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
2102.00798	Landmark Breaker: Obstructing DeepFake By Disturbing Landmark Extraction	The recent development of Deep Neural Networks (DNN) has significantly increased the realism of AI-synthesized faces, with the most notable examples being the DeepFakes. The DeepFake technology can synthesize a face of target subject from a face of another subject, while retains the same face attributes. With the rapid...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	217,912
2408.12752	High-distance codes with transversal Clifford and T-gates	The non-local interactions in several quantum devices allow for the realization of more compact quantum encodings while retaining the same degree of protection against noise. Anticipating that short to medium-length codes will soon be realizable, it is important to construct stabilizer codes that, for a given code dist...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	482,863
2301.03635	Evolutionary Carrier Selection for Shared Truck Delivery Services	With multiple carriers in a logistics market, customers can choose the best carrier to deliver their products and packages. In this paper, we present a novel approach of using the stochastic evolutionary game to analyze the decision-making of the customers using the less-than-truckload (LTL) delivery service. We propos...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	339,851
2302.02650	Tree-Based Learning on Amperometric Time Series Data Demonstrates High Accuracy for Classification	Elucidating exocytosis processes provide insights into cellular neurotransmission mechanisms, and may have potential in neurodegenerative diseases research. Amperometry is an established electrochemical method for the detection of neurotransmitters released from and stored inside cells. An important aspect of the amper...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	344,076
2211.13672	A Self-Attention Ansatz for Ab-initio Quantum Chemistry	We present a novel neural network architecture using self-attention, the Wavefunction Transformer (Psiformer), which can be used as an approximation (or Ansatz) for solving the many-electron Schr\"odinger equation, the fundamental equation for quantum chemistry and material science. This equation can be solved from fir...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	332,548
1805.12243	Novel Video Prediction for Large-scale Scene using Optical Flow	Making predictions of future frames is a critical challenge in autonomous driving research. Most of the existing methods for video prediction attempt to generate future frames in simple and fixed scenes. In this paper, we propose a novel and effective optical flow conditioned method for the task of video prediction wit...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	99,122
2112.13021	Noninvasive Fetal Electrocardiography: Models, Technologies and Algorithms	The fetal electrocardiogram (fECG) was first recorded from the maternal abdominal surface in the early 1900s. During the past fifty years, the most advanced electronics technologies and signal processing algorithms have been used to convert noninvasive fetal electrocardiography into a reliable technology for fetal card...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,120
1602.04418	Identifiability Assumptions and Algorithm for Directed Graphical Models with Feedback	Directed graphical models provide a useful framework for modeling causal or directional relationships for multivariate data. Prior work has largely focused on identifiability and search algorithms for directed acyclic graphical (DAG) models. In many applications, feedback naturally arises and directed graphical models ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	52,127
2010.05312	Covid-19 vaccination strategies with limited resources -- a model based on social network graphs	We develop a model of infection spread that takes into account the existence of a vulnerable group as well as the variability of the social relations of individuals. We develop a compartmentalized power-law model, with power-law connections between the vulnerable and the general population, considering these connection...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	200,065
2310.17041	On Surgical Fine-tuning for Language Encoders	Fine-tuning all the layers of a pre-trained neural language encoder (either using all the parameters or using parameter-efficient methods) is often the de-facto way of adapting it to a new task. We show evidence that for different downstream language tasks, fine-tuning only a subset of layers is sufficient to obtain pe...	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	false	false	402,968
2407.00706	Sum-of-norms regularized Nonnegative Matrix Factorization	When applying nonnegative matrix factorization (NMF), generally the rank parameter is unknown. Such rank in NMF, called the nonnegative rank, is usually estimated heuristically since computing the exact value of it is NP-hard. In this work, we propose an approximation method to estimate such rank while solving NMF on-t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,977
2311.14777	From Text to Image: Exploring GPT-4Vision's Potential in Advanced Radiological Analysis across Subspecialties	The study evaluates and compares GPT-4 and GPT-4Vision for radiological tasks, suggesting GPT-4Vision may recognize radiological features from images, thereby enhancing its diagnostic potential over text-based descriptions.	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	410,259
