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
1907.03399	A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context	Common grounding is the process of creating, repairing and updating mutual understandings, which is a critical aspect of sophisticated human communication. However, traditional dialogue systems have limited capability of establishing common ground, and we also lack task formulations which introduce natural difficulty i...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	137,854
cs/0205067	Evaluating the Effectiveness of Ensembles of Decision Trees in Disambiguating Senseval Lexical Samples	This paper presents an evaluation of an ensemble--based system that participated in the English and Spanish lexical sample tasks of Senseval-2. The system combines decision trees of unigrams, bigrams, and co--occurrences into a single classifier. The analysis is extended to include the Senseval-1 data.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,588
2408.02622	Language Model Can Listen While Speaking	Dialogue serves as the most natural manner of human-computer interaction (HCI). Recent advancements in speech language models (SLM) have significantly enhanced speech-based conversational AI. However, these models are limited to turn-based conversation, lacking the ability to interact with humans in real-time spoken sc...	true	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	478,697
1701.00289	Integrating sentiment and social structure to determine preference alignments: The Irish Marriage Referendum	We examine the relationship between social structure and sentiment through the analysis of a large collection of tweets about the Irish Marriage Referendum of 2015. We obtain the sentiment of every tweet with the hashtags #marref and #marriageref that was posted in the days leading to the referendum, and construct netw...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	66,253
2309.15031	Nuclear Pleomorphism in Canine Cutaneous Mast Cell Tumors: Comparison of Reproducibility and Prognostic Relevance between Estimates, Manual Morphometry and Algorithmic Morphometry	Variation in nuclear size and shape is an important criterion of malignancy for many tumor types; however, categorical estimates by pathologists have poor reproducibility. Measurements of nuclear characteristics (morphometry) can improve reproducibility, but manual methods are time consuming. The aim of this study was ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,825
2409.08474	Rethinking Meta-Learning from a Learning Lens	Meta-learning has emerged as a powerful approach for leveraging knowledge from previous tasks to solve new tasks. The mainstream methods focus on training a well-generalized model initialization, which is then adapted to different tasks with limited data and updates. However, it pushes the model overfitting on the trai...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	487,918
2002.02851	On the Estimation of Information Measures of Continuous Distributions	The estimation of information measures of continuous distributions based on samples is a fundamental problem in statistics and machine learning. In this paper, we analyze estimates of differential entropy in $K$-dimensional Euclidean space, computed from a finite number of samples, when the probability density function...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	163,052
2205.10821	Information Leakage in Index Coding	We study the information leakage to a guessing adversary in index coding with a general message distribution. Under both vanishing-error and zero-error decoding assumptions, we develop lower and upper bounds on the optimal leakage rate, which are based on the broadcast rate of the subproblem induced by the set of messa...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	297,883
2207.08162	Natural language processing for clusterization of genes according to their functions	There are hundreds of methods for analysis of data obtained in mRNA-sequencing. The most of them are focused on small number of genes. In this study, we propose an approach that reduces the analysis of several thousand genes to analysis of several clusters. The list of genes is enriched with information from open datab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	308,479
2205.10739	Offline Policy Comparison with Confidence: Benchmarks and Baselines	Decision makers often wish to use offline historical data to compare sequential-action policies at various world states. Importantly, computational tools should produce confidence values for such offline policy comparison (OPC) to account for statistical variance and limited data coverage. Nevertheless, there is little...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	297,843
2306.14899	FunQA: Towards Surprising Video Comprehension	Surprising videos, such as funny clips, creative performances, or visual illusions, attract significant attention. Enjoyment of these videos is not simply a response to visual stimuli; rather, it hinges on the human capacity to understand (and appreciate) commonsense violations depicted in these videos. We introduce Fu...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	true	375,854
1711.08238	Multi-Level Recurrent Residual Networks for Action Recognition	Most existing Convolutional Neural Networks(CNNs) used for action recognition are either difficult to optimize or underuse crucial temporal information. Inspired by the fact that the recurrent model consistently makes breakthroughs in the task related to sequence, we propose a novel Multi-Level Recurrent Residual Netwo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,166
1708.02191	Unsupervised Domain Adaptation for Face Recognition in Unlabeled Videos	Despite rapid advances in face recognition, there remains a clear gap between the performance of still image-based face recognition and video-based face recognition, due to the vast difference in visual quality between the domains and the difficulty of curating diverse large-scale video datasets. This paper addresses b...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	78,537
