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
2103.09161	Large System Achievable Rate Analysis of RIS-Assisted MIMO Wireless Communication with Statistical CSIT	Reconfigurable intelligent surface (RIS) is an emerging technology to enhance wireless communication in terms of energy cost and system performance by equipping a considerable quantity of nearly passive reflecting elements. This study focuses on a downlink RIS-assisted multiple-input multiple-output (MIMO) wireless com...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	225,097
2411.09449	Image Regeneration: Evaluating Text-to-Image Model via Generating Identical Image with Multimodal Large Language Models	Diffusion models have revitalized the image generation domain, playing crucial roles in both academic research and artistic expression. With the emergence of new diffusion models, assessing the performance of text-to-image models has become increasingly important. Current metrics focus on directly matching the input te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	508,252
1904.00138	On Arrhythmia Detection by Deep Learning and Multidimensional Representation	An electrocardiogram (ECG) is a time-series signal that is represented by one-dimensional (1-D) data. Higher dimensional representation contains more information that is accessible for feature extraction. Hidden variables such as frequency relation and morphology of segment is not directly accessible in the time domain...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	125,801
1206.3027	Social Networks, Functional Differentiation of Society, and Data Protection	Most scholars, politicians, and activists are following individualistic theories of privacy and data protection. In contrast, some of the pioneers of the data protection legislation in Germany like Adalbert Podlech, Paul J. M\"uller, and Ulrich Dammann used a systems theory approach. Following Niklas Luhmann, the aim o...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	16,473
2304.01371	The Interconnected Nature of Online Harm and Moderation: Investigating the Cross-Platform Spread of Harmful Content between YouTube and Twitter	The proliferation of harmful content shared online poses a threat to online information integrity and the integrity of discussion across platforms. Despite various moderation interventions adopted by social media platforms, researchers and policymakers are calling for holistic solutions. This study explores how a targe...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	356,043
1707.09613	Sparse Vector Recovery: Bernoulli-Gaussian Message Passing	Low-cost message passing (MP) algorithm has been recognized as a promising technique for sparse vector recovery. However, the existing MP algorithms either focus on mean square error (MSE) of the value recovery while ignoring the sparsity requirement, or support error rate (SER) of the sparse support (non-zero position...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	78,038
2411.19229	Habit Coach: Customising RAG-based chatbots to support behavior change	This paper presents the iterative development of Habit Coach, a GPT-based chatbot designed to support users in habit change through personalized interaction. Employing a user-centered design approach, we developed the chatbot using a Retrieval-Augmented Generation (RAG) system, which enables behavior personalization wi...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	512,164
2210.12427	Hard Gate Knowledge Distillation -- Leverage Calibration for Robust and Reliable Language Model	In knowledge distillation, a student model is trained with supervisions from both knowledge from a teacher and observations drawn from a training data distribution. Knowledge of a teacher is considered a subject that holds inter-class relations which send a meaningful supervision to a student; hence, much effort has be...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	325,737
2302.04702	REIN: A Comprehensive Benchmark Framework for Data Cleaning Methods in ML Pipelines	Nowadays, machine learning (ML) plays a vital role in many aspects of our daily life. In essence, building well-performing ML applications requires the provision of high-quality data throughout the entire life-cycle of such applications. Nevertheless, most of the real-world tabular data suffer from different types of d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	344,785
1302.3446	Adaptive Temporal Compressive Sensing for Video	This paper introduces the concept of adaptive temporal compressive sensing (CS) for video. We propose a CS algorithm to adapt the compression ratio based on the scene's temporal complexity, computed from the compressed data, without compromising the quality of the reconstructed video. The temporal adaptivity is manifes...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	22,007
2205.02052	Exploring Rawlsian Fairness for K-Means Clustering	We conduct an exploratory study that looks at incorporating John Rawls' ideas on fairness into existing unsupervised machine learning algorithms. Our focus is on the task of clustering, specifically the k-means clustering algorithm. To the best of our knowledge, this is the first work that uses Rawlsian ideas in cluste...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	294,819
1905.10691	Safe Reinforcement Learning with Nonlinear Dynamics via Model Predictive Shielding	Reinforcement learning is a promising approach to synthesizing policies for challenging robotics tasks. A key problem is how to ensure safety of the learned policy---e.g., that a walking robot does not fall over or that an autonomous car does not run into an obstacle. We focus on the setting where the dynamics are know...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,152
