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
1910.13328	Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks	Histology-based grade classification is clinically important for many cancer types in stratifying patients distinct treatment groups. In prostate cancer, the Gleason score is a grading system used to measure the aggressiveness of prostate cancer from the spatial organization of cells and the distribution of glands. How...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	151,368
2103.13225	Structure-Aware Face Clustering on a Large-Scale Graph with $\bf{10^{7}}$ Nodes	Face clustering is a promising method for annotating unlabeled face images. Recent supervised approaches have boosted the face clustering accuracy greatly, however their performance is still far from satisfactory. These methods can be roughly divided into global-based and local-based ones. Global-based methods suffer f...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	226,426
1907.05697	Dreaming machine learning: Lipschitz extensions for reinforcement learning on financial markets	We consider a quasi-metric topological structure for the construction of a new reinforcement learning model in the framework of financial markets. It is based on a Lipschitz type extension of reward functions defined in metric spaces. Specifically, the McShane and Whitney extensions are considered for a reward function...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,433
2104.03597	GKD: Semi-supervised Graph Knowledge Distillation for Graph-Independent Inference	The increased amount of multi-modal medical data has opened the opportunities to simultaneously process various modalities such as imaging and non-imaging data to gain a comprehensive insight into the disease prediction domain. Recent studies using Graph Convolutional Networks (GCNs) provide novel semi-supervised appro...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	229,121
2502.00158	Resolving Editing-Unlearning Conflicts: A Knowledge Codebook Framework for Large Language Model Updating	Large Language Models (LLMs) excel in natural language processing by encoding extensive human knowledge, but their utility relies on timely updates as knowledge evolves. Updating LLMs involves two key tasks simultaneously: unlearning to remove unwanted knowledge and editing to incorporate new information. Existing meth...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	529,233
2407.17767	Online Learning for Autonomous Management of Intent-based 6G Networks	The growing complexity of networks and the variety of future scenarios with diverse and often stringent performance requirements call for a higher level of automation. Intent-based management emerges as a solution to attain high level of automation, enabling human operators to solely communicate with the network throug...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	476,104
2212.13007	Visual Tactile Sensor Based Force Estimation for Position-Force Teleoperation	Vision-based tactile sensors have gained extensive attention in the robotics community. The sensors are highly expected to be capable of extracting contact information i.e. haptic information during in-hand manipulation. This nature of tactile sensors makes them a perfect match for haptic feedback applications. In this...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	338,196
2012.05966	A tuning algorithm for a sliding mode controller of buildings with ATMD	This paper proposes an automatic tuning algorithm for a sliding mode controller (SMC) based on the Ackermann's formula, that attenuates the structural vibrations of a seismically excited building equipped with an Active Tuned Mass Damper (ATMD) mounted on its top floor. The switching gain and sliding surface of the SMC...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	210,940
2111.09485	3D Lip Event Detection via Interframe Motion Divergence at Multiple Temporal Resolutions	The lip is a dominant dynamic facial unit when a person is speaking. Detecting lip events is beneficial to speech analysis and support for the hearing impaired. This paper proposes a 3D lip event detection pipeline that automatically determines the lip events from a 3D speaking lip sequence. We define a motion divergen...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	267,028
1808.05577	Deeper Image Quality Transfer: Training Low-Memory Neural Networks for 3D Images	In this paper we address the memory demands that come with the processing of 3-dimensional, high-resolution, multi-channeled medical images in deep learning. We exploit memory-efficient backpropagation techniques, to reduce the memory complexity of network training from being linear in the network's depth, to being rou...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	105,379
1910.05624	A Research Platform for Multi-Robot Dialogue with Humans	This paper presents a research platform that supports spoken dialogue interaction with multiple robots. The demonstration showcases our crafted MultiBot testing scenario in which users can verbally issue search, navigate, and follow instructions to two robotic teammates: a simulated ground robot and an aerial robot. Th...	true	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	149,124
2312.01445	Classification of Home Network Problems with Transformers	We propose a classifier that can identify ten common home network problems based on the raw textual output of networking tools such as ping, dig, and ip. Our deep learning model uses an encoder-only transformer architecture with a particular pre-tokenizer that we propose for splitting the tool output into token sequenc...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	412,442
