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
2306.17575	Augmenting Holistic Review in University Admission using Natural Language Processing for Essays and Recommendation Letters	University admission at many highly selective institutions uses a holistic review process, where all aspects of the application, including protected attributes (e.g., race, gender), grades, essays, and recommendation letters are considered, to compose an excellent and diverse class. In this study, we empirically evalua...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	376,748
2110.04022	Learning Sparse Graphs with a Core-periphery Structure	In this paper, we focus on learning sparse graphs with a core-periphery structure. We propose a generative model for data associated with core-periphery structured networks to model the dependence of node attributes on core scores of the nodes of a graph through a latent graph structure. Using the proposed model, we jo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,718
0706.3753	Multiple Access Channels with Generalized Feedback and Confidential Messages	This paper considers the problem of secret communication over a multiple access channel with generalized feedback. Two trusted users send independent confidential messages to an intended receiver, in the presence of a passive eavesdropper. In this setting, an active cooperation between two trusted users is enabled thro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	357
1811.04301	Centralized adaptive traffic control strategy design across multiple intersections based on vehicle path flows: An approximated Lagrangian decomposition approach	In this paper, we first present a centralized traffic control model based on the emerging dynamic path flows. This new model in essence views the whole target network as one integral piece in which traffic propagates based on traffic flow dynamics, vehicle paths, and traffic control. In light of this centralized traffi...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	113,049
2009.13979	On the Outage Performance of SWIPT-NOMA-CRS with imperfect SIC and CSI	In this paper, a non-orthogonal multiple access based cooperative relaying system (NOMA-CRS) is considered to increase spectral efficiency. Besides, the simultaneous wireless information and power transfer (SWIPT) is proposed for the relay in NOMA-CRS. In SWIPT-NOMA-CRS, three different energy harvesting (EH) protocols...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	197,905
2311.07093	On the Effectiveness of ASR Representations in Real-world Noisy Speech Emotion Recognition	This paper proposes an efficient attempt to noisy speech emotion recognition (NSER). Conventional NSER approaches have proven effective in mitigating the impact of artificial noise sources, such as white Gaussian noise, but are limited to non-stationary noises in real-world environments due to their complexity and unce...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	407,195
1707.00383	Physics Inspired Optimization on Semantic Transfer Features: An Alternative Method for Room Layout Estimation	In this paper, we propose an alternative method to estimate room layouts of cluttered indoor scenes. This method enjoys the benefits of two novel techniques. The first one is semantic transfer (ST), which is: (1) a formulation to integrate the relationship between scene clutter and room layout into convolutional neural...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	76,340
2111.15656	Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection	3D object detection networks tend to be biased towards the data they are trained on. Evaluation on datasets captured in different locations, conditions or sensors than that of the training (source) data results in a drop in model performance due to the gap in distribution with the test (or target) data. Current methods...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,005
1805.02350	Efficient active learning of sparse halfspaces	We study the problem of efficient PAC active learning of homogeneous linear classifiers (halfspaces) in $\mathbb{R}^d$, where the goal is to learn a halfspace with low error using as few label queries as possible. Under the extra assumption that there is a $t$-sparse halfspace that performs well on the data ($t \ll d$)...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,847
1805.05286	AMR Parsing as Graph Prediction with Latent Alignment	Abstract meaning representations (AMRs) are broad-coverage sentence-level semantic representations. AMRs represent sentences as rooted labeled directed acyclic graphs. AMR parsing is challenging partly due to the lack of annotated alignments between nodes in the graphs and words in the corresponding sentences. We intro...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	97,400
2007.09410	Optimizing Off-Chain Payment Networks in Cryptocurrencies	Off-chain transaction channels represent one of the leading techniques to scale the transaction throughput in cryptocurrencies such as Bitcoin. They allow multiple agents to route payments through one another. So far, the topology and construction of payment networks has not been explored much. Participants are expecte...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	187,937
1912.04485	NeuRoRA: Neural Robust Rotation Averaging	Multiple rotation averaging is an essential task for structure from motion, mapping, and robot navigation. The task is to estimate the absolute orientations of several cameras given some of their noisy relative orientation measurements. The conventional methods for this task seek parameters of the absolute orientations...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,857
