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
2106.04835	Joint System-Wise Optimization for Pipeline Goal-Oriented Dialog System	Recent work (Takanobu et al., 2020) proposed the system-wise evaluation on dialog systems and found that improvement on individual components (e.g., NLU, policy) in prior work may not necessarily bring benefit to pipeline systems in system-wise evaluation. To improve the system-wise performance, in this paper, we propo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	239,876
1908.11799	Dense Dilated Convolutions Merging Network for Semantic Mapping of Remote Sensing Images	We propose a network for semantic mapping called the Dense Dilated Convolutions Merging Network (DDCM-Net) to provide a deep learning approach that can recognize multi-scale and complex shaped objects with similar color and textures, such as buildings, surfaces/roads, and trees in very high resolution remote sensing im...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	143,471
2207.08757	Preventing Inferences through Data Dependencies on Sensitive Data	Simply restricting the computation to non-sensitive part of the data may lead to inferences on sensitive data through data dependencies. Inference control from data dependencies has been studied in the prior work. However, existing solutions either detect and deny queries which may lead to leakage -- resulting in poor ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	308,679
2211.17188	Automated Play-Testing Through RL Based Human-Like Play-Styles Generation	The increasing complexity of gameplay mechanisms in modern video games is leading to the emergence of a wider range of ways to play games. The variety of possible play-styles needs to be anticipated by designers, through automated tests. Reinforcement Learning is a promising answer to the need of automating video game ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	333,890
2205.07352	Long-term Control for Dialogue Generation: Methods and Evaluation	Current approaches for controlling dialogue response generation are primarily focused on high-level attributes like style, sentiment, or topic. In this work, we focus on constrained long-term dialogue generation, which involves more fine-grained control and requires a given set of control words to appear in generated r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	296,571
2210.01320	Wi-Closure: Reliable and Efficient Search of Inter-robot Loop Closures Using Wireless Sensing	In this paper we propose a novel algorithm, Wi-Closure, to improve computational efficiency and robustness of loop closure detection in multi-robot SLAM. Our approach decreases the computational overhead of classical approaches by pruning the search space of potential loop closures, prior to evaluation by a typical mul...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	321,215
2403.08721	Historical Astronomical Diagrams Decomposition in Geometric Primitives	Automatically extracting the geometric content from the hundreds of thousands of diagrams drawn in historical manuscripts would enable historians to study the diffusion of astronomical knowledge on a global scale. However, state-of-the-art vectorization methods, often designed to tackle modern data, are not adapted to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	437,440
1911.12961	Stochastic Optimal Power Flow with Network Reconfiguration: Congestion Management and Facilitating Grid Integration of Renewables	There has been a significant growth of variable renewable generation in the power grid today. However, the industry still uses deterministic optimization to model and solve the optimal power flow (OPF) problem for real-time generation dispatch that ignores the uncertainty associated with intermittent renewable power. T...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	155,540
2312.00046	Retail Analytics in the New Normal: The Influence of Artificial Intelligence and the Covid-19 Pandemic	The COVID-19 pandemic has severely disrupted the retail landscape and has accelerated the adoption of innovative technologies. A striking example relates to the proliferation of online grocery orders and the technology deployed to facilitate such logistics. In fact, for many retailers, this disruption was a wake-up cal...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	411,873
2110.14879	Pilot Optimization and Channel Estimation for Two-way Relaying Network Aided by IRS with Finite Discrete Phase Shifters	In this paper, we investigate the problem of pilot optimization and channel estimation of two-way relaying network (TWRN) aided by an intelligent reflecting surface (IRS) with finite discrete phase shifters. In a TWRN, there exists a challenging problem that the two cascading channels from source-to-IRS-to-Relay and de...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	263,678
2002.10111	SMOKE: Single-Stage Monocular 3D Object Detection via Keypoint Estimation	Estimating 3D orientation and translation of objects is essential for infrastructure-less autonomous navigation and driving. In case of monocular vision, successful methods have been mainly based on two ingredients: (i) a network generating 2D region proposals, (ii) a R-CNN structure predicting 3D object pose by utiliz...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,290
1604.06194	Dynamic matrix factorization with social influence	Matrix factorization is a key component of collaborative filtering-based recommendation systems because it allows us to complete sparse user-by-item ratings matrices under a low-rank assumption that encodes the belief that similar users give similar ratings and that similar items garner similar ratings. This paradigm h...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	54,910
