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
2209.07075	Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients	Deep learning based approaches like Physics-informed neural networks (PINNs) and DeepONets have shown promise on solving PDE constrained optimization (PDECO) problems. However, existing methods are insufficient to handle those PDE constraints that have a complicated or nonlinear dependency on optimization targets. In t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	317,620
2406.03684	Principles of Designing Robust Remote Face Anti-Spoofing Systems	Protecting digital identities of human face from various attack vectors is paramount, and face anti-spoofing plays a crucial role in this endeavor. Current approaches primarily focus on detecting spoofing attempts within individual frames to detect presentation attacks. However, the emergence of hyper-realistic generat...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	461,336
2212.00973	A Domain-Knowledge-Inspired Music Embedding Space and a Novel Attention Mechanism for Symbolic Music Modeling	Following the success of the transformer architecture in the natural language domain, transformer-like architectures have been widely applied to the domain of symbolic music recently. Symbolic music and text, however, are two different modalities. Symbolic music contains multiple attributes, both absolute attributes (e...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	334,261
1808.06698	VERAM: View-Enhanced Recurrent Attention Model for 3D Shape Classification	Multi-view deep neural network is perhaps the most successful approach in 3D shape classification. However, the fusion of multi-view features based on max or average pooling lacks a view selection mechanism, limiting its application in, e.g., multi-view active object recognition by a robot. This paper presents VERAM, a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	105,587
1003.0337	Change of word types to word tokens ratio in the course of translation (based on Russian translations of K. Vonnegut novels)	The article provides lexical statistical analysis of K. Vonnegut's two novels and their Russian translations. It is found out that there happen some changes between the speed of word types and word tokens ratio change in the source and target texts. The author hypothesizes that these changes are typical for English-Rus...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	5,810
1809.01774	Deep Recurrent Electricity Theft Detection in AMI Networks with Random Tuning of Hyper-parameters	Modern smart grids rely on advanced metering infrastructure (AMI) networks for monitoring and billing purposes. However, such an approach suffers from electricity theft cyberattacks. Different from the existing research that utilizes shallow, static, and customer-specific-based electricity theft detectors, this paper p...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	106,888
2203.13696	Speech-enhanced and Noise-aware Networks for Robust Speech Recognition	Compensation for channel mismatch and noise interference is essential for robust automatic speech recognition. Enhanced speech has been introduced into the multi-condition training of acoustic models to improve their generalization ability. In this paper, a noise-aware training framework based on two cascaded neural st...	false	false	true	false	true	false	true	false	true	false	false	false	false	false	false	false	false	true	287,731
2009.08169	Holistic Filter Pruning for Efficient Deep Neural Networks	Deep neural networks (DNNs) are usually over-parameterized to increase the likelihood of getting adequate initial weights by random initialization. Consequently, trained DNNs have many redundancies which can be pruned from the model to reduce complexity and improve the ability to generalize. Structural sparsity, as ach...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	196,157
2210.09439	CAN-BERT do it? Controller Area Network Intrusion Detection System based on BERT Language Model	Due to the rising number of sophisticated customer functionalities, electronic control units (ECUs) are increasingly integrated into modern automotive systems. However, the high connectivity between the in-vehicle and the external networks paves the way for hackers who could exploit in-vehicle network protocols' vulner...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	324,528
2404.12724	Graph Convolutional Network For Semi-supervised Node Classification With Subgraph Sketching	In this paper, we propose the Graph-Learning-Dual Graph Convolutional Neural Network called GLDGCN based on the classic Graph Convolutional Neural Network(GCN) by introducing dual convolutional layer and graph learning layer. We apply GLDGCN to the semi-supervised node classification task. Compared with the baseline me...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	448,005
2001.05650	Control of the Final-Phase of Closed-Loop Visual Grasping using Image-Based Visual Servoing	This paper considers the final approach phase of visual-closed-loop grasping where the RGB-D camera is no longer able to provide valid depth information. Many current robotic grasping controllers are not closed-loop and therefore fail for moving objects. Closed-loop grasp controllers based on RGB-D imagery can track a ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	160,597
1907.09395	Mining Temporal Evolution of Knowledge Graph and Genealogical Features for Literature-based Discovery Prediction	Literature-based knowledge discovery process identifies the important but implicit relations among information embedded in published literature. Existing techniques from Information Retrieval and Natural Language Processing attempt to identify the hidden or unpublished connections between information concepts within pu...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	139,347