1905.12806	Exploiting Epistemic Uncertainty of Anatomy Segmentation for Anomaly Detection in Retinal OCT	Diagnosis and treatment guidance are aided by detecting relevant biomarkers in medical images. Although supervised deep learning can perform accurate segmentation of pathological areas, it is limited by requiring a-priori definitions of these regions, large-scale annotations, and a representative patient cohort in the ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	132,886
2312.17147	Risk of Cascading Collisions in Network of Vehicles with Delayed Communication	This paper establishes and explores a framework to analyze the risk of cascading failures in a platoon of autonomous vehicles, accounting for communication time-delays and input uncertainty. Our proposed framework yields closed-form expressions for cascading collisions, which we quantify using the coherent Average Valu...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	418,632
2104.02096	Compressing Visual-linguistic Model via Knowledge Distillation	Despite exciting progress in pre-training for visual-linguistic (VL) representations, very few aspire to a small VL model. In this paper, we study knowledge distillation (KD) to effectively compress a transformer-based large VL model into a small VL model. The major challenge arises from the inconsistent regional visua...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	228,584
2012.06718	Learning Consistent Deep Generative Models from Sparse Data via Prediction Constraints	We develop a new framework for learning variational autoencoders and other deep generative models that balances generative and discriminative goals. Our framework optimizes model parameters to maximize a variational lower bound on the likelihood of observed data, subject to a task-specific prediction constraint that pr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	211,194
1811.03081	Forging new worlds: high-resolution synthetic galaxies with chained generative adversarial networks	Astronomy of the 21st century increasingly finds itself with extreme quantities of data. This growth in data is ripe for modern technologies such as deep image processing, which has the potential to allow astronomers to automatically identify, classify, segment and deblend various astronomical objects. In this paper, w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	112,752
2210.10994	MBTI Personality Prediction for Fictional Characters Using Movie Scripts	An NLP model that understands stories should be able to understand the characters in them. To support the development of neural models for this purpose, we construct a benchmark, Story2Personality. The task is to predict a movie character's MBTI or Big 5 personality types based on the narratives of the character. Exper...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	325,137
2107.06097	Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets	While deep learning has revolutionized research and applications in NLP and computer vision, this has not yet been the case for behavioral modeling and behavioral health applications. This is because the domain's datasets are smaller, have heterogeneous datatypes, and typically exhibit a large degree of missingness. Th...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	245,984
2303.11452	A Cheeger Inequality for Size-Specific Conductance	The $\mu$-conductance measure proposed by Lovasz and Simonovits is a size-specific conductance score that identifies the set with smallest conductance while disregarding those sets with volume smaller than a $\mu$ fraction of the whole graph. Using $\mu$-conductance enables us to study in new ways. In this manuscript w...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	352,854
1606.00134	Constructions of Good Entanglement-Assisted Quantum Error Correcting Codes	Entanglement-assisted quantum error correcting codes (EAQECCs) are a simple and fundamental class of codes. They allow for the construction of quantum codes from classical codes by relaxing the duality condition and using pre-shared entanglement between the sender and receiver. However, in general it is not easy to det...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	56,635
2201.06834	Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale	The ever-growing demand and complexity of machine learning are putting pressure on hyper-parameter tuning systems: while the evaluation cost of models continues to increase, the scalability of state-of-the-arts starts to become a crucial bottleneck. In this paper, inspired by our experience when deploying hyper-paramet...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	275,848
2401.04960	Why Change Your Controller When You Can Change Your Planner: Drag-Aware Trajectory Generation for Quadrotor Systems	Motivated by the increasing use of quadrotors for payload delivery, we consider a joint trajectory generation and feedback control design problem for a quadrotor experiencing aerodynamic wrenches. Unmodeled aerodynamic drag forces from carried payloads can lead to catastrophic outcomes. Prior work model aerodynamic eff...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	420,602
2107.08442	Sleep Staging Based on Multi Scale Dual Attention Network	Sleep staging plays an important role on the diagnosis of sleep disorders. In general, experts classify sleep stages manually based on polysomnography (PSG), which is quite time-consuming. Meanwhile, the acquisition process of multiple signals is much complex, which can affect the subject's sleep. Therefore, the use of...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,732
