quality of draft clinical notes for physicians. This technique is concentrated on the ability to model implicit physician conversation styles and note preferences. We also introduce a novel technique for the enrollment of new physicians when a limited number of ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	479,179
2203.15643	Nix-TTS: Lightweight and End-to-End Text-to-Speech via Module-wise Distillation	Several solutions for lightweight TTS have shown promising results. Still, they either rely on a hand-crafted design that reaches non-optimum size or use a neural architecture search but often suffer training costs. We present Nix-TTS, a lightweight TTS achieved via knowledge distillation to a high-quality yet large-si...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	288,486
2412.04260	Enhancing Whole Slide Image Classification through Supervised Contrastive Domain Adaptation	Domain shift in the field of histopathological imaging is a common phenomenon due to the intra- and inter-hospital variability of staining and digitization protocols. The implementation of robust models, capable of creating generalized domains, represents a need to be solved. In this work, a new domain adaptation metho...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	514,329
2211.11977	SemanticLoop: loop closure with 3D semantic graph matching	Loop closure can effectively correct the accumulated error in robot localization, which plays a critical role in the long-term navigation of the robot. Traditional appearance-based methods rely on local features and are prone to failure in ambiguous environments. On the other hand, object recognition can infer objects'...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	331,945
1701.07221	Community-aware network sparsification	Network sparsification aims to reduce the number of edges of a network while maintaining its structural properties; such properties include shortest paths, cuts, spectral measures, or network modularity. Sparsification has multiple applications, such as, speeding up graph-mining algorithms, graph visualization, as well...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	67,254
1701.07411	iPhone's Digital Marketplace: Characterizing the Big Spenders	With mobile shopping surging in popularity, people are spending ever more money on digital purchases through their mobile devices and phones. However, few large-scale studies of mobile shopping exist. In this paper we analyze a large data set consisting of more than 776M digital purchases made on Apple mobile devices t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	67,285
2102.03385	Global minimization via classical tunneling assisted by collective force field formation	Simple dynamical models can produce intricate behaviors in large networks. These behaviors can often be observed in a wide variety of physical systems captured by the network of interactions. Here we describe a phenomenon where the increase of dimensions self-consistently generates a force field due to dynamical instab...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	218,726
2410.03728	Exploring QUIC Dynamics: A Large-Scale Dataset for Encrypted Traffic Analysis	QUIC, an increasingly adopted transport protocol, addresses limitations of TCP by offering improved security, performance, and features such as stream multiplexing and connection migration. However, these enhancements also introduce challenges for network operators in monitoring and analyzing web traffic, especially du...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	494,919
2411.00948	Multiplex Imaging Analysis in Pathology: a Comprehensive Review on Analytical Approaches and Digital Toolkits	Conventional histopathology has long been essential for disease diagnosis, relying on visual inspection of tissue sections. Immunohistochemistry aids in detecting specific biomarkers but is limited by its single-marker approach, restricting its ability to capture the full tissue environment. The advent of multiplexed i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	504,846
2002.02547	Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow	Flow models have recently made great progress at modeling ordinal discrete data such as images and audio. Due to the continuous nature of flow models, dequantization is typically applied when using them for such discrete data, resulting in lower bound estimates of the likelihood. In this paper, we introduce subset flow...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	162,954
2308.15898	An xAI Approach for Data-to-Text Processing with ASP	The generation of natural language text from data series gained renewed interest among AI research goals. Not surprisingly, the few proposals in the state of the art are based on training some system, in order to produce a text that describes and that is coherent to the data provided as input. Main challenges of such a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	388,842
1412.2324	Rethinking serializable multiversion concurrency control	Multi-versioned database systems have the potential to significantly increase the amount of concurrency in transaction processing because they can avoid read-write conflicts. Unfortunately, the increase in concurrency usually comes at the cost of transaction serializability. If a database user requests full serializabi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	38,193
