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
2311.11342	On the Communication Complexity of Decentralized Bilevel Optimization	Stochastic bilevel optimization finds widespread applications in machine learning, including meta-learning, hyperparameter optimization, and neural architecture search. To extend stochastic bilevel optimization to distributed data, several decentralized stochastic bilevel optimization algorithms have been developed. Ho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	408,914
2311.10492	A Relay System for Semantic Image Transmission based on Shared Feature Extraction and Hyperprior Entropy Compression	Nowadays, the need for high-quality image reconstruction and restoration is more and more urgent. However, most image transmission systems may suffer from image quality degradation or transmission interruption in the face of interference such as channel noise and link fading. To solve this problem, a relay communicatio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,545
2105.02033	Polynomial Graph Parsing with Non-Structural Reentrancies	Graph-based semantic representations are valuable in natural language processing, where it is often simple and effective to represent linguistic concepts as nodes, and relations as edges between them. Several attempts has been made to find a generative device that is sufficiently powerful to represent languages of sema...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	233,708
2302.12186	RSFDM-Net: Real-time Spatial and Frequency Domains Modulation Network for Underwater Image Enhancement	Underwater images typically experience mixed degradations of brightness and structure caused by the absorption and scattering of light by suspended particles. To address this issue, we propose a Real-time Spatial and Frequency Domains Modulation Network (RSFDM-Net) for the efficient enhancement of colors and details in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	347,466
2001.00709	Stability Analysis of Continuous-Time Linear Time-Invariant Systems	This paper focuses on the mathematical approaches to the analysis of stability that is a crucial step in the design of dynamical systems. Three methods are presented, namely, absolutely integrable impulse response, Fourier integral, and Laplace transform. The superiority of Laplace transform over the other methods beco...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	159,306
1507.08373	When VLAD met Hilbert	Vectors of Locally Aggregated Descriptors (VLAD) have emerged as powerful image/video representations that compete with or even outperform state-of-the-art approaches on many challenging visual recognition tasks. In this paper, we address two fundamental limitations of VLAD: its requirement for the local descriptors to...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,562
2106.03442	Average-Reward Reinforcement Learning with Trust Region Methods	Most of reinforcement learning algorithms optimize the discounted criterion which is beneficial to accelerate the convergence and reduce the variance of estimates. Although the discounted criterion is appropriate for certain tasks such as financial related problems, many engineering problems treat future rewards equall...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	239,321
2306.01111	Exploring the Versatility of Zero-Shot CLIP for Interstitial Lung Disease Classification	Interstitial lung diseases (ILD) present diagnostic challenges due to their varied manifestations and overlapping imaging features. To address this, we propose a machine learning approach that utilizes CLIP, a multimodal (image and text) self-supervised model, for ILD classification. We extensively integrate zero-shot ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	370,297
2210.04265	3D Reconstruction of Sculptures from Single Images via Unsupervised Domain Adaptation on Implicit Models	Acquiring the virtual equivalent of exhibits, such as sculptures, in virtual reality (VR) museums, can be labour-intensive and sometimes infeasible. Deep learning based 3D reconstruction approaches allow us to recover 3D shapes from 2D observations, among which single-view-based approaches can reduce the need for human...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	322,389
1706.01727	Clustering Spectrum of scale-free networks	Real-world networks often have power-law degrees and scale-free properties such as ultra-small distances and ultra-fast information spreading. In this paper, we study a third universal property: three-point correlations that suppress the creation of triangles and signal the presence of hierarchy. We quantify this prope...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	74,852
2107.01892	NOTE: Solution for KDD-CUP 2021 WikiKG90M-LSC	WikiKG90M in KDD Cup 2021 is a large encyclopedic knowledge graph, which could benefit various downstream applications such as question answering and recommender systems. Participants are invited to complete the knowledge graph by predicting missing triplets. Recent representation learning methods have achieved great s...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	244,636
2303.13013	GesGPT: Speech Gesture Synthesis With Text Parsing from ChatGPT	Gesture synthesis has gained significant attention as a critical research field, aiming to produce contextually appropriate and natural gestures corresponding to speech or textual input. Although deep learning-based approaches have achieved remarkable progress, they often overlook the rich semantic information present ...	true	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	353,504
1801.10502	Learning from Informants: Relations between Learning Success Criteria	Learning from positive and negative information, so-called \emph{informants}, being one of the models for human and machine learning introduced by E.~M.~Gold, is investigated. Particularly, naturally arising questions about this learning setting, originating in results on learning from solely positive information, are ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	89,307
