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
2501.12815	Certified Guidance for Planning with Deep Generative Models	Deep generative models, such as generative adversarial networks and diffusion models, have recently emerged as powerful tools for planning tasks and behavior synthesis in autonomous systems. Various guidance strategies have been introduced to steer the generative process toward outputs that are more likely to satisfy t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	526,446
2103.14065	Quantitative Prediction on the Enantioselectivity of Multiple Chiral Iodoarene Scaffolds Based on Whole Geometry	The mechanistic underpinnings of asymmetric catalysis at atomic levels provide shortcuts for developing the potential value of chiral catalysts beyond the current state-of-the-art. In the enantioselective redox transformations, the present intuition-driven studies require a systematic approach to support their intuitiv...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,709
2502.03935	Thermal Model Calibration of a Squirrel-Cage Induction Machine	Accurate and efficient thermal simulations of induction machines are indispensable for detecting thermal hot spots and hence avoiding potential material failure in an early design stage. A goal is the better utilization of the machines with reduced safety margins due to a better knowledge of the critical conditions. In...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	530,916
2403.10949	SelfIE: Self-Interpretation of Large Language Model Embeddings	How do large language models (LLMs) obtain their answers? The ability to explain and control an LLM's reasoning process is key for reliability, transparency, and future model developments. We propose SelfIE (Self-Interpretation of Embeddings), a framework that enables LLMs to interpret their own embeddings in natural l...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	438,447
2406.07023	LiSD: An Efficient Multi-Task Learning Framework for LiDAR Segmentation and Detection	With the rapid proliferation of autonomous driving, there has been a heightened focus on the research of lidar-based 3D semantic segmentation and object detection methodologies, aiming to ensure the safety of traffic participants. In recent decades, learning-based approaches have emerged, demonstrating remarkable perfo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	462,863
1310.7198	Anti-rumor dynamics and emergence of the timing threshold on complex network	Anti-rumor dynamics is proposed on the basis of rumor dynamics and the characteristics of anti-rumor dynamics are explored by both mean-field equations and numerical simulations on complex network. The main metrics we study are the timing effect of combating rumor and the identification of influential nodes, which are ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	28,015
1906.02031	OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images	Deep learning models, such as the fully convolutional network (FCN), have been widely used in 3D biomedical segmentation and achieved state-of-the-art performance. Multiple modalities are often used for disease diagnosis and quantification. Two approaches are widely used in the literature to fuse multiple modalities in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	133,915
2212.03095	Interpretation of Neural Networks is Susceptible to Universal Adversarial Perturbations	Interpreting neural network classifiers using gradient-based saliency maps has been extensively studied in the deep learning literature. While the existing algorithms manage to achieve satisfactory performance in application to standard image recognition datasets, recent works demonstrate the vulnerability of widely-us...	false	false	false	false	true	false	true	false	false	false	false	true	true	false	false	false	false	false	334,996
2410.20957	Neuro-symbolic Learning Yielding Logical Constraints	Neuro-symbolic systems combine the abilities of neural perception and logical reasoning. However, end-to-end learning of neuro-symbolic systems is still an unsolved challenge. This paper proposes a natural framework that fuses neural network training, symbol grounding, and logical constraint synthesis into a coherent a...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	503,028
1707.07189	Using PCA and Factor Analysis for Dimensionality Reduction of Bio-informatics Data	Large volume of Genomics data is produced on daily basis due to the advancement in sequencing technology. This data is of no value if it is not properly analysed. Different kinds of analytics are required to extract useful information from this raw data. Classification, Prediction, Clustering and Pattern Extraction are...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	77,568
2407.05335	Understanding and Addressing Gender Bias in Expert Finding Task	The Expert Finding (EF) task is critical in community Question&Answer (CQ&A) platforms, significantly enhancing user engagement by improving answer quality and reducing response times. However, biases, especially gender biases, have been identified in these platforms. This study investigates gender bias in state-of-the...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	470,929
2406.18467	Algebraic Connectivity Control and Maintenance in Multi-Agent Networks under Attack	This paper studies the problem of increasing the connectivity of an ad-hoc peer-to-peer network subject to cyber-attacks targeting the agents in the network. The adopted strategy involves the design of local interaction rules for the agents to locally modify the graph topology by adding and removing links with neighbor...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	468,021