2311.11469	DiffGANPaint: Fast Inpainting Using Denoising Diffusion GANs	Free-form image inpainting is the task of reconstructing parts of an image specified by an arbitrary binary mask. In this task, it is typically desired to generalize model capabilities to unseen mask types, rather than learning certain mask distributions. Capitalizing on the advances in diffusion models, in this paper,...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,957
2006.03654	DeBERTa: Decoding-enhanced BERT with Disentangled Attention	Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks. In this paper we propose a new model architecture DeBERTa (Decoding-enhanced BERT with disentangled attention) that improves the BERT and RoBERTa models using two novel techn...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	180,385
2404.07739	Exploiting Object-based and Segmentation-based Semantic Features for Deep Learning-based Indoor Scene Classification	Indoor scenes are usually characterized by scattered objects and their relationships, which turns the indoor scene classification task into a challenging computer vision task. Despite the significant performance boost in classification tasks achieved in recent years, provided by the use of deep-learning-based methods, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,956
2208.14116	Distributed Constraint-Coupled Optimization over Lossy Networks	This paper considers distributed resource allocation and sum-preserving constrained optimization over lossy networks, where the links are unreliable and subject to packet drops. We define the conditions to ensure convergence under packet drops and link removal by focusing on two main properties of our allocation algori...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	315,225
2103.05219	Outdoor sub-THz Position Location and Tracking using Field Measurements at 142 GHz	Future sub-THz cellular deployments may be utilized to complement the coverage of the global positioning system (GPS) and provide centimeter-level accuracy. In this work, we use measurement data at 142 GHz to test a map-based position location algorithm in an outdoor urban microcell (UMi) environment. We utilize an ext...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	223,905
2312.02598	Impact of Tokenization on LLaMa Russian Adaptation	Latest instruction-tuned large language models (LLM) show great results on various tasks, however, they often face performance degradation for non-English input. There is evidence that the reason lies in inefficient tokenization caused by low language representation in pre-training data which hinders the comprehension ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	412,937
2004.11623	Low-latency hand gesture recognition with a low resolution thermal imager	Using hand gestures to answer a call or to control the radio while driving a car, is nowadays an established feature in more expensive cars. High resolution time-of-flight cameras and powerful embedded processors usually form the heart of these gesture recognition systems. This however comes with a price tag. We theref...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,959
2305.14815	Machine Reading Comprehension using Case-based Reasoning	We present an accurate and interpretable method for answer extraction in machine reading comprehension that is reminiscent of case-based reasoning (CBR) from classical AI. Our method (CBR-MRC) builds upon the hypothesis that contextualized answers to similar questions share semantic similarities with each other. Given ...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	367,273
1901.06376	An information theoretic model for summarization, and some basic results	A basic information theoretic model for summarization is formulated. Here summarization is considered as the process of taking a report of $v$ binary objects, and producing from it a $j$ element subset that captures most of the important features of the original report, with importance being defined via an arbitrary se...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	118,983
1808.02763	Bayesreef: A Bayesian inference framework for modelling reef growth in response to environmental change and biological dynamics	Estimating the impact of environmental processes on vertical reef development in geological time is a very challenging task. pyReef-Core is a deterministic carbonate stratigraphic forward model designed to simulate the key biological and environmental processes that determine vertical reef accretion and assemblage chan...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	104,823
2407.06174	The Tug-of-War Between Deepfake Generation and Detection	Multimodal generative models are rapidly evolving, leading to a surge in the generation of realistic video and audio that offers exciting possibilities but also serious risks. Deepfake videos, which can convincingly impersonate individuals, have particularly garnered attention due to their potential misuse in spreading...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,295
2007.11753	Leading Cruise Control in Mixed Traffic Flow	Vehicle-to-vehicle (V2V) communications have a great potential to improve traffic system performance. Most existing work of connected and autonomous vehicles (CAVs) focused on adaptation to downstream traffic conditions, neglecting the impact of CAVs' behaviors on upstream traffic flow. In this paper, we introduce a no...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	188,627
2304.09820	A Two-Stage Framework with Self-Supervised Distillation For Cross-Domain Text Classification	Cross-domain text classification aims to adapt models to a target domain that lacks labeled data. It leverages or reuses rich labeled data from the different but related source domain(s) and unlabeled data from the target domain. To this end, previous work focuses on either extracting domain-invariant features or task-...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	359,182
