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
2005.05716	AttViz: Online exploration of self-attention for transparent neural language modeling	Neural language models are becoming the prevailing methodology for the tasks of query answering, text classification, disambiguation, completion and translation. Commonly comprised of hundreds of millions of parameters, these neural network models offer state-of-the-art performance at the cost of interpretability; huma...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	176,806
1710.11268	Theoretical and Computational Guarantees of Mean Field Variational Inference for Community Detection	The mean field variational Bayes method is becoming increasingly popular in statistics and machine learning. Its iterative Coordinate Ascent Variational Inference algorithm has been widely applied to large scale Bayesian inference. See Blei et al. (2017) for a recent comprehensive review. Despite the popularity of the ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	83,555
2211.03065	Enabling Deep Learning-based Physical-layer Secret Key Generation for FDD-OFDM Systems in Multi-Environments	Deep learning-based physical-layer secret key generation (PKG) has been used to overcome the imperfect uplink/downlink channel reciprocity in frequency division duplexing (FDD) orthogonal frequency division multiplexing (OFDM) systems. However, existing efforts have focused on key generation for users in a specific env...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	328,821
2212.11892	An Adaptive Simulated Annealing-Based Machine Learning Approach for Developing an E-Triage Tool for Hospital Emergency Operations	Patient triage at emergency departments (EDs) is necessary to prioritize care for patients with critical and time-sensitive conditions. Different tools are used for patient triage and one of the most common ones is the emergency severity index (ESI), which has a scale of five levels, where level 1 is the most urgent an...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	337,913
2403.16354	ChatDBG: An AI-Powered Debugging Assistant	Debugging is a critical but challenging task for programmers. This paper proposes ChatDBG, an AI-powered debugging assistant. ChatDBG integrates large language models (LLMs) to significantly enhance the capabilities and user-friendliness of conventional debuggers. ChatDBG lets programmers engage in a collaborative dial...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	440,991
1204.2712	Learning to Rank Query Recommendations by Semantic Similarities	Logs of the interactions with a search engine show that users often reformulate their queries. Examining these reformulations shows that recommendations that precise the focus of a query are helpful, like those based on expansions of the original queries. But it also shows that queries that express some topical shift w...	true	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	15,434
1710.03077	Deeper, Broader and Artier Domain Generalization	The problem of domain generalization is to learn from multiple training domains, and extract a domain-agnostic model that can then be applied to an unseen domain. Domain generalization (DG) has a clear motivation in contexts where there are target domains with distinct characteristics, yet sparse data for training. For...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,279
2211.08914	Dual Class-Aware Contrastive Federated Semi-Supervised Learning	Federated semi-supervised learning (FSSL), facilitates labeled clients and unlabeled clients jointly training a global model without sharing private data. Existing FSSL methods predominantly employ pseudo-labeling and consistency regularization to exploit the knowledge of unlabeled data, achieving notable success in ra...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	330,814
2209.03261	Cooperative trajectory planning algorithm of USV-UAV with hull dynamic constraints	Efficient trajectory generation in complex dynamic environments remains an open problem in the unmanned surface vehicle (USV). The perception of the USV is usually interfered with by the swing of the hull and the ambient weather, making it challenging to plan the optimal USV trajectories. In this paper, a cooperative t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	316,456
2004.11482	Roof material classification from aerial imagery	This paper describes an algorithm for classification of roof materials using aerial photographs. Main advantages of the algorithm are proposed methods to improve prediction accuracy. Proposed methods includes: method of converting ImageNet weights of neural networks for using multi-channel images; special set of featur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	173,921
2104.10213	Machine Learning Meets Natural Language Processing -- The story so far	Natural Language Processing (NLP) has evolved significantly over the last decade. This paper highlights the most important milestones of this period while trying to pinpoint the contribution of each individual model and algorithm to the overall progress. Furthermore, it focuses on issues still remaining to be solved, e...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	231,496
2410.02224	Efficient Semantic Segmentation via Lightweight Multiple-Information Interaction Network	Recently, the integration of the local modeling capabilities of Convolutional Neural Networks (CNNs) with the global dependency strengths of Transformers has created a sensation in the semantic segmentation community. However, substantial computational workloads and high hardware memory demands remain major obstacles t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	494,178