1905.04083	ES-CTC: A Deep Neuroevolution Model for Cooperative Intelligent Freeway Traffic Control	Cooperative intelligent freeway traffic control is an important application in intelligent transportation systems, which is expected to improve the mobility of freeway networks. In this paper, we propose a deep neuroevolution model, called ES-CTC, to achieve a cooperative control scheme of ramp metering, differential v...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	130,364
2304.04884	Multi-Sample Consensus Driven Unsupervised Normal Estimation for 3D Point Clouds	Deep normal estimators have made great strides on synthetic benchmarks. Unfortunately, their performance dramatically drops on the real scan data since they are supervised only on synthetic datasets. The point-wise annotation of ground truth normals is vulnerable to inefficiency and inaccuracies, which totally makes it...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	357,395
2308.13474	OCTAL: Graph Representation Learning for LTL Model Checking	Model Checking is widely applied in verifying the correctness of complex and concurrent systems against a specification. Pure symbolic approaches while popular, suffer from the state space explosion problem due to cross product operations required that make them prohibitively expensive for large-scale systems and/or sp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	387,932
2409.17547	Triple Point Masking	Existing 3D mask learning methods encounter performance bottlenecks under limited data, and our objective is to overcome this limitation. In this paper, we introduce a triple point masking scheme, named TPM, which serves as a scalable framework for pre-training of masked autoencoders to achieve multi-mask learning for ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	491,860
1806.00148	Interpreting Deep Learning: The Machine Learning Rorschach Test?	Theoretical understanding of deep learning is one of the most important tasks facing the statistics and machine learning communities. While deep neural networks (DNNs) originated as engineering methods and models of biological networks in neuroscience and psychology, they have quickly become a centerpiece of the machin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	99,244
2401.01053	Cheetah: Natural Language Generation for 517 African Languages	Low-resource African languages pose unique challenges for natural language processing (NLP) tasks, including natural language generation (NLG). In this paper, we develop Cheetah, a massively multilingual NLG language model for African languages. Cheetah supports 517 African languages and language varieties, allowing us...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	419,204
2501.04729	Stability Exchange near Folds: Analysis of an end-loaded Elastica with a Lever Arm	Numerous problems in physical sciences can be expressed as parameter-dependent variational problems. The associated family of equilibria may or may not exist realistically and can be determined after examining its stability. Hence, it is crucial to determine the stability and track its transitions. Generally, the stabi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	523,321
2401.11531	Tempo: Confidentiality Preservation in Cloud-Based Neural Network Training	Cloud deep learning platforms provide cost-effective deep neural network (DNN) training for customers who lack computation resources. However, cloud systems are often untrustworthy and vulnerable to attackers, leading to growing concerns about model privacy. Recently, researchers have sought to protect data privacy in ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	423,041
2310.13218	Deep Reinforcement Learning-Enabled Adaptive Forecasting-Aided State Estimation in Distribution Systems with Multi-Source Multi-Rate Data	Distribution system state estimation (DSSE) is paramount for effective state monitoring and control. However, stochastic outputs of renewables and asynchronous streaming of multi-rate measurements in practical systems largely degrade the estimation performance. This paper proposes a deep reinforcement learning (DRL)-en...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	401,339
2502.01908	Unlocking Efficient Large Inference Models: One-Bit Unrolling Tips the Scales	Recent advancements in Large Language Model (LLM) compression, such as BitNet and BitNet b1.58, have marked significant strides in reducing the computational demands of LLMs through innovative one-bit quantization techniques. We extend this frontier by looking at Large Inference Models (LIMs) that have become indispens...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	530,084
2404.15074	Outage Probability Analysis of Wireless Paths with Faulty Reconfigurable Intelligent Surfaces	We consider a next generation wireless network incorporating a base station a set of typically low-cost and faulty Reconfigurable Intelligent Surfaces (RISs). The base station needs to select the path including the RIS to provide the maximum signal-to-noise ratio (SNR) to the user. We study the effect of the number of ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	448,934
2406.17542	CDQuant: Greedy Coordinate Descent for Accurate LLM Quantization	Large language models (LLMs) have recently demonstrated remarkable performance across diverse language tasks. But their deployment is often constrained by their substantial computational and storage requirements. Quantization has emerged as a key technique for addressing this challenge, enabling the compression of larg...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	467,616
2305.08883	Watermarking Text Generated by Black-Box Language Models	LLMs now exhibit human-like skills in various fields, leading to worries about misuse. Thus, detecting generated text is crucial. However, passive detection methods are stuck in domain specificity and limited adversarial robustness. To achieve reliable detection, a watermark-based method was proposed for white-box LLMs...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	364,446