2109.05265	RVMDE: Radar Validated Monocular Depth Estimation for Robotics	Stereoscopy exposits a natural perception of distance in a scene, and its manifestation in 3D world understanding is an intuitive phenomenon. However, an innate rigid calibration of binocular vision sensors is crucial for accurate depth estimation. Alternatively, a monocular camera alleviates the limitation at the expe...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	254,730
2311.07608	MuST: Multimodal Spatiotemporal Graph-Transformer for Hospital Readmission Prediction	Hospital readmission prediction is considered an essential approach to decreasing readmission rates, which is a key factor in assessing the quality and efficacy of a healthcare system. Previous studies have extensively utilized three primary modalities, namely electronic health records (EHR), medical images, and clinic...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	407,407
2202.13370	Submodule codes as spherical codes in buildings	We give a generalization of subspace codes by means of codes of modules over finite commutative chain rings. We define a new class of Sperner codes and use results from extremal combinatorics to prove the optimality of such codes in different cases. Moreover, we explain the connection with Bruhat-Tits buildings and sho...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	282,579
2302.06079	Byzantine-Robust Learning on Heterogeneous Data via Gradient Splitting	Federated learning has exhibited vulnerabilities to Byzantine attacks, where the Byzantine attackers can send arbitrary gradients to a central server to destroy the convergence and performance of the global model. A wealth of robust AGgregation Rules (AGRs) have been proposed to defend against Byzantine attacks. Howeve...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	345,280
1505.06664	Quantifying the robustness of metro networks	Metros (heavy rail transit systems) are integral parts of urban transportation systems. Failures in their operations can have serious impacts on urban mobility, and measuring their robustness is therefore critical. Moreover, as physical networks, metros can be viewed as network topological entities, and as such they po...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	43,461
2409.15657	M$^2$PT: Multimodal Prompt Tuning for Zero-shot Instruction Learning	Multimodal Large Language Models (MLLMs) demonstrate remarkable performance across a wide range of domains, with increasing emphasis on enhancing their zero-shot generalization capabilities for unseen tasks across various modalities. Instruction tuning has emerged as an effective strategy for achieving zero-shot genera...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	490,999
1608.04307	Transitive Hashing Network for Heterogeneous Multimedia Retrieval	Hashing has been widely applied to large-scale multimedia retrieval due to the storage and retrieval efficiency. Cross-modal hashing enables efficient retrieval from database of one modality in response to a query of another modality. Existing work on cross-modal hashing assumes heterogeneous relationship across modali...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	59,807
2403.19178	Enhancing Trust and Privacy in Distributed Networks: A Comprehensive Survey on Blockchain-based Federated Learning	While centralized servers pose a risk of being a single point of failure, decentralized approaches like blockchain offer a compelling solution by implementing a consensus mechanism among multiple entities. Merging distributed computing with cryptographic techniques, decentralized technologies introduce a novel computin...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	true	442,244
2402.02941	Exploring the Synergies of Hybrid CNNs and ViTs Architectures for Computer Vision: A survey	The hybrid of Convolutional Neural Network (CNN) and Vision Transformers (ViT) architectures has emerged as a groundbreaking approach, pushing the boundaries of computer vision (CV). This comprehensive review provides a thorough examination of the literature on state-of-the-art hybrid CNN-ViT architectures, exploring t...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	426,792
1506.02066	Multilayer network decoding versatility and trust	In the recent years, the multilayer networks have increasingly been realized as a more realistic framework to understand emergent physical phenomena in complex real world systems. We analyze a massive time-varying social data drawn from the largest film industry of the world under multilayer network framework. The fram...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	43,856
2304.05889	Representation Learning with Multi-Step Inverse Kinematics: An Efficient and Optimal Approach to Rich-Observation RL	We study the design of sample-efficient algorithms for reinforcement learning in the presence of rich, high-dimensional observations, formalized via the Block MDP problem. Existing algorithms suffer from either 1) computational intractability, 2) strong statistical assumptions that are not necessarily satisfied in prac...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	357,776
1906.04670	Automatic Multi-Sensor Extrinsic Calibration for Mobile Robots	In order to fuse measurements from multiple sensors mounted on a mobile robot, it is needed to express them in a common reference system through their relative spatial transformations. In this paper, we present a method to estimate the full 6DoF extrinsic calibration parameters of multiple heterogeneous sensors (Lidars...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	134,794
2411.16595	Location-Based Service (LBS) Data Quality Metrics and Effects on Mobility Inference	Today, GPS-equipped mobile devices are ubiquitous, and they generate Location-Based Service (LBS) data, which has become a critical resource for understanding human mobility. However, inherent limitations in LBS datasets, primarily characterized by discontinuity and sparsity, may introduce significant biases in represe...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	511,081
