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
2303.06342	Enhanced K-Radar: Optimal Density Reduction to Improve Detection Performance and Accessibility of 4D Radar Tensor-based Object Detection	Recent works have shown the superior robustness of four-dimensional (4D) Radar-based three-dimensional (3D) object detection in adverse weather conditions. However, processing 4D Radar data remains a challenge due to the large data size, which require substantial amount of memory for computing and storage. In previous ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	350,804
2008.05888	A comprehensive dynamic growth and development model of Hermetia illucens larvae	Larvae of Hermetia illucens, also commonly known as black soldier fly (BSF) have gained significant importance in the feed industry, primarily used as feed for aquaculture and other livestock farming. Mathematical model such as Von Bertalanffy growth model and dynamic energy budget models are available for modelling th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	191,644
2307.14912	ARC-NLP at PAN 2023: Hierarchical Long Text Classification for Trigger Detection	Fanfiction, a popular form of creative writing set within established fictional universes, has gained a substantial online following. However, ensuring the well-being and safety of participants has become a critical concern in this community. The detection of triggering content, material that may cause emotional distre...	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	382,091
2010.04979	A Termination Criterion for Probabilistic PointClouds Registration	Probabilistic Point Clouds Registration (PPCR) is an algorithm that, in its multi-iteration version, outperformed state of the art algorithms for local point clouds registration. However, its performances have been tested using a fixed high number of iterations. To be of practical usefulness, we think that the algorith...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	199,948
1707.09751	Skill2vec: Machine Learning Approach for Determining the Relevant Skills from Job Description	Unsupervise learned word embeddings have seen tremendous success in numerous Natural Language Processing (NLP) tasks in recent years. The main contribution of this paper is to develop a technique called Skill2vec, which applies machine learning techniques in recruitment to enhance the search strategy to find candidates...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	78,066
1911.09963	Background Suppression Network for Weakly-supervised Temporal Action Localization	Weakly-supervised temporal action localization is a very challenging problem because frame-wise labels are not given in the training stage while the only hint is video-level labels: whether each video contains action frames of interest. Previous methods aggregate frame-level class scores to produce video-level predicti...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	154,684
2501.15007	Controllable Protein Sequence Generation with LLM Preference Optimization	Designing proteins with specific attributes offers an important solution to address biomedical challenges. Pre-trained protein large language models (LLMs) have shown promising results on protein sequence generation. However, to control sequence generation for specific attributes, existing work still exhibits poor func...	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	527,357
1711.05971	Learning to Find Good Correspondences	We develop a deep architecture to learn to find good correspondences for wide-baseline stereo. Given a set of putative sparse matches and the camera intrinsics, we train our network in an end-to-end fashion to label the correspondences as inliers or outliers, while simultaneously using them to recover the relative pose...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	84,688
2307.13702	Measuring Faithfulness in Chain-of-Thought Reasoning	Large language models (LLMs) perform better when they produce step-by-step, "Chain-of-Thought" (CoT) reasoning before answering a question, but it is unclear if the stated reasoning is a faithful explanation of the model's actual reasoning (i.e., its process for answering the question). We investigate hypotheses for ho...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	381,672
2404.05134	LLM-BT: Performing Robotic Adaptive Tasks based on Large Language Models and Behavior Trees	Large Language Models (LLMs) have been widely utilized to perform complex robotic tasks. However, handling external disturbances during tasks is still an open challenge. This paper proposes a novel method to achieve robotic adaptive tasks based on LLMs and Behavior Trees (BTs). It utilizes ChatGPT to reason the descrip...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	444,954
2205.11397	Super Vision Transformer	We attempt to reduce the computational costs in vision transformers (ViTs), which increase quadratically in the token number. We present a novel training paradigm that trains only one ViT model at a time, but is capable of providing improved image recognition performance with various computational costs. Here, the trai...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	298,124
2205.04831	An Engineer's Nightmare: 102 Years of Critical Robotics	A critical and re-configured HRI might look to the arts, where another history of robots has been unfolding since the Czech artist Karel Capek's critical robotic labor parable of 1921, in which the word robot was coined in its modern usage. This paper explores several vectors by which artist-created robots, both physic...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	295,766
