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
2310.18440	Modeling Legal Reasoning: LM Annotation at the Edge of Human Agreement	Generative language models (LMs) are increasingly used for document class-prediction tasks and promise enormous improvements in cost and efficiency. Existing research often examines simple classification tasks, but the capability of LMs to classify on complex or specialized tasks is less well understood. We consider a ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	403,543
2410.03061	DocKD: Knowledge Distillation from LLMs for Open-World Document Understanding Models	Visual document understanding (VDU) is a challenging task that involves understanding documents across various modalities (text and image) and layouts (forms, tables, etc.). This study aims to enhance generalizability of small VDU models by distilling knowledge from LLMs. We identify that directly prompting LLMs often ...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	494,594
2202.10582	Debiasing Backdoor Attack: A Benign Application of Backdoor Attack in Eliminating Data Bias	Backdoor attack is a new AI security risk that has emerged in recent years. Drawing on the previous research of adversarial attack, we argue that the backdoor attack has the potential to tap into the model learning process and improve model performance. Based on Clean Accuracy Drop (CAD) in backdoor attack, we found th...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	281,577
0804.0317	Parts-of-Speech Tagger Errors Do Not Necessarily Degrade Accuracy in Extracting Information from Biomedical Text	A recent study reported development of Muscorian, a generic text processing tool for extracting protein-protein interactions from text that achieved comparable performance to biomedical-specific text processing tools. This result was unexpected since potential errors from a series of text analysis processes is likely t...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	1,516
1505.03116	Distributed Cohesive Control for Robot Swarms: Maintaining Good Connectivity in the Presence of Exterior Forces	We present a number of powerful local mechanisms for maintaining a dynamic swarm of robots with limited capabilities and information, in the presence of external forces and permanent node failures. We propose a set of local continuous algorithms that together produce a generalization of a Euclidean Steiner tree. At any...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	43,047
2109.11672	A Multi-Agent Deep Reinforcement Learning Coordination Framework for Connected and Automated Vehicles at Merging Roadways	The steady increase in the number of vehicles operating on the highways continues to exacerbate congestion, accidents, energy consumption, and greenhouse gas emissions. Emerging mobility systems, e.g., connected and automated vehicles (CAVs), have the potential to directly address these issues and improve transportatio...	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	257,016
1411.3969	Formal Semantic Annotations for Models Interoperability in a PLM environment	Nowadays, the need for system interoperability in or across enterprises has become more and more ubiquitous. Lots of research works have been carried out in the information exchange, transformation, discovery and reuse. One of the main challenges in these researches is to overcome the semantic heterogeneity between ent...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	37,556
2410.23644	Online Consistency of the Nearest Neighbor Rule	In the realizable online setting, a learner is tasked with making predictions for a stream of instances, where the correct answer is revealed after each prediction. A learning rule is online consistent if its mistake rate eventually vanishes. The nearest neighbor rule (Fix and Hodges, 1951) is a fundamental prediction ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,122
2103.12002	On the Robustness of Monte Carlo Dropout Trained with Noisy Labels	The memorization effect of deep learning hinders its performance to effectively generalize on test set when learning with noisy labels. Prior study has discovered that epistemic uncertainty techniques are robust when trained with noisy labels compared with neural networks without uncertainty estimation. They obtain pro...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	226,028
2408.08834	Gaussian Processes with Noisy Regression Inputs for Dynamical Systems	This paper is centered around the approximation of dynamical systems by means of Gaussian processes. To this end, trajectories of such systems must be collected to be used as training data. The measurements of these trajectories are typically noisy, which implies that both the regression inputs and outputs are corrupte...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	481,172
2305.14754	SUVR: A Search-based Approach to Unsupervised Visual Representation Learning	Unsupervised learning has grown in popularity because of the difficulty of collecting annotated data and the development of modern frameworks that allow us to learn from unlabeled data. Existing studies, however, either disregard variations at different levels of similarity or only consider negative samples from one ba...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	367,234
2304.10722	Reinforcement Learning Approaches for Traffic Signal Control under Missing Data	The emergence of reinforcement learning (RL) methods in traffic signal control tasks has achieved better performance than conventional rule-based approaches. Most RL approaches require the observation of the environment for the agent to decide which action is optimal for a long-term reward. However, in real-world urban...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	359,529