1810.11078	Generalised framework for multi-criteria method selection	Multi-Criteria Decision Analysis (MCDA) methods are widely used in various fields and disciplines. While most of the research has been focused on the development and improvement of new MCDA methods, relatively limited attention has been paid to their appropriate selection for the given decision problem. Their improper ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	111,426
2301.05651	Mutation Testing of Deep Reinforcement Learning Based on Real Faults	Testing Deep Learning (DL) systems is a complex task as they do not behave like traditional systems would, notably because of their stochastic nature. Nonetheless, being able to adapt existing testing techniques such as Mutation Testing (MT) to DL settings would greatly improve their potential verifiability. While some...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	340,414
2212.00793	Unite and Conquer: Plug & Play Multi-Modal Synthesis using Diffusion Models	Generating photos satisfying multiple constraints find broad utility in the content creation industry. A key hurdle to accomplishing this task is the need for paired data consisting of all modalities (i.e., constraints) and their corresponding output. Moreover, existing methods need retraining using paired data across ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,199
1702.04013	Is a Data-Driven Approach still Better than Random Choice with Naive Bayes classifiers?	We study the performance of data-driven, a priori and random approaches to label space partitioning for multi-label classification with a Gaussian Naive Bayes classifier. Experiments were performed on 12 benchmark data sets and evaluated on 5 established measures of classification quality: micro and macro averaged F1 s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,207
2410.15814	Kaninfradet3D:A Road-side Camera-LiDAR Fusion 3D Perception Model based on Nonlinear Feature Extraction and Intrinsic Correlation	With the development of AI-assisted driving, numerous methods have emerged for ego-vehicle 3D perception tasks, but there has been limited research on roadside perception. With its ability to provide a global view and a broader sensing range, the roadside perspective is worth developing. LiDAR provides precise three-di...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	500,741
2007.15356	What does BERT know about books, movies and music? Probing BERT for Conversational Recommendation	Heavily pre-trained transformer models such as BERT have recently shown to be remarkably powerful at language modelling by achieving impressive results on numerous downstream tasks. It has also been shown that they are able to implicitly store factual knowledge in their parameters after pre-training. Understanding what...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	189,651
2411.13076	Hints of Prompt: Enhancing Visual Representation for Multimodal LLMs in Autonomous Driving	In light of the dynamic nature of autonomous driving environments and stringent safety requirements, general MLLMs combined with CLIP alone often struggle to represent driving-specific scenarios accurately, particularly in complex interactions and long-tail cases. To address this, we propose the Hints of Prompt (HoP) f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	509,668
2406.11193	MMNeuron: Discovering Neuron-Level Domain-Specific Interpretation in Multimodal Large Language Model	Projecting visual features into word embedding space has become a significant fusion strategy adopted by Multimodal Large Language Models (MLLMs). However, its internal mechanisms have yet to be explored. Inspired by multilingual research, we identify domain-specific neurons in multimodal large language models. Specifi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	464,761
1803.07544	C3PO: Database and Benchmark for Early-stage Malicious Activity Detection in 3D Printing	Increasing malicious users have sought practices to leverage 3D printing technology to produce unlawful tools in criminal activities. Current regulations are inadequate to deal with the rapid growth of 3D printers. It is of vital importance to enable 3D printers to identify the objects to be printed, so that the manufa...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,078
2111.03906	Insights Into Incitement: A Computational Perspective on Dangerous Speech on Twitter in India	Dangerous speech on social media platforms can be framed as blatantly inflammatory, or be couched in innuendo. It is also centrally tied to who engages it - it can be driven by openly sectarian social media accounts, or through subtle nudges by influential accounts, allowing for complex means of reinforcing vilificatio...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	265,308
2304.13061	iMixer: hierarchical Hopfield network implies an invertible, implicit and iterative MLP-Mixer	In the last few years, the success of Transformers in computer vision has stimulated the discovery of many alternative models that compete with Transformers, such as the MLP-Mixer. Despite their weak inductive bias, these models have achieved performance comparable to well-studied convolutional neural networks. Recent ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	true	false	false	360,444
2109.08523	A Computable Piece of Uncomputable Art whose Expansion May Explain the Universe in Software Space	At the intersection of what I call uncomputable art and computational epistemology, a form of experimental philosophy, we find an exciting and promising area of science related to causation with an alternative, possibly best possible, solution to the challenge of the inverse problem. That is the problem of finding the ...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	true	255,927