2408.14845	AAVENUE: Detecting LLM Biases on NLU Tasks in AAVE via a Novel Benchmark	Detecting biases in natural language understanding (NLU) for African American Vernacular English (AAVE) is crucial to developing inclusive natural language processing (NLP) systems. To address dialect-induced performance discrepancies, we introduce AAVENUE ({AAVE} {N}atural Language {U}nderstanding {E}valuation), a ben...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	483,702
2109.06324	A Massively Multilingual Analysis of Cross-linguality in Shared Embedding Space	In cross-lingual language models, representations for many different languages live in the same space. Here, we investigate the linguistic and non-linguistic factors affecting sentence-level alignment in cross-lingual pretrained language models for 101 languages and 5,050 language pairs. Using BERT-based LaBSE and BiLS...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	255,106
2403.19317	Beyond Borders: Investigating Cross-Jurisdiction Transfer in Legal Case Summarization	Legal professionals face the challenge of managing an overwhelming volume of lengthy judgments, making automated legal case summarization crucial. However, prior approaches mainly focused on training and evaluating these models within the same jurisdiction. In this study, we explore the cross-jurisdictional generalizab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	442,294
1402.6422	A Novel User Pairing Scheme for Functional Decode-and-Forward Multi-way Relay Network	In this paper, we consider a functional decode and forward (FDF) multi-way relay network (MWRN) where a common user facilitates each user in the network to obtain messages from all other users. We propose a novel user pairing scheme, which is based on the principle of selecting a common user with the best average chann...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	31,176
1709.08800	TuringMobile: A Turing Machine of Oblivious Mobile Robots with Limited Visibility and its Applications	In this paper we investigate the computational power of a set of mobile robots with limited visibility. At each iteration, a robot takes a snapshot of its surroundings, uses the snapshot to compute a destination point, and it moves toward its destination. Each robot is punctiform and memoryless, it operates in $\mathbb...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	81,528
2411.01642	Quantum Rationale-Aware Graph Contrastive Learning for Jet Discrimination	In high-energy physics, particle jet tagging plays a pivotal role in distinguishing quark from gluon jets using data from collider experiments. While graph-based deep learning methods have advanced this task beyond traditional feature-engineered approaches, the complex data structure and limited labeled samples present...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	505,164
2003.02197	Evaluating Low-Resource Machine Translation between Chinese and Vietnamese with Back-Translation	Back translation (BT) has been widely used and become one of standard techniques for data augmentation in Neural Machine Translation (NMT), BT has proven to be helpful for improving the performance of translation effectively, especially for low-resource scenarios. While most works related to BT mainly focus on European...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	166,873
cs/0409045	Augmenting ALC(D) (atemporal) roles and (aspatial) concrete domain with temporal roles and a spatial concrete domain -first results	We consider the well-known family ALC(D) of description logics with a concrete domain, and provide first results on a framework obtained by augmenting ALC(D) atemporal roles and aspatial concrete domain with temporal roles and a spatial concrete domain.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	538,341
2202.04036	Residual Aligned: Gradient Optimization for Non-Negative Image Synthesis	In this work, we address an important problem of optical see through (OST) augmented reality: non-negative image synthesis. Most of the image generation methods fail under this condition, since they assume full control over each pixel and cannot create darker pixels by adding light. In order to solve the non-negative i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	279,433
2004.04574	Model-based actor-critic: GAN (model generator) + DRL (actor-critic) => AGI	Our effort is toward unifying GAN and DRL algorithms into a unifying AI model (AGI or general-purpose AI or artificial general intelligence which has general-purpose applications to: (A) offline learning (of stored data) like GAN in (un/semi-/fully-)SL setting such as big data analytics (mining) and visualization; (B) ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	171,921
1611.07634	Interpretation of Prediction Models Using the Input Gradient	State of the art machine learning algorithms are highly optimized to provide the optimal prediction possible, naturally resulting in complex models. While these models often outperform simpler more interpretable models by order of magnitudes, in terms of understanding the way the model functions, we are often facing a ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	64,382
2406.17807	Enhancing Commentary Strategies for Imperfect Information Card Games: A Study of Large Language Models in Guandan Commentary	Recent advancements in large language models (LLMs) have unlocked the potential for generating high-quality game commentary. However, producing insightful and engaging commentary for complex games with incomplete information remains a significant challenge. In this paper, we introduce a novel commentary method that com...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	467,738