2308.01868	Multi-variable Hard Physical Constraints for Climate Model Downscaling	Global Climate Models (GCMs) are the primary tool to simulate climate evolution and assess the impacts of climate change. However, they often operate at a coarse spatial resolution that limits their accuracy in reproducing local-scale phenomena. Statistical downscaling methods leveraging deep learning offer a solution ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	383,395
1910.03787	Supervised feature selection with orthogonal regression and feature weighting	Effective features can improve the performance of a model, which can thus help us understand the characteristics and underlying structure of complex data. Previous feature selection methods usually cannot keep more local structure information. To address the defects previously mentioned, we propose a novel supervised o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,586
2407.09237	Cool URIs for FAIR Knowledge Graphs	This guide is for everyone who seeks advice for creating stable, secure, and persistent Uniform Resource Identifiers (URIs) in order to publish their data in accordance to the FAIR principles. The use case does not matter. It could range from publishing the results of a small research project to a large knowledge graph...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	472,501
1009.0499	A PAC-Bayesian Analysis of Graph Clustering and Pairwise Clustering	We formulate weighted graph clustering as a prediction problem: given a subset of edge weights we analyze the ability of graph clustering to predict the remaining edge weights. This formulation enables practical and theoretical comparison of different approaches to graph clustering as well as comparison of graph cluste...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	7,461
2208.06474	Review of research on fireworks algorithm	Fireworks algorithm is a new type of intelligent optimization algorithm. Because of its fast convergence speed, easy implementation, explosiveness, diversity, simplicity and randomness, it has attracted more and more attention in many research fields recently. This paper introduces the background, composition, improvem...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	312,727
2105.10590	Parallelizing Contextual Bandits	Standard approaches to decision-making under uncertainty focus on sequential exploration of the space of decisions. However, \textit{simultaneously} proposing a batch of decisions, which leverages available resources for parallel experimentation, has the potential to rapidly accelerate exploration. We present a family ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,440
2011.14960	BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning	We introduce a binary latent space autoencoder architecture to rehearse training samples for the continual learning of neural networks. The ability to extend the knowledge of a model with new data without forgetting previously learned samples is a fundamental requirement in continual learning. Existing solutions addres...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	208,944
2002.01925	Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review	With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early detection and prediction of disease to timely provide preventive interventions. Thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	162,777
2102.10084	Hate-Alert@DravidianLangTech-EACL2021: Ensembling strategies for Transformer-based Offensive language Detection	Social media often acts as breeding grounds for different forms of offensive content. For low resource languages like Tamil, the situation is more complex due to the poor performance of multilingual or language-specific models and lack of proper benchmark datasets. Based on this shared task, Offensive Language Identifi...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	220,972
2501.13125	Generating Plausible Distractors for Multiple-Choice Questions via Student Choice Prediction	In designing multiple-choice questions (MCQs) in education, creating plausible distractors is crucial for identifying students' misconceptions and gaps in knowledge and accurately assessing their understanding. However, prior studies on distractor generation have not paid sufficient attention to enhancing the difficult...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	526,570
2411.14917	Task-Aware Robotic Grasping by evaluating Quality Diversity Solutions through Foundation Models	Task-aware robotic grasping is a challenging problem that requires the integration of semantic understanding and geometric reasoning. Traditional grasp planning approaches focus on stable or feasible grasps, often disregarding the specific tasks the robot needs to accomplish. This paper proposes a novel framework that ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	510,370
1804.02729	Distributed Non-Convex First-Order Optimization and Information Processing: Lower Complexity Bounds and Rate Optimal Algorithms	We consider a class of popular distributed non-convex optimization problems, in which agents connected by a network $\mathcal{G}$ collectively optimize a sum of smooth (possibly non-convex) local objective functions. We address the following question: if the agents can only access the gradients of local functions, what...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	94,475
2108.03751	Incompatibility between 't Hooft's and Wolfram's models of quantum mechanics	Stephen Wolfram and Gerard 't Hooft developed classical models of quantum mechanics. We show that the descriptive complexity grows differently as a function of time in each model. Therefore, they cannot describe the same physical system. In addition, we propose an interpretation of the Wolfram model, which shares some ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	249,768