1606.04250	Experimental and causal view on information integration in autonomous agents	The amount of digitally available but heterogeneous information about the world is remarkable, and new technologies such as self-driving cars, smart homes, or the internet of things may further increase it. In this paper we present preliminary ideas about certain aspects of the problem of how such heterogeneous informa...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	57,221
1105.6061	Distributed Detection/Isolation Procedures for Quickest Event Detection in Large Extent Wireless Sensor Networks	We study a problem of distributed detection of a stationary point event in a large extent wireless sensor network ($\wsn$), where the event influences the observations of the sensors only in the vicinity of where it occurs. An event occurs at an unknown time and at a random location in the coverage region (or region of...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	10,589
2312.01097	Planning as In-Painting: A Diffusion-Based Embodied Task Planning Framework for Environments under Uncertainty	Task planning for embodied AI has been one of the most challenging problems where the community does not meet a consensus in terms of formulation. In this paper, we aim to tackle this problem with a unified framework consisting of an end-to-end trainable method and a planning algorithm. Particularly, we propose a task-...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	412,310
2004.02958	TSInsight: A local-global attribution framework for interpretability in time-series data	With the rise in the employment of deep learning methods in safety-critical scenarios, interpretability is more essential than ever before. Although many different directions regarding interpretability have been explored for visual modalities, time-series data has been neglected with only a handful of methods tested du...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	171,389
1410.7050	A PTAS for Agnostically Learning Halfspaces	We present a PTAS for agnostically learning halfspaces w.r.t. the uniform distribution on the $d$ dimensional sphere. Namely, we show that for every $\mu>0$ there is an algorithm that runs in time $\mathrm{poly}(d,\frac{1}{\epsilon})$, and is guaranteed to return a classifier with error at most $(1+\mu)\mathrm{opt}+\ep...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	37,034
2106.08307	Learning Incident Prediction Models Over Large Geographical Areas for Emergency Response Systems	Principled decision making in emergency response management necessitates the use of statistical models that predict the spatial-temporal likelihood of incident occurrence. These statistical models are then used for proactive stationing which allocates first responders across the spatial area in order to reduce overall ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	241,249
2102.06296	No-Regret Algorithms for Time-Varying Bayesian Optimization	In this paper, we consider the time-varying Bayesian optimization problem. The unknown function at each time is assumed to lie in an RKHS (reproducing kernel Hilbert space) with a bounded norm. We adopt the general variation budget model to capture the time-varying environment, and the variation is characterized by the...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,707
1910.01226	Piracy Resistant Watermarks for Deep Neural Networks	As companies continue to invest heavily in larger, more accurate and more robust deep learning models, they are exploring approaches to monetize their models while protecting their intellectual property. Model licensing is promising, but requires a robust tool for owners to claim ownership of models, i.e. a watermark. ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	147,878
2304.10074	Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks	In this paper, we provide a theory of using graph neural networks (GNNs) for \textit{multi-node representation learning}, where we are interested in learning a representation for a set of more than one node such as a link. Existing GNNs are mainly designed to learn single-node representations. When we want to learn a n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	359,281
2007.13262	REXUP: I REason, I EXtract, I UPdate with Structured Compositional Reasoning for Visual Question Answering	Visual question answering (VQA) is a challenging multi-modal task that requires not only the semantic understanding of both images and questions, but also the sound perception of a step-by-step reasoning process that would lead to the correct answer. So far, most successful attempts in VQA have been focused on only one...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	189,073
2202.09952	A wonderful triangle in compressed sensing	In order to determine the sparse approximation function which has a direct metric relationship with the $\ell_{0}$ quasi-norm, we introduce a wonderful triangle whose sides are composed of $\Vert \mathbf{x} \Vert_{0}$, $\Vert \mathbf{x} \Vert_{1}$ and $\Vert \mathbf{x} \Vert_{\infty}$ for any non-zero vector $\mathbf{x...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	281,373
2105.10766	Embedding Information onto a Dynamical System	The celebrated Takens' embedding theorem concerns embedding an attractor of a dynamical system in a Euclidean space of appropriate dimension through a generic delay-observation map. The embedding also establishes a topological conjugacy. In this paper, we show how an arbitrary sequence can be mapped into another space ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	236,495
1607.01419	Extended LTLvis Motion Planning interface (Extended Technical Report)	This paper introduces an extended version of the Linear Temporal Logic (LTL) graphical interface. It is a sketch based interface built on the Android platform which makes the LTL control interface more straightforward and friendly to nonexpert users. By predefining a set of areas of interest, this interface can quickly...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	58,219