2105.04222	Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking	Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper, we propose a slot description enhanced generative approach for zero-shot cross-domain DST. Specifically, our model first encodes dialogue co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	234,433
1401.1753	A Solution of Degree Constrained Spanning Tree Using Hybrid GA	In real life, it is always an urge to reach our goal in minimum effort i.e., it should have a minimum constrained path. The path may be shortest route in practical life, either physical or electronic medium. The scenario is to represents the ambiance as a graph and to find a spanning tree with custom design criteria. H...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	29,680
2110.03232	Design of an Intelligent Vision Algorithm for Recognition and Classification of Apples in an Orchard Scene	Apple is one of the remarkable fresh fruit that contains a high degree of nutritious and medicinal value. Hand harvesting of apples by seasonal farmworkers increases physical damages on the surface of these fruits, which causes a great loss in marketing quality. The main objective of this study is focused on designing ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	259,418
2106.00576	Exposing Previously Undetectable Faults in Deep Neural Networks	Existing methods for testing DNNs solve the oracle problem by constraining the raw features (e.g. image pixel values) to be within a small distance of a dataset example for which the desired DNN output is known. But this limits the kinds of faults these approaches are able to detect. In this paper, we introduce a novel...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	238,178
1906.09762	Closed-Form Delay-Optimal Computation Offloading in Mobile Edge Computing Systems	Mobile edge computing (MEC) has recently emerged as a promising technology to release the tension between computation-intensive applications and resource-limited mobile terminals (MTs). In this paper, we study the delay-optimal computation offloading in computation-constrained MEC systems. We consider the computation t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	136,260
2408.04708	MulliVC: Multi-lingual Voice Conversion With Cycle Consistency	Voice conversion aims to modify the source speaker's voice to resemble the target speaker while preserving the original speech content. Despite notable advancements in voice conversion these days, multi-lingual voice conversion (including both monolingual and cross-lingual scenarios) has yet to be extensively studied. ...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	479,498
2307.01069	Shi-NeSS: Detecting Good and Stable Keypoints with a Neural Stability Score	Learning a feature point detector presents a challenge both due to the ambiguity of the definition of a keypoint and correspondingly the need for a specially prepared ground truth labels for such points. In our work, we address both of these issues by utilizing a combination of a hand-crafted Shi detector and a neural ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	377,224
1910.11106	Label-Conditioned Next-Frame Video Generation with Neural Flows	Recent state-of-the-art video generation systems employ Generative Adversarial Networks (GANs) or Variational Autoencoders (VAEs) to produce novel videos. However, VAE models typically produce blurry outputs when faced with sub-optimal conditioning of the input, and GANs are known to be unstable for large output sizes....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,685
1910.08216	A language processing algorithm for predicting tactical solutions to an operational planning problem under uncertainty	This paper is devoted to the prediction of solutions to a stochastic discrete optimization problem. Through an application, we illustrate how we can use a state-of-the-art neural machine translation (NMT) algorithm to predict the solutions by defining appropriate vocabularies, syntaxes and constraints. We attend to app...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,805
2111.10078	Defeating Catastrophic Forgetting via Enhanced Orthogonal Weights Modification	The ability of neural networks (NNs) to learn and remember multiple tasks sequentially is facing tough challenges in achieving general artificial intelligence due to their catastrophic forgetting (CF) issues. Fortunately, the latest OWM Orthogonal Weights Modification) and other several continual learning (CL) methods ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	267,201
2102.03674	Generating Artificial Core Users for Interpretable Condensed Data	Recent work has shown that in a dataset of user ratings on items there exists a group of Core Users who hold most of the information necessary for recommendation. This set of Core Users can be as small as 20 percent of the users. Core Users can be used to make predictions for out-of-sample users without much additional...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	218,827
2311.13231	Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model	Using reinforcement learning with human feedback (RLHF) has shown significant promise in fine-tuning diffusion models. Previous methods start by training a reward model that aligns with human preferences, then leverage RL techniques to fine-tune the underlying models. However, crafting an efficient reward model demands...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	409,675
1909.02688	AutoGMM: Automatic and Hierarchical Gaussian Mixture Modeling in Python	Background: Gaussian mixture modeling is a fundamental tool in clustering, as well as discriminant analysis and semiparametric density estimation. However, estimating the optimal model for any given number of components is an NP-hard problem, and estimating the number of components is in some respects an even harder pr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	144,258