2110.15350	XDEEP-MSI: Explainable Bias-Rejecting Microsatellite Instability Deep Learning System In Colorectal Cancer	We present a system for the prediction of microsatellite instability (MSI) from H&E images of colorectal cancer using deep learning (DL) techniques customized for tissue microarrays (TMAs). The system incorporates an end-to-end image preprocessing module that produces tiles at multiple magnifications in the regions of ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	263,854
0805.1437	On the Spectrum of Large Random Hermitian Finite-Band Matrices	The open problem of calculating the limiting spectrum (or its Shannon transform) of increasingly large random Hermitian finite-band matrices is described. In general, these matrices include a finite number of non-zero diagonals around their main diagonal regardless of their size. Two different communication setups whic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,743
1702.06819	Distributed Representations of Signed Networks	Recent successes in word embedding and document embedding have motivated researchers to explore similar representations for networks and to use such representations for tasks such as edge prediction, node label prediction, and community detection. Such network embedding methods are largely focused on finding distribute...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	68,678
2206.00007	A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling	Data insufficiency problems (i.e., data missing and label scarcity) caused by inadequate services and infrastructures or imbalanced development levels of cities have seriously affected the urban computing tasks in real scenarios. Prior transfer learning methods inspire an elegant solution to the data insufficiency, but...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	299,960
2309.14841	Towards a Neuronally Consistent Ontology for Robotic Agents	The Collaborative Research Center for Everyday Activity Science & Engineering (CRC EASE) aims to enable robots to perform environmental interaction tasks with close to human capacity. It therefore employs a shared ontology to model the activity of both kinds of agents, empowering robots to learn from human experiences....	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,759
2401.12471	Training-Free Action Recognition and Goal Inference with Dynamic Frame Selection	We introduce VidTFS, a Training-free, open-vocabulary video goal and action inference framework that combines the frozen vision foundational model (VFM) and large language model (LLM) with a novel dynamic Frame Selection module. Our experiments demonstrate that the proposed frame selection module improves the performan...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	423,388
2011.04021	On the role of planning in model-based deep reinforcement learning	Model-based planning is often thought to be necessary for deep, careful reasoning and generalization in artificial agents. While recent successes of model-based reinforcement learning (MBRL) with deep function approximation have strengthened this hypothesis, the resulting diversity of model-based methods has also made ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	205,435
2302.00284	Selective Uncertainty Propagation in Offline RL	We consider the finite-horizon offline reinforcement learning (RL) setting, and are motivated by the challenge of learning the policy at any step h in dynamic programming (DP) algorithms. To learn this, it is sufficient to evaluate the treatment effect of deviating from the behavioral policy at step h after having opti...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	343,169
1912.07277	ITENE: Intrinsic Transfer Entropy Neural Estimator	Quantifying the directionality of information flow is instrumental in understanding, and possibly controlling, the operation of many complex systems, such as transportation, social, neural, or gene-regulatory networks. The standard Transfer Entropy (TE) metric follows Granger's causality principle by measuring the Mutu...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	157,566
2502.10786	Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak	Tuberculosis (TB) remains a formidable global health challenge, driven by complex spatiotemporal transmission dynamics and influenced by factors such as population mobility and behavioral changes. We propose an Epidemic-Guided Deep Learning (EGDL) approach that fuses mechanistic epidemiological principles with advanced...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,044
2112.08808	Simple Questions Generate Named Entity Recognition Datasets	Recent named entity recognition (NER) models often rely on human-annotated datasets, requiring the significant engagement of professional knowledge on the target domain and entities. This research introduces an ask-to-generate approach that automatically generates NER datasets by asking questions in simple natural lang...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	271,945
2110.01463	Asynchronous Upper Confidence Bound Algorithms for Federated Linear Bandits	Linear contextual bandit is a popular online learning problem. It has been mostly studied in centralized learning settings. With the surging demand of large-scale decentralized model learning, e.g., federated learning, how to retain regret minimization while reducing communication cost becomes an open challenge. In thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	258,781
2304.04752	A Practitioner's Guide to Bayesian Inference in Pharmacometrics using Pumas	This paper provides a comprehensive tutorial for Bayesian practitioners in pharmacometrics using Pumas workflows. We start by giving a brief motivation of Bayesian inference for pharmacometrics highlighting limitations in existing software that Pumas addresses. We then follow by a description of all the steps of a stan...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	357,341