2010.13233	Now You See Me (CME): Concept-based Model Extraction	Deep Neural Networks (DNNs) have achieved remarkable performance on a range of tasks. A key step to further empowering DNN-based approaches is improving their explainability. In this work we present CME: a concept-based model extraction framework, used for analysing DNN models via concept-based extracted models. Using ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	203,047
2103.07502	Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics Models	There has been a surge in the interest of using machine learning techniques to assist in the scientific process of formulating knowledge to explain observational data. We demonstrate the use of Bayesian Hidden Physics Models to first uncover the physics governing the propagation of acoustic impulses in metallic specime...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	224,605
1907.00635	Dermtrainer: A Decision Support System for Dermatological Diseases	Dermtrainer is a medical decision support system that assists general practitioners in diagnosing skin diseases and serves as a training platform for dermatologists. Its key components are a comprehensive dermatological knowledge base, a clinical algorithm for diagnosing skin diseases, a reasoning component for deducin...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	137,103
2001.08979	Forecasting NIFTY 50 benchmark Index using Seasonal ARIMA time series models	This paper analyses how Time Series Analysis techniques can be applied to capture movement of an exchange traded index in a stock market. Specifically, Seasonal Auto Regressive Integrated Moving Average (SARIMA) class of models is applied to capture the movement of Nifty 50 index which is one of the most actively excha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	161,445
2407.04352	UpStory: the Uppsala Storytelling dataset	Friendship and rapport play an important role in the formation of constructive social interactions, and have been widely studied in educational settings due to their impact on student outcomes. Given the growing interest in automating the analysis of such phenomena through Machine Learning (ML), access to annotated int...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	470,529
1610.02237	Weakly supervised learning of actions from transcripts	We present an approach for weakly supervised learning of human actions from video transcriptions. Our system is based on the idea that, given a sequence of input data and a transcript, i.e. a list of the order the actions occur in the video, it is possible to infer the actions within the video stream, and thus, learn t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	62,068
2312.02202	Volumetric Rendering with Baked Quadrature Fields	We propose a novel Neural Radiance Field (NeRF) representation for non-opaque scenes that enables fast inference by utilizing textured polygons. Despite the high-quality novel view rendering that NeRF provides, a critical limitation is that it relies on volume rendering that can be computationally expensive and does no...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	412,755
1808.08718	Wide Activation for Efficient and Accurate Image Super-Resolution	In this report we demonstrate that with same parameters and computational budgets, models with wider features before ReLU activation have significantly better performance for single image super-resolution (SISR). The resulted SR residual network has a slim identity mapping pathway with wider ($2\times$ to $4\times$...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	106,022
1808.07991	Predicting Extubation Readiness in Extreme Preterm Infants based on Patterns of Breathing	Extremely preterm infants commonly require intubation and invasive mechanical ventilation after birth. While the duration of mechanical ventilation should be minimized in order to avoid complications, extubation failure is associated with increases in morbidities and mortality. As part of a prospective observational st...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	105,848
1611.06478	Visualizing Linguistic Shift	Neural network based models are a very powerful tool for creating word embeddings, the objective of these models is to group similar words together. These embeddings have been used as features to improve results in various applications such as document classification, named entity recognition, etc. Neural language mode...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	64,200
2407.06095	Accelerating Diffusion for SAR-to-Optical Image Translation via Adversarial Consistency Distillation	Synthetic Aperture Radar (SAR) provides all-weather, high-resolution imaging capabilities, but its unique imaging mechanism often requires expert interpretation, limiting its widespread applicability. Translating SAR images into more easily recognizable optical images using diffusion models helps address this challenge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	471,249
2412.21200	Distributed Mixture-of-Agents for Edge Inference with Large Language Models	Mixture-of-Agents (MoA) has recently been proposed as a method to enhance performance of large language models (LLMs), enabling multiple individual LLMs to work together for collaborative inference. This collaborative approach results in improved responses to user prompts compared to relying on a single LLM. In this pa...	false	false	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	true	521,481
2109.08604	Enforcing fairness in private federated learning via the modified method of differential multipliers	Federated learning with differential privacy, or private federated learning, provides a strategy to train machine learning models while respecting users' privacy. However, differential privacy can disproportionately degrade the performance of the models on under-represented groups, as these parts of the distribution ar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	255,948