1610.02567	Mining the Web for Pharmacovigilance: the Case Study of Duloxetine and Venlafaxine	Adverse reactions caused by drugs following their release into the market are among the leading causes of death in many countries. The rapid growth of electronically available health related information, and the ability to process large volumes of them automatically, using natural language processing (NLP) and machine ...	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	62,119
2010.03146	Unsupervised Parsing via Constituency Tests	We propose a method for unsupervised parsing based on the linguistic notion of a constituency test. One type of constituency test involves modifying the sentence via some transformation (e.g. replacing the span with a pronoun) and then judging the result (e.g. checking if it is grammatical). Motivated by this idea, we ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	199,294
2207.02736	Characterizing disruptions in online gaming behavior following software patches	Multiplayer online games are ideal settings for studying the effects of technological disruptions on social behavior. Software patches to online games cause significant changes to the game's rules and require players to develop new strategies to cope with these disruptions. We surveyed players, analyzed the content of ...	true	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	true	306,604
2404.02595	QFNN-FFD: Quantum Federated Neural Network for Financial Fraud Detection	This study introduces the Quantum Federated Neural Network for Financial Fraud Detection (QFNN-FFD), a cutting-edge framework merging Quantum Machine Learning (QML) and quantum computing with Federated Learning (FL) for financial fraud detection. Using quantum technologies' computational power and the robust data priva...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	443,931
1206.6404	Policy Gradients with Variance Related Risk Criteria	Managing risk in dynamic decision problems is of cardinal importance in many fields such as finance and process control. The most common approach to defining risk is through various variance related criteria such as the Sharpe Ratio or the standard deviation adjusted reward. It is known that optimizing many of the vari...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	16,939
2406.04746	PQPP: A Joint Benchmark for Text-to-Image Prompt and Query Performance Prediction	Text-to-image generation has recently emerged as a viable alternative to text-to-image retrieval, due to the visually impressive results of generative diffusion models. Although query performance prediction is an active research topic in information retrieval, to the best of our knowledge, there is no prior study that ...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	false	461,823
2001.05571	On Model Evaluation under Non-constant Class Imbalance	Many real-world classification problems are significantly class-imbalanced to detriment of the class of interest. The standard set of proper evaluation metrics is well-known but the usual assumption is that the test dataset imbalance equals the real-world imbalance. In practice, this assumption is often broken for vari...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	160,576
2208.06416	Uni6Dv2: Noise Elimination for 6D Pose Estimation	Uni6D is the first 6D pose estimation approach to employ a unified backbone network to extract features from both RGB and depth images. We discover that the principal reasons of Uni6D performance limitations are Instance-Outside and Instance-Inside noise. Uni6D's simple pipeline design inherently introduces Instance-Ou...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,712
2401.08135	Machine Learning-Based Malicious Vehicle Detection for Security Threats and Attacks in Vehicle Ad-hoc Network (VANET) Communications	With the rapid growth of Vehicle Ad-hoc Network (VANET) as a promising technology for efficient and reliable communication among vehicles and infrastructure, the security and integrity of VANET communications has become a critical concern. One of the significant threats to VANET is the presence of blackhole attacks, wh...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	421,777
2301.13359	IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing	Image anomaly detection (IAD) is an emerging and vital computer vision task in industrial manufacturing (IM). Recently, many advanced algorithms have been reported, but their performance deviates considerably with various IM settings. We realize that the lack of a uniform IM benchmark is hindering the development and u...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	342,873
1902.09155	CityJSON: a compact and easy-to-use encoding of the CityGML data model	The international standard CityGML is both a data model and an exchange format to store digital 3D models of cities. While the data model is used by several cities, companies, and governments, in this paper we argue that its XML-based exchange format has several drawbacks. These drawbacks mean that it is difficult for ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	122,357
1806.02375	Understanding Batch Normalization	Batch normalization (BN) is a technique to normalize activations in intermediate layers of deep neural networks. Its tendency to improve accuracy and speed up training have established BN as a favorite technique in deep learning. Yet, despite its enormous success, there remains little consensus on the exact reason and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	99,764