cs/0611011	Hedging predictions in machine learning	Recent advances in machine learning make it possible to design efficient prediction algorithms for data sets with huge numbers of parameters. This paper describes a new technique for "hedging" the predictions output by many such algorithms, including support vector machines, kernel ridge regression, kernel nearest neig...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	539,847
2104.12158	Computing a Task-Dependent Grasp Metric Using Second Order Cone Programs	Evaluating a grasp generated by a set of hand-object contact locations is a key component of many grasp planning algorithms. In this paper, we present a novel second order cone program (SOCP) based optimization formulation for evaluating a grasps' ability to apply wrenches to generate a linear motion along a given dire...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	232,131
0902.3725	Statistical Inference of Functional Connectivity in Neuronal Networks using Frequent Episodes	Identifying the spatio-temporal network structure of brain activity from multi-neuronal data streams is one of the biggest challenges in neuroscience. Repeating patterns of precisely timed activity across a group of neurons is potentially indicative of a microcircuit in the underlying neural tissue. Frequent episode di...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	3,212
1911.03127	AI Aided Noise Processing of Spintronic Based IoT Sensor for Magnetocardiography Application	As we are about to embark upon the highly hyped "Society 5.0", powered by the Internet of Things (IoT), traditional ways to monitor human heart signals for tracking cardio-vascular conditions are challenging, particularly in remote healthcare settings. On the merits of low power consumption, portability, and non-intrus...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,566
2501.15446	Token Democracy: The Architectural Limits of Alignment in Transformer-Based Language Models	Modern language models paradoxically combine unprecedented capability with persistent vulnerability in that they can draft poetry yet cannot reliably refuse harmful requests. We reveal this fragility stems not from inadequate training, but from a fundamental architectural limitation: transformers process all tokens as ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	527,561
2205.02919	Action Languages Based Actual Causality for Computational Ethics: a Sound and Complete Implementation in ASP	Although moral responsibility is not circumscribed by causality, they are both closely intermixed. Furthermore, rationally understanding the evolution of the physical world is inherently linked with the idea of causality. Thus, the decision-making applications based on automated planning inevitably have to deal with ca...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	295,107
1905.04579	Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification	Graph Neural Nets (GNNs) have received increasing attentions, partially due to their superior performance in many node and graph classification tasks. However, there is a lack of understanding on what they are learning and how sophisticated the learned graph functions are. In this work, we propose a dissection of GNNs ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	130,509
2305.10664	Posterior Inference on Shallow Infinitely Wide Bayesian Neural Networks under Weights with Unbounded Variance	From the classical and influential works of Neal (1996), it is known that the infinite width scaling limit of a Bayesian neural network with one hidden layer is a Gaussian process, when the network weights have bounded prior variance. Neal's result has been extended to networks with multiple hidden layers and to convol...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	365,169
2012.00187	Statistical patterns of word frequency suggesting the probabilistic nature of human languages	Traditional linguistic theories have largely regard language as a formal system composed of rigid rules. However, their failures in processing real language, the recent successes in statistical natural language processing, and the findings of many psychological experiments have suggested that language may be more a pro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	209,047
2107.12858	Coarse to Fine: Domain Adaptive Crowd Counting via Adversarial Scoring Network	Recent deep networks have convincingly demonstrated high capability in crowd counting, which is a critical task attracting widespread attention due to its various industrial applications. Despite such progress, trained data-dependent models usually can not generalize well to unseen scenarios because of the inherent dom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	248,029
2011.12149	SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration	Extracting robust and general 3D local features is key to downstream tasks such as point cloud registration and reconstruction. Existing learning-based local descriptors are either sensitive to rotation transformations, or rely on classical handcrafted features which are neither general nor representative. In this pape...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	208,072
2407.03896	Specification-guided temporal logic control for stochastic systems: a multi-layered approach	Designing controllers to satisfy temporal requirements has proven to be challenging for dynamical systems that are affected by uncertainty. This is mainly due to the states evolving in a continuous uncountable space, the stochastic evolution of the states, and infinite-horizon temporal requirements on the system evolut...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	470,336