2402.05367	Principled Preferential Bayesian Optimization	We study the problem of preferential Bayesian optimization (BO), where we aim to optimize a black-box function with only preference feedback over a pair of candidate solutions. Inspired by the likelihood ratio idea, we construct a confidence set of the black-box function using only the preference feedback. An optimisti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	427,826
2404.04927	Holographic Integrated Data and Energy Transfer	Thanks to the application of metamaterials, holographic multiple-input multiple-output (H-MIMO) is expected to achieve a higher spatial diversity gain by enabling the ability to generate any current distribution on the surface. With the aid of electromagnetic (EM) manipulation capability of H-MIMO, integrated data and ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	444,865
2402.10175	Unlocking Structure Measuring: Introducing PDD, an Automatic Metric for Positional Discourse Coherence	Recent large language models (LLMs) have shown remarkable performance in aligning generated text with user intentions across various tasks. When it comes to long-form text generation, there has been a growing interest in generation from a discourse coherence perspective. However, existing lexical or semantic metrics su...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	429,852
2410.07295	IterGen: Iterative Structured LLM Generation	Large Language Models (LLMs) are widely used for tasks such as natural language and code generation. Still, their outputs often suffer from issues like privacy violations, and semantically inaccurate code generation. Current libraries for LLM generation rely on left-to-right decoding without systematic support for back...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	496,574
2211.16238	A Cross-Conformal Predictor for Multi-label Classification	Unlike the typical classification setting where each instance is associated with a single class, in multi-label learning each instance is associated with multiple classes simultaneously. Therefore the learning task in this setting is to predict the subset of classes to which each instance belongs. This work examines th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	333,569
2210.06894	Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation	Despite the potential of federated learning, it is known to be vulnerable to backdoor attacks. Many robust federated aggregation methods are proposed to reduce the potential backdoor risk. However, they are mainly validated in the CV field. In this paper, we find that NLP backdoors are hard to defend against than CV, a...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	323,494
2311.08107	SAIE Framework: Support Alone Isn't Enough -- Advancing LLM Training with Adversarial Remarks	Large Language Models (LLMs) can justify or critique their predictions through discussions with other models or humans, thereby enriching their intrinsic understanding of instances. While proactive discussions in the inference phase have been shown to boost performance, such interactions have not been extensively explo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	407,592
1910.09335	Redistribution Mechanism on Networks	Redistribution mechanisms have been proposed for more efficient resource allocation but not for profit. We consider redistribution mechanism design in a setting where participants are connected and the resource owner is only connected to some of them. In this setting, to make the resource allocation more efficient, the...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	150,158
1911.12402	Dynamical fitness models: evidence of universality classes for preferential attachment graphs	In this paper we define a family of preferential attachment models for random graphs with fitness in the following way: independently for each node, at each time step a random fitness is drawn according to the position of a moving average process with positive increments. We will define two regimes in which our graph r...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	155,378
2403.09092	MCFEND: A Multi-source Benchmark Dataset for Chinese Fake News Detection	The prevalence of fake news across various online sources has had a significant influence on the public. Existing Chinese fake news detection datasets are limited to news sourced solely from Weibo. However, fake news originating from multiple sources exhibits diversity in various aspects, including its content and soci...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	437,625
1806.00137	PID2018 Benchmark Challenge: Model-based Feedforward Compensator with A Conditional Integrator	Since proportional-integral-derivative (PID) controllers absolutely dominate the control engineering, numbers of different control structures and theories have been developed to enhance the efficiency of PID controllers. Thus, it is essential and inspiring to operate different PID control strategies to the PID2018 Benc...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	99,239
1106.0243	On Reasonable and Forced Goal Orderings and their Use in an Agenda-Driven Planning Algorithm	The paper addresses the problem of computing goal orderings, which is one of the longstanding issues in AI planning. It makes two new contributions. First, it formally defines and discusses two different goal orderings, which are called the reasonable and the forced ordering. Both orderings are defined for simple STRIP...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,651
2203.12104	Fast on-line signature recognition based on VQ with time modeling	This paper proposes a multi-section vector quantization approach for on-line signature recognition. We have used the MCYT database, which consists of 330 users and 25 skilled forgeries per person performed by 5 different impostors. This database is larger than those typically used in the literature. Nevertheless, we al...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	287,139