2111.10400	RacketStore: Measurements of ASO Deception in Google Play via Mobile and App Usage	Online app search optimization (ASO) platforms that provide bulk installs and fake reviews for paying app developers in order to fraudulently boost their search rank in app stores, were shown to employ diverse and complex strategies that successfully evade state-of-the-art detection methods. In this paper we introduce ...	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	267,308
2309.16661	SA2-Net: Scale-aware Attention Network for Microscopic Image Segmentation	Microscopic image segmentation is a challenging task, wherein the objective is to assign semantic labels to each pixel in a given microscopic image. While convolutional neural networks (CNNs) form the foundation of many existing frameworks, they often struggle to explicitly capture long-range dependencies. Although tra...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	395,437
2008.12010	OFFER: A Motif Dimensional Framework for Network Representation Learning	Aiming at better representing multivariate relationships, this paper investigates a motif dimensional framework for higher-order graph learning. The graph learning effectiveness can be improved through OFFER. The proposed framework mainly aims at accelerating and improving higher-order graph learning results. We apply ...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	193,463
2406.12235	Holmes-VAD: Towards Unbiased and Explainable Video Anomaly Detection via Multi-modal LLM	Towards open-ended Video Anomaly Detection (VAD), existing methods often exhibit biased detection when faced with challenging or unseen events and lack interpretability. To address these drawbacks, we propose Holmes-VAD, a novel framework that leverages precise temporal supervision and rich multimodal instructions to e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	465,290
1406.5665	Constant Factor Approximation for Balanced Cut in the PIE model	We propose and study a new semi-random semi-adversarial model for Balanced Cut, a planted model with permutation-invariant random edges (PIE). Our model is much more general than planted models considered previously. Consider a set of vertices V partitioned into two clusters $L$ and $R$ of equal size. Let $G$ be an arb...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	34,047
1607.00913	Superintelligence cannot be contained: Lessons from Computability Theory	Superintelligence is a hypothetical agent that possesses intelligence far surpassing that of the brightest and most gifted human minds. In light of recent advances in machine intelligence, a number of scientists, philosophers and technologists have revived the discussion about the potential catastrophic risks entailed ...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	58,151
1703.05148	Random Forests and VGG-NET: An Algorithm for the ISIC 2017 Skin Lesion Classification Challenge	This manuscript briefly describes an algorithm developed for the ISIC 2017 Skin Lesion Classification Competition. In this task, participants are asked to complete two independent binary image classification tasks that involve three unique diagnoses of skin lesions (melanoma, nevus, and seborrheic keratosis). In the fi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,030
2412.01840	Zonal Architecture Development with evolution of Artificial Intelligence	This paper explains how traditional centralized architectures are transitioning to distributed zonal approaches to address challenges in scalability, reliability, performance, and cost-effectiveness. The role of edge computing and neural networks in enabling sophisticated sensor fusion and decision-making capabilities ...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	false	false	513,289
cs/0308013	A Robust and Computational Characterisation of Peer-to-Peer Database Systems	In this paper we give a robust logical and computational characterisation of peer-to-peer database systems. We first define a pre- cise model-theoretic semantics of a peer-to-peer system, which allows for local inconsistency handling. We then characterise the general computa- tional properties for the problem of answer...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	537,954
2305.18455	Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models	Due to the ease of training, ability to scale, and high sample quality, diffusion models (DMs) have become the preferred option for generative modeling, with numerous pre-trained models available for a wide variety of datasets. Containing intricate information about data distributions, pre-trained DMs are valuable asse...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	369,071
2105.07454	A Synchronized Action Framework for Responsible Detection of Coordination on Social Media	The study of coordinated manipulation of conversations on social media has become more prevalent as social media's role in amplifying misinformation, hate, and polarization has come under scrutiny. We discuss the implications of successful coordination detection algorithms based on shifts of power, and consider how res...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	235,437
0905.3830	Tag Clouds for Displaying Semantics: The Case of Filmscripts	We relate tag clouds to other forms of visualization, including planar or reduced dimensionality mapping, and Kohonen self-organizing maps. Using a modified tag cloud visualization, we incorporate other information into it, including text sequence and most pertinent words. Our notion of word pertinence goes beyond just...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	3,756
1311.6647	DoF Analysis of the K-user MISO Broadcast Channel with Alternating CSIT	We consider a $K$-user multiple-input single-output (MISO) broadcast channel (BC) where the channel state information (CSI) of user $i(i=1,2,\ldots,K)$ may be either perfect (P), delayed (D) or not known (N) at the transmitter with probabilities $\lambda_P^i$, $\lambda_D^i$ and $\lambda_N^i$, respectively. In this chan...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,672