2112.03119	Requirements for Open Political Information: Transparency Beyond Open Data	A politically informed citizenry is imperative for a welldeveloped democracy. While the US government has pursued policies for open data, these efforts have been insufficient in achieving an open government because only people with technical and domain knowledge can access information in the data. In this work, we cond...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	270,094
1711.03517	A Submodular Approach for Electricity Distribution Network Reconfiguration	Distribution network reconfiguration (DNR) is a tool used by operators to balance line load flows and mitigate losses. As distributed generation and flexible load adoption increases, the impact of DNR on the security, efficiency, and reliability of the grid will increase as well. Today, heuristic-based actions like bra...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	84,223
2101.03967	Real-Time Optimized N-gram For Mobile Devices	With the increasing number of mobile devices, there has been continuous research on generating optimized Language Models (LMs) for soft keyboard. In spite of advances in this domain, building a single LM for low-end feature phones as well as high-end smartphones is still a pressing need. Hence, we propose a novel techn...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	215,037
1704.00552	A Transition-Based Directed Acyclic Graph Parser for UCCA	We present the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation. UCCA poses a challenge for existing parsing techniques, as it exhibits reentrancy (resulting in DAG structures), discontinuous structur...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	71,103
cmp-lg/9602004	Assessing agreement on classification tasks: the kappa statistic	Currently, computational linguists and cognitive scientists working in the area of discourse and dialogue argue that their subjective judgments are reliable using several different statistics, none of which are easily interpretable or comparable to each other. Meanwhile, researchers in content analysis have already exp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,496
2311.05014	Interpreting Pretrained Language Models via Concept Bottlenecks	Pretrained language models (PLMs) have made significant strides in various natural language processing tasks. However, the lack of interpretability due to their ``black-box'' nature poses challenges for responsible implementation. Although previous studies have attempted to improve interpretability by using, e.g., atte...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	406,435
1302.4941	Clustering Without (Thinking About) Triangulation	The undirected technique for evaluating belief networks [Jensen, et.al., 1990, Lauritzen and Spiegelhalter, 1988] requires clustering the nodes in the network into a junction tree. In the traditional view, the junction tree is constructed from the cliques of the moralized and triangulated belief network: triangulation ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,215
2307.11654	FEDD -- Fair, Efficient, and Diverse Diffusion-based Lesion Segmentation and Malignancy Classification	Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, the scarcity of annotated medical images, especially for rare diseases and underrepresented skin tones, poses a challen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	380,985
2403.19012	ReflectSumm: A Benchmark for Course Reflection Summarization	This paper introduces ReflectSumm, a novel summarization dataset specifically designed for summarizing students' reflective writing. The goal of ReflectSumm is to facilitate developing and evaluating novel summarization techniques tailored to real-world scenarios with little training data, %practical tasks with potenti...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	442,164
1602.07567	New Stability and Exact Observability Conditions for Semilinear Wave Equations	The problem of estimating the initial state of 1-D wave equations with globally Lipschitz nonlinearities from boundary measurements on a finite interval was solved recently by using the sequence of forward and backward observers, and deriving the upper bound for exact observability time in terms of Linear Matrix Inequa...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	52,530
1810.13111	Enhanced Quasi-Maximum Likelihood Decoding of Short LDPC Codes based on Saturation	In this paper, we propose an enhanced quasi-maximum likelihood (EQML) decoder for LDPC codes with short block lengths. After the failure of the conventional belief propagation (BP) decoding, the proposed EQML decoder selects unreliable variable nodes (VNs) and saturates their associated channel output values to generat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	111,913
1609.09365	Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks	This paper presents an end-to-end approach for tracking static and dynamic objects for an autonomous vehicle driving through crowded urban environments. Unlike traditional approaches to tracking, this method is learned end-to-end, and is able to directly predict a full unoccluded occupancy grid map from raw laser input...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	61,708
2501.04845	Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors	This R\&D project, initiated by the DOE Nuclear Physics AI-Machine Learning initiative in 2022, leverages AI to address data processing challenges in high-energy nuclear experiments (RHIC, LHC, and future EIC). Our focus is on developing a demonstrator for real-time processing of high-rate data streams from sPHENIX exp...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	523,364