2111.05819	Look Before You Leap: Safe Model-Based Reinforcement Learning with Human Intervention	Safety has become one of the main challenges of applying deep reinforcement learning to real world systems. Currently, the incorporation of external knowledge such as human oversight is the only means to prevent the agent from visiting the catastrophic state. In this paper, we propose MBHI, a novel framework for safe m...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	265,888
2101.00153	Graphmax for Text Generation	In text generation, a large language model (LM) makes a choice of each new word based only on the former selection of its context using the softmax function. Nevertheless, the link statistics information of concurrent words based on a scene-specific corpus is valuable in choosing the next word, which can help to ensure...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,981
1412.2457	Weighted Polynomial Approximations: Limits for Learning and Pseudorandomness	Polynomial approximations to boolean functions have led to many positive results in computer science. In particular, polynomial approximations to the sign function underly algorithms for agnostically learning halfspaces, as well as pseudorandom generators for halfspaces. In this work, we investigate the limits of these...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	38,211
2403.14183	OTSeg: Multi-prompt Sinkhorn Attention for Zero-Shot Semantic Segmentation	The recent success of CLIP has demonstrated promising results in zero-shot semantic segmentation by transferring muiltimodal knowledge to pixel-level classification. However, leveraging pre-trained CLIP knowledge to closely align text embeddings with pixel embeddings still has limitations in existing approaches. To add...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	439,953
2203.07682	Enriched CNN-Transformer Feature Aggregation Networks for Super-Resolution	Recent transformer-based super-resolution (SR) methods have achieved promising results against conventional CNN-based methods. However, these approaches suffer from essential shortsightedness created by only utilizing the standard self-attention-based reasoning. In this paper, we introduce an effective hybrid SR networ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,521
1701.08107	Deconvolution and Restoration of Optical Endomicroscopy Images	Optical endomicroscopy (OEM) is an emerging technology platform with preclinical and clinical imaging applications. Pulmonary OEM via fibre bundles has the potential to provide in vivo, in situ molecular signatures of disease such as infection and inflammation. However, enhancing the quality of data acquired by this te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,411
1911.05449	Crowd Video Captioning	Describing a video automatically with natural language is a challenging task in the area of computer vision. In most cases, the on-site situation of great events is reported in news, but the situation of the off-site spectators in the entrance and exit is neglected which also arouses people's interest. Since the deploy...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,262
1906.04762	Deep 2FBSDEs For Systems With Control Multiplicative Noise	We present a deep recurrent neural network architecture to solve a class of stochastic optimal control problems described by fully nonlinear Hamilton Jacobi Bellmanpartial differential equations. Such PDEs arise when one considers stochastic dynamics characterized by uncertainties that are additive and control multipli...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	134,832
2003.02260	Spatiotemporal-Aware Augmented Reality: Redefining HCI in Image-Guided Therapy	Suboptimal interaction with patient data and challenges in mastering 3D anatomy based on ill-posed 2D interventional images are essential concerns in image-guided therapies. Augmented reality (AR) has been introduced in the operating rooms in the last decade; however, in image-guided interventions, it has often only be...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	166,892
2006.13591	Randomized Block-Diagonal Preconditioning for Parallel Learning	We study preconditioned gradient-based optimization methods where the preconditioning matrix has block-diagonal form. Such a structural constraint comes with the advantage that the update computation is block-separable and can be parallelized across multiple independent tasks. Our main contribution is to demonstrate th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	183,965
2407.09006	Perturbation-based Sequence Selection for Probabilistic Amplitude Shaping	We introduce a practical sign-dependent sequence selection metric for probabilistic amplitude shaping and propose a simple method to predict the gains in signal-to-noise ratio (SNR) for sequence selection. The proposed metric provides a $0.5$ dB SNR gain for single-polarized 256-QAM transmission over a long-haul fiber ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	472,406
2306.15244	Cutting-Edge Techniques for Depth Map Super-Resolution	To overcome hardware limitations in commercially available depth sensors which result in low-resolution depth maps, depth map super-resolution (DMSR) is a practical and valuable computer vision task. DMSR requires upscaling a low-resolution (LR) depth map into a high-resolution (HR) space. Joint image filtering for DMS...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	375,960