2307.01618	A Stackelberg viral marketing design for two competing players	A Stackelberg duopoly model in which two firms compete to maximize their market share is considered. The firms offer a service/product to customers that are spread over several geographical regions (e.g., countries, provinces, or states). Each region has its own characteristics (spreading and recovery rates) of each se...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	377,414
1905.09797	Interpreting Adversarially Trained Convolutional Neural Networks	We attempt to interpret how adversarially trained convolutional neural networks (AT-CNNs) recognize objects. We design systematic approaches to interpret AT-CNNs in both qualitative and quantitative ways and compare them with normally trained models. Surprisingly, we find that adversarial training alleviates the textur...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	131,837
1908.04682	CMB-GAN: Fast Simulations of Cosmic Microwave background anisotropy maps using Deep Learning	Cosmic Microwave Background (CMB) has been a cornerstone in many cosmology experiments and studies since it was discovered back in 1964. Traditional computational models like CAMB that are used for generating CMB temperature anisotropy maps are extremely resource intensive and act as a bottleneck in cosmology experimen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	141,541
2303.16209	AmorProt: Amino Acid Molecular Fingerprints Repurposing based Protein Fingerprint	As protein therapeutics play an important role in almost all medical fields, numerous studies have been conducted on proteins using artificial intelligence. Artificial intelligence has enabled data driven predictions without the need for expensive experiments. Nevertheless, unlike the various molecular fingerprint algo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	354,786
1811.05721	A Deterministic Algorithm for Bridging Anaphora Resolution	Previous work on bridging anaphora resolution (Poesio et al., 2004; Hou et al., 2013b) use syntactic preposition patterns to calculate word relatedness. However, such patterns only consider NPs' head nouns and hence do not fully capture the semantics of NPs. Recently, Hou (2018) created word embeddings (embeddings_PP) ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	113,374
2111.01701	Improve Single-Point Zeroth-Order Optimization Using High-Pass and Low-Pass Filters	Single-point zeroth-order optimization (SZO) is useful in solving online black-box optimization and control problems in time-varying environments, as it queries the function value only once at each time step. However, the vanilla SZO method is known to suffer from a large estimation variance and slow convergence, which...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	264,638
2007.06512	Deep Learning for Distributed Channel Feedback and Multiuser Precoding in FDD Massive MIMO	This paper shows that deep neural network (DNN) can be used for efficient and distributed channel estimation, quantization, feedback, and downlink multiuser precoding for a frequency-division duplex massive multiple-input multiple-output system in which a base station (BS) serves multiple mobile users, but with rate-li...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	187,033
1602.04375	Science Question Answering using Instructional Materials	We provide a solution for elementary science test using instructional materials. We posit that there is a hidden structure that explains the correctness of an answer given the question and instructional materials and present a unified max-margin framework that learns to find these hidden structures (given a corpus of q...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	52,119
2210.02604	Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces	Data-driven machine learning models are being increasingly employed in several important inference problems in biology, chemistry, and physics which require learning over combinatorial spaces. Recent empirical evidence (see, e.g., [1], [2], [3]) suggests that regularizing the spectral representation of such models impr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	321,704
1711.05885	Crowdsourcing Question-Answer Meaning Representations	We introduce Question-Answer Meaning Representations (QAMRs), which represent the predicate-argument structure of a sentence as a set of question-answer pairs. We also develop a crowdsourcing scheme to show that QAMRs can be labeled with very little training, and gather a dataset with over 5,000 sentences and 100,000 q...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	84,664
2306.16619	Laxity-Aware Scalable Reinforcement Learning for HVAC Control	Demand flexibility plays a vital role in maintaining grid balance, reducing peak demand, and saving customers' energy bills. Given their highly shiftable load and significant contribution to a building's energy consumption, Heating, Ventilation, and Air Conditioning (HVAC) systems can provide valuable demand flexibilit...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	376,418
2404.12317	Synthetic Participatory Planning of Shard Automated Electric Mobility Systems	Unleashing the synergies among rapidly evolving mobility technologies in a multi-stakeholder setting presents unique challenges and opportunities for addressing urban transportation problems. This paper introduces a novel synthetic participatory method that critically leverages large language models (LLMs) to create di...	true	true	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	447,833
2205.03096	Desaparecidxs: characterizing the population of missing children using Twitter	Missing children, i.e., children reported to a relevant authority as having "disappeared," constitute an important but often overlooked population. From a research perspective, missing children constitute a hard-to-reach population about which little is known. This is a particular problem in regions of the Global South...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	295,168