2412.04521	FedDW: Distilling Weights through Consistency Optimization in Heterogeneous Federated Learning	Federated Learning (FL) is an innovative distributed machine learning paradigm that enables neural network training across devices without centralizing data. While this addresses issues of information sharing and data privacy, challenges arise from data heterogeneity across clients and increasing network scale, leading...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	514,454
2407.17374	Co-designing an AI Impact Assessment Report Template with AI Practitioners and AI Compliance Experts	In the evolving landscape of AI regulation, it is crucial for companies to conduct impact assessments and document their compliance through comprehensive reports. However, current reports lack grounding in regulations and often focus on specific aspects like privacy in relation to AI systems, without addressing the rea...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	475,940
2407.05687	Learning Lane Graphs from Aerial Imagery Using Transformers	The robust and safe operation of automated vehicles underscores the critical need for detailed and accurate topological maps. At the heart of this requirement is the construction of lane graphs, which provide essential information on lane connectivity, vital for navigating complex urban environments autonomously. While...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	471,089
2103.08157	Pretraining Neural Architecture Search Controllers with Locality-based Self-Supervised Learning	Neural architecture search (NAS) has fostered various fields of machine learning. Despite its prominent dedications, many have criticized the intrinsic limitations of high computational cost. We aim to ameliorate this by proposing a pretraining scheme that can be generally applied to controller-based NAS. Our method, l...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	224,815
2109.13073	Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information	Context: Stack Overflow is very helpful for software developers who are seeking answers to programming problems. Previous studies have shown that a growing number of questions are of low quality and thus obtain less attention from potential answerers. Gao et al. proposed an LSTM-based model (i.e., BiLSTM-CC) to automat...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	true	257,514
2006.13282	Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads	Filtering data based on predicates is one of the most fundamental operations for any modern data warehouse. Techniques to accelerate the execution of filter expressions include clustered indexes, specialized sort orders (e.g., Z-order), multi-dimensional indexes, and, for high selectivity queries, secondary indexes. Ho...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	183,849
2305.07759	TinyStories: How Small Can Language Models Be and Still Speak Coherent English?	Language models (LMs) are powerful tools for natural language processing, but they often struggle to produce coherent and fluent text when they are small. Models with around 125M parameters such as GPT-Neo (small) or GPT-2 (small) can rarely generate coherent and consistent English text beyond a few words even after ex...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	364,012
2409.09444	KAN-HyperpointNet for Point Cloud Sequence-Based 3D Human Action Recognition	Point cloud sequence-based 3D action recognition has achieved impressive performance and efficiency. However, existing point cloud sequence modeling methods cannot adequately balance the precision of limb micro-movements with the integrity of posture macro-structure, leading to the loss of crucial information cues in a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	488,320
2208.14039	CAIR: Fast and Lightweight Multi-Scale Color Attention Network for Instagram Filter Removal	Image restoration is an important and challenging task in computer vision. Reverting a filtered image to its original image is helpful in various computer vision tasks. We employ a nonlinear activation function free network (NAFNet) for a fast and lightweight model and add a color attention module that extracts useful ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	315,205
2104.15023	Post-training deep neural network pruning via layer-wise calibration	We present a post-training weight pruning method for deep neural networks that achieves accuracy levels tolerable for the production setting and that is sufficiently fast to be run on commodity hardware such as desktop CPUs or edge devices. We propose a data-free extension of the approach for computer vision models bas...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	233,029
1607.05408	Discriminating between similar languages in Twitter using label propagation	Identifying the language of social media messages is an important first step in linguistic processing. Existing models for Twitter focus on content analysis, which is successful for dissimilar language pairs. We propose a label propagation approach that takes the social graph of tweet authors into account as well as co...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	58,749
2202.03360	Discrete-Event Controller Synthesis for Autonomous Systems with Deep-Learning Perception Components	We present DeepDECS, a new method for the synthesis of correct-by-construction discrete-event controllers for autonomous systems that use deep neural network (DNN) classifiers for the perception step of their decision-making processes. Despite major advances in deep learning in recent years, providing safety guarantees...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,177
1909.03471	Learning Geometrically Consistent Mesh Corrections	Building good 3D maps is a challenging and expensive task, which requires high-quality sensors and careful, time-consuming scanning. We seek to reduce the cost of building good reconstructions by correcting views of existing low-quality ones in a post-hoc fashion using learnt priors over surfaces and appearance. We tra...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	144,494