2406.06043	Modeling User Retention through Generative Flow Networks	Recommender systems aim to fulfill the user's daily demands. While most existing research focuses on maximizing the user's engagement with the system, it has recently been pointed out that how frequently the users come back for the service also reflects the quality and stability of recommendations. However, optimizing ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	462,413
1209.6492	Information Retrieval on the web and its evaluation	Internet is one of the main sources of information for millions of people. One can find information related to practically all matters on internet. Moreover if we want to retrieve information about some particular topic we may find thousands of Web Pages related to that topic. But our main concern is to find relevant W...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	18,822
2305.07186	Learning to Code on Graphs for Topological Interference Management	The state-of-the-art coding schemes for topological interference management (TIM) problems are usually handcrafted for specific families of network topologies, relying critically on experts' domain knowledge. This inevitably restricts the potential wider applications to wireless communication systems, due to the limite...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	363,804
2008.08919	SentiQ: A Probabilistic Logic Approach to Enhance Sentiment Analysis Tool Quality	The opinion expressed in various Web sites and social-media is an essential contributor to the decision making process of several organizations. Existing sentiment analysis tools aim to extract the polarity (i.e., positive, negative, neutral) from these opinionated contents. Despite the advance of the research in the f...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	192,549
2102.10957	Co-occurrences using Fasttext embeddings for word similarity tasks in Urdu	Urdu is a widely spoken language in South Asia. Though immoderate literature exists for the Urdu language still the data isn't enough to naturally process the language by NLP techniques. Very efficient language models exist for the English language, a high resource language, but Urdu and other under-resourced languages...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	221,272
1910.04875	FastEstimator: A Deep Learning Library for Fast Prototyping and Productization	As the complexity of state-of-the-art deep learning models increases by the month, implementation, interpretation, and traceability become ever-more-burdensome challenges for AI practitioners around the world. Several AI frameworks have risen in an effort to stem this tide, but the steady advance of the field has begun...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	148,895
2309.16654	Novel Deep Learning Pipeline for Automatic Weapon Detection	Weapon and gun violence have recently become a pressing issue today. The degree of these crimes and activities has risen to the point of being termed as an epidemic. This prevalent misuse of weapons calls for an automatic system that detects weapons in real-time. Real-time surveillance video is captured and recorded in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	395,435
1904.08477	A Game Theoretical Framework for the Evaluation of Unmanned Aircraft Systems Airspace Integration Concepts	Predicting the outcomes of integrating Unmanned Aerial Systems (UAS) into the National Aerospace (NAS) is a complex problem which is required to be addressed by simulation studies before allowing the routine access of UAS into the NAS. This thesis focuses on providing 2D and 3D simulation frameworks using a game theore...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	128,068
2010.06579	Fantastic Features and Where to Find Them: Detecting Cognitive Impairment with a Subsequence Classification Guided Approach	Despite the widely reported success of embedding-based machine learning methods on natural language processing tasks, the use of more easily interpreted engineered features remains common in fields such as cognitive impairment (CI) detection. Manually engineering features from noisy text is time and resource consuming,...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	200,530
2307.08574	FedCME: Client Matching and Classifier Exchanging to Handle Data Heterogeneity in Federated Learning	Data heterogeneity across clients is one of the key challenges in Federated Learning (FL), which may slow down the global model convergence and even weaken global model performance. Most existing approaches tackle the heterogeneity by constraining local model updates through reference to global information provided by ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	379,853
2306.14696	How About Kind of Generating Hedges using End-to-End Neural Models?	Hedging is a strategy for softening the impact of a statement in conversation. In reducing the strength of an expression, it may help to avoid embarrassment (more technically, ``face threat'') to one's listener. For this reason, it is often found in contexts of instruction, such as tutoring. In this work, we develop a ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	375,780
2008.10808	A Federated Multi-View Deep Learning Framework for Privacy-Preserving Recommendations	Privacy-preserving recommendations are recently gaining momentum, since the decentralized user data is increasingly harder to collect, by recommendation service providers, due to the serious concerns over user privacy and data security. This situation is further exacerbated by the strict government regulations such as ...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	193,096