2004.01951	A Dependency Syntactic Knowledge Augmented Interactive Architecture for End-to-End Aspect-based Sentiment Analysis	The aspect-based sentiment analysis (ABSA) task remains to be a long-standing challenge, which aims to extract the aspect term and then identify its sentiment orientation.In previous approaches, the explicit syntactic structure of a sentence, which reflects the syntax properties of natural language and hence is intuiti...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	171,066
1702.02295	Guided Optical Flow Learning	We study the unsupervised learning of CNNs for optical flow estimation using proxy ground truth data. Supervised CNNs, due to their immense learning capacity, have shown superior performance on a range of computer vision problems including optical flow prediction. They however require the ground truth flow which is usu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	67,958
1906.06911	Combining Safe Interval Path Planning and Constrained Path Following Control: Preliminary Results	We study the navigation problem for a robot moving amidst static and dynamic obstacles and rely on a hierarchical approach to solve it. First, the reference trajectory is planned by the safe interval path planning algorithm that is capable of handling any-angle translations and rotations. Second, the path following pro...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	135,460
1702.01182	Uncertainty-Aware Reinforcement Learning for Collision Avoidance	Reinforcement learning can enable complex, adaptive behavior to be learned automatically for autonomous robotic platforms. However, practical deployment of reinforcement learning methods must contend with the fact that the training process itself can be unsafe for the robot. In this paper, we consider the specific case...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	67,762
2501.10441	A Review of Detection, Evolution, and Data Reconstruction Strategies for False Data Injection Attacks in Power Cyber-Physical Systems	The integration of information and physical systems in modern power grids has heightened vulnerabilities to False Data Injection Attacks (FDIAs), threatening the secure operation of power cyber-physical systems (CPS). This paper reviews FDIA detection, evolution, and data reconstruction strategies, highlighting cross-d...	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	525,522
2403.10245	CoLeCLIP: Open-Domain Continual Learning via Joint Task Prompt and Vocabulary Learning	This paper explores the problem of continual learning (CL) of vision-language models (VLMs) in open domains, where the models need to perform continual updating and inference on a streaming of datasets from diverse seen and unseen domains with novel classes. Such a capability is crucial for various applications in open...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	438,115
2404.18976	Foundations of Multisensory Artificial Intelligence	Building multisensory AI systems that learn from multiple sensory inputs such as text, speech, video, real-world sensors, wearable devices, and medical data holds great promise for impact in many scientific areas with practical benefits, such as in supporting human health and well-being, enabling multimedia content pro...	false	false	false	false	true	false	true	false	true	false	false	true	false	false	false	false	false	true	450,463
2403.19414	BP4ER: Bootstrap Prompting for Explicit Reasoning in Medical Dialogue Generation	Medical dialogue generation (MDG) has gained increasing attention due to its substantial practical value. Previous works typically employ a sequence-to-sequence framework to generate medical responses by modeling dialogue context as sequential text with annotated medical entities. While these methods have been successf...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	442,333
2210.09598	Planning for Sample Efficient Imitation Learning	Imitation learning is a class of promising policy learning algorithms that is free from many practical issues with reinforcement learning, such as the reward design issue and the exploration hardness. However, the current imitation algorithm struggles to achieve both high performance and high in-environment sample effi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	324,597
2102.07492	DOBF: A Deobfuscation Pre-Training Objective for Programming Languages	Recent advances in self-supervised learning have dramatically improved the state of the art on a wide variety of tasks. However, research in language model pre-training has mostly focused on natural languages, and it is unclear whether models like BERT and its variants provide the best pre-training when applied to othe...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	220,121
2107.12320	End-to-End Deep Learning of Long-Haul Coherent Optical Fiber Communications via Regular Perturbation Model	We present a novel end-to-end autoencoder-based learning for coherent optical communications using a "parallelizable" perturbative channel model. We jointly optimized constellation shaping and nonlinear pre-emphasis achieving mutual information gain of 0.18 bits/sym./pol. simulating 64 GBd dual-polarization single-chan...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	247,860
2310.17255	Generalizing to Unseen Domains in Diabetic Retinopathy Classification	Diabetic retinopathy (DR) is caused by long-standing diabetes and is among the fifth leading cause for visual impairments. The process of early diagnosis and treatments could be helpful in curing the disease, however, the detection procedure is rather challenging and mostly tedious. Therefore, automated diabetic retino...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	403,065