2402.11839	An enhanced Teaching-Learning-Based Optimization (TLBO) with Grey Wolf Optimizer (GWO) for text feature selection and clustering	Text document clustering can play a vital role in organizing and handling the everincreasing number of text documents. Uninformative and redundant features included in large text documents reduce the effectiveness of the clustering algorithm. Feature selection (FS) is a well-known technique for removing these features....	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	430,599
2109.12516	Prioritized Experience-based Reinforcement Learning with Human Guidance for Autonomous Driving	Reinforcement learning (RL) requires skillful definition and remarkable computational efforts to solve optimization and control problems, which could impair its prospect. Introducing human guidance into reinforcement learning is a promising way to improve learning performance. In this paper, a comprehensive human guida...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	257,324
2312.09244	Helping or Herding? Reward Model Ensembles Mitigate but do not Eliminate Reward Hacking	Reward models play a key role in aligning language model applications towards human preferences. However, this setup creates an incentive for the language model to exploit errors in the reward model to achieve high estimated reward, a phenomenon often termed \emph{reward hacking}. A natural mitigation is to train an en...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,648
2010.04914	Helpfulness as a Key Metric of Human-Robot Collaboration	As robotic teammates become more common in society, people will assess the robots' roles in their interactions along many dimensions. One such dimension is effectiveness: people will ask whether their robotic partners are trustworthy and effective collaborators. This begs a crucial question: how can we quantitatively m...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	199,919
cs/9811010	Learning to Resolve Natural Language Ambiguities: A Unified Approach	We analyze a few of the commonly used statistics based and machine learning algorithms for natural language disambiguation tasks and observe that they can be re-cast as learning linear separators in the feature space. Each of the methods makes a priori assumptions, which it employs, given the data, when searching for i...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	540,434
2410.16024	A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models	StarCraft Multi-Agent Challenge (SMAC) is one of the most commonly used experimental environments in multi-agent reinforcement learning (MARL), where the specific task is to control a set number of allied units to defeat enemy forces. Traditional MARL algorithms often require interacting with the environment for up to ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	500,844
2008.05122	The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models	We present the Language Interpretability Tool (LIT), an open-source platform for visualization and understanding of NLP models. We focus on core questions about model behavior: Why did my model make this prediction? When does it perform poorly? What happens under a controlled change in the input? LIT integrates local e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	191,420
2502.07230	Physics-Informed Recurrent Network for Gas Pipeline Network Parameters Identification	As a part of the integrated energy system (IES), gas pipeline networks can provide additional flexibility to power systems through coordinated optimal dispatch. An accurate pipeline network model is critical for the optimal operation and control of IESs. However, inaccuracies or unavailability of accurate pipeline para...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	532,498
2008.08818	Ensemble learning reveals dissimilarity between rare-earth transition metal binary alloys with respect to the Curie temperature	We propose a data-driven method to extract dissimilarity between materials, with respect to a given target physical property. The technique is based on an ensemble method with Kernel ridge regression as the predicting model; multiple random subset sampling of the materials is done to generate prediction models and the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	192,512
2208.13017	A Multi-Format Transfer Learning Model for Event Argument Extraction via Variational Information Bottleneck	Event argument extraction (EAE) aims to extract arguments with given roles from texts, which have been widely studied in natural language processing. Most previous works have achieved good performance in specific EAE datasets with dedicated neural architectures. Whereas, these architectures are usually difficult to ada...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	314,925
2407.12315	ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion Map	Multi-modal embeddings form the foundation for vision-language models, such as CLIP embeddings, the most widely used text-image embeddings. However, these embeddings are vulnerable to subtle misalignment of cross-modal features, resulting in decreased model performance and diminished generalization. To address this pro...	true	false	false	false	true	true	false	false	false	false	false	true	false	false	false	false	false	false	473,866
2208.02474	CFARnet: deep learning for target detection with constant false alarm rate	We consider the problem of target detection with a constant false alarm rate (CFAR). This constraint is crucial in many practical applications and is a standard requirement in classical composite hypothesis testing. In settings where classical approaches are computationally expensive or where only data samples are give...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	311,478