2211.15441	Graceful Forgetting II. Data as a Process	Data are rapidly growing in size and importance for society, a trend motivated by their enabling power. The accumulation of new data, sustained by progress in technology, leads to a boundless expansion of stored data, in some cases with an exponential increase in the accrual rate itself. Massive data are hard to proces...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	true	false	333,268
2405.00228	Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion	Face Recognition (FR) models are trained on large-scale datasets, which have privacy and ethical concerns. Lately, the use of synthetic data to complement or replace genuine data for the training of FR models has been proposed. While promising results have been obtained, it still remains unclear if generative models ca...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	450,836
2405.03092	Bayesian optimization for stable properties amid processing fluctuations in sputter deposition	We introduce a Bayesian optimization approach to guide the sputter deposition of molybdenum thin films, aiming to achieve desired residual stress and sheet resistance while minimizing susceptibility to stochastic fluctuations during deposition. Thin films are pivotal in numerous technologies, including semiconductors a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	452,044
2311.05945	Intersection-free Robot Manipulation with Soft-Rigid Coupled Incremental Potential Contact	This paper presents a novel simulation platform, ZeMa, designed for robotic manipulation tasks concerning soft objects. Such simulation ideally requires three properties: two-way soft-rigid coupling, intersection-free guarantees, and frictional contact modeling, with acceptable runtime suitable for deep and reinforceme...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	406,770
1808.05443	Transfer Learning and Organic Computing for Autonomous Vehicles	Autonomous Vehicles(AV) are one of the brightest promises of the future which would help cut down fatalities and improve travel time while working in harmony. Autonomous vehicles will face with challenging situations and experiences not seen before. These experiences should be converted to knowledge and help the vehicl...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	105,351
2112.01653	Learning Curves for Continual Learning in Neural Networks: Self-Knowledge Transfer and Forgetting	Sequential training from task to task is becoming one of the major objects in deep learning applications such as continual learning and transfer learning. Nevertheless, it remains unclear under what conditions the trained model's performance improves or deteriorates. To deepen our understanding of sequential training, ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	269,565
1210.4876	Active Imitation Learning via Reduction to I.I.D. Active Learning	In standard passive imitation learning, the goal is to learn a target policy by passively observing full execution trajectories of it. Unfortunately, generating such trajectories can require substantial expert effort and be impractical in some cases. In this paper, we consider active imitation learning with the goal of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	19,201
2211.10475	Turning Silver into Gold: Domain Adaptation with Noisy Labels for Wearable Cardio-Respiratory Fitness Prediction	Deep learning models have shown great promise in various healthcare applications. However, most models are developed and validated on small-scale datasets, as collecting high-quality (gold-standard) labels for health applications is often costly and time-consuming. As a result, these models may suffer from overfitting ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,322
1211.2651	Correlation dimension of complex networks	We propose a new measure to characterize the dimension of complex networks based on the ergodic theory of dynamical systems. This measure is derived from the correlation sum of a trajectory generated by a random walker navigating the network, and extends the classical Grassberger-Procaccia algorithm to the context of c...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	19,691
1604.00061	Distribution Market Clearing and Settlement	There are various undergoing efforts by system operators to set up an electricity market at the distribution level to enable a rapid and widespread deployment of distributed energy resources (DERs) and microgrids. This paper follows the previous work of the authors in implementing the distribution market operator (DMO)...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	53,965
1902.04741	Learning to Screen	Imagine a large firm with multiple departments that plans a large recruitment. Candidates arrive one-by-one, and for each candidate the firm decides, based on her data (CV, skills, experience, etc), whether to summon her for an interview. The firm wants to recruit the best candidates while minimizing the number of inte...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	121,411
2301.07999	An Ergonomic Role Allocation Framework for Dynamic Human-Robot Collaborative Tasks	By incorporating ergonomics principles into the task allocation processes, human-robot collaboration (HRC) frameworks can favour the prevention of work-related musculoskeletal disorders (WMSDs). In this context, existing offline methodologies do not account for the variability of human actions and states; therefore, pl...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	341,068