1408.4409	Robust width: A characterization of uniformly stable and robust compressed sensing	Compressed sensing seeks to invert an underdetermined linear system by exploiting additional knowledge of the true solution. Over the last decade, several instances of compressed sensing have been studied for various applications, and for each instance, reconstruction guarantees are available provided the sensing opera...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	35,455
1503.07431	Coordination and Efficiency in Decentralized Collaboration	Environments for decentralized on-line collaboration are now widespread on the Web, underpinning open-source efforts, knowledge creation sites including Wikipedia, and other experiments in joint production. When a distributed group works together in such a setting, the mechanisms they use for coordination can play an i...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	41,472
2104.02960	Community Detection with Contextual Multilayer Networks	In this paper, we study community detection when we observe $m$ sparse networks and a high dimensional covariate matrix, all encoding the same community structure among $n$ subjects. In the asymptotic regime where the number of features $p$ and the number of subjects $n$ grows proportionally, we derive an exact formula...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	228,917
2309.04655	Intelligent upper-limb exoskeleton integrated with soft wearable bioelectronics and deep-learning for human intention-driven strength augmentation based on sensory feedback	The age and stroke-associated decline in musculoskeletal strength degrades the ability to perform daily human tasks using the upper extremities. Although there are a few examples of exoskeletons, they need manual operations due to the absence of sensor feedback and no intention prediction of movements. Here, we introdu...	false	false	false	false	false	false	true	true	false	false	true	false	false	false	false	false	false	false	390,795
2210.11657	MnEdgeNet -- Accurate Decomposition of Mixed Oxidation States for Mn XAS and EELS L2,3 Edges without Reference and Calibration	Accurate decomposition of the mixed Mn oxidation states is highly important for characterizing the electronic structures, charge transfer, and redox centers for electronic, electrocatalytic, and energy storage materials that contain Mn. Electron energy loss spectroscopy (EELS) and soft X-ray absorption spectroscopy (XA...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	325,396
2207.08214	FEJ-VIRO: A Consistent First-Estimate Jacobian Visual-Inertial-Ranging Odometry	In recent years, Visual-Inertial Odometry (VIO) has achieved many significant progresses. However, VIO methods suffer from localization drift over long trajectories. In this paper, we propose a First-Estimates Jacobian Visual-Inertial-Ranging Odometry (FEJ-VIRO) to reduce the localization drifts of VIO by incorporating...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	308,504
1512.01914	Rademacher Complexity of the Restricted Boltzmann Machine	Boltzmann machine, as a fundamental construction block of deep belief network and deep Boltzmann machines, is widely used in deep learning community and great success has been achieved. However, theoretical understanding of many aspects of it is still far from clear. In this paper, we studied the Rademacher complexity ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	49,884
2205.08891	A Scalable Workflow to Build Machine Learning Classifiers with Clinician-in-the-Loop to Identify Patients in Specific Diseases	Clinicians may rely on medical coding systems such as International Classification of Diseases (ICD) to identify patients with diseases from Electronic Health Records (EHRs). However, due to the lack of detail and specificity as well as a probability of miscoding, recent studies suggest the ICD codes often cannot chara...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	297,090
2403.05592	Eternal Sunshine of the Mechanical Mind: The Irreconcilability of Machine Learning and the Right to be Forgotten	As we keep rapidly advancing toward an era where artificial intelligence is a constant and normative experience for most of us, we must also be aware of what this vision and this progress entail. By first approximating neural connections and activities in computer circuits and then creating more and more sophisticated ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	436,077
2411.18767	Multi-Task Learning for Integrated Automated Contouring and Voxel-Based Dose Prediction in Radiotherapy	Deep learning-based automated contouring and treatment planning has been proven to improve the efficiency and accuracy of radiotherapy. However, conventional radiotherapy treatment planning process has the automated contouring and treatment planning as separate tasks. Moreover in deep learning (DL), the contouring and ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	511,996
2006.05065	Self-Distillation as Instance-Specific Label Smoothing	It has been recently demonstrated that multi-generational self-distillation can improve generalization. Despite this intriguing observation, reasons for the enhancement remain poorly understood. In this paper, we first demonstrate experimentally that the improved performance of multi-generational self-distillation is i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,923