cs/0410070	Using image partitions in 4th Dimension	I have plotted an image by using mathematical functions in the Database "4th Dimension". I'm going to show an alternative method to: detect which sector has been clicked; highlight it and combine it with other sectors already highlighted; store the graph information in an efficient way; load and splat image layers to r...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	538,381
1211.2245	Composite Strategy for Multicriteria Ranking/Sorting (methodological issues, examples)	The paper addresses the modular design of composite solving strategies for multicriteria ranking (sorting). Here a 'scale of creativity' that is close to creative levels proposed by Altshuller is used as the reference viewpoint: (i) a basic object, (ii) a selected object, (iii) a modified object, and (iv) a designed ob...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	19,662
2110.13197	Nested Graph Neural Networks	Graph neural network (GNN)'s success in graph classification is closely related to the Weisfeiler-Lehman (1-WL) algorithm. By iteratively aggregating neighboring node features to a center node, both 1-WL and GNN obtain a node representation that encodes a rooted subtree around the center node. These rooted subtree repr...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	263,091
2007.13018	Federated Self-Supervised Learning of Multi-Sensor Representations for Embedded Intelligence	Smartphones, wearables, and Internet of Things (IoT) devices produce a wealth of data that cannot be accumulated in a centralized repository for learning supervised models due to privacy, bandwidth limitations, and the prohibitive cost of annotations. Federated learning provides a compelling framework for learning mode...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	188,995
2501.03857	Progressive Document-level Text Simplification via Large Language Models	Research on text simplification has primarily focused on lexical and sentence-level changes. Long document-level simplification (DS) is still relatively unexplored. Large Language Models (LLMs), like ChatGPT, have excelled in many natural language processing tasks. However, their performance on DS tasks is unsatisfacto...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	523,016
1611.09948	Contextualizing Geometric Data Analysis and Related Data Analytics: A Virtual Microscope for Big Data Analytics	The relevance and importance of contextualizing data analytics is described. Qualitative characteristics might form the context of quantitative analysis. Topics that are at issue include: contrast, baselining, secondary data sources, supplementary data sources, dynamic and heterogeneous data. In geometric data analysis...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	64,747
1712.08767	Complete MDP convolutional codes	Maximum distance profile (MDP) convolutional codes have the property that their column distances are as large as possible. It has been shown that, transmitting over an erasure channel, these codes have optimal recovery rate for windows of a certain length. Reverse MDP convolutional codes have the additional advantage t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	87,250
2301.09729	Long-term stable Electromyography classification using Canonical Correlation Analysis	Discrimination of hand gestures based on the decoding of surface electromyography (sEMG) signals is a well-establish approach for controlling prosthetic devices and for Human-Machine Interfaces (HMI). However, despite the promising results achieved by this approach in well-controlled experimental conditions, its deploy...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,582
1705.02950	Learning non-maximum suppression	Object detectors have hugely profited from moving towards an end-to-end learning paradigm: proposals, features, and the classifier becoming one neural network improved results two-fold on general object detection. One indispensable component is non-maximum suppression (NMS), a post-processing algorithm responsible for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,089
2405.16606	Link Prediction on Textual Edge Graphs	Textual-edge Graphs (TEGs), characterized by rich text annotations on edges, are increasingly significant in network science due to their ability to capture rich contextual information among entities. Existing works have proposed various edge-aware graph neural networks (GNNs) or let language models directly make predi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	457,517
2410.20848	Deep Insights into Automated Optimization with Large Language Models and Evolutionary Algorithms	Designing optimization approaches, whether heuristic or meta-heuristic, usually demands extensive manual intervention and has difficulty generalizing across diverse problem domains. The combination of Large Language Models (LLMs) and Evolutionary Algorithms (EAs) offers a promising new approach to overcome these limita...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	502,991
2010.10203	Replacing Human Audio with Synthetic Audio for On-device Unspoken Punctuation Prediction	We present a novel multi-modal unspoken punctuation prediction system for the English language which combines acoustic and text features. We demonstrate for the first time, that by relying exclusively on synthetic data generated using a prosody-aware text-to-speech system, we can outperform a model trained with expensi...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	201,817