1705.10272	Who's to say what's funny? A computer using Language Models and Deep Learning, That's Who!	Humor is a defining characteristic of human beings. Our goal is to develop methods that automatically detect humorous statements and rank them on a continuous scale. In this paper we report on results using a Language Model approach, and outline our plans for using methods from Deep Learning.	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	74,363
2109.06906	Recovering individual emotional states from sparse ratings using collaborative filtering	A fundamental challenge in emotion research is measuring feeling states with high granularity and temporal precision without disrupting the emotion generation process. Here we introduce and validate a new approach in which responses are sparsely sampled and the missing data are recovered using a computational technique...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	255,311
2211.15440	Near-Field Channel Estimation for Extremely Large-Scale Array Communications: A model-based deep learning approach	Extremely large-scale massive MIMO (XL-MIMO) has been reviewed as a promising technology for future wireless communications. The deployment of XL-MIMO, especially at high-frequency bands, leads to users being located in the near-field region instead of the conventional far-field. This letter proposes efficient model-ba...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	333,267
2502.00528	Vision-Language Modeling in PET/CT for Visual Grounding of Positive Findings	Vision-language models can connect the text description of an object to its specific location in an image through visual grounding. This has potential applications in enhanced radiology reporting. However, these models require large annotated image-text datasets, which are lacking for PET/CT. We developed an automated ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	529,421
2301.02555	"No, to the Right" -- Online Language Corrections for Robotic Manipulation via Shared Autonomy	Systems for language-guided human-robot interaction must satisfy two key desiderata for broad adoption: adaptivity and learning efficiency. Unfortunately, existing instruction-following agents cannot adapt, lacking the ability to incorporate online natural language supervision, and even if they could, require hundreds ...	true	false	false	false	true	false	true	true	true	false	false	false	false	false	false	false	false	false	339,535
1909.06794	Run-Length Encoding in a Finite Universe	Text compression schemes and compact data structures usually combine sophisticated probability models with basic coding methods whose average codeword length closely match the entropy of known distributions. In the frequent case where basic coding represents run-lengths of outcomes that have probability $p$, i.e. the g...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	145,485
1308.0761	On estimating total time to solve SAT in distributed computing environments: Application to the SAT@home project	This paper proposes a method to estimate the total time required to solve SAT in distributed environments via partitioning approach. It is based on the observation that for some simple forms of problem partitioning one can use the Monte Carlo approach to estimate the time required to solve an original problem. The meth...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	true	26,250
1602.03585	Generating Discriminative Object Proposals via Submodular Ranking	A multi-scale greedy-based object proposal generation approach is presented. Based on the multi-scale nature of objects in images, our approach is built on top of a hierarchical segmentation. We first identify the representative and diverse exemplar clusters within each scale by using a diversity ranking algorithm. Obj...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	52,018
2306.00256	DSGD-CECA: Decentralized SGD with Communication-Optimal Exact Consensus Algorithm	Decentralized Stochastic Gradient Descent (SGD) is an emerging neural network training approach that enables multiple agents to train a model collaboratively and simultaneously. Rather than using a central parameter server to collect gradients from all the agents, each agent keeps a copy of the model parameters and com...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	369,933
1708.08177	Hyperprior on symmetric Dirichlet distribution	In this article we introduce how to put vague hyperprior on Dirichlet distribution, and we update the parameter of it by adaptive rejection sampling (ARS). Finally we analyze this hyperprior in an over-fitted mixture model by some synthetic experiments.	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	79,606
2311.04550	Regression with Cost-based Rejection	Learning with rejection is an important framework that can refrain from making predictions to avoid critical mispredictions by balancing between prediction and rejection. Previous studies on cost-based rejection only focused on the classification setting, which cannot handle the continuous and infinite target space in ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	406,270
2401.15626	TA&AT: Enhancing Task-Oriented Dialog with Turn-Level Auxiliary Tasks and Action-Tree Based Scheduled Sampling	Task-oriented dialog systems have witnessed substantial progress due to conversational pre-training techniques. Yet, two significant challenges persist. First, most systems primarily utilize the latest turn's state label for the generator. This practice overlooks the comprehensive value of state labels in boosting the ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	424,524
2012.15127	Improving Zero-Shot Translation by Disentangling Positional Information	Multilingual neural machine translation has shown the capability of directly translating between language pairs unseen in training, i.e. zero-shot translation. Despite being conceptually attractive, it often suffers from low output quality. The difficulty of generalizing to new translation directions suggests the model...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	213,704