2308.12494	MOFA: A Model Simplification Roadmap for Image Restoration on Mobile Devices	Image restoration aims to restore high-quality images from degraded counterparts and has seen significant advancements through deep learning techniques. The technique has been widely applied to mobile devices for tasks such as mobile photography. Given the resource limitations on mobile devices, such as memory constrai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	387,554
2011.05927	On Using Hamiltonian Monte Carlo Sampling for Reinforcement Learning Problems in High-dimension	Value function based reinforcement learning (RL) algorithms, for example, $Q$-learning, learn optimal policies from datasets of actions, rewards, and state transitions. However, when the underlying state transition dynamics are stochastic and evolve on a high-dimensional space, generating independent and identically di...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	206,084
2303.09307	Depth Super-Resolution from Explicit and Implicit High-Frequency Features	We propose a novel multi-stage depth super-resolution network, which progressively reconstructs high-resolution depth maps from explicit and implicit high-frequency features. The former are extracted by an efficient transformer processing both local and global contexts, while the latter are obtained by projecting color...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,992
2105.08667	Image Cropping on Twitter: Fairness Metrics, their Limitations, and the Importance of Representation, Design, and Agency	Twitter uses machine learning to crop images, where crops are centered around the part predicted to be the most salient. In fall 2020, Twitter users raised concerns that the automated image cropping system on Twitter favored light-skinned over dark-skinned individuals, as well as concerns that the system favored croppi...	true	false	false	false	false	false	true	false	false	false	false	true	false	true	false	false	false	false	235,835
2410.04234	Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks	Optimization methods are widely employed in deep learning to identify and mitigate undesired model responses. While gradient-based techniques have proven effective for image models, their application to language models is hindered by the discrete nature of the input space. This study introduces a novel optimization app...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	495,187
2409.20326	MARLadona - Towards Cooperative Team Play Using Multi-Agent Reinforcement Learning	Robot soccer, in its full complexity, poses an unsolved research challenge. Current solutions heavily rely on engineered heuristic strategies, which lack robustness and adaptability. Deep reinforcement learning has gained significant traction in various complex robotics tasks such as locomotion, manipulation, and compe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	493,085
2109.12434	Emergent behavior and neural dynamics in artificial agents tracking turbulent plumes	Tracking a turbulent plume to locate its source is a complex control problem because it requires multi-sensory integration and must be robust to intermittent odors, changing wind direction, and variable plume statistics. This task is routinely performed by flying insects, often over long distances, in pursuit of food o...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	true	false	false	257,288
1907.07107	An efficient method to construct self-dual cyclic codes of length $p^s$ over $\mathbb{F}_{p^m}+u\mathbb{F}_{p^m}$	Let $p$ be an odd prime number, $\mathbb{F}_{p^m}$ be a finite field of cardinality $p^m$ and $s$ a positive integer. Using some combinatorial identities, we obtain certain properties for Kronecker product of matrices over $\mathbb{F}_p$ with a specific type. On that basis, we give an explicit representation and enumer...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	138,783
2205.01805	Splicing Detection and Localization In Satellite Imagery Using Conditional GANs	The widespread availability of image editing tools and improvements in image processing techniques allow image manipulation to be very easy. Oftentimes, easy-to-use yet sophisticated image manipulation tools yields distortions/changes imperceptible to the human observer. Distribution of forged images can have drastic r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	294,721
2404.07654	rollama: An R package for using generative large language models through Ollama	rollama is an R package that wraps the Ollama API, which allows you to run different Generative Large Language Models (GLLM) locally. The package and learning material focus on making it easy to use Ollama for annotating textual or imagine data with open-source models as well as use these models for document embedding....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	445,919
2203.17209	Adversarial Examples in Random Neural Networks with General Activations	A substantial body of empirical work documents the lack of robustness in deep learning models to adversarial examples. Recent theoretical work proved that adversarial examples are ubiquitous in two-layers networks with sub-exponential width and ReLU or smooth activations, and multi-layer ReLU networks with sub-exponent...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	289,068
2109.06912	fairseq S^2: A Scalable and Integrable Speech Synthesis Toolkit	This paper presents fairseq S^2, a fairseq extension for speech synthesis. We implement a number of autoregressive (AR) and non-AR text-to-speech models, and their multi-speaker variants. To enable training speech synthesis models with less curated data, a number of preprocessing tools are built and their importance is...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	255,315
2310.10651	HairCLIPv2: Unifying Hair Editing via Proxy Feature Blending	Hair editing has made tremendous progress in recent years. Early hair editing methods use well-drawn sketches or masks to specify the editing conditions. Even though they can enable very fine-grained local control, such interaction modes are inefficient for the editing conditions that can be easily specified by languag...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	400,327