2208.04897	Sports Video Analysis on Large-Scale Data	This paper investigates the modeling of automated machine description on sports video, which has seen much progress recently. Nevertheless, state-of-the-art approaches fall quite short of capturing how human experts analyze sports scenes. There are several major reasons: (1) The used dataset is collected from non-offic...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,257
2111.05125	Segmentation of Multiple Myeloma Plasma Cells in Microscopy Images with Noisy Labels	A key component towards an improved and fast cancer diagnosis is the development of computer-assisted tools. In this article, we present the solution that won the SegPC-2021 competition for the segmentation of multiple myeloma plasma cells in microscopy images. The labels used in the competition dataset were generated ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	265,702
2407.11073	SemiAdv: Query-Efficient Black-Box Adversarial Attack with Unlabeled Images	Adversarial attack has garnered considerable attention due to its profound implications for the secure deployment of robots in sensitive security scenarios. To potentially push for advances in the field, this paper studies the adversarial attack in the black-box setting and proposes an unlabeled data-driven adversarial...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	473,288
2005.03913	The localization of non-backtracking centrality in networks and its physical consequences	The spectrum of the non-backtracking matrix plays a crucial role in determining various structural and dynamical properties of networked systems, ranging from the threshold in bond percolation and non-recurrent epidemic processes, to community structure, to node importance. Here we calculate the largest eigenvalue of t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	176,298
2204.05201	A Post-Processing Tool and Feasibility Study for Three-Dimensional Imaging with Electrical Impedance Tomography During Deep Brain Stimulation Surgery	Electrical impedance tomography (EIT) is a promising technique for biomedical imaging. The strength of EIT is its ability to reconstruct images of the body's internal structures through radiation-safe techniques. EIT is regarded as safe for patients' health, and it is currently being actively researched. This paper inv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	290,951
1810.10777	Efficient Learning of Restricted Boltzmann Machines Using Covariance Estimates	Learning RBMs using standard algorithms such as CD(k) involves gradient descent on the negative log-likelihood. One of the terms in the gradient, which involves expectation w.r.t. the model distribution, is intractable and is obtained through an MCMC estimate. In this work we show that the Hessian of the log-likelihood...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	111,362
2411.05572	Why These Documents? Explainable Generative Retrieval with Hierarchical Category Paths	Generative retrieval has recently emerged as a new alternative of traditional information retrieval approaches. However, existing generative retrieval methods directly decode docid when a query is given, making it impossible to provide users with explanations as an answer for "Why this document is retrieved?". To addre...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	506,713
1909.04315	Fine-grained Knowledge Fusion for Sequence Labeling Domain Adaptation	In sequence labeling, previous domain adaptation methods focus on the adaptation from the source domain to the entire target domain without considering the diversity of individual target domain samples, which may lead to negative transfer results for certain samples. Besides, an important characteristic of sequence lab...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	144,771
1804.10335	Communication, Computing and Caching for Mobile VR Delivery: Modeling and Trade-off	Mobile virtual reality (VR) delivery is gaining increasing attention from both industry and academia due to its ability to provide an immersive experience. However, achieving mobile VR delivery requires ultra-high transmission rate, deemed as a first killer application for 5G wireless networks. In this paper, in order ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	96,143
2403.14327	Investigating the validity of structure learning algorithms in identifying risk factors for intervention in patients with diabetes	Diabetes, a pervasive and enduring health challenge, imposes significant global implications on health, financial healthcare systems, and societal well-being. This study undertakes a comprehensive exploration of various structural learning algorithms to discern causal pathways amongst potential risk factors influencing...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	440,015
2209.12827	Advanced Skills by Learning Locomotion and Local Navigation End-to-End	The common approach for local navigation on challenging environments with legged robots requires path planning, path following and locomotion, which usually requires a locomotion control policy that accurately tracks a commanded velocity. However, by breaking down the navigation problem into these sub-tasks, we limit t...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	319,674
2004.01275	AI4COVID-19: AI Enabled Preliminary Diagnosis for COVID-19 from Cough Samples via an App	Background: The inability to test at scale has become humanity's Achille's heel in the ongoing war against the COVID-19 pandemic. A scalable screening tool would be a game changer. Building on the prior work on cough-based diagnosis of respiratory diseases, we propose, develop and test an Artificial Intelligence (AI)-p...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	170,863