1710.09085	Re-evaluating the need for Modelling Term-Dependence in Text Classification Problems	A substantial amount of research has been carried out in developing machine learning algorithms that account for term dependence in text classification. These algorithms offer acceptable performance in most cases but they are associated with a substantial cost. They require significantly greater resources to operate. T...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	83,162
1508.01755	Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking	The natural language generation (NLG) component of a spoken dialogue system (SDS) usually needs a substantial amount of handcrafting or a well-labeled dataset to be trained on. These limitations add significantly to development costs and make cross-domain, multi-lingual dialogue systems intractable. Moreover, human lan...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	45,819
1912.01954	EmbedMask: Embedding Coupling for One-stage Instance Segmentation	Current instance segmentation methods can be categorized into segmentation-based methods that segment first then do clustering, and proposal-based methods that detect first then predict masks for each instance proposal using repooling. In this work, we propose a one-stage method, named EmbedMask, that unifies both meth...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	156,218
1506.02181	The LASSO with Non-linear Measurements is Equivalent to One With Linear Measurements	Consider estimating an unknown, but structured, signal $x_0\in R^n$ from $m$ measurement $y_i=g_i(a_i^Tx_0)$, where the $a_i$'s are the rows of a known measurement matrix $A$, and, $g$ is a (potentially unknown) nonlinear and random link-function. Such measurement functions could arise in applications where the measure...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	43,884
2304.10687	VisFusion: Visibility-aware Online 3D Scene Reconstruction from Videos	We propose VisFusion, a visibility-aware online 3D scene reconstruction approach from posed monocular videos. In particular, we aim to reconstruct the scene from volumetric features. Unlike previous reconstruction methods which aggregate features for each voxel from input views without considering its visibility, we ai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,511
2403.10313	Interactive Trimming against Evasive Online Data Manipulation Attacks: A Game-Theoretic Approach	With the exponential growth of data and its crucial impact on our lives and decision-making, the integrity of data has become a significant concern. Malicious data poisoning attacks, where false values are injected into the data, can disrupt machine learning processes and lead to severe consequences. To mitigate these ...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	438,145
2108.06181	Detecting socially interacting groups using f-formation: A survey of taxonomy, methods, datasets, applications, challenges, and future research directions	Robots in our daily surroundings are increasing day by day. Their usability and acceptability largely depend on their explicit and implicit interaction capability with fellow human beings. As a result, social behavior is one of the most sought-after qualities that a robot can possess. However, there is no specific aspe...	true	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	250,527
2308.14056	CTR is not Enough: a Novel Reinforcement Learning based Ranking Approach for Optimizing Session Clicks	Ranking is a crucial module using in the recommender system. In particular, the ranking module using in our YoungTao recommendation scenario is to provide an ordered list of items to users, to maximize the click number throughout the recommendation session for each user. However, we found that the traditional ranking m...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	388,165
2203.06639	Revisiting Deep Semi-supervised Learning: An Empirical Distribution Alignment Framework and Its Generalization Bound	In this work, we revisit the semi-supervised learning (SSL) problem from a new perspective of explicitly reducing empirical distribution mismatch between labeled and unlabeled samples. Benefited from this new perspective, we first propose a new deep semi-supervised learning framework called Semi-supervised Learning by ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,183
2409.00301	ContextVLM: Zero-Shot and Few-Shot Context Understanding for Autonomous Driving using Vision Language Models	In recent years, there has been a notable increase in the development of autonomous vehicle (AV) technologies aimed at improving safety in transportation systems. While AVs have been deployed in the real-world to some extent, a full-scale deployment requires AVs to robustly navigate through challenges like heavy rain, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,866
2409.12076	Unsupervised Domain Adaptation Via Data Pruning	The removal of carefully-selected examples from training data has recently emerged as an effective way of improving the robustness of machine learning models. However, the best way to select these examples remains an open question. In this paper, we consider the problem from the perspective of unsupervised domain adapt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	489,428
2302.08381	Fast evaluation of spherical harmonics with sphericart	Spherical harmonics provide a smooth, orthogonal, and symmetry-adapted basis to expand functions on a sphere, and they are used routinely in physical and theoretical chemistry as well as in different fields of science and technology, from geology and atmospheric sciences to signal processing and computer graphics. More...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,034