2409.19272	Perception Compressor: A Training-Free Prompt Compression Framework in Long Context Scenarios	Large language models (LLMs) demonstrate exceptional capabilities in various scenarios. However, they suffer from much redundant information and are sensitive to the position of key information in long context scenarios. To address these challenges, we present Perception Compressor, a training-free prompt compression f...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	492,611
2005.03247	Training and Classification using a Restricted Boltzmann Machine on the D-Wave 2000Q	Restricted Boltzmann Machine (RBM) is an energy based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate exact gradient of log-likelihood cost function. In...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	176,104
2111.00774	On the number of $q$-ary quasi-perfect codes with covering radius 2	In this paper we present a family of $q$-ary nonlinear quasi-perfect codes with covering radius 2. The codes have length $n = q^m$ and size $ M = q^{n - m - 1}$ where $q$ is a prime power, $q \geq 3$, $m$ is an integer, $m \geq 2$. We prove that there are more than $q^{q^{cn}}$ nonequivalent such codes of length $n$, f...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	264,336
2302.08149	URCDC-Depth: Uncertainty Rectified Cross-Distillation with CutFlip for Monocular Depth Estimation	This work aims to estimate a high-quality depth map from a single RGB image. Due to the lack of depth clues, making full use of the long-range correlation and the local information is critical for accurate depth estimation. Towards this end, we introduce an uncertainty rectified cross-distillation between Transformer a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	345,961
2405.09365	SARATR-X: Toward Building A Foundation Model for SAR Target Recognition	Despite the remarkable progress in synthetic aperture radar automatic target recognition (SAR ATR), recent efforts have concentrated on detecting and classifying a specific category, e.g., vehicles, ships, airplanes, or buildings. One of the fundamental limitations of the top-performing SAR ATR methods is that the lear...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	454,382
2408.07689	Detecting Near-Duplicate Face Images	Near-duplicate images are often generated when applying repeated photometric and geometric transformations that produce imperceptible variants of the original image. Consequently, a deluge of near-duplicates can be circulated online posing copyright infringement concerns. The concerns are more severe when biometric dat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	480,688
2306.08075	BPKD: Boundary Privileged Knowledge Distillation For Semantic Segmentation	Current knowledge distillation approaches in semantic segmentation tend to adopt a holistic approach that treats all spatial locations equally. However, for dense prediction, students' predictions on edge regions are highly uncertain due to contextual information leakage, requiring higher spatial sensitivity knowledge ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	373,273
2501.12902	Learning to Optimize Joint Chance-constrained Power Dispatch Problems	The ever-increasing integration of stochastic renewable energy sources into power systems operation is making the supply-demand balance more challenging. While joint chance-constrained methods are equipped to model these complexities and uncertainties, solving these models using the traditional iterative solvers is tim...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	526,479
cmp-lg/9404003	Restricting the Weak-Generative Capacity of Synchronous Tree-Adjoining Grammars	The formalism of synchronous tree-adjoining grammars, a variant of standard tree-adjoining grammars (TAG), was intended to allow the use of TAGs for language transduction in addition to language specification. In previous work, the definition of the transduction relation defined by a synchronous TAG was given by appeal...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,036
1311.5322	More Efficient Privacy Amplification with Less Random Seeds via Dual Universal Hash Function	We explicitly construct random hash functions for privacy amplification (extractors) that require smaller random seed lengths than the previous literature, and still allow efficient implementations with complexity $O(n\log n)$ for input length $n$. The key idea is the concept of dual universal$_2$ hash function introdu...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	28,557
2411.01135	Music Foundation Model as Generic Booster for Music Downstream Tasks	We demonstrate the efficacy of using intermediate representations from a single foundation model to enhance various music downstream tasks. We introduce SoniDo, a music foundation model (MFM) designed to extract hierarchical features from target music samples. By leveraging hierarchical intermediate features, SoniDo co...	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	504,924
2006.06261	XiaoiceSing: A High-Quality and Integrated Singing Voice Synthesis System	This paper presents XiaoiceSing, a high-quality singing voice synthesis system which employs an integrated network for spectrum, F0 and duration modeling. We follow the main architecture of FastSpeech while proposing some singing-specific design: 1) Besides phoneme ID and position encoding, features from musical score ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	181,366
2210.08654	Learning to Sample and Aggregate: Few-shot Reasoning over Temporal Knowledge Graphs	In this paper, we investigate a realistic but underexplored problem, called few-shot temporal knowledge graph reasoning, that aims to predict future facts for newly emerging entities based on extremely limited observations in evolving graphs. It offers practical value in applications that need to derive instant new kno...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	324,237