2112.00527	Subtask-dominated Transfer Learning for Long-tail Person Search	Person search unifies person detection and person re-identification (Re-ID) to locate query persons from the panoramic gallery images. One major challenge comes from the imbalanced long-tail person identity distributions, which prevents the one-step person search model from learning discriminative person features for t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	269,161
1211.2116	Localisation of Numerical Date Field in an Indian Handwritten Document	This paper describes a method to localise all those areas which may constitute the date field in an Indian handwritten document. Spatial patterns of the date field are studied from various handwritten documents and an algorithm is developed through statistical analysis to identify those sets of connected components whi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	19,650
2008.12949	VR-Caps: A Virtual Environment for Capsule Endoscopy	Current capsule endoscopes and next-generation robotic capsules for diagnosis and treatment of gastrointestinal diseases are complex cyber-physical platforms that must orchestrate complex software and hardware functions. The desired tasks for these systems include visual localization, depth estimation, 3D mapping, dise...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	193,717
2405.20047	Schubert Subspace Codes	In this paper, we initiate the study of constant dimension subspace codes restricted to Schubert varieties, which we call Schubert subspace codes. These codes have a very natural geometric description, as objects that we call intersecting sets with respect to a fixed subspace. We provide a geometric construction of max...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	459,173
2412.16766	Apples to Apples: Establishing Comparability in Knowledge Generation Tasks Involving Users	Knowledge graph construction (KGC) from (semi-)structured data is challenging, and facilitating user involvement is an issue frequently brought up within this community. We cannot deny the progress we have made with respect to (declarative) knowledge generation languages and tools to help build such mappings. However, ...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	519,672
1905.11133	A collaborative filtering model with heterogeneous neural networks for recommender systems	In recent years, deep neural network is introduced in recommender systems to solve the collaborative filtering problem, which has achieved immense success on computer vision, speech recognition and natural language processing. On one hand, deep neural network can be used to model the auxiliary information in recommende...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	132,339
2010.05620	$\ell_0$-based Sparse Canonical Correlation Analysis	Canonical Correlation Analysis (CCA) models are powerful for studying the associations between two sets of variables. The canonically correlated representations, termed \textit{canonical variates} are widely used in unsupervised learning to analyze unlabeled multi-modal registered datasets. Despite their success, CCA m...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	200,203
2010.03158	Multilingual Knowledge Graph Completion via Ensemble Knowledge Transfer	Predicting missing facts in a knowledge graph (KG) is a crucial task in knowledge base construction and reasoning, and it has been the subject of much research in recent works using KG embeddings. While existing KG embedding approaches mainly learn and predict facts within a single KG, a more plausible solution would b...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	199,302
1804.06011	God Save the Queen	Queen Daniela of Sardinia is asleep at the center of a round room at the top of the tower in her castle. She is accompanied by her faithful servant, Eva. Suddenly, they are awakened by cries of "Fire". The room is pitch black and they are disoriented. There is exactly one exit from the room somewhere along its boundary...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	95,204
2204.02397	SALISA: Saliency-based Input Sampling for Efficient Video Object Detection	High-resolution images are widely adopted for high-performance object detection in videos. However, processing high-resolution inputs comes with high computation costs, and naive down-sampling of the input to reduce the computation costs quickly degrades the detection performance. In this paper, we propose SALISA, a no...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	289,930
1707.08207	A Fully Quaternion-Valued Capon Beamformer Based on Crossed-Dipole Arrays	Quaternion models have been developed for both direction of arrival estimation and beamforming based on crossed-dipole arrays in the past. However, for almost all the models, especially for adaptive beamforming, the desired signal is still complex-valued and one example is the quaternion-Capon beamformer. However, sinc...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	77,774
2405.15772	Scenario Engineering for Autonomous Transportation: A New Stage in Open-Pit Mines	In recent years, open-pit mining has seen significant advancement, the cooperative operation of various specialized machinery substantially enhancing the efficiency of mineral extraction. However, the harsh environment and complex conditions in open-pit mines present substantial challenges for the implementation of aut...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	457,088
2405.04828	ChuXin: 1.6B Technical Report	In this report, we present ChuXin, an entirely open-source language model with a size of 1.6 billion parameters. Unlike the majority of works that only open-sourced the model weights and architecture, we have made everything needed to train a model available, including the training data, the training process, and the e...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	452,697