2012.06954	MEME: Generating RNN Model Explanations via Model Extraction	Recurrent Neural Networks (RNNs) have achieved remarkable performance on a range of tasks. A key step to further empowering RNN-based approaches is improving their explainability and interpretability. In this work we present MEME: a model extraction approach capable of approximating RNNs with interpretable models repre...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	211,282
2501.06158	GenMol: A Drug Discovery Generalist with Discrete Diffusion	Drug discovery is a complex process that involves multiple scenarios and stages, such as fragment-constrained molecule generation, hit generation and lead optimization. However, existing molecular generative models can only tackle one or two of these scenarios and lack the flexibility to address various aspects of the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,858
2409.09795	CROSS-JEM: Accurate and Efficient Cross-encoders for Short-text Ranking Tasks	Ranking a set of items based on their relevance to a given query is a core problem in search and recommendation. Transformer-based ranking models are the state-of-the-art approaches for such tasks, but they score each query-item independently, ignoring the joint context of other relevant items. This leads to sub-optima...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	488,479
1805.01618	Distribution Assertive Regression	In regression modelling approach, the main step is to fit the regression line as close as possible to the target variable. In this process most algorithms try to fit all of the data in a single line and hence fitting all parts of target variable in one go. It was observed that the error between predicted and target var...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	96,683
1707.03199	A Cognitive Theory-based Opportunistic Resource-Pooling Scheme for Ad hoc Networks	Resource pooling in ad hoc networks deals with accumulating computing and network resources to implement network control schemes such as routing, congestion, traffic management, and so on. Pooling of resources can be accomplished using the distributed and dynamic nature of ad hoc networks to achieve collaboration betwe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	76,821
2205.13532	Selective Classification Via Neural Network Training Dynamics	Selective classification is the task of rejecting inputs a model would predict incorrectly on through a trade-off between input space coverage and model accuracy. Current methods for selective classification impose constraints on either the model architecture or the loss function; this inhibits their usage in practice....	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	298,971
2203.10944	Spreadsheet computing with Finite Domain Constraint Enhancements	Spreadsheet computing is one of the more popular computing methodologies in today's modern society. The spreadsheet application's ease of use and usefulness has enabled non-programmers to perform programming-like tasks in a familiar setting modeled after the tabular "pen and paper" approach. However, spreadsheet applic...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	286,743
2112.02548	Generative Modeling of Turbulence	We present a mathematically well founded approach for the synthetic modeling of turbulent flows using generative adversarial networks (GAN). Based on the analysis of chaotic, deterministic systems in terms of ergodicity, we outline a mathematical proof that GAN can actually learn to sample state snapshots form the inva...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,883
2404.08303	A Large Scale Survey of Motivation in Software Development and Analysis of its Validity	Context: Motivation is known to improve performance. In software development in particular, there has been considerable interest in the motivation of contributors to open source. Objective: We identify 11 motivators from the literature (enjoying programming, ownership of code, learning, self use, etc.), and evaluate th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	446,187
2402.08183	Pixel Sentence Representation Learning	Pretrained language models are long known to be subpar in capturing sentence and document-level semantics. Though heavily investigated, transferring perturbation-based methods from unsupervised visual representation learning to NLP remains an unsolved problem. This is largely due to the discreteness of subword units br...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	428,993
1310.2805	MizAR 40 for Mizar 40	As a present to Mizar on its 40th anniversary, we develop an AI/ATP system that in 30 seconds of real time on a 14-CPU machine automatically proves 40% of the theorems in the latest official version of the Mizar Mathematical Library (MML). This is a considerable improvement over previous performance of large- theory AI...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	27,702
2002.12217	Multi-agent maintenance scheduling based on the coordination between central operator and decentralized producers in an electricity market	Condition-based and predictive maintenance enable early detection of critical system conditions and thereby enable decision makers to forestall faults and mitigate them. However, decision makers also need to take the operational and production needs into consideration for optimal decision-making when scheduling mainten...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	165,961
2212.08798	Leveraging Wastewater Monitoring for COVID-19 Forecasting in the US: a Deep Learning study	The outburst of COVID-19 in late 2019 was the start of a health crisis that shook the world and took millions of lives in the ensuing years. Many governments and health officials failed to arrest the rapid circulation of infection in their communities. The long incubation period and the large proportion of asymptomatic...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	336,876