2410.03085	Optimization Proxies using Limited Labeled Data and Training Time -- A Semi-Supervised Bayesian Neural Network Approach	Constrained optimization problems arise in various engineering system operations such as inventory management and electric power grids. However, the requirement to repeatedly solve such optimization problems with uncertain parameters poses a significant computational challenge. This work introduces a learning scheme us...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	494,612
1104.2599	Streaming Tree Transducers	Theory of tree transducers provides a foundation for understanding expressiveness and complexity of analysis problems for specification languages for transforming hierarchically structured data such as XML documents. We introduce streaming tree transducers as an analyzable, executable, and expressive model for transfor...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	9,975
1711.07227	Linear-Complexity Relaxed Word Mover's Distance with GPU Acceleration	The amount of unstructured text-based data is growing every day. Querying, clustering, and classifying this big data requires similarity computations across large sets of documents. Whereas low-complexity similarity metrics are available, attention has been shifting towards more complex methods that achieve a higher ac...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	84,942
2204.11855	Discovering Gateway Ports in Maritime Using Temporal Graph Neural Network Port Classification	Vessel navigation is influenced by various factors, such as dynamic environmental factors that change over time or static features such as vessel type or depth of the ocean. These dynamic and static navigational factors impose limitations on vessels, such as long waiting times in regions outside the actual ports, and w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	293,296
2006.01175	Lexical Normalization for Code-switched Data and its Effect on POS-tagging	Lexical normalization, the translation of non-canonical data to standard language, has shown to improve the performance of manynatural language processing tasks on social media. Yet, using multiple languages in one utterance, also called code-switching (CS), is frequently overlooked by these normalization systems, desp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	179,692
2104.09415	Cross-Domain Adaptive Clustering for Semi-Supervised Domain Adaptation	In semi-supervised domain adaptation, a few labeled samples per class in the target domain guide features of the remaining target samples to aggregate around them. However, the trained model cannot produce a highly discriminative feature representation for the target domain because the training data is dominated by lab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	231,232
1311.5502	Evolution of Communities with Focus on Stability (extended abstract)	The detection of communities is an important tool used to analyze the social graph of mobile phone users. Within each community, customers are susceptible of attracting new ones, retaining old ones and/or accepting new products or services through the leverage of mutual influences. The communities of users are smaller ...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	28,565
1911.04766	Investigating Constraint Programming and Hybrid Methods for Real World Industrial Test Laboratory Scheduling	In this paper we deal with a complex real world scheduling problem closely related to the well-known Resource-Constrained Project Scheduling Problem (RCPSP). The problem concerns industrial test laboratories in which a large number of tests has to be performed by qualified personnel using specialised equipment, while r...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	153,076
2401.09132	Admittance Controller Complemented with Real-time Singularity Avoidance for Rehabilitation Parallel Robots	Rehabilitation tasks demand robust and accurate trajectory-tracking performance, mainly achieved with parallel robots. In this field, limiting the value of the force exerted on the patient is crucial, especially when an injured limb is involved. In human-robot interaction studies, the admittance controller modifies the...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	422,161
1807.07878	An Operational Approach to Information Leakage	Given two random variables $X$ and $Y$, an operational approach is undertaken to quantify the ``leakage'' of information from $X$ to $Y$. The resulting measure $\mathcal{L}(X \!\! \to \!\! Y)$ is called \emph{maximal leakage}, and is defined as the multiplicative increase, upon observing $Y$, of the probability of corr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	103,404
2405.10997	Transcript of GPT-4 playing a rogue AGI in a Matrix Game	Matrix Games are a type of unconstrained wargame used by planners to explore scenarios. Players propose actions, and give arguments and counterarguments for their success. An umpire, assisted by dice rolls modified according to the offered arguments, adjudicates the outcome of each action. A recent online play of the M...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	454,964
2402.11143	Foundation Models for Recommender Systems: A Survey and New Perspectives	Recently, Foundation Models (FMs), with their extensive knowledge bases and complex architectures, have offered unique opportunities within the realm of recommender systems (RSs). In this paper, we attempt to thoroughly examine FM-based recommendation systems (FM4RecSys). We start by reviewing the research background o...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	430,255
2110.02927	Data Twinning	In this work, we develop a method named Twinning, for partitioning a dataset into statistically similar twin sets. Twinning is based on SPlit, a recently proposed model-independent method for optimally splitting a dataset into training and testing sets. Twinning is orders of magnitude faster than the SPlit algorithm, w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,307