2407.07412	Pseudo-RIS: Distinctive Pseudo-supervision Generation for Referring Image Segmentation	We propose a new framework that automatically generates high-quality segmentation masks with their referring expressions as pseudo supervisions for referring image segmentation (RIS). These pseudo supervisions allow the training of any supervised RIS methods without the cost of manual labeling. To achieve this, we inco...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	471,755
2402.09360	HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference	Autoregressive decoding with generative Large Language Models (LLMs) on accelerators (GPUs/TPUs) is often memory-bound where most of the time is spent on transferring model parameters from high bandwidth memory (HBM) to cache. On the other hand, recent works show that LLMs can maintain quality with significant sparsity...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	429,483
1804.08204	Knowledge-based end-to-end memory networks	End-to-end dialog systems have become very popular because they hold the promise of learning directly from human to human dialog interaction. Retrieval and Generative methods have been explored in this area with mixed results. A key element that is missing so far, is the incorporation of a-priori knowledge about the ta...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	95,710
2404.03455	Synergy as the failure of distributivity	The concept of emergence, or synergy in its simplest form, is widely used but lacks a rigorous definition. Our work connects information and set theory to uncover the mathematical nature of synergy as the failure of distributivity. It resolves the persistent self-contradiction of information decomposition theory and re...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	444,267
2410.13122	Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum	We propose a novel framework, Stable Diffusion-based Momentum Integrated Adversarial Examples (SD-MIAE), for generating adversarial examples that can effectively mislead neural network classifiers while maintaining visual imperceptibility and preserving the semantic similarity to the original class label. Our method le...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	499,380
2007.13534	Coupling Learning of Complex Interactions	Complex applications such as big data analytics involve different forms of coupling relationships that reflect interactions between factors related to technical, business (domain-specific) and environmental (including socio-cultural and economic) aspects. There are diverse forms of couplings embedded in poor-structured...	false	false	false	false	true	true	true	false	false	false	false	false	false	false	false	false	false	false	189,165
1906.01562	Privacy-preserving Crowd-guided AI Decision-making in Ethical Dilemmas	With the rapid development of artificial intelligence (AI), ethical issues surrounding AI have attracted increasing attention. In particular, autonomous vehicles may face moral dilemmas in accident scenarios, such as staying the course resulting in hurting pedestrians or swerving leading to hurting passengers. To inves...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	133,755
1205.7031	Nonlinear Trellis Description for Convolutionally Encoded Transmission Over ISI-channels with Applications for CPM	In this paper we propose a matched decoding scheme for convolutionally encoded transmission over intersymbol interference (ISI) channels and devise a nonlinear trellis description. As an application we show that for coded continuous phase modulation (CPM) using a non-coherent receiver the number of states of the super ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	16,268
2010.14730	DisenE: Disentangling Knowledge Graph Embeddings	Knowledge graph embedding (KGE), aiming to embed entities and relations into low-dimensional vectors, has attracted wide attention recently. However, the existing research is mainly based on the black-box neural models, which makes it difficult to interpret the learned representation. In this paper, we introduce DisenE...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	203,550
2206.02757	Robust Calibration with Multi-domain Temperature Scaling	Uncertainty quantification is essential for the reliable deployment of machine learning models to high-stakes application domains. Uncertainty quantification is all the more challenging when training distribution and test distribution are different, even the distribution shifts are mild. Despite the ubiquity of distrib...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	301,017
2405.09928	Unified Modeling and Performance Comparison for Cellular and Cell-Free Massive MIMO	Cell-free massive multi-input multi-output (MIMO) has recently gained a lot of attention due to its high potential in sixth-generation (6G) wireless systems. The goal of this paper is to first present a unified modeling for massive MIMO, encompassing both cellular and cell-free architectures with a variable number of a...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	454,585
2002.00984	The Design of a Space-based Observation and Tracking System for Interstellar Objects	The recent observation of interstellar objects, 1I/Oumuamua and 2I/Borisov cross the solar system opened new opportunities for planetary science and planetary defense. As the first confirmed objects originating outside of the solar system, there are myriads of origin questions to explore and discuss, including where th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	true	false	false	162,531
2005.02439	Contextualizing Hate Speech Classifiers with Post-hoc Explanation	Hate speech classifiers trained on imbalanced datasets struggle to determine if group identifiers like "gay" or "black" are used in offensive or prejudiced ways. Such biases manifest in false positives when these identifiers are present, due to models' inability to learn the contexts which constitute a hateful usage of...	false	false	false	false	false	true	true	false	true	false	false	false	false	false	false	false	false	false	175,868