2205.00570	Budgeted Classification with Rejection: An Evolutionary Method with Multiple Objectives	Classification systems are often deployed in resource-constrained settings where labels must be assigned to inputs on a budget of time, memory, etc. Budgeted, sequential classifiers (BSCs) address these scenarios by processing inputs through a sequence of partial feature acquisition and evaluation steps with early-exit...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	294,306
2112.05779	Quantum Architecture Search via Continual Reinforcement Learning	Quantum computing has promised significant improvement in solving difficult computational tasks over classical computers. Designing quantum circuits for practical use, however, is not a trivial objective and requires expert-level knowledge. To aid this endeavor, this paper proposes a machine learning-based method to co...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	270,950
2306.15217	Unsupervised Episode Generation for Graph Meta-learning	We propose Unsupervised Episode Generation method called Neighbors as Queries (NaQ) to solve the Few-Shot Node-Classification (FSNC) task by unsupervised Graph Meta-learning. Doing so enables full utilization of the information of all nodes in a graph, which is not possible in current supervised meta-learning methods f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	375,950
2112.06223	ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation	Code-switching is a speech phenomenon occurring when a speaker switches language during a conversation. Despite the spontaneous nature of code-switching in conversational spoken language, most existing works collect code-switching data from read speech instead of spontaneous speech. ASCEND (A Spontaneous Chinese-Englis...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,102
2001.07904	Dynamic multi-object Gaussian process models: A framework for data-driven functional modelling of human joints	Statistical shape models (SSMs) are state-of-the-art medical image analysis tools for extracting and explaining features across a set of biological structures. However, a principled and robust way to combine shape and pose features has been illusive due to three main issues: 1) Non-homogeneity of the data (data with li...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	161,155
2309.11028	The Topology and Geometry of Neural Representations	A central question for neuroscience is how to characterize brain representations of perceptual and cognitive content. An ideal characterization should distinguish different functional regions with robustness to noise and idiosyncrasies of individual brains that do not correspond to computational differences. Previous s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	393,245
1912.10519	Non-Orthogonal eMBB-URLLC Radio Access for Cloud Radio Access Networks with Analog Fronthauling	This paper considers the coexistence of Ultra Reliable Low Latency Communications (URLLC) and enhanced Mobile BroadBand (eMBB) services in the uplink of Cloud Radio Access Network (C-RAN) architecture based on the relaying of radio signals over analog fronthaul links. While Orthogonal Multiple Access (OMA) to the radio...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	158,340
2111.05934	A soft thumb-sized vision-based sensor with accurate all-round force perception	Vision-based haptic sensors have emerged as a promising approach to robotic touch due to affordable high-resolution cameras and successful computer-vision techniques. However, their physical design and the information they provide do not yet meet the requirements of real applications. We present a robust, soft, low-cos...	false	false	false	false	false	false	true	true	false	false	true	true	false	false	false	false	false	false	265,914
1110.0585	Discriminately Decreasing Discriminability with Learned Image Filters	In machine learning and computer vision, input images are often filtered to increase data discriminability. In some situations, however, one may wish to purposely decrease discriminability of one classification task (a "distractor" task), while simultaneously preserving information relevant to another (the task-of-inte...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	12,470
2210.03970	KG-MTT-BERT: Knowledge Graph Enhanced BERT for Multi-Type Medical Text Classification	Medical text learning has recently emerged as a promising area to improve healthcare due to the wide adoption of electronic health record (EHR) systems. The complexity of the medical text such as diverse length, mixed text types, and full of medical jargon, poses a great challenge for developing effective deep learning...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	322,253
2403.17122	6D Movable Antenna Enhanced Wireless Network Via Discrete Position and Rotation Optimization	Six-dimensional movable antenna (6DMA) is an effective approach to improve wireless network capacity by adjusting the 3D positions and 3D rotations of distributed antenna surfaces based on the users' spatial distribution and statistical channel information. Although continuously positioning/rotating 6DMA surfaces can a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	441,317
2108.00913	I2V-GAN: Unpaired Infrared-to-Visible Video Translation	Human vision is often adversely affected by complex environmental factors, especially in night vision scenarios. Thus, infrared cameras are often leveraged to help enhance the visual effects via detecting infrared radiation in the surrounding environment, but the infrared videos are undesirable due to the lack of detai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	248,870