2212.01004	Planogram Compliance Control via Object Detection, Sequence Alignment, and Focused Iterative Search	Smart retail stores are becoming the fact of our lives. Several computer vision and sensor based systems are working together to achieve such a complex and automated operation. Besides, the retail sector already has several open and challenging problems which can be solved with the help of pattern recognition and compu...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	334,275
2103.06648	Domain State Tracking for a Simplified Dialogue System	Task-oriented dialogue systems aim to help users achieve their goals in specific domains. Recent neural dialogue systems use the entire dialogue history for abundant contextual information accumulated over multiple conversational turns. However, the dialogue history becomes increasingly longer as the number of turns in...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	224,370
2201.00690	Improved Topic modeling in Twitter through Community Pooling	Social networks play a fundamental role in propagation of information and news. Characterizing the content of the messages becomes vital for different tasks, like breaking news detection, personalized message recommendation, fake users detection, information flow characterization and others. However, Twitter posts are ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	274,035
2101.01861	TGCN: Time Domain Graph Convolutional Network for Multiple Objects Tracking	Multiple object tracking is to give each object an id in the video. The difficulty is how to match the predicted objects and detected objects in same frames. Matching features include appearance features, location features, etc. These features of the predicted object are basically based on some previous frames. However...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	214,463
2402.08105	Learning Cartesian Product Graphs with Laplacian Constraints	Graph Laplacian learning, also known as network topology inference, is a problem of great interest to multiple communities. In Gaussian graphical models (GM), graph learning amounts to endowing covariance selection with the Laplacian structure. In graph signal processing (GSP), it is essential to infer the unobserved g...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	428,960
2412.10152	Direct Encoding of Declare Constraints in ASP	Answer Set Programming (ASP), a well-known declarative logic programming paradigm, has recently found practical application in Process Mining. In particular, ASP has been used to model tasks involving declarative specifications of business processes. In this area, Declare stands out as the most widely adopted declarati...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	516,807
2207.05549	PoeticTTS -- Controllable Poetry Reading for Literary Studies	Speech synthesis for poetry is challenging due to specific intonation patterns inherent to poetic speech. In this work, we propose an approach to synthesise poems with almost human like naturalness in order to enable literary scholars to systematically examine hypotheses on the interplay between text, spoken realisatio...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	307,584
2011.13965	Compiling Spiking Neural Networks to Mitigate Neuromorphic Hardware Constraints	Spiking Neural Networks (SNNs) are efficient computation models to perform spatio-temporal pattern recognition on {resource}- and {power}-constrained platforms. SNNs executed on neuromorphic hardware can further reduce energy consumption of these platforms. With increasing model size and complexity, mapping SNN-based a...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	208,623
2008.08352	Deep Controllable Backlight Dimming	Dual-panel displays require local dimming algorithms in order to reproduce content with high fidelity and high dynamic range. In this work, a novel deep learning based local dimming method is proposed for rendering HDR images on dual-panel HDR displays. The method uses a Convolutional Neural Network to predict backligh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	192,395
2202.10554	Ensemble Learning techniques for object detection in high-resolution satellite images	Ensembling is a method that aims to maximize the detection performance by fusing individual detectors. While rarely mentioned in deep-learning articles applied to remote sensing, ensembling methods have been widely used to achieve high scores in recent data science com-petitions, such as Kaggle. The few remote sensing ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	281,561
1210.0685	Local stability and robustness of sparse dictionary learning in the presence of noise	A popular approach within the signal processing and machine learning communities consists in modelling signals as sparse linear combinations of atoms selected from a learned dictionary. While this paradigm has led to numerous empirical successes in various fields ranging from image to audio processing, there have only ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	18,888
1510.01391	Abstraction/Representation Theory for Heterotic Physical Computing	We give a rigorous framework for the interaction of physical computing devices with abstract computation. Device and program are mediated by the non-logical 'representation relation'; we give the conditions under which representation and device theory give rise to commuting diagrams between logical and physical domains...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	47,611
1108.1966	A Concise Query Language with Search and Transform Operations for Corpora with Multiple Levels of Annotation	The usefulness of annotated corpora is greatly increased if there is an associated tool that can allow various kinds of operations to be performed in a simple way. Different kinds of annotation frameworks and many query languages for them have been proposed, including some to deal with multiple layers of annotation. We...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	11,612