2106.15182	Enhancing the Analysis of Software Failures in Cloud Computing Systems with Deep Learning	Identifying the failure modes of cloud computing systems is a difficult and time-consuming task, due to the growing complexity of such systems, and the large volume and noisiness of failure data. This paper presents a novel approach for analyzing failure data from cloud systems, in order to relieve human analysts from ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	243,640
2112.13289	Prevalence Threshold and bounds in the Accuracy of Binary Classification Systems	The accuracy of binary classification systems is defined as the proportion of correct predictions - both positive and negative - made by a classification model or computational algorithm. A value between 0 (no accuracy) and 1 (perfect accuracy), the accuracy of a classification model is dependent on several factors, no...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	273,200
2203.04940	Data-Efficient Structured Pruning via Submodular Optimization	Structured pruning is an effective approach for compressing large pre-trained neural networks without significantly affecting their performance. However, most current structured pruning methods do not provide any performance guarantees, and often require fine-tuning, which makes them inapplicable in the limited-data re...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	284,658
2310.10114	Node classification in networks via simplicial interactions	In the node classification task, it is natural to presume that densely connected nodes tend to exhibit similar attributes. Given this, it is crucial to first define what constitutes a dense connection and to develop a reliable mathematical tool for assessing node cohesiveness. In this paper, we propose a probability-ba...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	400,098
2403.19457	Transmissive RIS Transmitter Enabled Spatial Modulation for MIMO Systems	In this paper, we propose a novel transmissive reconfigurable intelligent surface (TRIS) transmitter-enabled spatial modulation (SM) multiple-input multiple-output (MIMO) system. In the transmission phase, a column-wise activation strategy is implemented for the TRIS panel, where the specific column elements are activa...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	442,355
1802.04162	Policy Gradients for Contextual Recommendations	Decision making is a challenging task in online recommender systems. The decision maker often needs to choose a contextual item at each step from a set of candidates. Contextual bandit algorithms have been successfully deployed to such applications, for the trade-off between exploration and exploitation and the state-o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	90,157
1907.03817	Towards the Internet of Robotic Things: Analysis, Architecture, Components and Challenges	Internet of Things (IoT) and robotics cannot be considered two separate domains these days. Internet of Robotics Things (IoRT) is a concept that has been recently introduced to describe the integration of robotics technologies in IoT scenarios. As a consequence, these two research fields have started interacting, and t...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	137,941
2403.07403	From Canteen Food to Daily Meals: Generalizing Food Recognition to More Practical Scenarios	The precise recognition of food categories plays a pivotal role for intelligent health management, attracting significant research attention in recent years. Prominent benchmarks, such as Food-101 and VIREO Food-172, provide abundant food image resources that catalyze the prosperity of research in this field. Neverthel...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	436,870
1603.08132	Optimal Joint Power and Subcarrier Allocation for MC-NOMA Systems	In this paper, we investigate the resource allocation algorithm design for multicarrier non-orthogonal multiple access (MC-NOMA) systems. The proposed algorithm is obtained from the solution of a non-convex optimization problem for the maximization of the weighted system throughput. We employ monotonic optimization to ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	53,731
2306.11051	Concavity-Induced Distance for Unoriented Point Cloud Decomposition	We propose Concavity-induced Distance (CID) as a novel way to measure the dissimilarity between a pair of points in an unoriented point cloud. CID indicates the likelihood of two points or two sets of points belonging to different convex parts of an underlying shape represented as a point cloud. After analyzing its pro...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	374,461
2408.03404	Set2Seq Transformer: Learning Permutation Aware Set Representations of Artistic Sequences	We propose Set2Seq Transformer, a novel sequential multiple instance architecture, that learns to rank permutation aware set representations of sequences. First, we illustrate that learning temporal position-aware representations of discrete timesteps can greatly improve static visual multiple instance learning methods...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	479,000
2007.01684	New Classes of Quantum Codes Associated with Surface Maps	If the cyclic sequences of {face types} {at} all vertices in a map are the same, then the map is said to be a semi-equivelar map. In particular, a semi-equivelar map is equivelar if the faces are the same type. Homological quantum codes represent a subclass of topological quantum codes. In this article, we introduce {t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	185,507
2011.05788	Assessment of text coherence based on the cohesion estimation	In this paper, a graph-based coherence estimation method based on the cohesion estimation is suggested. Our method uses a graph-based approach to provide a user with an understanding of the evaluation process. Moreover, it can be applied to different languages, therefore, the effectiveness of this method is examined on...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	206,044