2407.03834	10 Years of Fair Representations: Challenges and Opportunities	Fair Representation Learning (FRL) is a broad set of techniques, mostly based on neural networks, that seeks to learn new representations of data in which sensitive or undesired information has been removed. Methodologically, FRL was pioneered by Richard Zemel et al. about ten years ago. The basic concepts, objectives ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	470,306
1904.01620	Towards Human Body-Part Learning for Model-Free Gait Recognition	Gait based biometric aims to discriminate among people by the way or manner they walk. It represents a biometric at distance which has many advantages over other biometric modalities. State-of-the-art methods require a limited cooperation from the individuals. Consequently, contrary to other modalities, gait is a non-i...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	126,187
0805.4023	Robust Joint Source-Channel Coding for Delay-Limited Applications	In this paper, we consider the problem of robust joint source-channel coding over an additive white Gaussian noise channel. We propose a new scheme which achieves the optimal slope of the signal-to-distortion (SDR) curve (unlike the previously known coding schemes). Also, we propose a family of robust codes which toget...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,825
1907.00641	Permutohedral Attention Module for Efficient Non-Local Neural Networks	Medical image processing tasks such as segmentation often require capturing non-local information. As organs, bones, and tissues share common characteristics such as intensity, shape, and texture, the contextual information plays a critical role in correctly labeling them. Segmentation and labeling is now typically don...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,104
2408.08551	Integrating Multi-view Analysis: Multi-view Mixture-of-Expert for Textual Personality Detection	Textual personality detection aims to identify personality traits by analyzing user-generated content. To achieve this effectively, it is essential to thoroughly examine user-generated content from various perspectives. However, previous studies have struggled with automatically extracting and effectively integrating i...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	481,038
2209.10656	Learning from Symmetry: Meta-Reinforcement Learning with Symmetrical Behaviors and Language Instructions	Meta-reinforcement learning (meta-RL) is a promising approach that enables the agent to learn new tasks quickly. However, most meta-RL algorithms show poor generalization in multi-task scenarios due to the insufficient task information provided only by rewards. Language-conditioned meta-RL improves the generalization c...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	318,926
2203.10593	Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation	Open-vocabulary object detection aims to detect novel object categories beyond the training set. The advanced open-vocabulary two-stage detectors employ instance-level visual-to-visual knowledge distillation to align the visual space of the detector with the semantic space of the Pre-trained Visual-Language Model (PV...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	286,603
2501.16800	DIRIGENt: End-To-End Robotic Imitation of Human Demonstrations Based on a Diffusion Model	There has been substantial progress in humanoid robots, with new skills continuously being taught, ranging from navigation to manipulation. While these abilities may seem impressive, the teaching methods often remain inefficient. To enhance the process of teaching robots, we propose leveraging a mechanism effectively u...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	528,115
2405.10991	Relative Counterfactual Contrastive Learning for Mitigating Pretrained Stance Bias in Stance Detection	Stance detection classifies stance relations (namely, Favor, Against, or Neither) between comments and targets. Pretrained language models (PLMs) are widely used to mine the stance relation to improve the performance of stance detection through pretrained knowledge. However, PLMs also embed ``bad'' pretrained knowledge...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	454,961
2306.05715	Exploring the Responses of Large Language Models to Beginner Programmers' Help Requests	Background and Context: Over the past year, large language models (LLMs) have taken the world by storm. In computing education, like in other walks of life, many opportunities and threats have emerged as a consequence. Objectives: In this article, we explore such opportunities and threats in a specific area: respondi...	true	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	true	372,308
2502.05439	Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews	The advent of large language models has ushered in a new era of agentic systems, where artificial intelligence programs exhibit remarkable autonomous decision-making capabilities across diverse domains. This paper explores agentic system workflows in the financial services industry. In particular, we build agentic crew...	false	true	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	531,607
2502.00374	A Unit-based System and Dataset for Expressive Direct Speech-to-Speech Translation	Current research in speech-to-speech translation (S2ST) primarily concentrates on translation accuracy and speech naturalness, often overlooking key elements like paralinguistic information, which is essential for conveying emotions and attitudes in communication. To address this, our research introduces a novel, caref...	false	false	true	false	false	false	false	false	true	false	false	true	false	false	false	false	false	true	529,349
2108.04751	Logical Information Cells I	In this study we explore the spontaneous apparition of visible intelligible reasoning in simple artificial networks, and we connect this experimental observation with a notion of semantic information. We start with the reproduction of a DNN model of natural neurons in monkeys, studied by Neromyliotis and Moschovakis in...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	250,105