2306.17561	Weighted Sum Rate Enhancement by Using Dual-Side IOS-Assisted Full-Duplex for Multi-User MIMO Systems	This paper established a novel multi-input multi-output (MIMO) communication network, in the presence of full-duplex (FD) transmitters and receivers with the assistance of dual-side intelligent omni surface. Compared with the traditional IOS, the dual-side IOS allows signals from both sides to reflect and refract simul...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	376,742
1408.6515	Large Scale Purchase Prediction with Historical User Actions on B2C Online Retail Platform	This paper describes the solution of Bazinga Team for Tmall Recommendation Prize 2014. With real-world user action data provided by Tmall, one of the largest B2C online retail platforms in China, this competition requires to predict future user purchases on Tmall website. Predictions are judged on F1Score, which consid...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	35,634
2405.03946	Association between centrality and flourishing trait: analyzing student co-occurrence networks drawn from dining activities	Comprehending the association between social capabilities and individual psychological traits is paramount for educational administrators. Presently, many studies heavily depend on online questionnaires and self-reported data, while analysis of the connection between offline social networks and mental health status rem...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	452,372
2205.04833	Envelopes and Waves: Safe Multivehicle Collision Avoidance for Horizontal Non-deterministic Turns	We present an approach to analyzing the safety of asynchronous, independent, non-deterministic, turn-to-bearing horizontal maneuvers for two vehicles. Future turn rates, final bearings, and continuously varying ground speeds throughout the encounter are unknown but restricted to known ranges. We develop a library of fo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	295,767
2309.09725	Neural Collapse for Unconstrained Feature Model under Cross-entropy Loss with Imbalanced Data	Recent years have witnessed the huge success of deep neural networks (DNNs) in various tasks of computer vision and text processing. Interestingly, these DNNs with massive number of parameters share similar structural properties on their feature representation and last-layer classifier at terminal phase of training (TP...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	392,720
2501.18954	LLMDet: Learning Strong Open-Vocabulary Object Detectors under the Supervision of Large Language Models	Recent open-vocabulary detectors achieve promising performance with abundant region-level annotated data. In this work, we show that an open-vocabulary detector co-training with a large language model by generating image-level detailed captions for each image can further improve performance. To achieve the goal, we fir...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	528,936
1906.10861	Assessing Post Deletion in Sina Weibo: Multi-modal Classification of Hot Topics	Widespread Chinese social media applications such as Weibo are widely known for monitoring and deleting posts to conform to Chinese government requirements. In this paper, we focus on analyzing a dataset of censored and uncensored posts in Weibo. Despite previous work that only considers text content of posts, we take ...	false	false	false	true	false	false	true	false	false	false	false	false	true	false	false	false	false	false	136,535
2006.07981	Geodesic-HOF: 3D Reconstruction Without Cutting Corners	Single-view 3D object reconstruction is a challenging fundamental problem in computer vision, largely due to the morphological diversity of objects in the natural world. In particular, high curvature regions are not always captured effectively by methods trained using only set-based loss functions, resulting in reconst...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	182,024
2409.02580	AlignGroup: Learning and Aligning Group Consensus with Member Preferences for Group Recommendation	Group activities are important behaviors in human society, providing personalized recommendations for groups is referred to as the group recommendation task. Existing methods can usually be categorized into two strategies to infer group preferences: 1) determining group preferences by aggregating members' personalized ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	485,757
1906.10948	Latent Multi-Criteria Ratings for Recommendations	Multi-criteria recommender systems have been increasingly valuable for helping consumers identify the most relevant items based on different dimensions of user experiences. However, previously proposed multi-criteria models did not take into account latent embeddings generated from user reviews, which capture latent se...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	136,554
2204.12456	Event Detection Explorer: An Interactive Tool for Event Detection Exploration	Event Detection (ED) is an important task in natural language processing. In the past few years, many datasets have been introduced for advancing ED machine learning models. However, most of these datasets are under-explored because not many tools are available for people to study events, trigger words, and event menti...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	293,481
1206.6863	Bayesian Multicategory Support Vector Machines	We show that the multi-class support vector machine (MSVM) proposed by Lee et. al. (2004), can be viewed as a MAP estimation procedure under an appropriate probabilistic interpretation of the classifier. We also show that this interpretation can be extended to a hierarchical Bayesian architecture and to a fully-Bayesia...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	17,087
1812.06619	PaToPaEM: A Data-Driven Parameter and Topology Joint Estimation Framework for Time Varying System in Distribution Grids	Grid topology and line parameters are essential for grid operation and planning, which may be missing or inaccurate in distribution grids. Existing data-driven approaches for recovering such information usually suffer from ignoring 1) input measurement errors and 2) possible state changes among historical measurements....	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	116,656