2203.15072	Semantic Motion Correction Via Iterative Nonlinear Optimization and Animation	Here, we present an end-to-end method to create 2D animation for a goalkeeper attempting to block a penalty kick, and then correct that motion using an iterative nonlinear optimization scheme. The input is a raw video that is fed into pose and object detection networks to find the skeleton of the goalkeeper and the bal...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	288,221
1912.04859	Privacy-Preserving Blockchain Based Federated Learning with Differential Data Sharing	For the modern world where data is becoming one of the most valuable assets, robust data privacy policies rooted in the fundamental infrastructure of networks and applications are becoming an even bigger necessity to secure sensitive user data. In due course with the ever-evolving nature of newer statistical techniques...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	156,940
2102.07000	Adaptive Optimization of Autonomous Vehicle Computational Resources for Performance and Energy Improvement	Autonomous vehicles usually consume a large amount of computational power for their operations, especially for the tasks of sensing and perception with artificial intelligence algorithms. Such a computation may not only cost a significant amount of energy but also cause performance issues when the onboard computational...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	219,951
2304.01091	Changes to Captions: An Attentive Network for Remote Sensing Change Captioning	In recent years, advanced research has focused on the direct learning and analysis of remote sensing images using natural language processing (NLP) techniques. The ability to accurately describe changes occurring in multi-temporal remote sensing images is becoming increasingly important for geospatial understanding and...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	355,932
2402.18826	The Machine Can't Replace the Human Heart	What is the true heart of mental healthcare -- innovation or humanity? Can virtual therapy ever replicate the profound human bonds where healing arises? As artificial intelligence and immersive technologies promise expanded access, safeguards must ensure technologies remain supplementary tools guided by providers' wisd...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	433,578
1706.05296	Value-Decomposition Networks For Cooperative Multi-Agent Learning	We study the problem of cooperative multi-agent reinforcement learning with a single joint reward signal. This class of learning problems is difficult because of the often large combined action and observation spaces. In the fully centralized and decentralized approaches, we find the problem of spurious rewards and a p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	75,490
2112.01064	AutoGEL: An Automated Graph Neural Network with Explicit Link Information	Recently, Graph Neural Networks (GNNs) have gained popularity in a variety of real-world scenarios. Despite the great success, the architecture design of GNNs heavily relies on manual labor. Thus, automated graph neural network (AutoGNN) has attracted interest and attention from the research community, which makes sign...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	269,362
1802.01451	Quantitative Fine-Grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian	This paper presents a quantitative fine-grained manual evaluation approach to comparing the performance of different machine translation (MT) systems. We build upon the well-established Multidimensional Quality Metrics (MQM) error taxonomy and implement a novel method that assesses whether the differences in performanc...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	89,607
2211.14298	PIP: Positional-encoding Image Prior	In Deep Image Prior (DIP), a Convolutional Neural Network (CNN) is fitted to map a latent space to a degraded (e.g. noisy) image but in the process learns to reconstruct the clean image. This phenomenon is attributed to CNN's internal image-prior. We revisit the DIP framework, examining it from the perspective of a neu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	332,773
1910.02498	Predicting popularity of EV charging infrastructure from GIS data	The availability of charging infrastructure is essential for large-scale adoption of electric vehicles (EV). Charging patterns and the utilization of infrastructure have consequences not only for the energy demand, loading local power grids but influence the economic returns, parking policies and further adoption of EV...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,260
2105.04382	Numerical studies of CO$_2$ leakage remediation by micp-based plugging technology	Microbially induced calcite precipitation (MICP) is a technology for sealing leakage paths to ensure the safe storage of CO$_2$ in geological formations. In this work we introduce a numerical simulator of MICP for field-scale studies. This simulator is implemented in the open porous media (OPM) framework. We compare th...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	234,491
1911.06185	Convolutional Neural Network for Convective Storm Nowcasting Using 3D Doppler Weather Radar Data	Convective storms are one of the severe weather hazards found during the warm season. Doppler weather radar is the only operational instrument that can frequently sample the detailed structure of convective storm which has a small spatial scale and short lifetime. For the challenging task of short-term convective storm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,472