2103.12681	A Distributed Active Set Method for Model Predictive Control	This paper presents a novel distributed active set method for model predictive control of linear systems. The method combines a primal active set strategy with a decentralized conjugate gradient method to solve convex quadratic programs. An advantage of the proposed method compared to existing distributed model predict...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	226,254
2307.02497	Multi-gauge Hydrological Variational Data Assimilation: Regionalization Learning with Spatial Gradients using Multilayer Perceptron and Bayesian-Guided Multivariate Regression	Tackling the difficult problem of estimating spatially distributed hydrological parameters, especially for floods on ungauged watercourses, this contribution presents a novel seamless regionalization technique for learning complex regional transfer functions designed for high-resolution hydrological models. The transfe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	377,717
2311.09261	Emerging Drug Interaction Prediction Enabled by Flow-based Graph Neural Network with Biomedical Network	Accurately predicting drug-drug interactions (DDI) for emerging drugs, which offer possibilities for treating and alleviating diseases, with computational methods can improve patient care and contribute to efficient drug development. However, many existing computational methods require large amounts of known DDI inform...	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	408,071
1703.04336	A Visual Representation of Wittgenstein's Tractatus Logico-Philosophicus	In this paper we present a data visualization method together with its potential usefulness in digital humanities and philosophy of language. We compile a multilingual parallel corpus from different versions of Wittgenstein's Tractatus Logico-Philosophicus, including the original in German and translations into English...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	69,878
1801.05768	The Asymptotic Capacity of Private Search	The private search problem is introduced, where a dataset comprised of $L$ i.i.d. records is replicated across $N$ non-colluding servers, each record takes values uniformly from an alphabet of size $K$, and a user wishes to search for all records that match a privately chosen value, without revealing any information ab...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	88,511
2411.12293	Generative Timelines for Instructed Visual Assembly	The objective of this work is to manipulate visual timelines (e.g. a video) through natural language instructions, making complex timeline editing tasks accessible to non-expert or potentially even disabled users. We call this task Instructed visual assembly. This task is challenging as it requires (i) identifying rele...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	509,369
2010.12938	Comments on "Precoding and Artificial Noise Design for Cognitive MIMOME Wiretap Channels"	Several gaps and errors in [1] are identified and corrected. While accommodating these corrections, a rigours proof is given that the successive convex approximation algorithm in [1] for secrecy rate maximization (SRM) does generate an increasing and bounded sequence of true secrecy rates and hence converges. It is fur...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	202,939
2203.16180	Millimeter-Wave Sensing for Avoidance of High-Risk Ground Conditions for Mobile Robots	Mobile robot autonomy has made significant advances in recent years, with navigation algorithms well developed and used commercially in certain well-defined environments, such as warehouses. The common link in usage scenarios is that the environments in which the robots are utilized have a high degree of certainty. Ope...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	288,687
2405.20245	Retrieval Augmented Structured Generation: Business Document Information Extraction As Tool Use	Business Document Information Extraction (BDIE) is the problem of transforming a blob of unstructured information (raw text, scanned documents, etc.) into a structured format that downstream systems can parse and use. It has two main tasks: Key-Information Extraction (KIE) and Line Items Recognition (LIR). In this pape...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	459,256
2311.15460	Privacy-Preserving Data Sharing in Agriculture: Enforcing Policy Rules for Secure and Confidential Data Synthesis	Big Data empowers the farming community with the information needed to optimize resource usage, increase productivity, and enhance the sustainability of agricultural practices. The use of Big Data in farming requires the collection and analysis of data from various sources such as sensors, satellites, and farmer survey...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	410,518
2109.13559	A Note on Nussbaum-type Control and Lie-bracket Approximation	In this paper, we propose an adaptive control law for completely unknown scalar linear systems based on Lie-bracket approximation methods. We investigate stability and convergence properties for the resulting Lie-bracket system, compare our proposal with existing Nussbaum-type solutions and demonstrate our results with...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	257,672
1311.6674	Modelling of the gravity compensators in robotic manufacturing cells	The paper deals with the modeling and identification of the gravity compensators used in heavy industrial robots. The main attention is paid to the geometrical parameters identification and calibration accuracy. To reduce impact of the measurement errors, the design of calibration experiments is used. The advantages of...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	28,674