1002.0406	MIMO Transmission with Residual Transmit-RF Impairments	Physical transceiver implementations for multiple-input multiple-output (MIMO) wireless communication systems suffer from transmit-RF (Tx-RF) impairments. In this paper, we study the effect on channel capacity and error-rate performance of residual Tx-RF impairments that defy proper compensation. In particular, we demo...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,589
cs/0402009	Resolving Clinicians Queries Across a Grids Infrastructure	The past decade has witnessed order of magnitude increases in computing power, data storage capacity and network speed, giving birth to applications which may handle large data volumes of increased complexity, distributed over the Internet. Grids computing promises to resolve many of the difficulties in facilitating me...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	538,094
2207.01115	USHER: Unbiased Sampling for Hindsight Experience Replay	Dealing with sparse rewards is a long-standing challenge in reinforcement learning (RL). Hindsight Experience Replay (HER) addresses this problem by reusing failed trajectories for one goal as successful trajectories for another. This allows for both a minimum density of reward and for generalization across multiple go...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	306,042
2410.10857	Mirror-Consistency: Harnessing Inconsistency in Majority Voting	Self-Consistency, a widely-used decoding strategy, significantly boosts the reasoning capabilities of Large Language Models (LLMs). However, it depends on the plurality voting rule, which focuses on the most frequent answer while overlooking all other minority responses. These inconsistent minority views often illumina...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	498,275
1704.06393	Neural System Combination for Machine Translation	Neural machine translation (NMT) becomes a new approach to machine translation and generates much more fluent results compared to statistical machine translation (SMT). However, SMT is usually better than NMT in translation adequacy. It is therefore a promising direction to combine the advantages of both NMT and SMT....	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	72,168
1106.4221	Understanding opinions. A cognitive and formal account	The study of opinions, their formation and change, is one of the defining topics addressed by social psychology, but in recent years other disciplines, as computer science and complexity, have addressed this challenge. Despite the flourishing of different models and theories in both fields, several key questions still ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,933
1507.08905	Deep Networks for Image Super-Resolution with Sparse Prior	Deep learning techniques have been successfully applied in many areas of computer vision, including low-level image restoration problems. For image super-resolution, several models based on deep neural networks have been recently proposed and attained superior performance that overshadows all previous handcrafted model...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	45,610
1605.01030	Comparing Kalman Filters and Observers for Power System Dynamic State Estimation with Model Uncertainty and Malicious Cyber Attacks	Kalman filters and observers are two main classes of dynamic state estimation (DSE) routines. Power system DSE has been implemented by various Kalman filters, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). In this paper, we discuss two challenges for an effective power system DSE: (a) m...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	55,421
2404.18065	Grounded Compositional and Diverse Text-to-3D with Pretrained Multi-View Diffusion Model	In this paper, we propose an effective two-stage approach named Grounded-Dreamer to generate 3D assets that can accurately follow complex, compositional text prompts while achieving high fidelity by using a pre-trained multi-view diffusion model. Multi-view diffusion models, such as MVDream, have shown to generate high...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	450,115
1905.00455	Machine Learning for Classification of Protein Helix Capping Motifs	The biological function of a protein stems from its 3-dimensional structure, which is thermodynamically determined by the energetics of interatomic forces between its amino acid building blocks (the order of amino acids, known as the sequence, defines a protein). Given the costs (time, money, human resources) of determ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	129,471
2006.02903	A Comprehensive Survey of Neural Architecture Search: Challenges and Solutions	Deep learning has made breakthroughs and substantial in many fields due to its powerful automatic representation capabilities. It has been proven that neural architecture design is crucial to the feature representation of data and the final performance. However, the design of the neural architecture heavily relies on t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	180,166
2111.10085	Mate! Are You Really Aware? An Explainability-Guided Testing Framework for Robustness of Malware Detectors	Numerous open-source and commercial malware detectors are available. However, their efficacy is threatened by new adversarial attacks, whereby malware attempts to evade detection, e.g., by performing feature-space manipulation. In this work, we propose an explainability-guided and model-agnostic testing framework for r...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	267,204