2212.09284	An Investigation of Indian Native Language Phonemic Influences on L2 English Pronunciations	Speech systems are sensitive to accent variations. This is especially challenging in the Indian context, with an abundance of languages but a dearth of linguistic studies characterising pronunciation variations. The growing number of L2 English speakers in India reinforces the need to study accents and L1-L2 interactio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,063
2006.03221	Evaluating Text Coherence at Sentence and Paragraph Levels	In this paper, to evaluate text coherence, we propose the paragraph ordering task as well as conducting sentence ordering. We collected four distinct corpora from different domains on which we investigate the adaptation of existing sentence ordering methods to a paragraph ordering task. We also compare the learnability...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	180,252
1510.05751	Semi-Implicit Time Integration of Atmospheric Flows with Characteristic-Based Flux Partitioning	This paper presents a characteristic-based flux partitioning for the semi-implicit time integration of atmospheric flows. Nonhydrostatic models require the solution of the compressible Euler equations. The acoustic time-scale is significantly faster than the advective scale, yet it is typically not relevant to atmosphe...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	48,049
2310.04528	DPGOMI: Differentially Private Data Publishing with Gaussian Optimized Model Inversion	High-dimensional data are widely used in the era of deep learning with numerous applications. However, certain data which has sensitive information are not allowed to be shared without privacy protection. In this paper, we propose a novel differentially private data releasing method called Differentially Private Data P...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	397,697
2501.15048	YouTube Recommendations Reinforce Negative Emotions: Auditing Algorithmic Bias with Emotionally-Agentic Sock Puppets	Personalized recommendation algorithms, like those on YouTube, significantly shape online content consumption. These systems aim to maximize engagement by learning users' preferences and aligning content accordingly but may unintentionally reinforce impulsive and emotional biases. Using a sock-puppet audit methodology,...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	527,374
2411.05238	Generating Highly Designable Proteins with Geometric Algebra Flow Matching	We introduce a generative model for protein backbone design utilizing geometric products and higher order message passing. In particular, we propose Clifford Frame Attention (CFA), an extension of the invariant point attention (IPA) architecture from AlphaFold2, in which the backbone residue frames and geometric featur...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,592
2003.11059	Integrating Physiological Time Series and Clinical Notes with Deep Learning for Improved ICU Mortality Prediction	Intensive Care Unit Electronic Health Records (ICU EHRs) store multimodal data about patients including clinical notes, sparse and irregularly sampled physiological time series, lab results, and more. To date, most methods designed to learn predictive models from ICU EHR data have focused on a single modality. In this ...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	169,497
cs/0205061	Aging, double helix and small world property in genetic algorithms	Over a quarter of century after the invention of genetic algorithms and miriads of their modifications, as well as successful implementations, we are still lacking many essential details of thorough analysis of it's inner working. One of such fundamental questions is: how many generations do we need to solve the optimi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	537,584
2010.02562	Cross-Lingual Text Classification with Minimal Resources by Transferring a Sparse Teacher	Cross-lingual text classification alleviates the need for manually labeled documents in a target language by leveraging labeled documents from other languages. Existing approaches for transferring supervision across languages require expensive cross-lingual resources, such as parallel corpora, while less expensive cros...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	199,081
2110.10342	Minibatch vs Local SGD with Shuffling: Tight Convergence Bounds and Beyond	In distributed learning, local SGD (also known as federated averaging) and its simple baseline minibatch SGD are widely studied optimization methods. Most existing analyses of these methods assume independent and unbiased gradient estimates obtained via with-replacement sampling. In contrast, we study shuffling-based v...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	262,116
2309.03437	Byzantine-Robust Federated Learning with Variance Reduction and Differential Privacy	Federated learning (FL) is designed to preserve data privacy during model training, where the data remains on the client side (i.e., IoT devices), and only model updates of clients are shared iteratively for collaborative learning. However, this process is vulnerable to privacy attacks and Byzantine attacks: the local ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	390,375
2205.02921	Conversational Analysis of Daily Dialog Data using Polite Emotional Dialogue Acts	Many socio-linguistic cues are used in conversational analysis, such as emotion, sentiment, and dialogue acts. One of the fundamental cues is politeness, which linguistically possesses properties such as social manners useful in conversational analysis. This article presents findings of polite emotional dialogue act as...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	295,108