1704.07953	Linear Convergence of Accelerated Stochastic Gradient Descent for Nonconvex Nonsmooth Optimization	In this paper, we study the stochastic gradient descent (SGD) method for the nonconvex nonsmooth optimization, and propose an accelerated SGD method by combining the variance reduction technique with Nesterov's extrapolation technique. Moreover, based on the local error bound condition, we establish the linear converge...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	72,450
2311.04325	Extending Machine Learning-Based Early Sepsis Detection to Different Demographics	Sepsis requires urgent diagnosis, but research is predominantly focused on Western datasets. In this study, we perform a comparative analysis of two ensemble learning methods, LightGBM and XGBoost, using the public eICU-CRD dataset and a private South Korean St. Mary's Hospital's dataset. Our analysis reveals the effec...	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	false	false	406,184
2112.08078	Joint Demand Prediction for Multimodal Systems: A Multi-task Multi-relational Spatiotemporal Graph Neural Network Approach	Dynamic demand prediction is crucial for the efficient operation and management of urban transportation systems. Extensive research has been conducted on single-mode demand prediction, ignoring the fact that the demands for different transportation modes can be correlated with each other. Despite some recent efforts, e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	271,688
2202.12499	PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks	This paper focuses on the Data Augmentation for low-resource Natural Language Understanding (NLU) tasks. We propose Prompt-based D}ata Augmentation model (PromDA) which only trains small-scale Soft Prompt (i.e., a set of trainable vectors) in the frozen Pre-trained Language Models (PLMs). This avoids human effort in co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	282,262
2502.09947	Analyzing Patient Daily Movement Behavior Dynamics Using Two-Stage Encoding Model	In the analysis of remote healthcare monitoring data, time series representation learning offers substantial value in uncovering deeper patterns of patient behavior, especially given the fine temporal granularity of the data. In this study, we focus on a dataset of home activity records from people living with Dementia...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	533,675
2204.00665	CipherDAug: Ciphertext based Data Augmentation for Neural Machine Translation	We propose a novel data-augmentation technique for neural machine translation based on ROT-$k$ ciphertexts. ROT-$k$ is a simple letter substitution cipher that replaces a letter in the plaintext with the $k$th letter after it in the alphabet. We first generate multiple ROT-$k$ ciphertexts using different values of $k$ ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	289,343
2310.08418	Privacy-Preserved Aggregate Thermal Dynamic Model of Buildings	The thermal inertia of buildings brings considerable flexibility to the heating and cooling load, which is known to be a promising demand response resource. The aggregate model that can describe the thermal dynamics of the building cluster is an important interference for energy systems to exploit its intrinsic thermal...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	399,383
2304.03536	Leveraging GANs for data scarcity of COVID-19: Beyond the hype	Artificial Intelligence (AI)-based models can help in diagnosing COVID-19 from lung CT scans and X-ray images; however, these models require large amounts of data for training and validation. Many researchers studied Generative Adversarial Networks (GANs) for producing synthetic lung CT scans and X-Ray images to improv...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	356,851
2310.06935	Quantum Shadow Gradient Descent for Variational Quantum Algorithms	Gradient-based optimizers have been proposed for training variational quantum circuits in settings such as quantum neural networks (QNNs). The task of gradient estimation, however, has proven to be challenging, primarily due to distinctive quantum features such as state collapse and measurement incompatibility. Convent...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	398,768
1911.11306	SRG: Snippet Relatedness-based Temporal Action Proposal Generator	Recent temporal action proposal generation approaches have suggested integrating segment- and snippet score-based methodologies to produce proposals with high recall and accurate boundaries. In this paper, different from such a hybrid strategy, we focus on the potential of the snippet score-based approach. Specifically...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	155,076
2203.16746	Resilient Distribution System Restoration with Communication Recovery by Drone Small Cells	Distribution system (DS) restoration after natural disasters often faces the challenge of communication failures to feeder automation (FA) facilities, resulting in prolonged load pick-up process. This letter discusses the utilization of drone small cells for wireless communication recovery of FA, and proposes an integr...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	288,895
2212.02924	Controlled Text Generation using T5 based Encoder-Decoder Soft Prompt Tuning and Analysis of the Utility of Generated Text in AI	Controlled text generation is a very important task in the arena of natural language processing due to its promising applications. In order to achieve this task we mainly introduce the novel soft prompt tuning method of using soft prompts at both encoder and decoder levels together in a T5 model and investigate the per...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	334,934
2211.03583	pyGSL: A Graph Structure Learning Toolkit	We introduce pyGSL, a Python library that provides efficient implementations of state-of-the-art graph structure learning models along with diverse datasets to evaluate them on. The implementations are written in GPU-friendly ways, allowing one to scale to much larger network tasks. A common interface is introduced for...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,975