2111.06056	Learning by Cheating : An End-to-End Zero Shot Framework for Autonomous Drone Navigation	This paper proposes a novel framework for autonomous drone navigation through a cluttered environment. Control policies are learnt in a low-level environment during training and are applied to a complex environment during inference. The controller learnt in the training environment is tricked into believing that the ro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	265,972
2311.13957	Efficient Trigger Word Insertion	With the boom in the natural language processing (NLP) field these years, backdoor attacks pose immense threats against deep neural network models. However, previous works hardly consider the effect of the poisoning rate. In this paper, our main objective is to reduce the number of poisoned samples while still achievin...	false	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	409,940
2410.07155	Trans4D: Realistic Geometry-Aware Transition for Compositional Text-to-4D Synthesis	Recent advances in diffusion models have demonstrated exceptional capabilities in image and video generation, further improving the effectiveness of 4D synthesis. Existing 4D generation methods can generate high-quality 4D objects or scenes based on user-friendly conditions, benefiting the gaming and video industries. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	496,507
2402.11901	Real-World Planning with PDDL+ and Beyond	Real-world applications of AI Planning often require a highly expressive modeling language to accurately capture important intricacies of target systems. Hybrid systems are ubiquitous in the real-world, and PDDL+ is the standardized modeling language for capturing such systems as planning domains. PDDL+ enables accurat...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	430,634
2202.04835	A robophysical model of spacetime dynamics	Systems consisting of spheres rolling on elastic membranes have been used to introduce a core conceptual idea of General Relativity (GR): how curvature guides the movement of matter. However, such schemes cannot accurately represent relativistic dynamics in the laboratory because of the dominance of dissipation and ext...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	279,687
2210.00040	Utility of the Koopman operator in output regulation of disturbed nonlinear systems	This paper studies the problem of output regulation for a class of nonlinear systems experiencing matched input disturbances. It is assumed that the disturbance signal is generated by an external autonomous dynamical system. First, we show that for a class of nonlinear systems admitting a finite-dimensional Koopman rep...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	320,701
2311.16500	LLMGA: Multimodal Large Language Model based Generation Assistant	In this paper, we introduce a Multimodal Large Language Model-based Generation Assistant (LLMGA), leveraging the vast reservoir of knowledge and proficiency in reasoning, comprehension, and response inherent in Large Language Models (LLMs) to assist users in image generation and editing. Diverging from existing approac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,925
2010.11750	Precise High-Dimensional Asymptotics for Quantifying Heterogeneous Transfers	The problem of learning one task with samples from another task has received much interest recently. In this paper, we ask a fundamental question: when is combining data from two tasks better than learning one task alone? Intuitively, the transfer effect from one task to another task depends on dataset shifts such as s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	202,416
1705.07609	View-Invariant Recognition of Action Style Self-Dissimilarity	Self-similarity was recently introduced as a measure of inter-class congruence for classification of actions. Herein, we investigate the dual problem of intra-class dissimilarity for classification of action styles. We introduce self-dissimilarity matrices that discriminate between same actions performed by different s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,869
2103.14107	Stepwise Goal-Driven Networks for Trajectory Prediction	We propose to predict the future trajectories of observed agents (e.g., pedestrians or vehicles) by estimating and using their goals at multiple time scales. We argue that the goal of a moving agent may change over time, and modeling goals continuously provides more accurate and detailed information for future trajecto...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	226,727
2406.04170	Element-wise Multiplication Based Deeper Physics-Informed Neural Networks	As a promising framework for resolving partial differential equations (PDEs), Physics-Informed Neural Networks (PINNs) have received widespread attention from industrial and scientific fields. However, lack of expressive ability and initialization pathology issues are found to prevent the application of PINNs in comple...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	461,552
2206.12829	On Comparison of Encoders for Attention based End to End Speech Recognition in Standalone and Rescoring Mode	The streaming automatic speech recognition (ASR) models are more popular and suitable for voice-based applications. However, non-streaming models provide better performance as they look at the entire audio context. To leverage the benefits of the non-streaming model in streaming applications like voice search, it is co...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	304,748

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