1603.03876	Variational Neural Discourse Relation Recognizer	Implicit discourse relation recognition is a crucial component for automatic discourselevel analysis and nature language understanding. Previous studies exploit discriminative models that are built on either powerful manual features or deep discourse representations. In this paper, instead, we explore generative models...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	53,162
2207.11511	SSBNet: Improving Visual Recognition Efficiency by Adaptive Sampling	Downsampling is widely adopted to achieve a good trade-off between accuracy and latency for visual recognition. Unfortunately, the commonly used pooling layers are not learned, and thus cannot preserve important information. As another dimension reduction method, adaptive sampling weights and processes regions that are...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	309,666
2207.05669	From Spectral Graph Convolutions to Large Scale Graph Convolutional Networks	Graph Convolutional Networks (GCNs) have been shown to be a powerful concept that has been successfully applied to a large variety of tasks across many domains over the past years. In this work we study the theory that paved the way to the definition of GCN, including related parts of classical graph theory. We also di...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	307,617
2405.08175	Comparative Analysis of AWS Model Deployment Services	Amazon Web Services (AWS) offers three important Model Deployment Services for model developers: SageMaker, Lambda, and Elastic Container Service (ECS). These services have critical advantages and disadvantages, influencing model developer's adoption decisions. This comparative analysis reviews the merits and drawbacks...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	454,002
1208.0081	Efficient Multi-way Theta-Join Processing Using MapReduce	Multi-way Theta-join queries are powerful in describing complex relations and therefore widely employed in real practices. However, existing solutions from traditional distributed and parallel databases for multi-way Theta-join queries cannot be easily extended to fit a shared-nothing distributed computing paradigm, wh...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	17,858
1711.02736	A Comparative Study of Interface Techniques for Transmission and Distribution Dynamic Co-Simulation	Transmission and distribution dynamic co-simulation is a practical and effective approach to leverage existing simulation tools for transmission and distribution systems to simulate dynamic stability and performance of transmission and distribution systems in a systematic manner. Given that these tools are developed as...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	84,102
2201.04929	Improving VAE based molecular representations for compound property prediction	Collecting labeled data for many important tasks in chemoinformatics is time consuming and requires expensive experiments. In recent years, machine learning has been used to learn rich representations of molecules using large scale unlabeled molecular datasets and transfer the knowledge to solve the more challenging ta...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,237
2208.14111	Transformers with Learnable Activation Functions	Activation functions can have a significant impact on reducing the topological complexity of input data and therefore improve the performance of the model. Selecting a suitable activation function is an essential step in neural model design. However, the choice of activation function is seldom discussed or explored in ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	315,223
2111.08004	Bag of Tricks and A Strong baseline for Image Copy Detection	Image copy detection is of great importance in real-life social media. In this paper, a bag of tricks and a strong baseline are proposed for image copy detection. Unsupervised pre-training substitutes the commonly-used supervised one. Beyond that, we design a descriptor stretching strategy to stabilize the scores of di...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	266,540
1904.03976	GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram	Recent advances in neural network -based text-to-speech have reached human level naturalness in synthetic speech. The present sequence-to-sequence models can directly map text to mel-spectrogram acoustic features, which are convenient for modeling, but present additional challenges for vocoding (i.e., waveform generati...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	126,900
2311.13905	A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists	Cyclists prefer to use infrastructure that separates them from motorized traffic. Using a traffic light to segregate car and bike flows, with the addition of bike-specific green phases, is a lightweight and cheap solution that can be deployed dynamically to assess the opportunity of a heavier infrastructure such as a s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	409,920
2402.05403	In-Context Principle Learning from Mistakes	In-context learning (ICL, also known as few-shot prompting) has been the standard method of adapting LLMs to downstream tasks, by learning from a few input-output examples. Nonetheless, all ICL-based approaches only learn from correct input-output pairs. In this paper, we revisit this paradigm, by learning more from th...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	427,849
0912.3441	On Space-Time Capacity Limits in Mobile and Delay Tolerant Networks	We investigate the fundamental capacity limits of space-time journeys of information in mobile and Delay Tolerant Networks (DTNs), where information is either transmitted or carried by mobile nodes, using store-carry-forward routing. We define the capacity of a journey (i.e., a path in space and time, from a source to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	5,175