2311.11566	Does complimentary information from multispectral imaging improve face presentation attack detection?	Presentation Attack Detection (PAD) has been extensively studied, particularly in the visible spectrum. With the advancement of sensing technology beyond the visible range, multispectral imaging has gained significant attention in this direction. We present PAD based on multispectral images constructed for eight differ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	408,995
2308.03083	Predicting Group Choices from Group Profiles	Group recommender systems (GRSs) identify items to recommend to a group of people by aggregating group members' individual preferences into a group profile, and selecting the items that have the largest score in the group profile. The GRS predicts that these recommendations would be chosen by the group, by assuming tha...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	383,891
2305.09302	Pink-Eggs Dataset V1: A Step Toward Invasive Species Management Using Deep Learning Embedded Solutions	We introduce a novel dataset consisting of images depicting pink eggs that have been identified as Pomacea canaliculata eggs, accompanied by corresponding bounding box annotations. The purpose of this dataset is to aid researchers in the analysis of the spread of Pomacea canaliculata species by utilizing deep learning ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	364,593
2501.13422	Atmospheric Noise-Resilient Image Classification in a Real-World Scenario: Using Hybrid CNN and Pin-GTSVM	Parking space occupation detection using deep learning frameworks has seen significant advancements over the past few years. While these approaches effectively detect partial obstructions and adapt to varying lighting conditions, their performance significantly diminishes when haze is present. This paper proposes a nov...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	526,683
1506.02442	NP-hardness of sortedness constraints	In Constraint Programming, global constraints allow to model and solve many combinatorial problems. Among these constraints, several sortedness constraints have been defined, for which propagation algorithms are available, but for which the tractability is not settled. We show that the sort(U,V) constraint (Older et. a...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	43,923
2305.00261	Analyzing drop coalescence in microfluidic device with a deep learning generative model	Predicting drop coalescence based on process parameters is crucial for experiment design in chemical engineering. However, predictive models can suffer from the lack of training data and more importantly, the label imbalance problem. In this study, we propose the use of deep learning generative models to tackle this bo...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	361,273
1504.04803	Algorithms and Throughput Analysis for MDS-Coded Switches	Network switches and routers need to serve packet writes and reads at rates that challenge the most advanced memory technologies. As a result, scaling the switching rates is commonly done by parallelizing the packet I/Os using multiple memory units. For improved read rates, packets can be coded with an [n,k] MDS code, ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	42,192
2409.14122	Efficient and Effective Model Extraction	Model extraction aims to create a functionally similar copy from a machine learning as a service (MLaaS) API with minimal overhead, typically for illicit profit or as a precursor to further attacks, posing a significant threat to the MLaaS ecosystem. However, recent studies have shown that model extraction is highly in...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	490,339
2409.00292	REFFLY: Melody-Constrained Lyrics Editing Model	Automatic melody-to-lyric generation aims to produce lyrics that align with a given melody. Although previous work can generate lyrics based on high-level control signals, such as keywords or genre, they often struggle with three challenges: (1) lack of controllability, as prior works are only able to produce lyrics fr...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	484,859
2006.06207	Pairwise Supervision Can Provably Elicit a Decision Boundary	Similarity learning is a general problem to elicit useful representations by predicting the relationship between a pair of patterns. This problem is related to various important preprocessing tasks such as metric learning, kernel learning, and contrastive learning. A classifier built upon the representations is expecte...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,350
1307.6303	Matching-Constrained Active Contours	In object segmentation by active contours, the initial contour is often required. Conventionally, the initial contour is provided by the user. This paper extends the conventional active contour model by incorporating feature matching in the formulation, which gives rise to a novel matching-constrained active contour. T...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	26,014
2308.02870	ApproBiVT: Lead ASR Models to Generalize Better Using Approximated Bias-Variance Tradeoff Guided Early Stopping and Checkpoint Averaging	The conventional recipe for Automatic Speech Recognition (ASR) models is to 1) train multiple checkpoints on a training set while relying on a validation set to prevent overfitting using early stopping and 2) average several last checkpoints or that of the lowest validation losses to obtain the final model. In this pap...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	383,800