2304.09355	To Compress or Not to Compress- Self-Supervised Learning and Information Theory: A Review	Deep neural networks excel in supervised learning tasks but are constrained by the need for extensive labeled data. Self-supervised learning emerges as a promising alternative, allowing models to learn without explicit labels. Information theory, and notably the information bottleneck principle, has been pivotal in sha...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	359,022
1806.08734	On the Spectral Bias of Neural Networks	Neural networks are known to be a class of highly expressive functions able to fit even random input-output mappings with $100\%$ accuracy. In this work, we present properties of neural networks that complement this aspect of expressivity. By using tools from Fourier analysis, we show that deep ReLU networks are biased...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	101,209
1906.02611	Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation	Deploying machine learning systems in the real world requires both high accuracy on clean data and robustness to naturally occurring corruptions. While architectural advances have led to improved accuracy, building robust models remains challenging. Prior work has argued that there is an inherent trade-off between robu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	134,123
1810.03423	Probabilistic Argumentation and Information Algebras of Probability Potentials on Families of Compatible Frames	Probabilistic argumentation is an alternative to causal modeling with Bayesian networks. Probabilistic argumentation structures (PAS) are defined on families of compatible frames (f.c.f). This is a generalization of the usual multivariate models based on families of variables. The crucial relation of conditional indepe...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	109,806
2009.04016	Brown University at TREC Deep Learning 2019	This paper describes Brown University's submission to the TREC 2019 Deep Learning track. We followed a 2-phase method for producing a ranking of passages for a given input query: In the the first phase, the user's query is expanded by appending 3 queries generated by a transformer model which was trained to rephrase an...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	194,946
2309.12032	Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets	Structure learning is the crux of causal inference. Notably, causal discovery (CD) algorithms are brittle when data is scarce, possibly inferring imprecise causal relations that contradict expert knowledge -- especially when considering latent confounders. To aggravate the issue, most CD methods do not provide uncertai...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	393,640
2406.14514	Solving a Stackelberg Game on Transportation Networks in a Dynamic Crime Scenario: A Mixed Approach on Multi-Layer Networks	Interdicting a criminal with limited police resources is a challenging task as the criminal changes location over time. The size of the large transportation network further adds to the difficulty of this scenario. To tackle this issue, we consider the concept of a layered graph. At each time stamp, we create a copy of ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	466,347
1904.00170	Adaptive Adjustment with Semantic Feature Space for Zero-Shot Recognition	In most recent years, zero-shot recognition (ZSR) has gained increasing attention in machine learning and image processing fields. It aims at recognizing unseen class instances with knowledge transferred from seen classes. This is typically achieved by exploiting a pre-defined semantic feature space (FS), i.e., semanti...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	125,811
2009.08942	Generating similes effortlessly like a Pro: A Style Transfer Approach for Simile Generation	Literary tropes, from poetry to stories, are at the crux of human imagination and communication. Figurative language such as a simile go beyond plain expressions to give readers new insights and inspirations. In this paper, we tackle the problem of simile generation. Generating a simile requires proper understanding fo...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	196,398
1701.01917	See the Near Future: A Short-Term Predictive Methodology to Traffic Load in ITS	The Intelligent Transportation System (ITS) targets to a coordinated traffic system by applying the advanced wireless communication technologies for road traffic scheduling. Towards an accurate road traffic control, the short-term traffic forecasting to predict the road traffic at the particular site in a short period ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	66,473
2411.13619	Non-Linear Outlier Synthesis for Out-of-Distribution Detection	The reliability of supervised classifiers is severely hampered by their limitations in dealing with unexpected inputs, leading to great interest in out-of-distribution (OOD) detection. Recently, OOD detectors trained on synthetic outliers, especially those generated by large diffusion models, have shown promising resul...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	509,865
2307.10315	Absolutist AI	This paper argues that training AI systems with absolute constraints -- which forbid certain acts irrespective of the amount of value they might produce -- may make considerable progress on many AI safety problems in principle. First, it provides a guardrail for avoiding the very worst outcomes of misalignment. Second,...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	380,515
2404.15552	Cross-Temporal Spectrogram Autoencoder (CTSAE): Unsupervised Dimensionality Reduction for Clustering Gravitational Wave Glitches	The advancement of The Laser Interferometer Gravitational-Wave Observatory (LIGO) has significantly enhanced the feasibility and reliability of gravitational wave detection. However, LIGO's high sensitivity makes it susceptible to transient noises known as glitches, which necessitate effective differentiation from real...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	449,136