2008.11355	Physically Unclonable Functions and AI: Two Decades of Marriage	The current chapter aims at establishing a relationship between artificial intelligence (AI) and hardware security. Such a connection between AI and software security has been confirmed and well-reviewed in the relevant literature. The main focus here is to explore the methods borrowed from AI to assess the security of...	false	false	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	193,251
2302.10888	Data-Efficient Protein 3D Geometric Pretraining via Refinement of Diffused Protein Structure Decoy	Learning meaningful protein representation is important for a variety of biological downstream tasks such as structure-based drug design. Having witnessed the success of protein sequence pretraining, pretraining for structural data which is more informative has become a promising research topic. However, there are thre...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	346,994
2201.12669	Identification of MIMO Wiener-type Koopman Models for Data-Driven Model Reduction using Deep Learning	We use Koopman theory to develop a data-driven nonlinear model reduction and identification strategy for multiple-input multiple-output (MIMO) input-affine dynamical systems. While the present literature has focused on linear and bilinear Koopman models, we derive and use a Wiener-type Koopman formulation. We discuss t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	277,733
2207.00265	Affordance Extraction with an External Knowledge Database for Text-Based Simulated Environments	Text-based simulated environments have proven to be a valid testbed for machine learning approaches. The process of affordance extraction can be used to generate possible actions for interaction within such an environment. In this paper the capabilities and challenges for utilizing external knowledge databases (in part...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	305,704
2307.13933	AIDE: A Vision-Driven Multi-View, Multi-Modal, Multi-Tasking Dataset for Assistive Driving Perception	Driver distraction has become a significant cause of severe traffic accidents over the past decade. Despite the growing development of vision-driven driver monitoring systems, the lack of comprehensive perception datasets restricts road safety and traffic security. In this paper, we present an AssIstive Driving pErcept...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,752
2308.12727	DeepLOC: Deep Learning-based Bone Pathology Localization and Classification in Wrist X-ray Images	In recent years, computer-aided diagnosis systems have shown great potential in assisting radiologists with accurate and efficient medical image analysis. This paper presents a novel approach for bone pathology localization and classification in wrist X-ray images using a combination of YOLO (You Only Look Once) and th...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	387,652
2005.01819	Neural Subdivision	This paper introduces Neural Subdivision, a novel framework for data-driven coarse-to-fine geometry modeling. During inference, our method takes a coarse triangle mesh as input and recursively subdivides it to a finer geometry by applying the fixed topological updates of Loop Subdivision, but predicting vertex position...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	175,682
2003.10554	Elle: Inferring Isolation Anomalies from Experimental Observations	Users who care about their data store it in databases, which (at least in principle) guarantee some form of transactional isolation. However, experience shows [Kleppmann 2019, Kingsbury and Patella 2019a] that many databases do not provide the isolation guarantees they claim. With the recent proliferation of new distri...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	169,367
2410.10228	QE-EBM: Using Quality Estimators as Energy Loss for Machine Translation	Reinforcement learning has shown great promise in aligning language models with human preferences in a variety of text generation tasks, including machine translation. For translation tasks, rewards can easily be obtained from quality estimation (QE) models which can generate rewards for unlabeled data. Despite its use...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	497,972
1608.00508	Blind phoneme segmentation with temporal prediction errors	Phonemic segmentation of speech is a critical step of speech recognition systems. We propose a novel unsupervised algorithm based on sequence prediction models such as Markov chains and recurrent neural network. Our approach consists in analyzing the error profile of a model trained to predict speech features frame-by-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	59,290
cs/0305004	Approximate Grammar for Information Extraction	In this paper, we present the concept of Approximate grammar and how it can be used to extract information from a documemt. As the structure of informational strings cannot be defined well in a document, we cannot use the conventional grammar rules to represent the information. Hence, the need arises to design an appro...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	537,828
1710.04011	A Review of Convolutional Neural Networks for Inverse Problems in Imaging	In this survey paper, we review recent uses of convolution neural networks (CNNs) to solve inverse problems in imaging. It has recently become feasible to train deep CNNs on large databases of images, and they have shown outstanding performance on object classification and segmentation tasks. Motivated by these success...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	82,408