1302.3663	Spatially Heterogeneous Biofilm Simulations using an Immersed Boundary Method with Lagrangian Nodes Defined by Bacterial Locations	In this work we consider how surface-adherent bacterial biofilm communities respond in flowing systems. We simulate the fluid-structure interaction and separation process using the immersed boundary method. In these simulations we model and simulate different density and viscosity values of the biofilm than that of the...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	22,081
1909.01106	ForkNet: Multi-branch Volumetric Semantic Completion from a Single Depth Image	We propose a novel model for 3D semantic completion from a single depth image, based on a single encoder and three separate generators used to reconstruct different geometric and semantic representations of the original and completed scene, all sharing the same latent space. To transfer information between the geometri...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	143,813
1709.05480	Subset Labeled LDA for Large-Scale Multi-Label Classification	Labeled Latent Dirichlet Allocation (LLDA) is an extension of the standard unsupervised Latent Dirichlet Allocation (LDA) algorithm, to address multi-label learning tasks. Previous work has shown it to perform in par with other state-of-the-art multi-label methods. Nonetheless, with increasing label sets sizes LLDA enc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	80,886
1908.09185	Approximation Algorithms for Coordinating Ad Campaigns on Social Networks	We study a natural model of coordinated social ad campaigns over a social network, based on models of Datta et al. and Aslay et al. Multiple advertisers are willing to pay the host - up to a known budget - per user exposure, whether the exposure is sponsored or orgain (i.e. shared by a friend). Campaigns are seeded wit...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	142,780
2111.10046	YMIR: A Rapid Data-centric Development Platform for Vision Applications	This paper introduces an open source platform to support the rapid development of computer vision applications at scale. The platform puts the efficient data development at the center of the machine learning development process, integrates active learning methods, data and model version control, and uses concepts such ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	267,190
2005.00119	Learning to Rank Intents in Voice Assistants	Voice Assistants aim to fulfill user requests by choosing the best intent from multiple options generated by its Automated Speech Recognition and Natural Language Understanding sub-systems. However, voice assistants do not always produce the expected results. This can happen because voice assistants choose from ambiguo...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	175,131
2012.09712	Deep Molecular Dreaming: Inverse machine learning for de-novo molecular design and interpretability with surjective representations	Computer-based de-novo design of functional molecules is one of the most prominent challenges in cheminformatics today. As a result, generative and evolutionary inverse designs from the field of artificial intelligence have emerged at a rapid pace, with aims to optimize molecules for a particular chemical property. The...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	212,152
2308.13917	Transfer Learning for Microstructure Segmentation with CS-UNet: A Hybrid Algorithm with Transformer and CNN Encoders	Transfer learning improves the performance of deep learning models by initializing them with parameters pre-trained on larger datasets. Intuitively, transfer learning is more effective when pre-training is on the in-domain datasets. A recent study by NASA has demonstrated that the microstructure segmentation with encod...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	388,109
2210.05769	Vote'n'Rank: Revision of Benchmarking with Social Choice Theory	The development of state-of-the-art systems in different applied areas of machine learning (ML) is driven by benchmarks, which have shaped the paradigm of evaluating generalisation capabilities from multiple perspectives. Although the paradigm is shifting towards more fine-grained evaluation across diverse tasks, the d...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	322,990
1706.03216	Articulation rate in Swedish child-directed speech increases as a function of the age of the child even when surprisal is controlled for	In earlier work, we have shown that articulation rate in Swedish child-directed speech (CDS) increases as a function of the age of the child, even when utterance length and differences in articulation rate between subjects are controlled for. In this paper we show on utterance level in spontaneous Swedish speech that i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	75,121
2106.02609	SBML2Modelica: integrating biochemical models within open-standard simulation ecosystems	Motivation: SBML is the most widespread language for the definition of biochemical models. Although dozens of SBML simulators are available, there is a general lack of support to the integration of SBML models within open-standard general-purpose simulation ecosystems. This hinders co-simulation and integration of SBML...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	238,944