2102.00177	SteemOps: Extracting and Analyzing Key Operations in Steemit Blockchain-based Social Media Platform	Advancements in distributed ledger technologies are driving the rise of blockchain-based social media platforms such as Steemit, where users interact with each other in similar ways as conventional social networks. These platforms are autonomously managed by users using decentralized consensus protocols in a cryptocurr...	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	true	false	217,687
2206.10543	Faster Diffusion Cardiac MRI with Deep Learning-based breath hold reduction	Diffusion Tensor Cardiac Magnetic Resonance (DT-CMR) enables us to probe the microstructural arrangement of cardiomyocytes within the myocardium in vivo and non-invasively, which no other imaging modality allows. This innovative technology could revolutionise the ability to perform cardiac clinical diagnosis, risk stra...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	303,942
cs/0404030	XML framework for concept description and knowledge representation	An XML framework for concept description is given, based upon the fact that the tree structure of XML implies the logical structure of concepts as defined by attributional calculus. Especially, the attribute-value representation is implementable in the XML framework. Since the attribute-value representation is an impor...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	538,154
2105.04659	Different Environment Feedback in Fast-slow Eco-evolutionary Dynamics	The fast-slow dynamics of an eco-evolutionary system are studied, where we consider the feedback actions of environmental resources that are classified into those that are self-renewing and those externally supplied. We show although these two types of resources are drastically different, the resulting closed-loop syst...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	234,573
2309.07478	Direct Text to Speech Translation System using Acoustic Units	This paper proposes a direct text to speech translation system using discrete acoustic units. This framework employs text in different source languages as input to generate speech in the target language without the need for text transcriptions in this language. Motivated by the success of acoustic units in previous wor...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	391,801
2308.03944	GraPhSyM: Graph Physical Synthesis Model	In this work, we introduce GraPhSyM, a Graph Attention Network (GATv2) model for fast and accurate estimation of post-physical synthesis circuit delay and area metrics from pre-physical synthesis circuit netlists. Once trained, GraPhSyM provides accurate visibility of final design metrics to early EDA stages, such as l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	384,222
2108.09646	A Systematic Review of Automated Query Reformulations in Source Code Search	Fixing software bugs and adding new features are two of the major maintenance tasks. Software bugs and features are reported as change requests. Developers consult these requests and often choose a few keywords from them as an ad hoc query. Then they execute the query with a search engine to find the exact locations wi...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	true	false	true	251,672
2211.15425	FAF: A novel multimodal emotion recognition approach integrating face, body and text	Multimodal emotion analysis performed better in emotion recognition depending on more comprehensive emotional clues and multimodal emotion dataset. In this paper, we developed a large multimodal emotion dataset, named "HED" dataset, to facilitate the emotion recognition task, and accordingly propose a multimodal emotio...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	333,258
2502.12177	Recent Advances of NeuroDiffEq -- An Open-Source Library for Physics-Informed Neural Networks	Solving differential equations is a critical challenge across a host of domains. While many software packages efficiently solve these equations using classical numerical approaches, there has been less effort in developing a library for researchers interested in solving such systems using neural networks. With PyTorch ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	534,732
1410.0993	Document Clustering Based On Max-Correntropy Non-Negative Matrix Factorization	Nonnegative matrix factorization (NMF) has been successfully applied to many areas for classification and clustering. Commonly-used NMF algorithms mainly target on minimizing the $l_2$ distance or Kullback-Leibler (KL) divergence, which may not be suitable for nonlinear case. In this paper, we propose a new decompositi...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	36,516
cs/0607042	Towards a classical proof of exponential lower bound for 2-probe smooth codes	Let C: {0,1}^n -> {0,1}^m be a code encoding an n-bit string into an m-bit string. Such a code is called a (q, c, e) smooth code if there exists a decoding algorithm which while decoding any bit of the input, makes at most q probes on the code word and the probability that it looks at any location is at most c/m. The e...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	539,573
2409.18645	The Craft of Selective Prediction: Towards Reliable Case Outcome Classification -- An Empirical Study on European Court of Human Rights Cases	In high-stakes decision-making tasks within legal NLP, such as Case Outcome Classification (COC), quantifying a model's predictive confidence is crucial. Confidence estimation enables humans to make more informed decisions, particularly when the model's certainty is low, or where the consequences of a mistake are signi...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	492,344