1709.06919	Bayesian Optimization with Automatic Prior Selection for Data-Efficient Direct Policy Search	One of the most interesting features of Bayesian optimization for direct policy search is that it can leverage priors (e.g., from simulation or from previous tasks) to accelerate learning on a robot. In this paper, we are interested in situations for which several priors exist but we do not know in advance which one fi...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	true	false	false	81,199
2301.13173	Shape-aware Text-driven Layered Video Editing	Temporal consistency is essential for video editing applications. Existing work on layered representation of videos allows propagating edits consistently to each frame. These methods, however, can only edit object appearance rather than object shape changes due to the limitation of using a fixed UV mapping field for te...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	342,808
2301.03142	Exploration in Model-based Reinforcement Learning with Randomized Reward	Model-based Reinforcement Learning (MBRL) has been widely adapted due to its sample efficiency. However, existing worst-case regret analysis typically requires optimistic planning, which is not realistic in general. In contrast, motivated by the theory, empirical study utilizes ensemble of models, which achieve state-o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	339,711
2007.15831	OREBA: A Dataset for Objectively Recognizing Eating Behaviour and Associated Intake	Automatic detection of intake gestures is a key element of automatic dietary monitoring. Several types of sensors, including inertial measurement units (IMU) and video cameras, have been used for this purpose. The common machine learning approaches make use of the labeled sensor data to automatically learn how to make ...	true	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	189,773
1912.05888	Variational Coupling Revisited: Simpler Models, Theoretical Connections, and Novel Applications	Variational models with coupling terms are becoming increasingly popular in image analysis. They involve auxiliary variables, such that their energy minimisation splits into multiple fractional steps that can be solved easier and more efficiently. In our paper we show that coupling models offer a number of interesting ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,212
2502.06802	Solving the Content Gap in Roblox Game Recommendations: LLM-Based Profile Generation and Reranking	With the vast and dynamic user-generated content on Roblox, creating effective game recommendations requires a deep understanding of game content. Traditional recommendation models struggle with the inconsistent and sparse nature of game text features such as titles and descriptions. Recent advancements in large langua...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	532,249
0806.1834	A Low-decoding-complexity, Large coding Gain, Full-rate, Full-diversity STBC for 4 X 2 MIMO System	This paper proposes a low decoding complexity, full-diversity and full-rate space-time block code (STBC) for 4 transmit and 2 receive ($4\times 2$) multiple-input multiple-output (MIMO) systems. For such systems, the best code known is the DjABBA code and recently, Biglieri, Hong and Viterbo have proposed another STBC ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	1,906
2210.02596	Role of Deep Learning in Wireless Communications	Traditional communication system design has always been based on the paradigm of first establishing a mathematical model of the communication channel, then designing and optimizing the system according to the model. The advent of modern machine learning techniques, specifically deep neural networks, has opened up oppor...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	321,701
1512.07103	A Class of Linear Codes with a Few Weights	Linear codes have been an interesting subject of study for many years, as linear codes with few weights have applications in secrete sharing, authentication codes, association schemes, and strongly regular graphs. In this paper, a class of linear codes with a few weights over the finite field $\gf(p)$ are presented and...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	50,390
2108.02924	Interpretable Visual Understanding with Cognitive Attention Network	While image understanding on recognition-level has achieved remarkable advancements, reliable visual scene understanding requires comprehensive image understanding on recognition-level but also cognition-level, which calls for exploiting the multi-source information as well as learning different levels of understanding...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	249,495
1706.07440	End-to-end Conversation Modeling Track in DSTC6	End-to-end training of neural networks is a promising approach to automatic construction of dialog systems using a human-to-human dialog corpus. Recently, Vinyals et al. tested neural conversation models using OpenSubtitles. Lowe et al. released the Ubuntu Dialogue Corpus for researching unstructured multi-turn dialogu...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	75,839
1604.06486	Humans and deep networks largely agree on which kinds of variation make object recognition harder	View-invariant object recognition is a challenging problem, which has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g. 3D rotations). Humans are thought to so...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	54,943
1909.03683	Don't Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases	State-of-the-art models often make use of superficial patterns in the data that do not generalize well to out-of-domain or adversarial settings. For example, textual entailment models often learn that particular key words imply entailment, irrespective of context, and visual question answering models learn to predict p...	false	false	false	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	144,575