2103.10198	Phylogenetic typology	In this article we propose a novel method to estimate the frequency distribution of linguistic variables while controlling for statistical non-independence due to shared ancestry. Unlike previous approaches, our technique uses all available data, from language families large and small as well as from isolates, while co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	225,381
2407.07596	Learning treatment effects while treating those in need	Many social programs attempt to allocate scarce resources to people with the greatest need. Indeed, public services increasingly use algorithmic risk assessments motivated by this goal. However, targeting the highest-need recipients often conflicts with attempting to evaluate the causal effect of the program as a whole...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	471,824
2308.05184	PromptPaint: Steering Text-to-Image Generation Through Paint Medium-like Interactions	While diffusion-based text-to-image (T2I) models provide a simple and powerful way to generate images, guiding this generation remains a challenge. For concepts that are difficult to describe through language, users may struggle to create prompts. Moreover, many of these models are built as end-to-end systems, lacking ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	384,707
1911.02972	Blockwise Self-Attention for Long Document Understanding	We present BlockBERT, a lightweight and efficient BERT model for better modeling long-distance dependencies. Our model extends BERT by introducing sparse block structures into the attention matrix to reduce both memory consumption and training/inference time, which also enables attention heads to capture either short- ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	152,509
2309.12767	Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models	Large Language Models (LLMs), acting as a powerful reasoner and generator, exhibit extraordinary performance across various natural language tasks, such as question answering (QA). Among these tasks, Multi-Hop Question Answering (MHQA) stands as a widely discussed category, necessitating seamless integration between LL...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	393,929
2109.05472	Compute and Energy Consumption Trends in Deep Learning Inference	The progress of some AI paradigms such as deep learning is said to be linked to an exponential growth in the number of parameters. There are many studies corroborating these trends, but does this translate into an exponential increase in energy consumption? In order to answer this question we focus on inference costs r...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	254,804
2412.14559	ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model	The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation remains largely unexplored. In this paper, we introduce a scalable motion generation framework that includes the motion tokenizer Motion FSQ-V...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	518,762
1804.07958	Expert Finding in Community Question Answering: A Review	The rapid development recently of Community Question Answering (CQA) satisfies users quest for professional and personal knowledge about anything. In CQA, one central issue is to find users with expertise and willingness to answer the given questions. Expert finding in CQA often exhibits very different challenges compa...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	95,649
2406.15331	Masked Extended Attention for Zero-Shot Virtual Try-On In The Wild	Virtual Try-On (VTON) is a highly active line of research, with increasing demand. It aims to replace a piece of garment in an image with one from another, while preserving person and garment characteristics as well as image fidelity. Current literature takes a supervised approach for the task, impairing generalization...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	466,699
2401.17100	The Influence of Presentation and Performance on User Satisfaction	The effectiveness of an IR system is gauged not just by its ability to retrieve relevant results but also by how it presents these results to users; an engaging presentation often correlates with increased user satisfaction. While existing research has delved into the link between user satisfaction, IR performance metr...	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	425,103
2309.00832	ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data	Despite powering sensitive systems like autonomous vehicles, object detection remains fairly brittle in part due to annotation errors that plague most real-world training datasets. We propose ObjectLab, a straightforward algorithm to detect diverse errors in object detection labels, including: overlooked bounding boxes...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	389,437
1711.09550	Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification	Recently, substantial research effort has focused on how to apply CNNs or RNNs to better extract temporal patterns from videos, so as to improve the accuracy of video classification. In this paper, however, we show that temporal information, especially longer-term patterns, may not be necessary to achieve competitive r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	85,432
2404.07061	A Tight $O(4^k/p_c)$ Runtime Bound for a ($\mu$+1) GA on Jump$_k$ for Realistic Crossover Probabilities	The Jump$_k$ benchmark was the first problem for which crossover was proven to give a speedup over mutation-only evolutionary algorithms. Jansen and Wegener (2002) proved an upper bound of $O({\rm poly}(n) + 4^k/p_c)$ for the ($\mu$+1)~Genetic Algorithm ($(\mu+1)$ GA), but only for unrealistically small crossover proba...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	445,703