1704.02544	A Linearly Relaxed Approximate Linear Program for Markov Decision Processes	Approximate linear programming (ALP) and its variants have been widely applied to Markov Decision Processes (MDPs) with a large number of states. A serious limitation of ALP is that it has an intractable number of constraints, as a result of which constraint approximations are of interest. In this paper, we define a li...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	71,466
2008.02354	CrowDEA: Multi-view Idea Prioritization with Crowds	Given a set of ideas collected from crowds with regard to an open-ended question, how can we organize and prioritize them in order to determine the preferred ones based on preference comparisons by crowd evaluators? As there are diverse latent criteria for the value of an idea, multiple ideas can be considered as "the ...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	190,588
2307.08706	Efficient Strongly Polynomial Algorithms for Quantile Regression	Linear Regression is a seminal technique in statistics and machine learning, where the objective is to build linear predictive models between a response (i.e., dependent) variable and one or more predictor (i.e., independent) variables. In this paper, we revisit the classical technique of Quantile Regression (QR), whic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	379,915
2105.00131	GistNet: a Geometric Structure Transfer Network for Long-Tailed Recognition	The problem of long-tailed recognition, where the number of examples per class is highly unbalanced, is considered. It is hypothesized that the well known tendency of standard classifier training to overfit to popular classes can be exploited for effective transfer learning. Rather than eliminating this overfitting, e....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,098
2402.16586	Improving the JPEG-resistance of Adversarial Attacks on Face Recognition by Interpolation Smoothing	JPEG compression can significantly impair the performance of adversarial face examples, which previous adversarial attacks on face recognition (FR) have not adequately addressed. Considering this challenge, we propose a novel adversarial attack on FR that aims to improve the resistance of adversarial examples against J...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,614
2207.14447	Dataset and Evaluation algorithm design for GOALS Challenge	Glaucoma causes irreversible vision loss due to damage to the optic nerve, and there is no cure for glaucoma.OCT imaging modality is an essential technique for assessing glaucomatous damage since it aids in quantifying fundus structures. To promote the research of AI technology in the field of OCT-assisted diagnosis of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	310,584
2405.11677	Advancing 6-DoF Instrument Pose Estimation in Variable X-Ray Imaging Geometries	Accurate 6-DoF pose estimation of surgical instruments during minimally invasive surgeries can substantially improve treatment strategies and eventual surgical outcome. Existing deep learning methods have achieved accurate results, but they require custom approaches for each object and laborious setup and training envi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	455,236
2312.03339	PointJEM: Self-supervised Point Cloud Understanding for Reducing Feature Redundancy via Joint Entropy Maximization	Most deep learning-based point cloud processing methods are supervised and require large scale of labeled data. However, manual labeling of point cloud data is laborious and time-consuming. Self-supervised representation learning can address the aforementioned issue by learning robust and generalized representations fr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,218
2006.03541	Sentiment Analysis Based on Deep Learning: A Comparative Study	The study of public opinion can provide us with valuable information. The analysis of sentiment on social networks, such as Twitter or Facebook, has become a powerful means of learning about the users' opinions and has a wide range of applications. However, the efficiency and accuracy of sentiment analysis is being hin...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	180,345
2401.14893	A structured regression approach for evaluating model performance across intersectional subgroups	Disaggregated evaluation is a central task in AI fairness assessment, where the goal is to measure an AI system's performance across different subgroups defined by combinations of demographic or other sensitive attributes. The standard approach is to stratify the evaluation data across subgroups and compute performance...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	424,252
2402.11771	Evaluating the Effectiveness of Index-Based Treatment Allocation	When resources are scarce, an allocation policy is needed to decide who receives a resource. This problem occurs, for instance, when allocating scarce medical resources and is often solved using modern ML methods. This paper introduces methods to evaluate index-based allocation policies -- that allocate a fixed number ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	430,561
2307.01449	A Double Machine Learning Approach to Combining Experimental and Observational Data	Experimental and observational studies often lack validity due to untestable assumptions. We propose a double machine learning approach to combine experimental and observational studies, allowing practitioners to test for assumption violations and estimate treatment effects consistently. Our framework tests for violati...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	377,354
2009.13480	Siamese Capsule Network for End-to-End Speaker Recognition In The Wild	We propose an end-to-end deep model for speaker verification in the wild. Our model uses thin-ResNet for extracting speaker embeddings from utterances and a Siamese capsule network and dynamic routing as the Back-end to calculate a similarity score between the embeddings. We conduct a series of experiments and comparis...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	197,756