2009.06224	Multi-Agent Reinforcement Learning in Cournot Games	In this work, we study the interaction of strategic agents in continuous action Cournot games with limited information feedback. Cournot game is the essential market model for many socio-economic systems where agents learn and compete without the full knowledge of the system or each other. We consider the dynamics of t...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	true	false	false	true	195,570
1302.2563	Temporal motifs reveal homophily, gender-specific patterns and group talk in mobile communication networks	Electronic communication records provide detailed information about temporal aspects of human interaction. Previous studies have shown that individuals' communication patterns have complex temporal structure, and that this structure has system-wide effects. In this paper we use mobile phone records to show that interac...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	21,953
2103.09153	Impact of Electric Vehicles Botnets on the Power Grid	The increased penetration of Electric Vehicles (EVs) in the transportation sector has increased the requirement of Fast Charging Direct Current (FCDC) stations to meet customer's speedy charging requirements. However, both charging stations and EVs connection to the communication infrastructure as well as the power gri...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	225,093
2310.15321	How language of interaction affects the user perception of a robot	Spoken language is the most natural way for a human to communicate with a robot. It may seem intuitive that a robot should communicate with users in their native language. However, it is not clear if a user's perception of a robot is affected by the language of interaction. We investigated this question by conducting...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	402,252
1802.04800	Adaptive Regulation of Sampling Rates for Power Efficient Embedded Control system Design	In recent times adaptive regulation of sampling rates has gained significant attention in research community and researchers has demonstrated it's effectiveness in embedded control applications from different perspectives. In low power embedded control systems, the sampling rate of the control tasks has a direct relati...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	90,310
1911.10461	Real-time Analysis of Privacy-(un)aware IoT Applications	Users trust IoT apps to control and automate their smart devices. These apps necessarily have access to sensitive data to implement their functionality. However, users lack visibility into how their sensitive data is used (or leaked), and they often blindly trust the app developers. In this paper, we present IoTWatcH, ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	154,844
2403.13079	Current-Based Impedance Control for Interacting with Mobile Manipulators	As robots shift from industrial to human-centered spaces, adopting mobile manipulators, which expand workspace capabilities, becomes crucial. In these settings, seamless interaction with humans necessitates compliant control. Two common methods for safe interaction, admittance, and impedance control, require force or t...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	439,460
2306.06919	Learning Multilingual Sentence Representations with Cross-lingual Consistency Regularization	Multilingual sentence representations are the foundation for similarity-based bitext mining, which is crucial for scaling multilingual neural machine translation (NMT) system to more languages. In this paper, we introduce MuSR: a one-for-all Multilingual Sentence Representation model that supports more than 220 languag...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	372,808
2112.03269	DIY Graphics Tab: A Cost-Effective Alternative to Graphics Tablet for Educators	Everyday, more and more people are turning to online learning, which has altered our traditional classroom method. Recording lectures has always been a normal task for online educators, and it has lately become even more important during the epidemic because actual lessons are still being postponed in several countries...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	270,145
1305.4081	Conditions for Convergence in Regularized Machine Learning Objectives	Analysis of the convergence rates of modern convex optimization algorithms can be achived through binary means: analysis of emperical convergence, or analysis of theoretical convergence. These two pathways of capturing information diverge in efficacy when moving to the world of distributed computing, due to the introdu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	24,664
1206.2190	Communication-Efficient Parallel Belief Propagation for Latent Dirichlet Allocation	This paper presents a novel communication-efficient parallel belief propagation (CE-PBP) algorithm for training latent Dirichlet allocation (LDA). Based on the synchronous belief propagation (BP) algorithm, we first develop a parallel belief propagation (PBP) algorithm on the parallel architecture. Because the extensiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,424
2006.09500	Logic of Machine Learning	The main question is: why and how can we ever predict based on a finite sample? The question is not answered by statistical learning theory. Here, I suggest that prediction requires belief in "predictability" of the underlying dependence, and learning involves search for a hypothesis where these beliefs are violated th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	182,559