2411.14593	A Systematic Study of Multi-Agent Deep Reinforcement Learning for Safe and Robust Autonomous Highway Ramp Entry	Vehicles today can drive themselves on highways and driverless robotaxis operate in major cities, with more sophisticated levels of autonomous driving expected to be available and become more common in the future. Yet, technically speaking, so-called "Level 5" (L5) operation, corresponding to full autonomy, has not bee...	false	false	false	false	true	false	true	true	false	false	true	false	false	false	true	false	false	false	510,241
1906.01408	Hypothesis-Driven Skill Discovery for Hierarchical Deep Reinforcement Learning	Deep reinforcement learning (DRL) is capable of learning high-performing policies on a variety of complex high-dimensional tasks, ranging from video games to robotic manipulation. However, standard DRL methods often suffer from poor sample efficiency, partially because they aim to be entirely problem-agnostic. In this ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	133,703
1206.4687	Cyclic Codes from APN and Planar Functions	Cyclic codes are a subclass of linear codes and have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this paper, almost perfect nonlinear functions and planar functions over finite fields are employed to construct a number...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,738
2109.13698	Anomaly Detection for High-Dimensional Data Using Large Deviations Principle	Most current anomaly detection methods suffer from the curse of dimensionality when dealing with high-dimensional data. We propose an anomaly detection algorithm that can scale to high-dimensional data using concepts from the theory of large deviations. The proposed Large Deviations Anomaly Detection (LAD) algorithm is...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	257,716
1903.10974	Verification of Very Low-Resolution Faces Using An Identity-Preserving Deep Face Super-Resolution Network	Face super-resolution methods usually aim at producing visually appealing results rather than preserving distinctive features for further face identification. In this work, we propose a deep learning method for face verification on very low-resolution face images that involves identity-preserving face super-resolution....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,407
1803.11361	DDRprog: A CLEVR Differentiable Dynamic Reasoning Programmer	We present a novel Dynamic Differentiable Reasoning (DDR) framework for jointly learning branching programs and the functions composing them; this resolves a significant nondifferentiability inhibiting recent dynamic architectures. We apply our framework to two settings in two highly compact and data efficient architec...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	93,878
2101.10351	A Receding Horizon Approach for Simultaneous Active Learning and Control using Gaussian Processes	This paper proposes a receding horizon active learning and control problem for dynamical systems in which Gaussian Processes (GPs) are utilized to model the system dynamics. The active learning objective in the optimization problem is presented by the exact conditional differential entropy of GP predictions at multiple...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	216,897
2303.18047	Differentially Private Stochastic Convex Optimization in (Non)-Euclidean Space Revisited	In this paper, we revisit the problem of Differentially Private Stochastic Convex Optimization (DP-SCO) in Euclidean and general $\ell_p^d$ spaces. Specifically, we focus on three settings that are still far from well understood: (1) DP-SCO over a constrained and bounded (convex) set in Euclidean space; (2) unconstrain...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	355,446
2102.07360	Generating Structured Adversarial Attacks Using Frank-Wolfe Method	White box adversarial perturbations are generated via iterative optimization algorithms most often by minimizing an adversarial loss on a $\ell_p$ neighborhood of the original image, the so-called distortion set. Constraining the adversarial search with different norms results in disparately structured adversarial exam...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	220,084
2302.10626	Lightweight-Yet-Efficient: Revitalizing Ball-Tree for Point-to-Hyperplane Nearest Neighbor Search	Finding the nearest neighbor to a hyperplane (or Point-to-Hyperplane Nearest Neighbor Search, simply P2HNNS) is a new and challenging problem with applications in many research domains. While existing state-of-the-art hashing schemes (e.g., NH and FH) are able to achieve sublinear time complexity without the assumption...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	true	346,872
2204.03498	On the Effectiveness of Pretrained Models for API Learning	Developers frequently use APIs to implement certain functionalities, such as parsing Excel Files, reading and writing text files line by line, etc. Developers can greatly benefit from automatic API usage sequence generation based on natural language queries for building applications in a faster and cleaner manner. Exis...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	290,320
2203.01623	ETCetera: beyond Event-Triggered Control	We present ETCetera, a Python library developed for the analysis and synthesis of the sampling behaviour of event triggered control (ETC) systems. In particular, the tool constructs abstractions of the sampling behaviour of given ETC systems, in the form of timed automata (TA) or finite-state transition systems (FSTSs)...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	283,453
2003.07333	RSVQA: Visual Question Answering for Remote Sensing Data	This paper introduces the task of visual question answering for remote sensing data (RSVQA). Remote sensing images contain a wealth of information which can be useful for a wide range of tasks including land cover classification, object counting or detection. However, most of the available methodologies are task-specif...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,393