2407.18569	PP-TIL: Personalized Planning for Autonomous Driving with Instance-based Transfer Imitation Learning	Personalized motion planning holds significant importance within urban automated driving, catering to the unique requirements of individual users. Nevertheless, prior endeavors have frequently encountered difficulties in simultaneously addressing two crucial aspects: personalized planning within intricate urban setting...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	476,437
2210.01124	Automatic Neural Network Hyperparameter Optimization for Extrapolation: Lessons Learned from Visible and Near-Infrared Spectroscopy of Mango Fruit	Neural networks are configured by choosing an architecture and hyperparameter values; doing so often involves expert intuition and hand-tuning to find a configuration that extrapolates well without overfitting. This paper considers automatic methods for configuring a neural network that extrapolates in time for the dom...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	321,141
2205.08835	Fair and Green Hyperparameter Optimization via Multi-objective and Multiple Information Source Bayesian Optimization	There is a consensus that focusing only on accuracy in searching for optimal machine learning models amplifies biases contained in the data, leading to unfair predictions and decision supports. Recently, multi-objective hyperparameter optimization has been proposed to search for machine learning models which offer equa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	297,075
2207.07308	Z-Index at CheckThat! Lab 2022: Check-Worthiness Identification on Tweet Text	The wide use of social media and digital technologies facilitates sharing various news and information about events and activities. Despite sharing positive information misleading and false information is also spreading on social media. There have been efforts in identifying such misleading information both manually by...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	308,168
2208.02105	Edge-Based Self-Supervision for Semi-Supervised Few-Shot Microscopy Image Cell Segmentation	Deep neural networks currently deliver promising results for microscopy image cell segmentation, but they require large-scale labelled databases, which is a costly and time-consuming process. In this work, we relax the labelling requirement by combining self-supervised with semi-supervised learning. We propose the pred...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	311,378
2502.07814	Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution	Accurate acquisition of surface meteorological conditions at arbitrary locations holds significant importance for weather forecasting and climate simulation. Due to the fact that meteorological states derived from satellite observations are often provided in the form of low-resolution grid fields, the direct applicatio...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,770
2208.05650	Diverse Generative Perturbations on Attention Space for Transferable Adversarial Attacks	Adversarial attacks with improved transferability - the ability of an adversarial example crafted on a known model to also fool unknown models - have recently received much attention due to their practicality. Nevertheless, existing transferable attacks craft perturbations in a deterministic manner and often fail to fu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	312,461
1809.00717	NTUA-SLP at IEST 2018: Ensemble of Neural Transfer Methods for Implicit Emotion Classification	In this paper we present our approach to tackle the Implicit Emotion Shared Task (IEST) organized as part of WASSA 2018 at EMNLP 2018. Given a tweet, from which a certain word has been removed, we are asked to predict the emotion of the missing word. In this work, we experiment with neural Transfer Learning (TL) method...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	106,637
2010.15884	Systolic Computing on GPUs for Productive Performance	We propose a language and compiler to productively build high-performance {\it software systolic arrays} that run on GPUs. Based on a rigorous mathematical foundation (uniform recurrence equations and space-time transform), our language has a high abstraction level and covers a wide range of applications. A programmer ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	203,889
2403.01698	Hypertext Entity Extraction in Webpage	Webpage entity extraction is a fundamental natural language processing task in both research and applications. Nowadays, the majority of webpage entity extraction models are trained on structured datasets which strive to retain textual content and its structure information. However, existing datasets all overlook the r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	434,538
1903.03846	The Web is missing an essential part of infrastructure: an Open Web Index	A proposal for building an index of the Web that separates the infrastructure part of the search engine - the index - from the services part that will form the basis for myriad search engines and other services utilizing Web data on top of a public infrastructure open to everyone.	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	123,835
2305.17456	Trustworthy Deep Learning for Medical Image Segmentation	Despite the recent success of deep learning methods at achieving new state-of-the-art accuracy for medical image segmentation, some major limitations are still restricting their deployment into clinics. One major limitation of deep learning-based segmentation methods is their lack of robustness to variability in the im...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	368,603
2409.15779	A Robust, Task-Agnostic and Fully-Scalable Voxel Mapping System for Large Scale Environments	Perception still remains a challenging problem for autonomous navigation in unknown environment, especially for aerial vehicles. Most mapping algorithms for autonomous navigation are specifically designed for their very intended task, which hinders extended usage or cooperative task. In this paper, we propose a voxel m...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	491,058