1904.01648	Sequential Adaptive Design for Jump Regression Estimation	Selecting input variables or design points for statistical models has been of great interest in adaptive design and active learning. Motivated by two scientific examples, this paper presents a strategy of selecting the design points for a regression model when the underlying regression function is discontinuous. The fi...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	126,196
1701.00874	Neural Probabilistic Model for Non-projective MST Parsing	In this paper, we propose a probabilistic parsing model, which defines a proper conditional probability distribution over non-projective dependency trees for a given sentence, using neural representations as inputs. The neural network architecture is based on bi-directional LSTM-CNNs which benefits from both word- and ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	66,328
2208.00287	Simplex Clustering via sBeta with Applications to Online Adjustment of Black-Box Predictions	We explore clustering the softmax predictions of deep neural networks and introduce a novel probabilistic clustering method, referred to as k-sBetas. In the general context of clustering discrete distributions, the existing methods focused on exploring distortion measures tailored to simplex data, such as the KL diverg...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	310,801
2311.12092	Concept Sliders: LoRA Adaptors for Precise Control in Diffusion Models	We present a method to create interpretable concept sliders that enable precise control over attributes in image generations from diffusion models. Our approach identifies a low-rank parameter direction corresponding to one concept while minimizing interference with other attributes. A slider is created using a small s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	409,210
2109.13845	Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations	Background: Artificial intelligence (AI) may demonstrate racial bias when skin or choroidal pigmentation is present in medical images. Recent studies have shown that convolutional neural networks (CNNs) can predict race from images that were not previously thought to contain race-specific features. We evaluate whether ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	257,761
2308.07781	Learning Image Deraining Transformer Network with Dynamic Dual Self-Attention	Recently, Transformer-based architecture has been introduced into single image deraining task due to its advantage in modeling non-local information. However, existing approaches tend to integrate global features based on a dense self-attention strategy since it tend to uses all similarities of the tokens between the q...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	385,645
2110.06931	A neural simulation-based inference approach for characterizing the Galactic Center $\gamma$-ray excess	The nature of the Fermi gamma-ray Galactic Center Excess (GCE) has remained a persistent mystery for over a decade. Although the excess is broadly compatible with emission expected due to dark matter annihilation, an explanation in terms of a population of unresolved astrophysical point sources e.g., millisecond pulsar...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	260,796
2102.07073	Costly Features Classification using Monte Carlo Tree Search	We consider the problem of costly feature classification, where we sequentially select the subset of features to make a balance between the classification error and the feature cost. In this paper, we first cast the task into a MDP problem and use Advantage Actor Critic algorithm to solve it. In order to further improv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	219,978
2401.06588	Dynamic Behaviour of Connectionist Speech Recognition with Strong Latency Constraints	This paper describes the use of connectionist techniques in phonetic speech recognition with strong latency constraints. The constraints are imposed by the task of deriving the lip movements of a synthetic face in real time from the speech signal, by feeding the phonetic string into an articulatory synthesiser. Particu...	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	421,209
1803.02082	Partitioning signed networks	Signed networks appear naturally in contexts where conflict or animosity is apparent. In this book chapter we review some of the literature on signed networks, especially in the context of partitioning. Most of the work is founded in what is known as structural balance theory. We cover the basic mathematical principles...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	91,986
1109.5348	Dynkin Game of Stochastic Differential Equations with Random Coefficients, and Associated Backward Stochastic Partial Differential Variational Inequality	A Dynkin game is considered for stochastic differential equations with random coefficients. We first apply Qiu and Tang's maximum principle for backward stochastic partial differential equations to generalize Krylov estimate for the distribution of a Markov process to that of a non-Markov process, and establish a gener...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	12,308
2205.11485	Conditional Supervised Contrastive Learning for Fair Text Classification	Contrastive representation learning has gained much attention due to its superior performance in learning representations from both image and sequential data. However, the learned representations could potentially lead to performance disparities in downstream tasks, such as increased silencing of underrepresented group...	false	false	false	false	true	false	true	false	true	false	false	false	false	true	false	false	false	false	298,164