2410.10846	Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models	Large Language Models (LLMs) typically generate outputs token by token using a fixed compute budget, leading to inefficient resource utilization. To address this shortcoming, recent advancements in mixture of expert (MoE) models, speculative decoding, and early exit strategies leverage the insight that computational de...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	498,265
2409.03893	Understanding Fairness in Recommender Systems: A Healthcare Perspective	Fairness in AI-driven decision-making systems has become a critical concern, especially when these systems directly affect human lives. This paper explores the public's comprehension of fairness in healthcare recommendations. We conducted a survey where participants selected from four fairness metrics -- Demographic Pa...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	486,212
2109.04986	Multi-agent deep reinforcement learning (MADRL) meets multi-user MIMO systems	A multi-agent deep reinforcement learning (MADRL) is a promising approach to challenging problems in wireless environments involving multiple decision-makers (or actors) with high-dimensional continuous action space. In this paper, we present a MADRL-based approach that can jointly optimize precoders to achieve the out...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	254,617
1809.01898	Propheticus: Generalizable Machine Learning Framework	Due to recent technological developments, Machine Learning (ML), a subfield of Artificial Intelligence (AI), has been successfully used to process and extract knowledge from a variety of complex problems. However, a thorough ML approach is complex and highly dependent on the problem at hand. Additionally, implementing ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	106,916
2411.05966	Energy Efficient Protein Language Models: Leveraging Small Language Models with LoRA for Controllable Protein Generation	Large language models (LLMs) have demonstrated significant success in natural language processing (NLP) tasks and have shown promising results in other domains such as protein sequence generation. However, there remain salient differences between LLMs used for NLP, which effectively handle multiple tasks and are availa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,910
2107.06343	Design of Adaptive Backstepping Control for Direct Power Control of Three-Phase PWM Rectifier)	In this paper, we focused on the design of an adaptive backstepping controller (adaptive-BSC) for direct power control (DPC) of a three-phase PWM rectifier. In the proposed system, it is desired to control both the output DC voltage of the rectifier and the reactive power simultaneously by making them track desired res...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	246,058
2411.09177	Enhancing reinforcement learning for population setpoint tracking in co-cultures	Efficient multiple setpoint tracking can enable advanced biotechnological applications, such as maintaining desired population levels in co-cultures for optimal metabolic division of labor. In this study, we employ reinforcement learning as a control method for population setpoint tracking in co-cultures, focusing on p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	508,159
2102.04702	AttDMM: An Attentive Deep Markov Model for Risk Scoring in Intensive Care Units	Clinical practice in intensive care units (ICUs) requires early warnings when a patient's condition is about to deteriorate so that preventive measures can be undertaken. To this end, prediction algorithms have been developed that estimate the risk of mortality in ICUs. In this work, we propose a novel generative deep ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	219,199
2004.09272	A Revised Generative Evaluation of Visual Dialogue	Evaluating Visual Dialogue, the task of answering a sequence of questions relating to a visual input, remains an open research challenge. The current evaluation scheme of the VisDial dataset computes the ranks of ground-truth answers in predefined candidate sets, which Massiceti et al. (2018) show can be susceptible to...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	173,298
2002.10327	Angle Aware User Cooperation for Secure Massive MIMO in Rician Fading Channel	Massive multiple-input multiple-output communications can achieve high-level security by concentrating radio frequency signals towards the legitimate users. However, this system is vulnerable in a Rician fading environment if the eavesdropper positions itself such that its channel is highly "similar" to the channel of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	165,367
2306.03229	Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception	Deep neural networks (DNNs) are known to have a fundamental sensitivity to adversarial attacks, perturbations of the input that are imperceptible to humans yet powerful enough to change the visual decision of a model. Adversarial attacks have long been considered the "Achilles' heel" of deep learning, which may eventua...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	371,237
2404.04057	Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation	We introduce Score identity Distillation (SiD), an innovative data-free method that distills the generative capabilities of pretrained diffusion models into a single-step generator. SiD not only facilitates an exponentially fast reduction in Fr\'echet inception distance (FID) during distillation but also approaches or ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	444,497
2406.19741	ROS-LLM: A ROS framework for embodied AI with task feedback and structured reasoning	We present a framework for intuitive robot programming by non-experts, leveraging natural language prompts and contextual information from the Robot Operating System (ROS). Our system integrates large language models (LLMs), enabling non-experts to articulate task requirements to the system through a chat interface. Ke...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	468,546