2108.02397	Decentralized Federated Learning with Unreliable Communications	Decentralized federated learning, inherited from decentralized learning, enables the edge devices to collaborate on model training in a peer-to-peer manner without the assistance of a server. However, existing decentralized learning frameworks usually assume perfect communication among devices, where they can reliably ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	249,307
2001.00155	DeepBeat: A multi-task deep learning approach to assess signal quality and arrhythmia detection in wearable devices	Wearable devices enable theoretically continuous, longitudinal monitoring of physiological measurements like step count, energy expenditure, and heart rate. Although the classification of abnormal cardiac rhythms such as atrial fibrillation from wearable devices has great potential, commercial algorithms remain proprie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	159,149
1804.04963	CNN-based Landmark Detection in Cardiac CTA Scans	Fast and accurate anatomical landmark detection can benefit many medical image analysis methods. Here, we propose a method to automatically detect anatomical landmarks in medical images. Automatic landmark detection is performed with a patch-based fully convolutional neural network (FCNN) that combines regression and c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	94,971
2406.05615	Video-Language Understanding: A Survey from Model Architecture, Model Training, and Data Perspectives	Humans use multiple senses to comprehend the environment. Vision and language are two of the most vital senses since they allow us to easily communicate our thoughts and perceive the world around us. There has been a lot of interest in creating video-language understanding systems with human-like senses since a video-l...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	462,211
2404.00230	Latent Watermark: Inject and Detect Watermarks in Latent Diffusion Space	Watermarking is a tool for actively identifying and attributing the images generated by latent diffusion models. Existing methods face the dilemma of image quality and watermark robustness. Watermarks with superior image quality usually have inferior robustness against attacks such as blurring and JPEG compression, whi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	442,821
2411.05531	CRC-Assisted Channel Codes for Integrated Passive Sensing and Communications	We propose a novel coded integrated passive sensing and communication (CIPSAC) system with orthogonal frequency division multiplexing (OFDM), where a multi-antenna base station (BS) passively senses the parameters of the targets and decodes the information bit sequences transmitted by a user. The transmitted signal is ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	506,700
2006.09616	Dynamic Tensor Rematerialization	Checkpointing enables the training of deep learning models under restricted memory budgets by freeing intermediate activations from memory and recomputing them on demand. Current checkpointing techniques statically plan these recomputations offline and assume static computation graphs. We demonstrate that a simple onli...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	182,600
2001.10422	NAS-Bench-1Shot1: Benchmarking and Dissecting One-shot Neural Architecture Search	One-shot neural architecture search (NAS) has played a crucial role in making NAS methods computationally feasible in practice. Nevertheless, there is still a lack of understanding on how these weight-sharing algorithms exactly work due to the many factors controlling the dynamics of the process. In order to allow a sc...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	161,825
2411.04510	Sliding Mode Roll Control of Active Suspension Electric Vehicles	Vehicle roll control has been a well studied problem. One of the ubiquitous methods to mitigate vehicle rollover in the automobile industry is via a mechanical anti-roll bar. However with the advent of electric vehicles, rollover mitigation can be pursued using electric actuation. In this work, we study a roll control ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	506,296
1611.00676	Knowledge-infused and Consistent Complex Event Processing over Real-time and Persistent Streams	Emerging applications in Internet of Things (IoT) and Cyber-Physical Systems (CPS) present novel challenges to Big Data platforms for performing online analytics. Ubiquitous sensors from IoT deployments are able to generate data streams at high velocity, that include information from a variety of domains, and accumulat...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	63,266
1909.06349	Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices	In real-world machine learning applications, data subsets correspond to especially critical outcomes: vulnerable cyclist detections are safety-critical in an autonomous driving task, and "question" sentences might be important to a dialogue agent's language understanding for product purposes. While machine learning mod...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	145,352
2207.01580	Dynamic Spatial Sparsification for Efficient Vision Transformers and Convolutional Neural Networks	In this paper, we present a new approach for model acceleration by exploiting spatial sparsity in visual data. We observe that the final prediction in vision Transformers is only based on a subset of the most informative tokens, which is sufficient for accurate image recognition. Based on this observation, we propose a...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	306,230