2105.07055	3D Two-Hop Cellular Networks with Wireless Backhauled UAVs: Modeling and Fundamentals	In this paper, we characterize the performance of a three-dimensional (3D) two-hop cellular network in which terrestrial base stations (BSs) coexist with unmanned aerial vehicles (UAVs) to serve a set of ground user equipment (UE). In particular, a UE connects either directly to its serving terrestrial BS by an access ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	235,299
2210.16776	Saliency Can Be All You Need In Contrastive Self-Supervised Learning	We propose an augmentation policy for Contrastive Self-Supervised Learning (SSL) in the form of an already established Salient Image Segmentation technique entitled Global Contrast based Salient Region Detection. This detection technique, which had been devised for unrelated Computer Vision tasks, was empirically obser...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	327,451
2410.18974	3D-Adapter: Geometry-Consistent Multi-View Diffusion for High-Quality 3D Generation	Multi-view image diffusion models have significantly advanced open-domain 3D object generation. However, most existing models rely on 2D network architectures that lack inherent 3D biases, resulting in compromised geometric consistency. To address this challenge, we introduce 3D-Adapter, a plug-in module designed to in...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	502,115
2402.18172	NiteDR: Nighttime Image De-Raining with Cross-View Sensor Cooperative Learning for Dynamic Driving Scenes	In real-world environments, outdoor imaging systems are often affected by disturbances such as rain degradation. Especially, in nighttime driving scenes, insufficient and uneven lighting shrouds the scenes in darkness, resulting degradation of both the image quality and visibility. Particularly, in the field of autonom...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	433,324
1903.06278	gym-gazebo2, a toolkit for reinforcement learning using ROS 2 and Gazebo	This paper presents an upgraded, real world application oriented version of gym-gazebo, the Robot Operating System (ROS) and Gazebo based Reinforcement Learning (RL) toolkit, which complies with OpenAI Gym. The content discusses the new ROS 2 based software architecture and summarizes the results obtained using Proxima...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	124,344
2101.08466	Anti-UAV: A Large Multi-Modal Benchmark for UAV Tracking	Unmanned Aerial Vehicle (UAV) offers lots of applications in both commerce and recreation. With this, monitoring the operation status of UAVs is crucially important. In this work, we consider the task of tracking UAVs, providing rich information such as location and trajectory. To facilitate research on this topic, we ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	216,331
2206.10892	I^2R-Net: Intra- and Inter-Human Relation Network for Multi-Person Pose Estimation	In this paper, we present the Intra- and Inter-Human Relation Networks (I^2R-Net) for Multi-Person Pose Estimation. It involves two basic modules. First, the Intra-Human Relation Module operates on a single person and aims to capture Intra-Human dependencies. Second, the Inter-Human Relation Module considers the relati...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	304,075
2105.05994	Neural Trajectory Fields for Dynamic Novel View Synthesis	Recent approaches to render photorealistic views from a limited set of photographs have pushed the boundaries of our interactions with pictures of static scenes. The ability to recreate moments, that is, time-varying sequences, is perhaps an even more interesting scenario, but it remains largely unsolved. We introduce ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	234,981
0707.4083	Chain of Separable Binary Goppa Codes and their Minimal Distance	It is shown that subclasses of separable binary Goppa codes, $\Gamma(L,G)$ - codes, with $L=\{\alpha \in GF(2^{2l}):G(\alpha)\neq 0 \}$ and special Goppa polynomials G(x) can be presented as a chain of embedded codes. The true minimal distance has been obtained for all codes of the chain.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	502
2011.07534	SAG-GAN: Semi-Supervised Attention-Guided GANs for Data Augmentation on Medical Images	Recently deep learning methods, in particular, convolutional neural networks (CNNs), have led to a massive breakthrough in the range of computer vision. Also, the large-scale annotated dataset is the essential key to a successful training procedure. However, it is a huge challenge to get such datasets in the medical do...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	206,593
2301.01149	I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation	Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image statistics and high-level contexts compromise the segmentation performance over the target domain. A key idea to tackle this problem is to perfor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	339,149
2401.06377	Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm	We propose a novel multi-section cable-driven soft robotic arm inspired by octopus tentacles along with a new modeling approach. Each section of the modular manipulator is made of a soft tubing backbone, a soft silicon arm body, and two rigid endcaps, which connect adjacent sections and decouple the actuation cables of...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	421,135
2301.06269	DarkVision: A Benchmark for Low-light Image/Video Perception	Imaging and perception in photon-limited scenarios is necessary for various applications, e.g., night surveillance or photography, high-speed photography, and autonomous driving. In these cases, cameras suffer from low signal-to-noise ratio, which degrades the image quality severely and poses challenges for downstream ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	340,603