2412.17787	Cross-Lingual Text-Rich Visual Comprehension: An Information Theory Perspective	Recent Large Vision-Language Models (LVLMs) have shown promising reasoning capabilities on text-rich images from charts, tables, and documents. However, the abundant text within such images may increase the model's sensitivity to language. This raises the need to evaluate LVLM performance on cross-lingual text-rich vis...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	520,112
2412.09200	Accuracy Improvements for Convolutional and Differential Distance Function Approximations	Given a bounded domain, we deal with the problem of estimating the distance function from the internal points of the domain to the boundary of the domain. Convolutional and differential distance estimation schemes are considered and, for both the schemes, accuracy improvements are proposed and evaluated. Asymptotics of...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	516,394
1701.08939	Deep Submodular Functions	We start with an overview of a class of submodular functions called SCMMs (sums of concave composed with non-negative modular functions plus a final arbitrary modular). We then define a new class of submodular functions we call {\em deep submodular functions} or DSFs. We show that DSFs are a flexible parametric family ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	67,560
1507.06682	Supervised Collective Classification for Crowdsourcing	Crowdsourcing utilizes the wisdom of crowds for collective classification via information (e.g., labels of an item) provided by labelers. Current crowdsourcing algorithms are mainly unsupervised methods that are unaware of the quality of crowdsourced data. In this paper, we propose a supervised collective classificatio...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	45,406
2106.05891	Temporal and Object Quantification Networks	We present Temporal and Object Quantification Networks (TOQ-Nets), a new class of neuro-symbolic networks with a structural bias that enables them to learn to recognize complex relational-temporal events. This is done by including reasoning layers that implement finite-domain quantification over objects and time. The s...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	240,270
1910.03320	One-To-Many Multilingual End-to-end Speech Translation	Nowadays, training end-to-end neural models for spoken language translation (SLT) still has to confront with extreme data scarcity conditions. The existing SLT parallel corpora are indeed orders of magnitude smaller than those available for the closely related tasks of automatic speech recognition (ASR) and machine tra...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	148,469
1510.01288	5G Ultra-Reliable Vehicular Communication	Applications enabled by Cooperative Intelligent Transport Systems (C-ITS) represent a major step towards making the road transport system safer and more efficient (green), and thus suited for a sustainable future. Wireless communication between vehicles and road infrastructure is an enabler for high-performance C-ITS a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	47,599
2405.02952	Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving	Scientific computing is an essential tool for scientific discovery and engineering design, and its computational cost is always a main concern in practice. To accelerate scientific computing, it is a promising approach to use machine learning (especially meta-learning) techniques for selecting hyperparameters of tradit...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	451,989
1512.07943	Toward a Research Agenda in Adversarial Reasoning: Computational Approaches to Anticipating the Opponent's Intent and Actions	This paper defines adversarial reasoning as computational approaches to inferring and anticipating an enemy's perceptions, intents and actions. It argues that adversarial reasoning transcends the boundaries of game theory and must also leverage such disciplines as cognitive modeling, control theory, AI planning and oth...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	50,468
2404.11803	TempBEV: Improving Learned BEV Encoders with Combined Image and BEV Space Temporal Aggregation	Autonomous driving requires an accurate representation of the environment. A strategy toward high accuracy is to fuse data from several sensors. Learned Bird's-Eye View (BEV) encoders can achieve this by mapping data from individual sensors into one joint latent space. For cost-efficient camera-only systems, this provi...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	447,617
1606.07232	Distributed Wireless Power Transfer with Energy Feedback	Energy beamforming (EB) is a key technique for achieving efficient radio-frequency (RF) transmission enabled wireless energy transfer (WET). By optimally designing the waveforms from multiple energy transmitters (ETs) over the wireless channels, they can be constructively combined at the energy receiver (ER) to achieve...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	57,676
2410.08549	Score Neural Operator: A Generative Model for Learning and Generalizing Across Multiple Probability Distributions	Most existing generative models are limited to learning a single probability distribution from the training data and cannot generalize to novel distributions for unseen data. An architecture that can generate samples from both trained datasets and unseen probability distributions would mark a significant breakthrough. ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	497,163