1806.04542	Approximate inference with Wasserstein gradient flows	We present a novel approximate inference method for diffusion processes, based on the Wasserstein gradient flow formulation of the diffusion. In this formulation, the time-dependent density of the diffusion is derived as the limit of implicit Euler steps that follow the gradients of a particular free energy functional....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,260
2005.13402	AVGZSLNet: Audio-Visual Generalized Zero-Shot Learning by Reconstructing Label Features from Multi-Modal Embeddings	In this paper, we propose a novel approach for generalized zero-shot learning in a multi-modal setting, where we have novel classes of audio/video during testing that are not seen during training. We use the semantic relatedness of text embeddings as a means for zero-shot learning by aligning audio and video embeddings...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	179,001
2306.04668	SMRVIS: Point cloud extraction from 3-D ultrasound for non-destructive testing	We propose to formulate point cloud extraction from ultrasound volumes as an image segmentation problem. Through this convenient formulation, a quick prototype exploring various variants of the Residual Network, U-Net, and the Squeeze and Excitation Network was developed and evaluated. This report documents the experim...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	371,852
1902.07605	Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs	Robust MDPs (RMDPs) can be used to compute policies with provable worst-case guarantees in reinforcement learning. The quality and robustness of an RMDP solution are determined by the ambiguity set---the set of plausible transition probabilities---which is usually constructed as a multi-dimensional confidence region. E...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	122,019
1806.06439	Online Prediction of Switching Graph Labelings with Cluster Specialists	We address the problem of predicting the labeling of a graph in an online setting when the labeling is changing over time. We present an algorithm based on a specialist approach; we develop the machinery of cluster specialists which probabilistically exploits the cluster structure in the graph. Our algorithm has two va...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	100,706
2404.01490	AAdaM at SemEval-2024 Task 1: Augmentation and Adaptation for Multilingual Semantic Textual Relatedness	This paper presents our system developed for the SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages. The shared task aims at measuring the semantic textual relatedness between pairs of sentences, with a focus on a range of under-represented languages. In this work, we propose using machin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	443,441
2308.14697	Assessing Trust in Construction AI-Powered Collaborative Robots using Structural Equation Modeling	This study aimed to investigate the key technical and psychological factors that impact the architecture, engineering, and construction (AEC) professionals' trust in collaborative robots (cobots) powered by artificial intelligence (AI). The study employed a nationwide survey of 600 AEC industry practitioners to gather ...	true	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	388,422
1610.07387	QoE-aware Scalable Video Transmission in MIMO~Systems	An important concept in wireless systems has been quality of experience (QoE)-aware video transmission. Such communications are considered not only connection-based communications but also content-aware communications, since the video quality is closely related to the content itself. It becomes necessary therefore for ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	62,780
2207.10141	AudioScopeV2: Audio-Visual Attention Architectures for Calibrated Open-Domain On-Screen Sound Separation	We introduce AudioScopeV2, a state-of-the-art universal audio-visual on-screen sound separation system which is capable of learning to separate sounds and associate them with on-screen objects by looking at in-the-wild videos. We identify several limitations of previous work on audio-visual on-screen sound separation, ...	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	309,143
1910.06621	A Method to Generate Synthetically Warped Document Image	The digital camera captured document images may often be warped and distorted due to different camera angles or document surfaces. A robust technique is needed to solve this kind of distortion. The research on dewarping of the document suffers due to the limited availability of benchmark public dataset. In recent times...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	149,395
2006.09892	STAD: Spatio-Temporal Adjustment of Traffic-Oblivious Travel-Time Estimation	Travel time estimation is an important component in modern transportation applications. The state of the art techniques for travel time estimation use GPS traces to learn the weights of a road network, often modeled as a directed graph, then apply Dijkstra-like algorithms to find shortest paths. Travel time is then com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,690
2311.09797	FinanceMath: Knowledge-Intensive Math Reasoning in Finance Domains	We introduce FinanceMath, a novel benchmark designed to evaluate LLMs' capabilities in solving knowledge-intensive math reasoning problems. Compared to prior works, this study features three core advancements. First, FinanceMath includes 1,200 problems with a hybrid of textual and tabular content. These problems requir...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	408,302
1304.4889	Hands-free Evolution of 3D-printable Objects via Eye Tracking	Interactive evolution has shown the potential to create amazing and complex forms in both 2-D and 3-D settings. However, the algorithm is slow and users quickly become fatigued. We propose that the use of eye tracking for interactive evolution systems will both reduce user fatigue and improve evolutionary success. We d...	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	24,042