1909.03850	Robust Multi-Modality Multi-Object Tracking	Multi-sensor perception is crucial to ensure the reliability and accuracy in autonomous driving system, while multi-object tracking (MOT) improves that by tracing sequential movement of dynamic objects. Most current approaches for multi-sensor multi-object tracking are either lack of reliability by tightly relying on a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	144,622
2402.17062	HOISDF: Constraining 3D Hand-Object Pose Estimation with Global Signed Distance Fields	Human hands are highly articulated and versatile at handling objects. Jointly estimating the 3D poses of a hand and the object it manipulates from a monocular camera is challenging due to frequent occlusions. Thus, existing methods often rely on intermediate 3D shape representations to increase performance. These repre...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	432,822
1711.05417	On the Anti-Jamming Performance of the NR-DCSK System	This paper investigates the anti-jamming performance of the NR-DCSK system. We consider several practical jamming environments including broad-band jamming (BBJ), partial-time jamming (PTJ), tone jamming (TJ) consisting of both single-tone and multi-tone, and sweep jamming (SWJ). We first analytically derived the bit e...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	84,564
2204.09362	Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selection	We study short-term prediction of wind speed and wind power (every 10 minutes up to 4 hours ahead). Accurate forecasts for these quantities are crucial to mitigate the negative effects of wind farms' intermittent production on energy systems and markets. We use machine learning to combine outputs from numerical weather...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	292,412
2207.02120	Bayesian NVH metamodels to assess interior cabin noise using measurement databases	In recent years, a great emphasis has been put on engineering the acoustic signature of vehicles that represents the overall comfort level for passengers. Due to highly uncertain behavior of production cars, probabilistic metamodels or surrogates can be useful to estimate the NVH dispersion and assess different NVH ris...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	306,408
2309.15719	Model Share AI: An Integrated Toolkit for Collaborative Machine Learning Model Development, Provenance Tracking, and Deployment in Python	Machine learning (ML) has the potential to revolutionize a wide range of research areas and industries, but many ML projects never progress past the proof-of-concept stage. To address this issue, we introduce Model Share AI (AIMS), an easy-to-use MLOps platform designed to streamline collaborative model development, mo...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	395,085
2402.15044	Fiducial Focus Augmentation for Facial Landmark Detection	Deep learning methods have led to significant improvements in the performance on the facial landmark detection (FLD) task. However, detecting landmarks in challenging settings, such as head pose changes, exaggerated expressions, or uneven illumination, continue to remain a challenge due to high variability and insuffic...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	431,967
2411.03855	MambaPEFT: Exploring Parameter-Efficient Fine-Tuning for Mamba	An ecosystem of Transformer-based models has been established by building large models with extensive data. Parameter-efficient fine-tuning (PEFT) is a crucial technology for deploying these models to downstream tasks with minimal cost while achieving effective performance. Recently, Mamba, a State Space Model (SSM)-ba...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	506,062
2201.10785	Security-Constrained Optimal Operation of Energy-Water Nexus based on a Fast Contingency Filtering Method	Water and power systems are increasingly interdependent due to the growing number of electricity-driven water facilities. The security of one system can be affected by a contingency in the other system. This paper investigates a security-constrained operation problem of the energy-water nexus (EWN), which is a computat...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	277,103
2305.02970	Functional Properties of the Ziv-Zakai bound with Arbitrary Inputs	This paper explores the Ziv-Zakai bound (ZZB), which is a well-known Bayesian lower bound on the Minimum Mean Squared Error (MMSE). First, it is shown that the ZZB holds without any assumption on the distribution of the estimand, that is, the estimand does not necessarily need to have a probability density function. Th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	362,230
2209.11908	Fast Lifelong Adaptive Inverse Reinforcement Learning from Demonstrations	Learning from Demonstration (LfD) approaches empower end-users to teach robots novel tasks via demonstrations of the desired behaviors, democratizing access to robotics. However, current LfD frameworks are not capable of fast adaptation to heterogeneous human demonstrations nor the large-scale deployment in ubiquitous ...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	319,346
1207.1915	Nonparametric Edge Detection in Speckled Imagery	We address the issue of edge detection in Synthetic Aperture Radar imagery. In particular, we propose nonparametric methods for edge detection, and numerically compare them to an alternative method that has been recently proposed in the literature. Our results show that some of the proposed methods display superior res...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	17,344