2304.12537	GARCIA: Powering Representations of Long-tail Query with Multi-granularity Contrastive Learning	Recently, the growth of service platforms brings great convenience to both users and merchants, where the service search engine plays a vital role in improving the user experience by quickly obtaining desirable results via textual queries. Unfortunately, users' uncontrollable search customs usually bring vast amounts o...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	360,255
1904.07642	SparseMask: Differentiable Connectivity Learning for Dense Image Prediction	In this paper, we aim at automatically searching an efficient network architecture for dense image prediction. Particularly, we follow the encoder-decoder style and focus on designing a connectivity structure for the decoder. To achieve that, we design a densely connected network with learnable connections, named Fully...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	127,852
2305.16811	Improved Visual Story Generation with Adaptive Context Modeling	Diffusion models developed on top of powerful text-to-image generation models like Stable Diffusion achieve remarkable success in visual story generation. However, the best-performing approach considers historically generated results as flattened memory cells, ignoring the fact that not all preceding images contribute ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	368,264
2002.10394	DeepPlume: Very High Resolution Real-Time Air Quality Mapping	This paper presents an engine able to predict jointly the real-time concentration of the main pollutants harming people's health: nitrogen dioxyde (NO2), ozone (O3) and particulate matter (PM2.5 and PM10, which are respectively the particles whose size are below 2.5 um and 10 um). The engine covers a large part of th...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	165,392
cs/0701182	Supplement to: Code Spectrum and Reliability Function: Binary Symmetric Channel	A much simpler proof of Theorem 1 from M.Burnashev "Code spectrum and reliability function: Binary symmetric channel" is presented.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,118
2308.13970	FAM: fast adaptive federated meta-learning	In this work, we propose a fast adaptive federated meta-learning (FAM) framework for collaboratively learning a single global model, which can then be personalized locally on individual clients. Federated learning enables multiple clients to collaborate to train a model without sharing data. Clients with insufficient d...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	388,126
2408.07003	Generative AI for automatic topic labelling	Topic Modeling has become a prominent tool for the study of scientific fields, as they allow for a large scale interpretation of research trends. Nevertheless, the output of these models is structured as a list of keywords which requires a manual interpretation for the labelling. This paper proposes to assess the relia...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	480,420
2005.10547	Perceptual Quality Assessment of Omnidirectional Images as Moving Camera Videos	Omnidirectional images (also referred to as static 360{\deg} panoramas) impose viewing conditions much different from those of regular 2D images. How do humans perceive image distortions in immersive virtual reality (VR) environments is an important problem which receives less attention. We argue that, apart from the d...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	178,215
2304.06876	Sampling-based Reactive Synthesis for Nondeterministic Hybrid Systems	This paper introduces a sampling-based strategy synthesis algorithm for nondeterministic hybrid systems with complex continuous dynamics under temporal and reachability constraints. We model the evolution of the hybrid system as a two-player game, where the nondeterminism is an adversarial player whose objective is to ...	false	false	false	false	true	false	false	true	false	false	true	false	false	false	false	false	false	false	358,140
1508.02884	Towards Real-time Customer Experience Prediction for Telecommunication Operators	Telecommunications operators (telcos) traditional sources of income, voice and SMS, are shrinking due to customers using over-the-top (OTT) applications such as WhatsApp or Viber. In this challenging environment it is critical for telcos to maintain or grow their market share, by providing users with as good an experie...	false	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	45,952
1811.11960	Prediction Factory: automated development and collaborative evaluation of predictive models	In this paper, we present a data science automation system called Prediction Factory. The system uses several key automation algorithms to enable data scientists to rapidly develop predictive models and share them with domain experts. To assess the system's impact, we implemented 3 different interfaces for creating pre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	114,892
1912.02671	Audio-Visual Target Speaker Enhancement on Multi-Talker Environment using Event-Driven Cameras	We propose a method to address audio-visual target speaker enhancement in multi-talker environments using event-driven cameras. State of the art audio-visual speech separation methods shows that crucial information is the movement of the facial landmarks related to speech production. However, all approaches proposed so...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,408