1605.03428	Image-level Classification in Hyperspectral Images using Feature Descriptors, with Application to Face Recognition	In this paper, we proposed a novel pipeline for image-level classification in the hyperspectral images. By doing this, we show that the discriminative spectral information at image-level features lead to significantly improved performance in a face recognition task. We also explored the potential of traditional feature...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	55,746
1911.01711	LACI: Low-effort Automatic Calibration of Infrastructure Sensors	Sensor calibration usually is a time consuming yet important task. While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping field of view (FOV), within this work, a cooperative intelligent vehicle is used as callibration target. The vehicleis detected in the sens...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	152,185
1912.03251	A Benchmark for Lidar Sensors in Fog: Is Detection Breaking Down?	Autonomous driving at level five does not only means self-driving in the sunshine. Adverse weather is especially critical because fog, rain, and snow degrade the perception of the environment. In this work, current state of the art light detection and ranging (lidar) sensors are tested in controlled conditions in a fog...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,547
2406.07721	Co-designing a Child-Robot Relational Norm Intervention to Regulate Children's Handwriting Posture	Persuasive social robots employ their social influence to modulate children's behaviours in child-robot interaction. In this work, we introduce the Child-Robot Relational Norm Intervention (CRNI) model, leveraging the passive role of social robots and children's reluctance to inconvenience others to influence children'...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	463,179
2407.20062	SalNAS: Efficient Saliency-prediction Neural Architecture Search with self-knowledge distillation	Recent advancements in deep convolutional neural networks have significantly improved the performance of saliency prediction. However, the manual configuration of the neural network architectures requires domain knowledge expertise and can still be time-consuming and error-prone. To solve this, we propose a new Neural ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	477,032
2310.04517	Domain Randomization for Sim2real Transfer of Automatically Generated Grasping Datasets	Robotic grasping refers to making a robotic system pick an object by applying forces and torques on its surface. Many recent studies use data-driven approaches to address grasping, but the sparse reward nature of this task made the learning process challenging to bootstrap. To avoid constraining the operational space, ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	397,694
2003.08533	Clustering with Fast, Automated and Reproducible assessment applied to longitudinal neural tracking	Across many areas, from neural tracking to database entity resolution, manual assessment of clusters by human experts presents a bottleneck in rapid development of scalable and specialized clustering methods. To solve this problem we develop C-FAR, a novel method for Fast, Automated and Reproducible assessment of multi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	168,767
1912.12898	PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection	We propose a single-stage Human-Object Interaction (HOI) detection method that has outperformed all existing methods on HICO-DET dataset at 37 fps on a single Titan XP GPU. It is the first real-time HOI detection method. Conventional HOI detection methods are composed of two stages, i.e., human-object proposals generat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,964
2402.14798	Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic	Recent language models enable new opportunities for structured reasoning with text, such as the construction of intuitive, proof-like textual entailment trees without relying on brittle formal logic. However, progress in this direction has been hampered by a long-standing lack of a clear protocol for determining what v...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	431,838
2303.02430	CFlowNets: Continuous Control with Generative Flow Networks	Generative flow networks (GFlowNets), as an emerging technique, can be used as an alternative to reinforcement learning for exploratory control tasks. GFlowNet aims to generate distribution proportional to the rewards over terminating states, and to sample different candidates in an active learning fashion. GFlowNets n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	349,355
1707.04896	An Accelerated Testing Approach for Automated Vehicles with Background Traffic Described by Joint Distributions	This paper proposes a new framework based on joint statistical models for evaluating risks of automated vehicles in a naturalistic driving environment. The previous studies on the Accelerated Evaluation for automated vehicles are extended from multi-independent-variate models to joint statistics. The proposed toolkit i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	77,123
2204.03635	Zero-Shot Category-Level Object Pose Estimation	Object pose estimation is an important component of most vision pipelines for embodied agents, as well as in 3D vision more generally. In this paper we tackle the problem of estimating the pose of novel object categories in a zero-shot manner. This extends much of the existing literature by removing the need for pose-l...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	290,375