2302.08680	Modeling Polypharmacy and Predicting Drug-Drug Interactions using Deep Generative Models on Multimodal Graphs	Latent representations of drugs and their targets produced by contemporary graph autoencoder models have proved useful in predicting many types of node-pair interactions on large networks, including drug-drug, drug-target, and target-target interactions. However, most existing approaches model either the node's latent ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,140
2302.00189	Detecting Lexical Borrowings from Dominant Languages in Multilingual Wordlists	Language contact is a pervasive phenomenon reflected in the borrowing of words from donor to recipient languages. Most computational approaches to borrowing detection treat all languages under study as equally important, even though dominant languages have a stronger impact on heritage languages than vice versa. We tes...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	343,130
1907.03250	Resource-Efficient Wearable Computing for Real-Time Reconfigurable Machine Learning: A Cascading Binary Classification	Advances in embedded systems have enabled integration of many lightweight sensory devices within our daily life. In particular, this trend has given rise to continuous expansion of wearable sensors in a broad range of applications from health and fitness monitoring to social networking and military surveillance. Wearab...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,821
2310.09929	Prompting Scientific Names for Zero-Shot Species Recognition	Trained on web-scale image-text pairs, Vision-Language Models (VLMs) such as CLIP can recognize images of common objects in a zero-shot fashion. However, it is underexplored how to use CLIP for zero-shot recognition of highly specialized concepts, e.g., species of birds, plants, and animals, for which their scientific ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	400,010
2302.14421	Publicly verifiable delegative democracy with secret voting power	In a democratic setting, we introduce a commitment scheme which allows for transparent validation of transfers and reversible delegations of voting power between citizens without sacrificing their privacy. A unit of voting power is publicly represented by the Merkle root of a tree consisting of its latest owner's publi...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	true	348,292
2105.05915	Better than BERT but Worse than Baseline	This paper compares BERT-SQuAD and Ab3P on the Abbreviation Definition Identification (ADI) task. ADI inputs a text and outputs short forms (abbreviations/acronyms) and long forms (expansions). BERT with reranking improves over BERT without reranking but fails to reach the Ab3P rule-based baseline. What is BERT missing...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	234,955
2009.10619	An Exponential Factorization Machine with Percentage Error Minimization to Retail Sales Forecasting	This paper proposes a new approach to sales forecasting for new products with long lead time but short product life cycle. These SKUs are usually sold for one season only, without any replenishments. An exponential factorization machine (EFM) sales forecast model is developed to solve this problem which not only consid...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	196,936
1703.06541	Native Language Identification using Stacked Generalization	Ensemble methods using multiple classifiers have proven to be the most successful approach for the task of Native Language Identification (NLI), achieving the current state of the art. However, a systematic examination of ensemble methods for NLI has yet to be conducted. Additionally, deeper ensemble architectures such...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	70,246
2406.03164	Topological Neural Networks go Persistent, Equivariant, and Continuous	Topological Neural Networks (TNNs) incorporate higher-order relational information beyond pairwise interactions, enabling richer representations than Graph Neural Networks (GNNs). Concurrently, topological descriptors based on persistent homology (PH) are being increasingly employed to augment the GNNs. We investigate ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,122
2105.05714	Representation in Dynamical Systems	The brain is often called a computer and likened to a Turing machine, in part because the mind can manipulate discrete symbols such as numbers. But the brain is a dynamical system, more like a Watt governor than a Turing machine. Can a dynamical system be said to operate using "representations"? This paper argues that ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	234,898
2410.02027	Quantifying the Gaps Between Translation and Native Perception in Training for Multimodal, Multilingual Retrieval	There is a scarcity of multilingual vision-language models that properly account for the perceptual differences that are reflected in image captions across languages and cultures. In this work, through a multimodal, multilingual retrieval case study, we quantify the existing lack of model flexibility. We empirically sh...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	494,064
1607.00225	Evaluating Unsupervised Dutch Word Embeddings as a Linguistic Resource	Word embeddings have recently seen a strong increase in interest as a result of strong performance gains on a variety of tasks. However, most of this research also underlined the importance of benchmark datasets, and the difficulty of constructing these for a variety of language-specific tasks. Still, many of the datas...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	58,047
1205.0837	Indexing Reverse Top-k Queries	We consider the recently introduced monochromatic reverse top-k queries which ask for, given a new tuple q and a dataset D, all possible top-k queries on D union {q} for which q is in the result. Towards this problem, we focus on designing indexes in two dimensions for repeated (or batch) querying, a novel but practica...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	15,791