1908.04092	Active Annotation: bootstrapping annotation lexicon and guidelines for supervised NLU learning	Natural Language Understanding (NLU) models are typically trained in a supervised learning framework. In the case of intent classification, the predicted labels are predefined and based on the designed annotation schema while the labelling process is based on a laborious task where annotators manually inspect each utte...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	141,404
2011.03078	Parameter Identification and Sensitivity Analysis for Zero-dimensional Physics-based Lithium-Sulfur Battery Models	This paper examines the problem of estimating the parameters of a Lithium-Sulfur (LiS) battery from experimental cycling data. LiS batteries are attractive compared to traditional Lithium-Ion batteries, thanks largely to their potential to provide higher energy densities. The literature presents a number of different L...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	205,119
2407.03618	BM25S: Orders of magnitude faster lexical search via eager sparse scoring	We introduce BM25S, an efficient Python-based implementation of BM25 that only depends on Numpy and Scipy. BM25S achieves up to a 500x speedup compared to the most popular Python-based framework by eagerly computing BM25 scores during indexing and storing them into sparse matrices. It also achieves considerable speedup...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	470,222
2010.08258	Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models	The learning and evaluation of energy-based latent variable models (EBLVMs) without any structural assumptions are highly challenging, because the true posteriors and the partition functions in such models are generally intractable. This paper presents variational estimates of the score function and its gradient with r...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	201,127
2305.15730	A Tutorial on Holographic MIMO Communications--Part II: Performance Analysis and Holographic Beamforming	As Part II of a three-part tutorial on holographic multiple-input multiple-output (HMIMO), this Letter focuses on the state-of-the-art in performance analysis and on holographic beamforming for HMIMO communications. We commence by discussing the spatial degrees of freedom (DoF) and ergodic capacity of a point-to-point ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	367,749
1805.07468	Unsupervised Learning of Neural Networks to Explain Neural Networks	This paper presents an unsupervised method to learn a neural network, namely an explainer, to interpret a pre-trained convolutional neural network (CNN), i.e., explaining knowledge representations hidden in middle conv-layers of the CNN. Given feature maps of a certain conv-layer of the CNN, the explainer performs like...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	97,829
2210.12254	Score-based Denoising Diffusion with Non-Isotropic Gaussian Noise Models	Generative models based on denoising diffusion techniques have led to an unprecedented increase in the quality and diversity of imagery that is now possible to create with neural generative models. However, most contemporary state-of-the-art methods are derived from a standard isotropic Gaussian formulation. In this wo...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	325,652
2301.10780	Quantum anomaly detection in the latent space of proton collision events at the LHC	The ongoing quest to discover new phenomena at the LHC necessitates the continuous development of algorithms and technologies. Established approaches like machine learning, along with emerging technologies such as quantum computing show promise in the enhancement of experimental capabilities. In this work, we propose a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,906
1706.07532	A generalized framework for the estimation of edge infection probabilities	Modeling the spread of infections on networks is a well-studied and important field of research. Most infection and diffusion models require a real value or probability on the edges of the network as an input, but this is rarely available in real-life applications. Our goal in this paper is to develop a general framewo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	75,863
2009.07469	Deep Sinogram Completion with Image Prior for Metal Artifact Reduction in CT Images	Computed tomography (CT) has been widely used for medical diagnosis, assessment, and therapy planning and guidance. In reality, CT images may be affected adversely in the presence of metallic objects, which could lead to severe metal artifacts and influence clinical diagnosis or dose calculation in radiation therapy. I...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	195,937
2111.02118	A Novel Actuation Strategy for an Agile Bio-inspired FWAV Performing a Morphing-coupled Wingbeat Pattern	Flying vertebrates exhibit sophisticated wingbeat kinematics. Their specialized forelimbs allow for the wing morphing motion to couple with the flapping motion during their level flight, Previous flyable bionic platforms have successfully applied bio-inspired wing morphing but cannot yet be propelled by the morphing-co...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	264,768
2303.09266	SmartBERT: A Promotion of Dynamic Early Exiting Mechanism for Accelerating BERT Inference	Dynamic early exiting has been proven to improve the inference speed of the pre-trained language model like BERT. However, all samples must go through all consecutive layers before early exiting and more complex samples usually go through more layers, which still exists redundant computation. In this paper, we propose ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	351,974

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