1906.07409	Active Scene Understanding via Online Semantic Reconstruction	We propose a novel approach to robot-operated active understanding of unknown indoor scenes, based on online RGBD reconstruction with semantic segmentation. In our method, the exploratory robot scanning is both driven by and targeting at the recognition and segmentation of semantic objects from the scene. Our algorithm...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	135,593
1203.3479	Maximum likelihood fitting of acyclic directed mixed graphs to binary data	Acyclic directed mixed graphs, also known as semi-Markov models represent the conditional independence structure induced on an observed margin by a DAG model with latent variables. In this paper we present the first method for fitting these models to binary data using maximum likelihood estimation.	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	14,927
2311.12401	CASR: Refining Action Segmentation via Marginalizing Frame-levle Causal Relationships	Integrating deep learning and causal discovery has increased the interpretability of Temporal Action Segmentation (TAS) tasks. However, frame-level causal relationships exist many complicated noises outside the segment-level, making it infeasible to directly express macro action semantics. Thus, we propose Causal Abstr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	409,320
2411.03923	Evaluation data contamination in LLMs: how do we measure it and (when) does it matter?	Hampering the interpretation of benchmark scores, evaluation data contamination has become a growing concern in the evaluation of LLMs, and an active area of research studies its effects. While evaluation data contamination is easily understood intuitively, it is surprisingly difficult to define precisely which samples...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	506,087
2410.01786	Learning To Solve Differential Equation Constrained Optimization Problems	Differential equations (DE) constrained optimization plays a critical role in numerous scientific and engineering fields, including energy systems, aerospace engineering, ecology, and finance, where optimal configurations or control strategies must be determined for systems governed by ordinary or stochastic differenti...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	493,944
2403.10205	Read between the lines -- Functionality Extraction From READMEs	While text summarization is a well-known NLP task, in this paper, we introduce a novel and useful variant of it called functionality extraction from Git README files. Though this task is a text2text generation at an abstract level, it involves its own peculiarities and challenges making existing text2text generation sy...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	438,100
2004.12806	Discussion of "Design of Controllers with Arbitrary Convergence Time" (Automatica 112 (2020) 108710)	This note corrects some technical inaccuracies in a recently published paper on predefined-time convergence (Automatica 112 (2020) 108710) and discusses implementation issues of the presented control algorithm.	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	174,357
2402.08109	From Data to Decisions: The Transformational Power of Machine Learning in Business Recommendations	This research aims to explore the impact of Machine Learning (ML) on the evolution and efficacy of Recommendation Systems (RS), particularly in the context of their growing significance in commercial business environments. Methodologically, the study delves into the role of ML in crafting and refining these systems, fo...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	428,963
2404.04920	Regularized Conditional Diffusion Model for Multi-Task Preference Alignment	Sequential decision-making is desired to align with human intents and exhibit versatility across various tasks. Previous methods formulate it as a conditional generation process, utilizing return-conditioned diffusion models to directly model trajectory distributions. Nevertheless, the return-conditioned paradigm relie...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	444,861
2502.13900	Optimistically Optimistic Exploration for Provably Efficient Infinite-Horizon Reinforcement and Imitation Learning	We study the problem of reinforcement learning in infinite-horizon discounted linear Markov decision processes (MDPs), and propose the first computationally efficient algorithm achieving near-optimal regret guarantees in this setting. Our main idea is to combine two classic techniques for optimistic exploration: additi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	535,567
2102.09029	Joint Continuous and Discrete Model Selection via Submodularity	In model selection problems for machine learning, the desire for a well-performing model with meaningful structure is typically expressed through a regularized optimization problem. In many scenarios, however, the meaningful structure is specified in some discrete space, leading to difficult nonconvex optimization prob...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	220,649
1302.1035	Leveraging Automorphisms of Quantum Codes for Fault-Tolerant Quantum Computation	Fault-tolerant quantum computation is a technique that is necessary to build a scalable quantum computer from noisy physical building blocks. Key for the implementation of fault-tolerant computations is the ability to perform a universal set of quantum gates that act on the code space of an underlying quantum code. To ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	21,775
2307.02637	Surge Routing: Event-informed Multiagent Reinforcement Learning for Autonomous Rideshare	Large events such as conferences, concerts and sports games, often cause surges in demand for ride services that are not captured in average demand patterns, posing unique challenges for routing algorithms. We propose a learning framework for an autonomous fleet of taxis that leverages event data from the internet to p...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	377,755