2406.02507	Guiding a Diffusion Model with a Bad Version of Itself	The primary axes of interest in image-generating diffusion models are image quality, the amount of variation in the results, and how well the results align with a given condition, e.g., a class label or a text prompt. The popular classifier-free guidance approach uses an unconditional model to guide a conditional model...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	true	false	false	460,797
2104.13289	Model-centric Data Manifold: the Data Through the Eyes of the Model	We discover that deep ReLU neural network classifiers can see a low-dimensional Riemannian manifold structure on data. Such structure comes via the local data matrix, a variation of the Fisher information matrix, where the role of the model parameters is taken by the data variables. We obtain a foliation of the data do...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	232,460
2409.01685	Optimizing Mortality Prediction for ICU Heart Failure Patients: Leveraging XGBoost and Advanced Machine Learning with the MIMIC-III Database	Heart failure affects millions of people worldwide, significantly reducing quality of life and leading to high mortality rates. Despite extensive research, the relationship between heart failure and mortality rates among ICU patients is not fully understood, indicating the need for more accurate prediction models. This...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	485,438
2502.05448	Distributionally Robust Model Predictive Control with Mixture of Gaussian Processes	Despite the success of Gaussian process based Model Predictive Control (MPC) in robotic control, its applicability scope is greatly hindered by multimodal disturbances that are prevalent in real-world settings. Here we propose a novel Mixture of Gaussian Processes based Distributionally Robust MPC (MoGP-DR-MPC) framewo...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	531,613
2312.12459	Prediction of Crash Injury Severity in Florida's Interstate-95	Drivers can sustain serious injuries in traffic accidents. In this study, traffic crashes on Florida's Interstate-95 from 2016 to 2021 were gathered, and several classification methods were used to estimate the severity of driver injuries. In the feature selection method, logistic regression was applied. To compare mod...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	416,962
2401.05060	MuTox: Universal MUltilingual Audio-based TOXicity Dataset and Zero-shot Detector	Research in toxicity detection in natural language processing for the speech modality (audio-based) is quite limited, particularly for languages other than English. To address these limitations and lay the groundwork for truly multilingual audio-based toxicity detection, we introduce MuTox, the first highly multilingua...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	420,635
2207.04457	TCR: A Transformer Based Deep Network for Predicting Cancer Drugs Response	Predicting clinical outcomes to anti-cancer drugs on a personalized basis is challenging in cancer treatment due to the heterogeneity of tumors. Traditional computational efforts have been made to model the effect of drug response on individual samples depicted by their molecular profile, yet overfitting occurs because...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	307,205
1602.03650	Higher order assortativity in complex networks	Assortativity was first introduced by Newman and has been extensively studied and applied to many real world networked systems since then. Assortativity is a graph metrics and describes the tendency of high degree nodes to be directly connected to high degree nodes and low degree nodes to low degree nodes. It can be in...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	52,034
1711.07752	Repulsion Loss: Detecting Pedestrians in a Crowd	Detecting individual pedestrians in a crowd remains a challenging problem since the pedestrians often gather together and occlude each other in real-world scenarios. In this paper, we first explore how a state-of-the-art pedestrian detector is harmed by crowd occlusion via experimentation, providing insights into the c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	85,061
2108.13051	Demystifying Drug Repurposing Domain Comprehension with Knowledge Graph Embedding	Drug repurposing is more relevant than ever due to drug development's rising costs and the need to respond to emerging diseases quickly. Knowledge graph embedding enables drug repurposing using heterogeneous data sources combined with state-of-the-art machine learning models to predict new drug-disease links in the kno...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	252,697
1906.12216	On the robust existence of piecewise quadratic Lyapunov functions for hybrid models of gene regulatory networks	In this work we addressed the problem of stability analysis for an uncertain piecewise affine model of a genetic regulatory network. In particular we considered polytopic parameter uncertainties on the proteins production rate functions, giving conditions for the existence of a piecewise quadratic Lyapunov function for...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	136,876
2404.01308	Learning to Solve Job Shop Scheduling under Uncertainty	Job-Shop Scheduling Problem (JSSP) is a combinatorial optimization problem where tasks need to be scheduled on machines in order to minimize criteria such as makespan or delay. To address more realistic scenarios, we associate a probability distribution with the duration of each task. Our objective is to generate a rob...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	443,366
1503.04238	A Knapsack-Like Code Using Recurrence Sequence Representations	We had recently shown that every positive integer can be represented uniquely using a recurrence sequence, when certain restrictions on the digit strings are satisfied. We present the details of how such representations can be used to build a knapsack-like public key cryptosystem. We also present new disguising methods...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	41,132