1805.06846	RotDCF: Decomposition of Convolutional Filters for Rotation-Equivariant Deep Networks	Explicit encoding of group actions in deep features makes it possible for convolutional neural networks (CNNs) to handle global deformations of images, which is critical to success in many vision tasks. This paper proposes to decompose the convolutional filters over joint steerable bases across the space and the group ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	97,689
2403.14111	HETAL: Efficient Privacy-preserving Transfer Learning with Homomorphic Encryption	Transfer learning is a de facto standard method for efficiently training machine learning models for data-scarce problems by adding and fine-tuning new classification layers to a model pre-trained on large datasets. Although numerous previous studies proposed to use homomorphic encryption to resolve the data privacy is...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	439,913
2309.02856	Getting too personal(ized): The importance of feature choice in online adaptive algorithms	Digital educational technologies offer the potential to customize students' experiences and learn what works for which students, enhancing the technology as more students interact with it. We consider whether and when attempting to discover how to personalize has a cost, such as if the adaptation to personal informatio...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	390,190
1902.03493	Deep Algorithm Unrolling for Blind Image Deblurring	Blind image deblurring remains a topic of enduring interest. Learning based approaches, especially those that employ neural networks have emerged to complement traditional model based methods and in many cases achieve vastly enhanced performance. That said, neural network approaches are generally empirically designed a...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	121,120
1702.03115	Texture Characterization by Using Shape Co-occurrence Patterns	Texture characterization is a key problem in image understanding and pattern recognition. In this paper, we present a flexible shape-based texture representation using shape co-occurrence patterns. More precisely, texture images are first represented by tree of shapes, each of which is associated with several geometric...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	68,081
2203.00924	Translation Invariant Global Estimation of Heading Angle Using Sinogram of LiDAR Point Cloud	Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value. With the aid of gravity alignment, the degree of freedom in point cloud registration could be reduced to 4DoF, in which only the heading angle is requir...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	283,184
1807.01948	Incremental Relational Lenses	Lenses are a popular approach to bidirectional transformations, a generalisation of the view update problem in databases, in which we wish to make changes to source tables to effect a desired change on a view. However, perhaps surprisingly, lenses have seldom actually been used to implement updatable views in databases...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	102,161
1901.06595	Evaluating Text-to-Image Matching using Binary Image Selection (BISON)	Providing systems the ability to relate linguistic and visual content is one of the hallmarks of computer vision. Tasks such as text-based image retrieval and image captioning were designed to test this ability but come with evaluation measures that have a high variance or are difficult to interpret. We study an altern...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	119,036
2408.13378	DrugAgent: Explainable Drug Repurposing Agent with Large Language Model-based Reasoning	Drug repurposing offers a promising avenue for accelerating drug development by identifying new therapeutic potentials of existing drugs. In this paper, we propose a multi-agent framework to enhance the drug repurposing process using state-of-the-art machine learning techniques and knowledge integration. Our framework ...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	483,124
2410.17584	Exploring Tokenization Methods for Multitrack Sheet Music Generation	This study explores the tokenization of multitrack sheet music in ABC notation, introducing two methods--bar-stream and line-stream patching. We compare these methods against existing techniques, including bar patching, byte patching, and Byte Pair Encoding (BPE). In terms of both computational efficiency and the music...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	501,533
2303.11666	A Survey on Causal Inference for Recommendation	Causal inference has recently garnered significant interest among recommender system (RS) researchers due to its ability to dissect cause-and-effect relationships and its broad applicability across multiple fields. It offers a framework to model the causality in recommender systems like confounding effects and deal wit...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	352,949
2501.05927	Expressing One's Identity Online: Left-Right and cross EU-country variation in self-representation in social media	We examine how social media users from eight European Union (EU) member states express their socio-political identities, focusing on users' online self-presentation and group identity cues conveyed through bios. Our goal is to explore commonalities and differences in topics discussed in social media profiles, across Le...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	523,769
2105.02646	Cascade Image Matting with Deformable Graph Refinement	Image matting refers to the estimation of the opacity of foreground objects. It requires correct contours and fine details of foreground objects for the matting results. To better accomplish human image matting tasks, we propose the Cascade Image Matting Network with Deformable Graph Refinement, which can automatically...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	233,879