1904.05330	Hierarchical Stochastic Block Model for Community Detection in Multiplex Networks	Multiplex networks have become increasingly more prevalent in many fields, and have emerged as a powerful tool for modeling the complexity of real networks. There is a critical need for developing inference models for multiplex networks that can take into account potential dependencies across different layers, particul...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	127,280
2307.02018	Comparative Analysis of GPT-4 and Human Graders in Evaluating Praise Given to Students in Synthetic Dialogues	Research suggests that providing specific and timely feedback to human tutors enhances their performance. However, it presents challenges due to the time-consuming nature of assessing tutor performance by human evaluators. Large language models, such as the AI-chatbot ChatGPT, hold potential for offering constructive f...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	377,553
2305.11541	Empower Large Language Model to Perform Better on Industrial Domain-Specific Question Answering	Large Language Model (LLM) has gained popularity and achieved remarkable results in open-domain tasks, but its performance in real industrial domain-specific scenarios is average due to its lack of specific domain knowledge. This issue has attracted widespread attention, but there are few relevant benchmarks available....	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	365,589
2410.13733	Improving Multi-modal Large Language Model through Boosting Vision Capabilities	We focus on improving the visual understanding capability for boosting the vision-language models. We propose \textbf{Arcana}, a multiModal language model, which introduces two crucial techniques. First, we present Multimodal LoRA (MM-LoRA), a module designed to enhance the decoder. Unlike traditional language-driven d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	499,658
2312.14862	YAYI 2: Multilingual Open-Source Large Language Models	As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artificial general intelligence. To better facilitate research on LLMs, many ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	417,772
1905.01025	Learned Quality Enhancement via Multi-Frame Priors for HEVC Compliant Low-Delay Applications	Networked video applications, e.g., video conferencing, often suffer from poor visual quality due to unexpected network fluctuation and limited bandwidth. In this paper, we have developed a Quality Enhancement Network (QENet) to reduce the video compression artifacts, leveraging the spatial and temporal priors generate...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,622
2305.06047	Piloting topic-aware research impact assessment features in BIP! Services	Various research activities rely on citation-based impact indicators. However these indicators are usually globally computed, hindering their proper interpretation in applications like research assessment and knowledge discovery. In this work, we advocate for the use of topic-aware categorical impact indicators, to all...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	363,385
1805.06511	Improving End-of-turn Detection in Spoken Dialogues by Detecting Speaker Intentions as a Secondary Task	This work focuses on the use of acoustic cues for modeling turn-taking in dyadic spoken dialogues. Previous work has shown that speaker intentions (e.g., asking a question, uttering a backchannel, etc.) can influence turn-taking behavior and are good predictors of turn-transitions in spoken dialogues. However, speaker ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	97,616
1306.0237	Guided Random Forest in the RRF Package	Random Forest (RF) is a powerful supervised learner and has been popularly used in many applications such as bioinformatics. In this work we propose the guided random forest (GRF) for feature selection. Similar to a feature selection method called guided regularized random forest (GRRF), GRF is built using the import...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	24,946
2102.10530	Semi-supervised learning combining backpropagation and STDP: STDP enhances learning by backpropagation with a small amount of labeled data in a spiking neural network	A semi-supervised learning method for spiking neural networks is proposed. The proposed method consists of supervised learning by backpropagation and subsequent unsupervised learning by spike-timing-dependent plasticity (STDP), which is a biologically plausible learning rule. Numerical experiments show that the propose...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	221,126
2403.14496	How Human-Centered Explainable AI Interface Are Designed and Evaluated: A Systematic Survey	Despite its technological breakthroughs, eXplainable Artificial Intelligence (XAI) research has limited success in producing the {\em effective explanations} needed by users. In order to improve XAI systems' usability, practical interpretability, and efficacy for real users, the emerging area of {\em Explainable Interf...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	440,104
2003.03900	FormulaZero: Distributionally Robust Online Adaptation via Offline Population Synthesis	Balancing performance and safety is crucial to deploying autonomous vehicles in multi-agent environments. In particular, autonomous racing is a domain that penalizes safe but conservative policies, highlighting the need for robust, adaptive strategies. Current approaches either make simplifying assumptions about other ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	true	false	false	false	167,399