2205.02607	RF Interference in Lens-Based Massive MIMO Systems -- An Application Note	We analyze the uplink radio frequency (RF) interference from a multiplicity of single-antenna user equipments transmitting to a cellular base station (BS) within the same time-frequency resource. The BS is assumed to operate with a lens antenna array, which induces additional focusing gain for the incoming signals. Con...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	294,994
1912.00120	One-Shot Pruning of Recurrent Neural Networks by Jacobian Spectrum Evaluation	Recent advances in the sparse neural network literature have made it possible to prune many large feed forward and convolutional networks with only a small quantity of data. Yet, these same techniques often falter when applied to the problem of recovering sparse recurrent networks. These failures are quantitative: when...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,673
1902.00220	A Classification Supervised Auto-Encoder Based on Predefined Evenly-Distributed Class Centroids	Classic variational autoencoders are used to learn complex data distributions, that are built on standard function approximators. Especially, VAE has shown promise on a lot of complex task. In this paper, a new autoencoder model - classification supervised autoencoder (CSAE) based on predefined evenly-distributed class...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	120,359
2206.02280	Annotation Error Detection: Analyzing the Past and Present for a More Coherent Future	Annotated data is an essential ingredient in natural language processing for training and evaluating machine learning models. It is therefore very desirable for the annotations to be of high quality. Recent work, however, has shown that several popular datasets contain a surprising amount of annotation errors or incons...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	300,826
2102.11163	Generator Surgery for Compressed Sensing	Image recovery from compressive measurements requires a signal prior for the images being reconstructed. Recent work has explored the use of deep generative models with low latent dimension as signal priors for such problems. However, their recovery performance is limited by high representation error. We introduce a me...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	221,344
2407.03963	LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs	This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and strong Japanese LLMs, and as of this writing, more than 1,500 participants from academia and industry are working together for this purpose. This...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	470,370
1411.0630	Active Inference for Binary Symmetric Hidden Markov Models	We consider active maximum a posteriori (MAP) inference problem for Hidden Markov Models (HMM), where, given an initial MAP estimate of the hidden sequence, we select to label certain states in the sequence to improve the estimation accuracy of the remaining states. We develop an analytical approach to this problem for...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	37,269
2403.09681	ViT-MUL: A Baseline Study on Recent Machine Unlearning Methods Applied to Vision Transformers	Machine unlearning (MUL) is an arising field in machine learning that seeks to erase the learned information of specific training data points from a trained model. Despite the recent active research in MUL within computer vision, the majority of work has focused on ResNet-based models. Given that Vision Transformers (V...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	437,867
cs/0008012	Applying System Combination to Base Noun Phrase Identification	We use seven machine learning algorithms for one task: identifying base noun phrases. The results have been processed by different system combination methods and all of these outperformed the best individual result. We have applied the seven learners with the best combinator, a majority vote of the top five systems, to...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,181
1706.00906	Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach	Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	74,712
1811.12320	Stability of Disturbance Based Unified Control	Introduction of renewable generation leads to significant reduction of inertia in power system, which deteriorates the quality of frequency control. This paper suggests a new control scheme utilizing controllable load to deal with low inertia systems. Optimization problem is formulated to minimize the systems deviation...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	114,988
2409.01073	SCOPE: Sign Language Contextual Processing with Embedding from LLMs	Sign languages, used by around 70 million Deaf individuals globally, are visual languages that convey visual and contextual information. Current methods in vision-based sign language recognition (SLR) and translation (SLT) struggle with dialogue scenes due to limited dataset diversity and the neglect of contextually re...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	485,197
1205.0030	A Market for Unbiased Private Data: Paying Individuals According to their Privacy Attitudes	Since there is, in principle, no reason why third parties should not pay individuals for the use of their data, we introduce a realistic market that would allow these payments to be made while taking into account the privacy attitude of the participants. And since it is usually important to use unbiased samples to obta...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	15,740

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