2302.08268	Retrieval-augmented Image Captioning	Inspired by retrieval-augmented language generation and pretrained Vision and Language (V&L) encoders, we present a new approach to image captioning that generates sentences given the input image and a set of captions retrieved from a datastore, as opposed to the image alone. The encoder in our model jointly processes ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	346,003
1709.07158	SceneCut: Joint Geometric and Object Segmentation for Indoor Scenes	This paper presents SceneCut, a novel approach to jointly discover previously unseen objects and non-object surfaces using a single RGB-D image. SceneCut's joint reasoning over scene semantics and geometry allows a robot to detect and segment object instances in complex scenes where modern deep learning-based methods e...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	81,233
2103.15046	Definition and Analytical Expression on State Observe Ability for Linear Discrete-time Systems with the Bounded Noise Energy	In this article, the definition on the observe ability and its relation to the signal detecting performance are studied systematically for the linear discrete-time(LDT) systems. Firstly, to define and analyze the observe ability for the practical systems with the measured noise, six kinds of bounded noise models are cl...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	227,063
2207.14373	Eye Gaze Estimation Model Analysis	We explore techniques for eye gaze estimation using machine learning. Eye gaze estimation is a common problem for various behavior analysis and human-computer interfaces. The purpose of this work is to discuss various model types for eye gaze estimation and present the results from predicting gaze direction using eye l...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	310,558
2305.16360	Modeling Task Relationships in Multi-variate Soft Sensor with Balanced Mixture-of-Experts	Accurate estimation of multiple quality variables is critical for building industrial soft sensor models, which have long been confronted with data efficiency and negative transfer issues. Methods sharing backbone parameters among tasks address the data efficiency issue; however, they still fail to mitigate the negativ...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	368,051
2209.09702	LEMURS: Learning Distributed Multi-Robot Interactions	This paper presents LEMURS, an algorithm for learning scalable multi-robot control policies from cooperative task demonstrations. We propose a port-Hamiltonian description of the multi-robot system to exploit universal physical constraints in interconnected systems and achieve closed-loop stability. We represent a mult...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	318,616
0811.0146	Effect of Tuned Parameters on a LSA MCQ Answering Model	This paper presents the current state of a work in progress, whose objective is to better understand the effects of factors that significantly influence the performance of Latent Semantic Analysis (LSA). A difficult task, which consists in answering (French) biology Multiple Choice Questions, is used to test the semant...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	2,601
1410.7026	Optimal topology of multi-agent systems with two leaders: a zero-sum game perspective	It is typical to assume that there is no conflict of interest among leaders. Under such assumption, it is known that, for a multi-agent system with two leaders, if the followers' interaction subgraph is undirected and connected, then followers will converge to a convex combination of two leaders' states with linear con...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	37,032
1209.2541	Absence of epidemic thresholds in a growing adaptive network	The structure of social contact networks strongly influences the dynamics of epidemic diseases. In particular the scale-free structure of real-world social networks allows unlikely diseases with low infection rates to spread and become endemic. However, in particular for potentially fatal diseases, also the impact of t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	18,516
2011.07577	Placement in Integrated Circuits using Cyclic Reinforcement Learning and Simulated Annealing	Physical design and production of Integrated Circuits (IC) is becoming increasingly more challenging as the sophistication in IC technology is steadily increasing. Placement has been one of the most critical steps in IC physical design. Through decades of research, partition-based, analytical-based and annealing-based ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	206,602
2406.06014	Network two-sample test for block models	We consider the two-sample testing problem for networks, where the goal is to determine whether two sets of networks originated from the same stochastic model. Assuming no vertex correspondence and allowing for different numbers of nodes, we address a fundamental network testing problem that goes beyond simple adjacenc...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	462,396
2208.10739	Quality-Constant Per-Shot Encoding by Two-Pass Learning-based Rate Factor Prediction	Providing quality-constant streams can simultaneously guarantee user experience and prevent wasting bit-rate. In this paper, we propose a novel deep learning based two-pass encoder parameter prediction framework to decide rate factor (RF), with which encoder can output streams with constant quality. For each one-shot s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	314,181