2411.05975	Adaptive Tracking Control with Binary-Valued Output Observations	This paper considers real-time control and learning problems for finite-dimensional linear systems under binary-valued and randomly disturbed output observations. This has long been regarded as an open problem because the exact values of the traditional regression vectors used in the construction of adaptive algorithms...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	506,912
2409.17158	Cross Dataset Analysis and Network Architecture Repair for Autonomous Car Lane Detection	Transfer Learning has become one of the standard methods to solve problems to overcome the isolated learning paradigm by utilizing knowledge acquired for one task to solve another related one. However, research needs to be done, to identify the initial steps before inducing transfer learning to applications for further...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	491,681
2005.00908	Clue: Cross-modal Coherence Modeling for Caption Generation	We use coherence relations inspired by computational models of discourse to study the information needs and goals of image captioning. Using an annotation protocol specifically devised for capturing image--caption coherence relations, we annotate 10,000 instances from publicly-available image--caption pairs. We introdu...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	175,424
1909.05950	Mutual-Information Regularization in Markov Decision Processes and Actor-Critic Learning	Cumulative entropy regularization introduces a regulatory signal to the reinforcement learning (RL) problem that encourages policies with high-entropy actions, which is equivalent to enforcing small deviations from a uniform reference marginal policy. This has been shown to improve exploration and robustness, and it ta...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	145,247
1210.2882	Online Adaptive Fault Tolerant based Feedback Control Scheduling Algorithm for Multiprocessor Embedded Systems	Since some years ago, use of Feedback Control Scheduling Algorithm (FCSA) in the control scheduling co-design of multiprocessor embedded system has increased. FCSA provides Quality of Service (QoS) in terms of overall system performance and resource allocation in open and unpredictable environment. FCSA uses quality co...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	19,048
2006.14925	Does the $\ell_1$-norm Learn a Sparse Graph under Laplacian Constrained Graphical Models?	We consider the problem of learning a sparse graph under the Laplacian constrained Gaussian graphical models. This problem can be formulated as a penalized maximum likelihood estimation of the Laplacian constrained precision matrix. Like in the classical graphical lasso problem, recent works made use of the $\ell_1$-no...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	184,371
2002.02770	A Survey on Causal Inference	Causal inference is a critical research topic across many domains, such as statistics, computer science, education, public policy and economics, for decades. Nowadays, estimating causal effect from observational data has become an appealing research direction owing to the large amount of available data and low budget r...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	163,022
2105.07044	SA-GAN: Structure-Aware GAN for Organ-Preserving Synthetic CT Generation	In medical image synthesis, model training could be challenging due to the inconsistencies between images of different modalities even with the same patient, typically caused by internal status/tissue changes as different modalities are usually obtained at a different time. This paper proposes a novel deep learning met...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	235,296
1502.02077	Quantum Energy Regression using Scattering Transforms	We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of multiscale wavelet transforms. It possesses appropriate invariant and stability...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	39,995
2011.07112	Benchmarking Domain Randomisation for Visual Sim-to-Real Transfer	Domain randomisation is a very popular method for visual sim-to-real transfer in robotics, due to its simplicity and ability to achieve transfer without any real-world images at all. Nonetheless, a number of design choices must be made to achieve optimal transfer. In this paper, we perform a comprehensive benchmarking ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	206,437
1602.00276	The Capacity of Online (Causal) $q$-ary Error-Erasure Channels	In the $q$-ary online (or "causal") channel coding model, a sender wishes to communicate a message to a receiver by transmitting a codeword $\mathbf{x} =(x_1,\ldots,x_n) \in \{0,1,\ldots,q-1\}^n$ symbol by symbol via a channel limited to at most $pn$ errors and/or $p^{*} n$ erasures. The channel is "online" in the sens...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	51,555
2203.13253	Video Instance Segmentation via Multi-scale Spatio-temporal Split Attention Transformer	State-of-the-art transformer-based video instance segmentation (VIS) approaches typically utilize either single-scale spatio-temporal features or per-frame multi-scale features during the attention computations. We argue that such an attention computation ignores the multi-scale spatio-temporal feature relationships th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,559
2303.09126	Evaluation of distance-based approaches for forensic comparison: Application to hand odor evidence	The issue of distinguishing between the same-source and different-source hypotheses based on various types of traces is a generic problem in forensic science. This problem is often tackled with Bayesian approaches, which are able to provide a likelihood ratio that quantifies the relative strengths of evidence supportin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	351,921