2310.06822	Neural Bounding	Bounding volumes are an established concept in computer graphics and vision tasks but have seen little change since their early inception. In this work, we study the use of neural networks as bounding volumes. Our key observation is that bounding, which so far has primarily been considered a problem of computational ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	398,722
1505.05114	Solving Random Quadratic Systems of Equations Is Nearly as Easy as Solving Linear Systems	We consider the fundamental problem of solving quadratic systems of equations in $n$ variables, where $y_i = \|\langle \boldsymbol{a}_i, \boldsymbol{x} \rangle\|^2$, $i = 1, \ldots, m$ and $\boldsymbol{x} \in \mathbb{R}^n$ is unknown. We propose a novel method, which starting with an initial guess computed by means of a ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	43,262
2009.00328	Secrecy Outage Analysis of Two-Hop Decode-and-Forward Mixed RF/UWOC Systems	We analyze the secrecy performance of a two-hop mixed radio frequency (RF)/underwater wireless optical communication (UWOC) system using a decode-and-forward (DF) relay. All RF and UWOC links are modeled by the $\alpha-\mu$ and exponential-generalized Gamma distributions, respectively. We first derive the expressions o...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	194,020
2101.09870	Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst Images	Denoising and demosaicking are essential yet correlated steps to reconstruct a full color image from the raw color filter array (CFA) data. By learning a deep convolutional neural network (CNN), significant progress has been achieved to perform denoising and demosaicking jointly. However, most existing CNN-based joint ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,746
2306.12621	RXFOOD: Plug-in RGB-X Fusion for Object of Interest Detection	The emergence of different sensors (Near-Infrared, Depth, etc.) is a remedy for the limited application scenarios of traditional RGB camera. The RGB-X tasks, which rely on RGB input and another type of data input to resolve specific problems, have become a popular research topic in multimedia. A crucial part in two-bra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,998
1806.03084	Unifying Identification and Context Learning for Person Recognition	Despite the great success of face recognition techniques, recognizing persons under unconstrained settings remains challenging. Issues like profile views, unfavorable lighting, and occlusions can cause substantial difficulties. Previous works have attempted to tackle this problem by exploiting the context, e.g. clothes...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	99,919
2412.11940	The Impact of Token Granularity on the Predictive Power of Language Model Surprisal	Word-by-word language model surprisal is often used to model the incremental processing of human readers, which raises questions about how various choices in language modeling influence its predictive power. One factor that has been overlooked in cognitive modeling is the granularity of subword tokens, which explicitly...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	517,649
2401.03467	Maintaining Journalistic Integrity in the Digital Age: A Comprehensive NLP Framework for Evaluating Online News Content	The rapid growth of online news platforms has led to an increased need for reliable methods to evaluate the quality and credibility of news articles. This paper proposes a comprehensive framework to analyze online news texts using natural language processing (NLP) techniques, particularly a language model specifically ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	420,114
2303.03991	OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception	Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant benchmarks lack diversity in urban scenes, and they only evaluate front-view predictions. Towards a comprehensive benchmarking of surrounding ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	349,924
2401.12406	Enhancing In-context Learning via Linear Probe Calibration	In-context learning (ICL) is a new paradigm for natural language processing that utilizes Generative Pre-trained Transformer (GPT)-like models. This approach uses prompts that include in-context demonstrations to generate the corresponding output for a new query input. However, applying ICL in real cases does not scale...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	423,359
2410.01028	Draft on the Fly: Adaptive Self-Speculative Decoding using Cosine Similarity	We present a simple on the fly method for faster inference of large language models. Unlike other (self-)speculative decoding techniques, our method does not require fine-tuning or black-box optimization to generate a fixed draft model, relying instead on simple rules to generate varying draft models adapted to the inp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	493,570
2012.08630	Open Problems in Cooperative AI	Problems of cooperation--in which agents seek ways to jointly improve their welfare--are ubiquitous and important. They can be found at scales ranging from our daily routines--such as driving on highways, scheduling meetings, and working collaboratively--to our global challenges--such as peace, commerce, and pandemic p...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	211,811
1705.01462	Ternary Neural Networks with Fine-Grained Quantization	We propose a novel fine-grained quantization (FGQ) method to ternarize pre-trained full precision models, while also constraining activations to 8 and 4-bits. Using this method, we demonstrate a minimal loss in classification accuracy on state-of-the-art topologies without additional training. We provide an improved th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	72,847