2404.10209	Demonstration of DB-GPT: Next Generation Data Interaction System Empowered by Large Language Models	The recent breakthroughs in large language models (LLMs) are positioned to transition many areas of software. The technologies of interacting with data particularly have an important entanglement with LLMs as efficient and intuitive data interactions are paramount. In this paper, we present DB-GPT, a revolutionary and ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	446,996
1506.02369	Automated Synthesis of Distributed Controllers	Synthesis is a particularly challenging problem for concurrent programs. At the same time it is a very promising approach, since concurrent programs are difficult to get right, or to analyze with traditional verification techniques. This paper gives an introduction to distributed synthesis in the setting of Mazurkiewic...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	43,915
2409.00045	PolypDB: A Curated Multi-Center Dataset for Development of AI Algorithms in Colonoscopy	Colonoscopy is the primary method for examination, detection, and removal of polyps. However, challenges such as variations among the endoscopists' skills, bowel quality preparation, and the complex nature of the large intestine contribute to high polyp miss-rate. These missed polyps can develop into cancer later, unde...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	484,737
2412.02408	Leveraging Ensemble-Based Semi-Supervised Learning for Illicit Account Detection in Ethereum DeFi Transactions	The advent of smart contracts has enabled the rapid rise of Decentralized Finance (DeFi) on the Ethereum blockchain, offering substantial rewards in financial innovation and inclusivity. However, this growth has also introduced significant security risks, including the proliferation of illicit accounts involved in frau...	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	513,529
2408.16262	On Convergence of Average-Reward Q-Learning in Weakly Communicating Markov Decision Processes	This paper analyzes reinforcement learning (RL) algorithms for Markov decision processes (MDPs) under the average-reward criterion. We focus on Q-learning algorithms based on relative value iteration (RVI), which are model-free stochastic analogues of the classical RVI method for average-reward MDPs. These algorithms h...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	484,260
2305.15294	Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy	Large language models are powerful text processors and reasoners, but are still subject to limitations including outdated knowledge and hallucinations, which necessitates connecting them to the world. Retrieval-augmented large language models have raised extensive attention for grounding model generation on external kn...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	367,554
2502.10632	Code-Mixed Telugu-English Hate Speech Detection	Hate speech detection in low-resource languages like Telugu is a growing challenge in NLP. This study investigates transformer-based models, including TeluguHateBERT, HateBERT, DeBERTa, Muril, IndicBERT, Roberta, and Hindi-Abusive-MuRIL, for classifying hate speech in Telugu. We fine-tune these models using Low-Rank Ad...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	533,973
0904.3340	Lossy Compression in Near-Linear Time via Efficient Random Codebooks and Databases	The compression-complexity trade-off of lossy compression algorithms that are based on a random codebook or a random database is examined. Motivated, in part, by recent results of Gupta-Verd\'{u}-Weissman (GVW) and their underlying connections with the pattern-matching scheme of Kontoyiannis' lossy Lempel-Ziv algorithm...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	3,573
2410.12064	LegalLens Shared Task 2024: Legal Violation Identification in Unstructured Text	This paper presents the results of the LegalLens Shared Task, focusing on detecting legal violations within text in the wild across two sub-tasks: LegalLens-NER for identifying legal violation entities and LegalLens-NLI for associating these violations with relevant legal contexts and affected individuals. Using an enh...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	498,839
1805.10515	A Survey of Parallel Sequential Pattern Mining	With the growing popularity of shared resources, large volumes of complex data of different types are collected automatically. Traditional data mining algorithms generally have problems and challenges including huge memory cost, low processing speed, and inadequate hard disk space. As a fundamental task of data mining,...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	98,698
2312.15474	A Conservative Approach for Few-Shot Transfer in Off-Dynamics Reinforcement Learning	Off-dynamics Reinforcement Learning (ODRL) seeks to transfer a policy from a source environment to a target environment characterized by distinct yet similar dynamics. In this context, traditional RL agents depend excessively on the dynamics of the source environment, resulting in the discovery of policies that excel i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	418,022
2202.01969	A Novel Assistive Controller Based on Differential Geometry for Users of the Differential-Drive Wheeled Mobile Robots	Certain wheeled mobile robots e.g., electric wheelchairs, can operate through indirect joystick controls from users. Correct steering angle becomes essential when the user should determine the vehicle direction and velocity, in particular for differential wheeled vehicles since the vehicle velocity and direction are co...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	278,659