2409.03701	LAST: Language Model Aware Speech Tokenization	Speech tokenization serves as the foundation of speech language model (LM), enabling them to perform various tasks such as spoken language modeling, text-to-speech, speech-to-text, etc. Most speech tokenizers are trained independently of the LM training process, relying on separate acoustic models and quantization meth...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	486,134
2207.06754	E2-AEN: End-to-End Incremental Learning with Adaptively Expandable Network	Expandable networks have demonstrated their advantages in dealing with catastrophic forgetting problem in incremental learning. Considering that different tasks may need different structures, recent methods design dynamic structures adapted to different tasks via sophisticated skills. Their routine is to search expanda...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	307,980
2402.17559	GraphMatch: Subgraph Query Processing on FPGAs	Efficiently finding subgraph embeddings in large graphs is crucial for many application areas like biology and social network analysis. Set intersections are the predominant and most challenging aspect of current join-based subgraph query processing systems for CPUs. Previous work has shown the viability of utilizing F...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	433,048
2303.12149	SPARTAN: Self-supervised Spatiotemporal Transformers Approach to Group Activity Recognition	In this paper, we propose a new, simple, and effective Self-supervised Spatio-temporal Transformers (SPARTAN) approach to Group Activity Recognition (GAR) using unlabeled video data. Given a video, we create local and global Spatio-temporal views with varying spatial patch sizes and frame rates. The proposed self-super...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,153
2003.02541	A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation	This work addresses the unsupervised domain adaptation problem, especially in the case of class labels in the target domain being only a subset of those in the source domain. Such a partial transfer setting is realistic but challenging and existing methods always suffer from two key problems, negative transfer and unce...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	166,963
1612.04966	Design of Image Matched Non-Separable Wavelet using Convolutional Neural Network	Image-matched nonseparable wavelets can find potential use in many applications including image classification, segmen- tation, compressive sensing, etc. This paper proposes a novel design methodology that utilizes convolutional neural net- work (CNN) to design two-channel non-separable wavelet matched to a given image...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	65,614
1803.00357	Cross-lingual and Multilingual Speech Emotion Recognition on English and French	Research on multilingual speech emotion recognition faces the problem that most available speech corpora differ from each other in important ways, such as annotation methods or interaction scenarios. These inconsistencies complicate building a multilingual system. We present results for cross-lingual and multilingual e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	91,656
1511.07271	Synthesizing Omnidirectional Antenna Patterns, Received Power and Path Loss from Directional Antennas for 5G Millimeter-Wave Communications	Omnidirectional path loss models are vital for radiosystem design in wireless communication systems, as they allow engineers to perform network simulations for systems with arbitrary antenna patterns. At millimeter-wave frequencies, channel measurements are frequently conducted using steerable highgain directional ante...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	49,402
2312.10040	Robust Errant Beam Prognostics with Conditional Modeling for Particle Accelerators	Particle accelerators are complex and comprise thousands of components, with many pieces of equipment running at their peak power. Consequently, particle accelerators can fault and abort operations for numerous reasons. These faults impact the availability of particle accelerators during scheduled run-time and hamper t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	415,976
1206.6449	Monte Carlo Bayesian Reinforcement Learning	Bayesian reinforcement learning (BRL) encodes prior knowledge of the world in a model and represents uncertainty in model parameters by maintaining a probability distribution over them. This paper presents Monte Carlo BRL (MC-BRL), a simple and general approach to BRL. MC-BRL samples a priori a finite set of hypotheses...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	16,984
1809.03985	On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation	This work investigates the alignment problem in state-of-the-art multi-head attention models based on the transformer architecture. We demonstrate that alignment extraction in transformer models can be improved by augmenting an additional alignment head to the multi-head source-to-target attention component. This is us...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	107,441
1804.06579	Semi-Supervised Co-Analysis of 3D Shape Styles from Projected Lines	We present a semi-supervised co-analysis method for learning 3D shape styles from projected feature lines, achieving style patch localization with only weak supervision. Given a collection of 3D shapes spanning multiple object categories and styles, we perform style co-analysis over projected feature lines of each 3D s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	95,335

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