1701.02190	Fragmenting very large XML data warehouses via K-means clustering algorithm	XML data sources are more and more gaining popularity in the context of a wide family of Business Intelligence (BI) and On-Line Analytical Processing (OLAP) applications, due to the amenities of XML in representing and managing semi-structured and complex multidimensional data. As a consequence, many XML data warehouse...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	66,520
1612.08076	Cooperative Access Schemes for Efficient SWIPT Transmissions in Cognitive Radio Networks	We investigate joint information and energy cooperative schemes in a slotted-time cognitive radio network with a primary transmitter-receiver pair and a set of secondary transmitter-receiver pairs. The primary transmitter is assumed to be an energy-harvesting node. We propose a three-stage cooperative transmission prot...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	66,025
2007.04206	Diverse Ensembles Improve Calibration	Modern deep neural networks can produce badly calibrated predictions, especially when train and test distributions are mismatched. Training an ensemble of models and averaging their predictions can help alleviate these issues. We propose a simple technique to improve calibration, using a different data augmentation for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,283
2305.09903	Privacy Loss of Noisy Stochastic Gradient Descent Might Converge Even for Non-Convex Losses	The Noisy-SGD algorithm is widely used for privately training machine learning models. Traditional privacy analyses of this algorithm assume that the internal state is publicly revealed, resulting in privacy loss bounds that increase indefinitely with the number of iterations. However, recent findings have shown that i...	false	false	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	364,822
2102.04805	AI-based Blackbox Code Deobfuscation: Understand, Improve and Mitigate	Code obfuscation aims at protecting Intellectual Property and other secrets embedded into software from being retrieved. Recent works leverage advances in artificial intelligence with the hope of getting blackbox deobfuscators completely immune to standard (whitebox) protection mechanisms. While promising, this new fie...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	219,233
2007.10962	Modern Design Methodologies and the Development of Mechatronic Products	This article presents a quick view on the development of mechatronic products and how the techniques of Design Thinking, Concurrent Engineering and Agilism can be integrated to address this development. Design Thinking is employed in the early stages in order to better explore creativity, whereas Concurrent Engineering...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	188,429
2203.06875	Improved Universal Sentence Embeddings with Prompt-based Contrastive Learning and Energy-based Learning	Contrastive learning has been demonstrated to be effective in enhancing pre-trained language models (PLMs) to derive superior universal sentence embeddings. However, existing contrastive methods still have two limitations. Firstly, previous works may acquire poor performance under domain shift settings, thus hindering ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	285,251
1910.02935	Automated Enriched Medical Concept Generation for Chest X-ray Images	Decision support tools that rely on supervised learning require large amounts of expert annotations. Using past radiological reports obtained from hospital archiving systems has many advantages as training data above manual single-class labels: they are expert annotations available in large quantities, covering a popul...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	148,373
1206.5361	Regional System Identification and Computer Based Switchable Control of a Nonlinear Hot Air Blower System	This paper describes the design and implementation of linear controllers with a switching condition for a nonlinear hot air blower system (HABS) process trainer PT326. The system is interfaced with a computer through a USB based data acquisition module and interfacing circuitry. A calibration equation is implemented th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	16,838
2410.17294	Improving Insurance Catastrophic Data with Resampling and GAN Methods	The precise and large dataset concerning catastrophic events is very important for insurers. To improve the quality of such data three methods based on the bootstrap, bootknife, and GAN algorithms are proposed. Using numerical experiments and real-life data, simulated outputs for these approaches are compared based on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	501,412
0907.3183	Why Did My Query Slow Down?	Many enterprise environments have databases running on network-attached server-storage infrastructure (referred to as Storage Area Networks or SANs). Both the database and the SAN are complex systems that need their own separate administrative teams. This paper puts forth the vision of an innovative management framewor...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	4,122
1009.3604	Geometric Decision Tree	In this paper we present a new algorithm for learning oblique decision trees. Most of the current decision tree algorithms rely on impurity measures to assess the goodness of hyperplanes at each node while learning a decision tree in a top-down fashion. These impurity measures do not properly capture the geometric stru...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	7,585
2307.04204	Trajectory Alignment: Understanding the Edge of Stability Phenomenon via Bifurcation Theory	Cohen et al. (2021) empirically study the evolution of the largest eigenvalue of the loss Hessian, also known as sharpness, along the gradient descent (GD) trajectory and observe the Edge of Stability (EoS) phenomenon. The sharpness increases at the early phase of training (referred to as progressive sharpening), and e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	378,324

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