2404.09453	Towards Greener Nights: Exploring AI-Driven Solutions for Light Pollution Management	This research endeavors to address the pervasive issue of light pollution through an interdisciplinary approach, leveraging data science and machine learning techniques. By analyzing extensive datasets and research findings, we aim to develop predictive models capable of estimating the degree of sky glow observed in va...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	446,676
1906.05838	Goal-conditioned Imitation Learning	Designing rewards for Reinforcement Learning (RL) is challenging because it needs to convey the desired task, be efficient to optimize, and be easy to compute. The latter is particularly problematic when applying RL to robotics, where detecting whether the desired configuration is reached might require considerable sup...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	135,136
2403.11057	Large Language Models Powered Context-aware Motion Prediction in Autonomous Driving	Motion prediction is among the most fundamental tasks in autonomous driving. Traditional methods of motion forecasting primarily encode vector information of maps and historical trajectory data of traffic participants, lacking a comprehensive understanding of overall traffic semantics, which in turn affects the perform...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	438,503
2403.02454	The Ink Splotch Effect: A Case Study on ChatGPT as a Co-Creative Game Designer	This paper studies how large language models (LLMs) can act as effective, high-level creative collaborators and ``muses'' for game design. We model the design of this study after the exercises artists use by looking at amorphous ink splotches for creative inspiration. Our goal is to determine whether AI-assistance can ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	434,808
2501.13134	UniRestore: Unified Perceptual and Task-Oriented Image Restoration Model Using Diffusion Prior	Image restoration aims to recover content from inputs degraded by various factors, such as adverse weather, blur, and noise. Perceptual Image Restoration (PIR) methods improve visual quality but often do not support downstream tasks effectively. On the other hand, Task-oriented Image Restoration (TIR) methods focus on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,575
2407.02953	Affine Frequency Division Multiplexing for Compressed Sensing of Time-Varying Channels	This paper addresses compressed sensing of linear time-varying (LTV) wireless propagation links under the assumption of double sparsity i.e., sparsity in both the delay and Doppler domains, using Affine Frequency Division Multiplexing (AFDM) measurements. By rigorously linking the double sparsity model to the hierarchi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	469,960
2003.10959	Learning to Exploit Multiple Vision Modalities by Using Grafted Networks	Novel vision sensors such as thermal, hyperspectral, polarization, and event cameras provide information that is not available from conventional intensity cameras. An obstacle to using these sensors with current powerful deep neural networks is the lack of large labeled training datasets. This paper proposes a Network ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	169,478
2104.06689	Learning Normal Dynamics in Videos with Meta Prototype Network	Frame reconstruction (current or future frame) based on Auto-Encoder (AE) is a popular method for video anomaly detection. With models trained on the normal data, the reconstruction errors of anomalous scenes are usually much larger than those of normal ones. Previous methods introduced the memory bank into AE, for enc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	230,161
2311.05840	Predictive AI for SME and Large Enterprise Financial Performance Management	Financial performance management is at the core of business management and has historically relied on financial ratio analysis using Balance Sheet and Income Statement data to assess company performance as compared with competitors. Little progress has been made in predicting how a company will perform or in assessing ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	406,724
2011.05533	Spoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop	With robotics rapidly advancing, more effective human-robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be part of the solution, our ability to provide spoken language interaction capabilities is still very limited. The National Science Foundation a...	true	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	205,951
2406.10719	Trading Devil: Robust backdoor attack via Stochastic investment models and Bayesian approach	With the growing use of voice-activated systems and speech recognition technologies, the danger of backdoor attacks on audio data has grown significantly. This research looks at a specific type of attack, known as a Stochastic investment-based backdoor attack (MarketBack), in which adversaries strategically manipulate ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	464,522
1909.01136	Pre-training A Neural Language Model Improves The Sample Efficiency of an Emergency Room Classification Model	To build a French national electronic injury surveillance system based on emergency room visits, we aim to develop a coding system to classify their causes from clinical notes in free-text. Supervised learning techniques have shown good results in this area but require a large amount of expert annotated dataset which i...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	143,822
2410.19110	Bio2Token: All-atom tokenization of any biomolecular structure with Mamba	Efficient encoding and representation of large 3D molecular structures with high fidelity is critical for biomolecular design applications. Despite this, many representation learning approaches restrict themselves to modeling smaller systems or use coarse-grained approximations of the systems, for example modeling prot...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	502,160