2003.00348	Information cartography in association rule mining	Association Rule Mining is a machine learning method for discovering the interesting relations between the attributes in a huge transaction database. Typically, algorithms for Association Rule Mining generate a huge number of association rules, from which it is hard to extract structured knowledge and present this auto...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	166,265
2012.07091	Reinforcement Learning with Subspaces using Free Energy Paradigm	In large-scale problems, standard reinforcement learning algorithms suffer from slow learning speed. In this paper, we follow the framework of using subspaces to tackle this problem. We propose a free-energy minimization framework for selecting the subspaces and integrate the policy of the state-space into the subspace...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	211,341
1904.05019	SOSNet: Second Order Similarity Regularization for Local Descriptor Learning	Despite the fact that Second Order Similarity (SOS) has been used with significant success in tasks such as graph matching and clustering, it has not been exploited for learning local descriptors. In this work, we explore the potential of SOS in the field of descriptor learning by building upon the intuition that a pos...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,187
2303.06458	ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation	Natural Language Generation (NLG) accepts input data in the form of images, videos, or text and generates corresponding natural language text as output. Existing NLG methods mainly adopt a supervised approach and rely heavily on coupled data-to-text pairs. However, for many targeted scenarios and for non-English langua...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	350,855
1704.06910	A discount strategy in word-of-mouth marketing and its assessment	This paper addresses the discount pricing in word-of-mouth (WOM) marketing. A new discount strategy known as the Infection-Based Discount (IBD) strategy is proposed. The basic idea of the IBD strategy lies in that each customer enjoys a discount that is linearly proportional to his/her influence in the WOM network. To ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	72,252
1806.05180	A Retrospective Analysis of the Fake News Challenge Stance Detection Task	The 2017 Fake News Challenge Stage 1 (FNC-1) shared task addressed a stance classification task as a crucial first step towards detecting fake news. To date, there is no in-depth analysis paper to critically discuss FNC-1's experimental setup, reproduce the results, and draw conclusions for next-generation stance class...	false	false	false	true	true	true	false	false	true	false	false	false	false	false	false	false	false	false	100,411
2406.07191	MeMSVD: Long-Range Temporal Structure Capturing Using Incremental SVD	This paper is on long-term video understanding where the goal is to recognise human actions over long temporal windows (up to minutes long). In prior work, long temporal context is captured by constructing a long-term memory bank consisting of past and future video features which are then integrated into standard (shor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	462,941
1905.12213	Where is the Information in a Deep Neural Network?	Whatever information a deep neural network has gleaned from training data is encoded in its weights. How this information affects the response of the network to future data remains largely an open question. Indeed, even defining and measuring information entails some subtleties, since a trained network is a determinist...	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	132,697
2210.04604	Actor-Critic Network for O-RAN Resource Allocation: xApp Design, Deployment, and Analysis	Open Radio Access Network (O-RAN) has introduced an emerging RAN architecture that enables openness, intelligence, and automated control. The RAN Intelligent Controller (RIC) provides the platform to design and deploy RAN controllers. xApps are the applications which will take this responsibility by leveraging machine ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	322,521
2312.03732	A Rank Stabilization Scaling Factor for Fine-Tuning with LoRA	As large language models (LLMs) have become increasingly compute and memory intensive, parameter-efficient fine-tuning (PEFT) methods are now a common strategy to fine-tune LLMs. A popular PEFT method is Low-Rank Adapters (LoRA), which adds trainable low-rank "adapters" to selected layers. Each adapter consists of a lo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	413,386
1809.06402	Crowdsourcing Lung Nodules Detection and Annotation	We present crowdsourcing as an additional modality to aid radiologists in the diagnosis of lung cancer from clinical chest computed tomography (CT) scans. More specifically, a complete workflow is introduced which can help maximize the sensitivity of lung nodule detection by utilizing the collective intelligence of the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	108,048
2103.04508	Predictive Visual Tracking: A New Benchmark and Baseline Approach	As a crucial robotic perception capability, visual tracking has been intensively studied recently. In the real-world scenarios, the onboard processing time of the image streams inevitably leads to a discrepancy between the tracking results and the real-world states. However, existing visual tracking benchmarks commonly...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	223,659