2404.19247	Improved AutoEncoder with LSTM module and KL divergence	The task of anomaly detection is to separate anomalous data from normal data in the dataset. Models such as deep convolutional autoencoder (CAE) network and deep supporting vector data description (SVDD) model have been universally employed and have demonstrated significant success in detecting anomalies. However, the ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	450,560
1910.02267	Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging	Semitic languages can be highly ambiguous, having several interpretations of the same surface forms, and morphologically rich, having many morphemes that realize several morphological features. This is further exacerbated for dialectal content, which is more prone to noise and lacks a standard orthography. The morpholo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	148,191
1507.05455	AMP: a new time-frequency feature extraction method for intermittent time-series data	The characterisation of time-series data via their most salient features is extremely important in a range of machine learning task, not least of all with regards to classification and clustering. While there exist many feature extraction techniques suitable for non-intermittent time-series data, these approaches are n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	45,289
2301.04725	Blockchain For Mobile Health Applications: Acceleration With GPU Computing	Blockchain is a linearly linked, distributed, and very robust data structure. Originally proposed as part of the Bitcoin distributed stack, it found a number of applications in a number of fields, most notably in smart contracts, social media, secure IoT, and cryptocurrency mining. It ensures data integrity by distribu...	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	340,148
1607.06556	Syntax-based Attention Model for Natural Language Inference	Introducing attentional mechanism in neural network is a powerful concept, and has achieved impressive results in many natural language processing tasks. However, most of the existing models impose attentional distribution on a flat topology, namely the entire input representation sequence. Clearly, any well-formed sen...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	58,905
1910.06855	On the Hardware Feasibility of Nonlinear Trajectory Optimization for Legged Locomotion based on a Simplified Dynamics	Simplified models are useful to increase the computational efficiency of a motion planning algorithm, but their lack of accuracy have to be managed. We propose two feasibility constraints to be included in a Single Rigid Body Dynamicsbased trajectory optimizer in order to obtain robust motions in challenging terrain. T...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	149,469
2306.04054	RescueSpeech: A German Corpus for Speech Recognition in Search and Rescue Domain	Despite the recent advancements in speech recognition, there are still difficulties in accurately transcribing conversational and emotional speech in noisy and reverberant acoustic environments. This poses a particular challenge in the search and rescue (SAR) domain, where transcribing conversations among rescue team m...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,583
2405.00954	X-Oscar: A Progressive Framework for High-quality Text-guided 3D Animatable Avatar Generation	Recent advancements in automatic 3D avatar generation guided by text have made significant progress. However, existing methods have limitations such as oversaturation and low-quality output. To address these challenges, we propose X-Oscar, a progressive framework for generating high-quality animatable avatars from text...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	451,145
2112.11279	Differential Parity: Relative Fairness Between Two Sets of Decisions	With AI systems widely applied to assist human in decision-making processes such as talent hiring, school admission, and loan approval; there is an increasing need to ensure that the decisions made are fair. One major challenge for analyzing fairness in decisions is that the standards are highly subjective and contextu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	272,666
2404.11795	Prompt-Driven Feature Diffusion for Open-World Semi-Supervised Learning	In this paper, we present a novel approach termed Prompt-Driven Feature Diffusion (PDFD) within a semi-supervised learning framework for Open World Semi-Supervised Learning (OW-SSL). At its core, PDFD deploys an efficient feature-level diffusion model with the guidance of class-specific prompts to support discriminativ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	447,613
2009.03482	Alternating Direction Method of Multipliers for Quantization	Quantization of the parameters of machine learning models, such as deep neural networks, requires solving constrained optimization problems, where the constraint set is formed by the Cartesian product of many simple discrete sets. For such optimization problems, we study the performance of the Alternating Direction Met...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	194,816
1907.05008	Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology	To deepen our understanding of graph neural networks, we investigate the representation power of Graph Convolutional Networks (GCN) through the looking glass of graph moments, a key property of graph topology encoding path of various lengths. We find that GCNs are rather restrictive in learning graph moments. Without c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,253

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