2305.02374	A Novel Plagiarism Detection Approach Combining BERT-based Word Embedding, Attention-based LSTMs and an Improved Differential Evolution Algorithm	Detecting plagiarism involves finding similar items in two different sources. In this article, we propose a novel method for detecting plagiarism that is based on attention mechanism-based long short-term memory (LSTM) and bidirectional encoder representations from transformers (BERT) word embedding, enhanced with opti...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	362,009
1512.04650	Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation	The attentional mechanism has proven to be effective in improving end-to-end neural machine translation. However, due to the intricate structural divergence between natural languages, unidirectional attention-based models might only capture partial aspects of attentional regularities. We propose agreement-based joint t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	50,151
2409.08185	Fine-tuning Large Language Models for Entity Matching	Generative large language models (LLMs) are a promising alternative to pre-trained language models for entity matching due to their high zero-shot performance and their ability to generalize to unseen entities. Existing research on using LLMs for entity matching has focused on prompt engineering and in-context learning...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	487,801
2210.01330	Doubly-Irregular Repeat-Accumulate Codes over Integer Rings for Multi-user Communications	Structured codes based on lattices were shown to provide enlarged capacity for multi-user communication networks. In this paper, we study capacity-approaching irregular repeat accumulate (IRA) codes over integer rings $\mathbb{Z}_{2^{m}}$ for $2^m$-PAM signaling, $m=1,2,\cdots$. Such codes feature the property that the...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	321,220
2309.15130	Understanding the Structure of QM7b and QM9 Quantum Mechanical Datasets Using Unsupervised Learning	This paper explores the internal structure of two quantum mechanics datasets (QM7b, QM9), composed of several thousands of organic molecules and described in terms of electronic properties. Understanding the structure and characteristics of this kind of data is important when predicting the atomic composition from the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	394,861
2311.15073	A discontinuous Galerkin method based isogeometric analysis framework for flexoelectricity in micro-architected dielectric solids	Flexoelectricity - the generation of electric field in response to a strain gradient - is a universal electromechanical coupling, dominant only at small scales due to its requirement of high strain gradients. This phenomenon is governed by a set of coupled fourth-order partial differential equations (PDEs), which requi...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	410,372
1611.01939	Artificial-Noise-Aided Secure Transmission in Wiretap Channels with Transmitter-Side Correlation	This work for the first time examines the impact of transmitter-side correlation on the artificial-noise-aided secure transmission, based on which a new power allocation strategy for artificial noise (AN) is devised for physical layer security enhancement. Specifically, we design a correlation-based power allocation (C...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	63,471
2304.13976	Moderately Distributional Exploration for Domain Generalization	Domain generalization (DG) aims to tackle the distribution shift between training domains and unknown target domains. Generating new domains is one of the most effective approaches, yet its performance gain depends on the distribution discrepancy between the generated and target domains. Distributionally robust optimiz...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	360,777
2210.08871	Industry-Scale Orchestrated Federated Learning for Drug Discovery	To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n{\deg}831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	324,332
2205.12393	Fine-tuned Language Models are Continual Learners	Recent work on large language models relies on the intuition that most natural language processing tasks can be described via natural language instructions. Language models trained on these instructions show strong zero-shot performance on several standard datasets. However, these models even though impressive still pe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	298,509
2005.11445	Evaluation of Non-Collocated Force Feedback Driven by Signal-Independent Noise	Individuals living with paralysis or amputation can operate robotic prostheses using input signals based on their intent or attempt to move. Because sensory function is lost or diminished in these individuals, haptic feedback must be non-collocated. The intracortical brain computer interface (iBCI) has enabled a variet...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	178,475
1901.02052	Multi-Source Transfer Learning for Non-Stationary Environments	In data stream mining, predictive models typically suffer drops in predictive performance due to concept drift. As enough data representing the new concept must be collected for the new concept to be well learnt, the predictive performance of existing models usually takes some time to recover from concept drift. To spe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	118,115
2311.08815	Self-Supervised Disentanglement by Leveraging Structure in Data Augmentations	Self-supervised representation learning often uses data augmentations to induce some invariance to "style" attributes of the data. However, with downstream tasks generally unknown at training time, it is difficult to deduce a priori which attributes of the data are indeed "style" and can be safely discarded. To deal wi...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	407,878

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