1109.5336	Achievable Rates for K-user Gaussian Interference Channels	The aim of this paper is to study the achievable rates for a $K$ user Gaussian interference channels for any SNR using a combination of lattice and algebraic codes. Lattice codes are first used to transform the Gaussian interference channel (G-IFC) into a discrete input-output noiseless channel, and subsequently algebr...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,306
2310.11778	Language Agents for Detecting Implicit Stereotypes in Text-to-image Models at Scale	The recent surge in the research of diffusion models has accelerated the adoption of text-to-image models in various Artificial Intelligence Generated Content (AIGC) commercial products. While these exceptional AIGC products are gaining increasing recognition and sparking enthusiasm among consumers, the questions regar...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	400,782
2405.06929	PRENet: A Plane-Fit Redundancy Encoding Point Cloud Sequence Network for Real-Time 3D Action Recognition	Recognizing human actions from point cloud sequence has attracted tremendous attention from both academia and industry due to its wide applications. However, most previous studies on point cloud action recognition typically require complex networks to extract intra-frame spatial features and inter-frame temporal featur...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,510
2309.05756	GlobalDoc: A Cross-Modal Vision-Language Framework for Real-World Document Image Retrieval and Classification	Visual document understanding (VDU) has rapidly advanced with the development of powerful multi-modal language models. However, these models typically require extensive document pre-training data to learn intermediate representations and often suffer a significant performance drop in real-world online industrial settin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,180
2502.01033	PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustment	In the realm of parameter-efficient fine-tuning (PEFT) methods, while options like LoRA are available, there is a persistent demand in the industry for a PEFT approach that excels in both efficiency and performance within the context of single-backbone multi-tenant applications. This paper introduces a new and straight...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	529,656
2212.09982	Joint Speech Transcription and Translation: Pseudo-Labeling with Out-of-Distribution Data	Self-training has been shown to be helpful in addressing data scarcity for many domains, including vision, speech, and language. Specifically, self-training, or pseudo-labeling, labels unsupervised data and adds that to the training pool. In this work, we investigate and use pseudo-labeling for a recently proposed nove...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	337,283
2401.10449	Contextualized Automatic Speech Recognition with Attention-Based Bias Phrase Boosted Beam Search	End-to-end (E2E) automatic speech recognition (ASR) methods exhibit remarkable performance. However, since the performance of such methods is intrinsically linked to the context present in the training data, E2E-ASR methods do not perform as desired for unseen user contexts (e.g., technical terms, personal names, and p...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	422,641
2406.03736	Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data	Discrete diffusion models with absorbing processes have shown promise in language modeling. The key quantities to be estimated are the ratios between the marginal probabilities of two transitive states at all timesteps, called the concrete score. In this paper, we reveal that the concrete score in absorbing diffusion c...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	461,370
2305.19036	Delayed Bandits: When Do Intermediate Observations Help?	We study a $K$-armed bandit with delayed feedback and intermediate observations. We consider a model where intermediate observations have a form of a finite state, which is observed immediately after taking an action, whereas the loss is observed after an adversarially chosen delay. We show that the regime of the mappi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,349
1703.05065	Joint Epipolar Tracking (JET): Simultaneous optimization of epipolar geometry and feature correspondences	Traditionally, pose estimation is considered as a two step problem. First, feature correspondences are determined by direct comparison of image patches, or by associating feature descriptors. In a second step, the relative pose and the coordinates of corresponding points are estimated, most often by minimizing the repr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,021
1908.09502	On Parameter Optimization of Product Codes for Iterative Bounded Distance Decoding with Scaled Reliability	We use density evolution to optimize the parameters of binary product codes (PCs) decoded based on the recently introduced iterative bounded distance decoding with scaled reliability. We show that binary PCs with component codes of 3-bit error correcting capability provide the best performance-complexity trade-off.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	142,867
1910.03197	Accelerating Federated Learning via Momentum Gradient Descent	Federated learning (FL) provides a communication-efficient approach to solve machine learning problems concerning distributed data, without sending raw data to a central server. However, existing works on FL only utilize first-order gradient descent (GD) and do not consider the preceding iterations to gradient update w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	148,441

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