2003.08502	Reconstructing Sinus Anatomy from Endoscopic Video -- Towards a Radiation-free Approach for Quantitative Longitudinal Assessment	Reconstructing accurate 3D surface models of sinus anatomy directly from an endoscopic video is a promising avenue for cross-sectional and longitudinal analysis to better understand the relationship between sinus anatomy and surgical outcomes. We present a patient-specific, learning-based method for 3D reconstruction o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	168,755
1804.09223	Hybrid LISA for Wideband Multiuser Millimeter Wave Communication Systems under Beam Squint	This work jointly addresses user scheduling and precoder/combiner design in the downlink of a wideband millimeter wave (mmWave) communications system. We consider Orthogonal Frequency Division Multiplexing (OFDM) modulation to overcome channel frequency selectivity and obtain a number of equivalent narrowband channels....	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	95,927
2406.00044	Stochastic Adversarial Networks for Multi-Domain Text Classification	Adversarial training has been instrumental in advancing multi-domain text classification (MDTC). Traditionally, MDTC methods employ a shared-private paradigm, with a shared feature extractor for domain-invariant knowledge and individual private feature extractors for domain-specific knowledge. Despite achieving state-o...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	459,681
2007.02393	Deep Convolutional Neural Network for Identifying Seam-Carving Forgery	Seam carving is a representative content-aware image retargeting approach to adjust the size of an image while preserving its visually prominent content. To maintain visually important content, seam-carving algorithms first calculate the connected path of pixels, referred to as the seam, according to a defined cost fun...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	true	185,725
2112.05662	Match Your Words! A Study of Lexical Matching in Neural Information Retrieval	Neural Information Retrieval models hold the promise to replace lexical matching models, e.g. BM25, in modern search engines. While their capabilities have fully shone on in-domain datasets like MS MARCO, they have recently been challenged on out-of-domain zero-shot settings (BEIR benchmark), questioning their actual g...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	270,915
2206.13559	ST-Adapter: Parameter-Efficient Image-to-Video Transfer Learning	Capitalizing on large pre-trained models for various downstream tasks of interest have recently emerged with promising performance. Due to the ever-growing model size, the standard full fine-tuning based task adaptation strategy becomes prohibitively costly in terms of model training and storage. This has led to a new ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	305,008
2003.10018	Navigation Systems May Deteriorate Stability in Traffic Networks	Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics originating from the widespread adoption of these tools have remained largely un...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	169,214
2407.09078	Dynamic Modeling and Stability Analysis of Balancing in Riderless Electric Scooters	Today, electric scooter is a trendy personal mobility vehicle. The rising demand and opportunities attract ride-share services. A common problem of such services is abandoned e-scooters. An autonomous e-scooter capable of moving to the charging station is a solution. This paper focuses on maintaining balance for these ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	472,445
2411.01612	Ontology Population using LLMs	Knowledge graphs (KGs) are increasingly utilized for data integration, representation, and visualization. While KG population is critical, it is often costly, especially when data must be extracted from unstructured text in natural language, which presents challenges, such as ambiguity and complex interpretations. Larg...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	505,152
1902.10119	Transfer Learning for Performance Modeling of Configurable Systems: A Causal Analysis	Modern systems (e.g., deep neural networks, big data analytics, and compilers) are highly configurable, which means they expose different performance behavior under different configurations. The fundamental challenge is that one cannot simply measure all configurations due to the sheer size of the configuration space. ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	122,589
1810.12620	Towards End-to-end Automatic Code-Switching Speech Recognition	Speech recognition in mixed language has difficulties to adapt end-to-end framework due to the lack of data and overlapping phone sets, for example in words such as "one" in English and "w\`an" in Chinese. We propose a CTC-based end-to-end automatic speech recognition model for intra-sentential English-Mandarin code-sw...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	111,812
2004.14303	TUNIZI: a Tunisian Arabizi sentiment analysis Dataset	On social media, Arabic people tend to express themselves in their own local dialects. More particularly, Tunisians use the informal way called "Tunisian Arabizi". Analytical studies seek to explore and recognize online opinions aiming to exploit them for planning and prediction purposes such as measuring the customer ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	174,839
1911.07251	DualVD: An Adaptive Dual Encoding Model for Deep Visual Understanding in Visual Dialogue	Different from Visual Question Answering task that requires to answer only one question about an image, Visual Dialogue involves multiple questions which cover a broad range of visual content that could be related to any objects, relationships or semantics. The key challenge in Visual Dialogue task is thus to learn a m...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	153,781

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