1702.08780	MILD: Multi-Index hashing for Loop closure Detection	Loop Closure Detection (LCD) has been proved to be extremely useful in global consistent visual Simultaneously Localization and Mapping (SLAM) and appearance-based robot relocalization. Methods exploiting binary features in bag of words representation have recently gained a lot of popularity for their efficiency, but s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	69,064
1607.00051	Geometric Learning and Topological Inference with Biobotic Networks: Convergence Analysis	In this study, we present and analyze a framework for geometric and topological estimation for mapping of unknown environments. We consider agents mimicking motion behaviors of cyborg insects, known as biobots, and exploit coordinate-free local interactions among them to infer geometric and topological information abou...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	58,022
1209.2868	Spatio-Temporal Small Worlds for Decentralized Information Retrieval in Social Networking	We discuss foundations and options for alternative, agent-based information retrieval (IR) approaches in Social Networking, especially Decentralized and Mobile Social Networking scenarios. In addition to usual semantic contexts, these approaches make use of long-term social and spatio-temporal contexts in order to sati...	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	18,541
2006.01632	A Review on End-To-End Methods for Brain Tumor Segmentation and Overall Survival Prediction	Brain tumor segmentation intends to delineate tumor tissues from healthy brain tissues. The tumor tissues include necrosis, peritumoral edema, and active tumor. In contrast, healthy brain tissues include white matter, gray matter, and cerebrospinal fluid. The MRI based brain tumor segmentation research is gaining popul...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	179,828
1112.2372	On Tractability Aspects of Optimal Resource Allocation in OFDMA Systems	Joint channel and rate allocation with power minimization in orthogonal frequency-division multiple access (OFDMA) has attracted extensive attention. Most of the research has dealt with the development of sub-optimal but low-complexity algorithms. In this paper, the contributions comprise new insights from revisiting t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	13,409
1707.01322	Automated Experiment Design for Data-Efficient Verification of Parametric Markov Decision Processes	We present a new method for statistical verification of quantitative properties over a partially unknown system with actions, utilising a parameterised model (in this work, a parametric Markov decision process) and data collected from experiments performed on the underlying system. We obtain the confidence that the und...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	true	76,518
1201.0216	Building Smart Communities with Cyber-Physical Systems	There is a growing trend towards the convergence of cyber-physical systems (CPS) and social computing, which will lead to the emergence of smart communities composed of various objects (including both human individuals and physical things) that interact and cooperate with each other. These smart communities promise to ...	false	false	false	true	true	false	false	false	false	false	false	false	false	true	false	false	false	false	13,635
2108.07574	When Product Search Meets Collaborative Filtering: A Hierarchical Heterogeneous Graph Neural Network Approach	Personalization lies at the core of boosting the product search system performance. Prior studies mainly resorted to the semantic matching between textual queries and user/product related documents, leaving the user collaborative behaviors untapped. In fact, the collaborative filtering signals between users intuitively...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	250,957
2307.11499	Adaptive ResNet Architecture for Distributed Inference in Resource-Constrained IoT Systems	As deep neural networks continue to expand and become more complex, most edge devices are unable to handle their extensive processing requirements. Therefore, the concept of distributed inference is essential to distribute the neural network among a cluster of nodes. However, distribution may lead to additional energy ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	380,929
2403.16427	Re2LLM: Reflective Reinforcement Large Language Model for Session-based Recommendation	Large Language Models (LLMs) are emerging as promising approaches to enhance session-based recommendation (SBR), where both prompt-based and fine-tuning-based methods have been widely investigated to align LLMs with SBR. However, the former methods struggle with optimal prompts to elicit the correct reasoning of LLMs d...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	441,034
1802.01536	Expressive Robot Motion Timing	Our goal is to enable robots to \emph{time} their motion in a way that is purposefully expressive of their internal states, making them more transparent to people. We start by investigating what types of states motion timing is capable of expressing, focusing on robot manipulation and keeping the path constant while sy...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	89,628
2212.05571	DOSnet as a Non-Black-Box PDE Solver: When Deep Learning Meets Operator Splitting	Deep neural networks (DNNs) recently emerged as a promising tool for analyzing and solving complex differential equations arising in science and engineering applications. Alternative to traditional numerical schemes, learning-based solvers utilize the representation power of DNNs to approximate the input-output relatio...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	335,823
2309.13006	Deep3DSketch+: Rapid 3D Modeling from Single Free-hand Sketches	The rapid development of AR/VR brings tremendous demands for 3D content. While the widely-used Computer-Aided Design (CAD) method requires a time-consuming and labor-intensive modeling process, sketch-based 3D modeling offers a potential solution as a natural form of computer-human interaction. However, the sparsity an...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,001