2003.03229	Non-linear Neurons with Human-like Apical Dendrite Activations	In order to classify linearly non-separable data, neurons are typically organized into multi-layer neural networks that are equipped with at least one hidden layer. Inspired by some recent discoveries in neuroscience, we propose a new model of artificial neuron along with a novel activation function enabling the learni...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	167,164
2207.10541	Unveiling the Latent Space Geometry of Push-Forward Generative Models	Many deep generative models are defined as a push-forward of a Gaussian measure by a continuous generator, such as Generative Adversarial Networks (GANs) or Variational Auto-Encoders (VAEs). This work explores the latent space of such deep generative models. A key issue with these models is their tendency to output sam...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	309,297
2107.08964	Transductive image segmentation: Self-training and effect of uncertainty estimation	Semi-supervised learning (SSL) uses unlabeled data during training to learn better models. Previous studies on SSL for medical image segmentation focused mostly on improving model generalization to unseen data. In some applications, however, our primary interest is not generalization but to obtain optimal predictions o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	246,892
2402.09050	End-to-End Training Induces Information Bottleneck through Layer-Role Differentiation: A Comparative Analysis with Layer-wise Training	End-to-end (E2E) training, optimizing the entire model through error backpropagation, fundamentally supports the advancements of deep learning. Despite its high performance, E2E training faces the problems of memory consumption, parallel computing, and discrepancy with the functionalities of the actual brain. Various a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	429,344
2004.11587	Concept Drift Detection via Equal Intensity k-means Space Partitioning	Data stream poses additional challenges to statistical classification tasks because distributions of the training and target samples may differ as time passes. Such distribution change in streaming data is called concept drift. Numerous histogram-based distribution change detection methods have been proposed to detect ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	173,953
2206.01815	Option Discovery for Autonomous Generation of Symbolic Knowledge	In this work we present an empirical study where we demonstrate the possibility of developing an artificial agent that is capable to autonomously explore an experimental scenario. During the exploration, the agent is able to discover and learn interesting options allowing to interact with the environment without any pr...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	300,613
2206.13028	Multi-Scale Spatial Temporal Graph Convolutional Network for Skeleton-Based Action Recognition	Graph convolutional networks have been widely used for skeleton-based action recognition due to their excellent modeling ability of non-Euclidean data. As the graph convolution is a local operation, it can only utilize the short-range joint dependencies and short-term trajectory but fails to directly model the distant ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	304,811
1406.0234	Joint PIC and relay selection based on greedy techniques for cooperative DS-CDMA systems	In this work, we propose a cross-layer design strategy based on the parallel interference cancellation (PIC) detection technique and a multi-relay selection algorithm for the uplink of cooperative direct-sequence code-division multiple access (DS-CDMA) systems. We devise a low-cost greedy list-based PIC (GL-PIC) strate...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	33,542
1905.08846	Discovering Hidden Structure in High Dimensional Human Behavioral Data via Tensor Factorization	In recent years, the rapid growth in technology has increased the opportunity for longitudinal human behavioral studies. Rich multimodal data, from wearables like Fitbit, online social networks, mobile phones etc. can be collected in natural environments. Uncovering the underlying low-dimensional structure of noisy mul...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,581
2310.06956	Adversarial optimization leads to over-optimistic security-constrained dispatch, but sampling can help	To ensure safe, reliable operation of the electrical grid, we must be able to predict and mitigate likely failures. This need motivates the classic security-constrained AC optimal power flow (SCOPF) problem. SCOPF is commonly solved using adversarial optimization, where the dispatcher and an adversary take turns optimi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	398,774
1907.02865	Cardiac MRI Segmentation with Strong Anatomical Guarantees	Recent publications have shown that the segmentation accuracy of modern-day convolutional neural networks (CNN) applied on cardiac MRI can reach the inter-expert variability, a great achievement in this area of research. However, despite these successes, CNNs still produce anatomically inaccurate segmentations as they ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,705
2407.20174	Advancing Multimodal Large Language Models in Chart Question Answering with Visualization-Referenced Instruction Tuning	Emerging multimodal large language models (MLLMs) exhibit great potential for chart question answering (CQA). Recent efforts primarily focus on scaling up training datasets (i.e., charts, data tables, and question-answer (QA) pairs) through data collection and synthesis. However, our empirical study on existing MLLMs a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	477,070

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