2407.20099	RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing Coding	Spiking Neural Networks (SNNs) have received widespread attention due to their unique neuronal dynamics and low-power nature. Previous research empirically shows that SNNs with Poisson coding are more robust than Artificial Neural Networks (ANNs) on small-scale datasets. However, it is still unclear in theory how the a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	477,045
2409.11230	Resilient and Adaptive Replanning for Multi-Robot Target Tracking with Sensing and Communication Danger Zones	Multi-robot collaboration for target tracking presents significant challenges in hazardous environments, including addressing robot failures, dynamic priority changes, and other unpredictable factors. Moreover, these challenges are increased in adversarial settings if the environment is unknown. In this paper, we propo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	489,062
2001.05097	Lightweight 3D Human Pose Estimation Network Training Using Teacher-Student Learning	We present MoVNect, a lightweight deep neural network to capture 3D human pose using a single RGB camera. To improve the overall performance of the model, we apply the teacher-student learning method based knowledge distillation to 3D human pose estimation. Real-time post-processing makes the CNN output yield temporall...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	160,439
1511.00195	Optimized Mission Planning for Planetary Exploration Rovers	The exploration of planetary surfaces is predominately unmanned, calling for a landing vehicle and an autonomous and/or teleoperated rover. Artificial intelligence and machine learning techniques can be leveraged for better mission planning. This paper describes the coordinated use of both global navigation and metaheu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	48,385
2109.14203	Identity-Expression Ambiguity in 3D Morphable Face Models	3D Morphable Models are a class of generative models commonly used to model faces. They are typically applied to ill-posed problems such as 3D reconstruction from 2D data. Several ambiguities in this problem's image formation process have been studied explicitly. We demonstrate that non-orthogonality of the variation i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	257,895
2203.11981	A Factor-Based Framework for Decision-Making Competency Self-Assessment	We summarize our efforts to date in developing a framework for generating succinct human-understandable competency self-assessments in terms of machine self confidence, i.e. a robot's self-trust in its functional abilities to accomplish assigned tasks. Whereas early work explored machine self-confidence in ad hoc ways ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	287,101
1804.02245	A Wikipedia-based approach to profiling activities on social media	Online user profiling is a very active research field, catalyzing great interest by both scientists and practitioners. In this paper, in particular, we look at approaches able to mine social media activities of users to create a rich user profile. We look at the case in which the profiling is meant to characterize the ...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	94,368
1304.7528	Semi-supervised Eigenvectors for Large-scale Locally-biased Learning	In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that prespecified target region. For example, one might be interested in the clusteri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	24,269
2006.04690	Network Structure Identification from Corrupt Data Streams	Complex networked systems can be modeled as graphs with nodes representing the agents and links describing the dynamic coupling between them. Previous work on network identification has shown that the network structure of linear time-invariant (LTI) systems can be reconstructed from the joint power spectrum of the data...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	180,780
2412.05825	Self-Supervised Learning with Probabilistic Density Labeling for Rainfall Probability Estimation	Numerical weather prediction (NWP) models are fundamental in meteorology for simulating and forecasting the behavior of various atmospheric variables. The accuracy of precipitation forecasts and the acquisition of sufficient lead time are crucial for preventing hazardous weather events. However, the performance of NWP ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	514,985
2410.15440	Evaluating Consistencies in LLM responses through a Semantic Clustering of Question Answering	In the realm of Large Language Model (LLM) functionalities, providing reliable information is paramount, yet reports suggest that LLM outputs lack consistency. This inconsistency, often at-tributed to randomness in token sampling, under-mines user trust as it leads to varying responses even for identical queries. In th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	500,539
1106.0676	Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System	Designing the dialogue policy of a spoken dialogue system involves many nontrivial choices. This paper presents a reinforcement learning approach for automatically optimizing a dialogue policy, which addresses the technical challenges in applying reinforcement learning to a working dialogue system with human users. We ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	10,709

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