2408.12885	T3M: Text Guided 3D Human Motion Synthesis from Speech	Speech-driven 3D motion synthesis seeks to create lifelike animations based on human speech, with potential uses in virtual reality, gaming, and the film production. Existing approaches reply solely on speech audio for motion generation, leading to inaccurate and inflexible synthesis results. To mitigate this problem, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	482,929
1712.03534	Dynamics Transfer GAN: Generating Video by Transferring Arbitrary Temporal Dynamics from a Source Video to a Single Target Image	In this paper, we propose Dynamics Transfer GAN; a new method for generating video sequences based on generative adversarial learning. The spatial constructs of a generated video sequence are acquired from the target image. The dynamics of the generated video sequence are imported from a source video sequence, with arb...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	86,465
2209.05486	Active Learning and Novel Model Calibration Measurements for Automated Visual Inspection in Manufacturing	Quality control is a crucial activity performed by manufacturing enterprises to ensure that their products meet quality standards and avoid potential damage to the brand's reputation. The decreased cost of sensors and connectivity enabled increasing digitalization of manufacturing. In addition, artificial intelligence ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	317,113
2404.04889	Ethos and Pathos in Online Group Discussions: Corpora for Polarisation Issues in Social Media	Growing polarisation in society caught the attention of the scientific community as well as news media, which devote special issues to this phenomenon. At the same time, digitalisation of social interactions requires to revise concepts from social science regarding establishment of trust, which is a key feature of all ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	444,843
1411.4246	GreMuTRRR: A Novel Genetic Algorithm to Solve Distance Geometry Problem for Protein Structures	Nuclear Magnetic Resonance (NMR) Spectroscopy is a widely used technique to predict the native structure of proteins. However, NMR machines are only able to report approximate and partial distances between pair of atoms. To build the protein structure one has to solve the Euclidean distance geometry problem given the i...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	37,606
1204.2995	Analytic Methods for Optimizing Realtime Crowdsourcing	Realtime crowdsourcing research has demonstrated that it is possible to recruit paid crowds within seconds by managing a small, fast-reacting worker pool. Realtime crowds enable crowd-powered systems that respond at interactive speeds: for example, cameras, robots and instant opinion polls. So far, these techniques hav...	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	15,454
2412.10448	Unlocking Visual Secrets: Inverting Features with Diffusion Priors for Image Reconstruction	Inverting visual representations within deep neural networks (DNNs) presents a challenging and important problem in the field of security and privacy for deep learning. The main goal is to invert the features of an unidentified target image generated by a pre-trained DNN, aiming to reconstruct the original image. Featu...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	516,938
2209.08381	Robust Reinforcement Learning Algorithm for Vision-based Ship Landing of UAVs	This paper addresses the problem of developing an algorithm for autonomous ship landing of vertical take-off and landing (VTOL) capable unmanned aerial vehicles (UAVs), using only a monocular camera in the UAV for tracking and localization. Ship landing is a challenging task due to the small landing space, six degrees ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	318,103
1004.4170	A New Metaheuristic Bat-Inspired Algorithm	Metaheuristic algorithms such as particle swarm optimization, firefly algorithm and harmony search are now becoming powerful methods for solving many tough optimization problems. In this paper, we propose a new metaheuristic method, the Bat Algorithm, based on the echolocation behaviour of bats. We also intend to combi...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	6,258
2409.02388	Gaussian Rate-Distortion-Perception Coding and Entropy-Constrained Scalar Quantization	This paper investigates the best known bounds on the quadratic Gaussian distortion-rate-perception function with limited common randomness for the Kullback-Leibler divergence-based perception measure, as well as their counterparts for the squared Wasserstein-2 distance-based perception measure, recently established by ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	485,679
2306.15788	Evaluating GPT-3.5 and GPT-4 on Grammatical Error Correction for Brazilian Portuguese	We investigate the effectiveness of GPT-3.5 and GPT-4, two large language models, as Grammatical Error Correction (GEC) tools for Brazilian Portuguese and compare their performance against Microsoft Word and Google Docs. We introduce a GEC dataset for Brazilian Portuguese with four categories: Grammar, Spelling, Intern...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	376,153
1301.6704	SPUDD: Stochastic Planning using Decision Diagrams	Markov decisions processes (MDPs) are becoming increasing popular as models of decision theoretic planning. While traditional dynamic programming methods perform well for problems with small state spaces, structured methods are needed for large problems. We propose and examine a value iteration algorithm for MDPs that ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	21,497

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