2409.20562	SpaceMesh: A Continuous Representation for Learning Manifold Surface Meshes	Meshes are ubiquitous in visual computing and simulation, yet most existing machine learning techniques represent meshes only indirectly, e.g. as the level set of a scalar field or deformation of a template, or as a disordered triangle soup lacking local structure. This work presents a scheme to directly generate manif...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	493,174
2103.10051	Data-free mixed-precision quantization using novel sensitivity metric	Post-training quantization is a representative technique for compressing neural networks, making them smaller and more efficient for deployment on edge devices. However, an inaccessible user dataset often makes it difficult to ensure the quality of the quantized neural network in practice. In addition, existing approac...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	225,335
2406.04815	Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning	Meta-Reinforcement Learning (Meta-RL) agents can struggle to operate across tasks with varying environmental features that require different optimal skills (i.e., different modes of behaviour). Using context encoders based on contrastive learning to enhance the generalisability of Meta-RL agents is now widely studied b...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	461,853
2208.04459	Bullwhip Effect of Supply Networks: Joint Impact of Network Structure and Market Demand	The progressive amplification of fluctuations in demand as the demand travels upstream the supply chains is known as the bullwhip effect. We first analytically characterize the bullwhip effect in general supply chain networks in two cases: (i) all suppliers have a unique layer position, where our method is founded on t...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	312,110
2412.12540	Stiefel Flow Matching for Moment-Constrained Structure Elucidation	Molecular structure elucidation is a fundamental step in understanding chemical phenomena, with applications in identifying molecules in natural products, lab syntheses, forensic samples, and the interstellar medium. We consider the task of predicting a molecule's all-atom 3D structure given only its molecular formula ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	517,913
1911.04379	Modeling EEG data distribution with a Wasserstein Generative Adversarial Network to predict RSVP Events	Electroencephalography (EEG) data are difficult to obtain due to complex experimental setups and reduced comfort with prolonged wearing. This poses challenges to train powerful deep learning model with the limited EEG data. Being able to generate EEG data computationally could address this limitation. We propose a nove...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,973
2101.06545	VideoClick: Video Object Segmentation with a Single Click	Annotating videos with object segmentation masks typically involves a two stage procedure of drawing polygons per object instance for all the frames and then linking them through time. While simple, this is a very tedious, time consuming and expensive process, making the creation of accurate annotations at scale only p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	215,754
2208.00638	Composable Text Controls in Latent Space with ODEs	Real-world text applications often involve composing a wide range of text control operations, such as editing the text w.r.t. an attribute, manipulating keywords and structure, and generating new text of desired properties. Prior work typically learns/finetunes a language model (LM) to perform individual or specific su...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	310,921
1209.0245	Diffusion maps for changing data	Graph Laplacians and related nonlinear mappings into low dimensional spaces have been shown to be powerful tools for organizing high dimensional data. Here we consider a data set X in which the graph associated with it changes depending on some set of parameters. We analyze this type of data in terms of the diffusion d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	18,354
2410.06725	Evaluating the Impact of Point Cloud Colorization on Semantic Segmentation Accuracy	Point cloud semantic segmentation, the process of classifying each point into predefined categories, is essential for 3D scene understanding. While image-based segmentation is widely adopted due to its maturity, methods relying solely on RGB information often suffer from degraded performance due to color inaccuracies. ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	496,327
1712.07242	Linear Time Clustering for High Dimensional Mixtures of Gaussian Clouds	Clustering mixtures of Gaussian distributions is a fundamental and challenging problem that is ubiquitous in various high-dimensional data processing tasks. While state-of-the-art work on learning Gaussian mixture models has focused primarily on improving separation bounds and their generalization to arbitrary classes ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	87,017
2311.03757	Manifold learning: what, how, and why	Manifold learning (ML), known also as non-linear dimension reduction, is a set of methods to find the low dimensional structure of data. Dimension reduction for large, high dimensional data is not merely a way to reduce the data; the new representations and descriptors obtained by ML reveal the geometric shape of high ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	405,983
1401.3985	Engineering the Hardware/Software Interface for Robotic Platforms - A Comparison of Applied Model Checking with Prolog and Alloy	Robotic platforms serve different use cases ranging from experiments for prototyping assistive applications up to embedded systems for realizing cyber-physical systems in various domains. We are using 1:10 scale miniature vehicles as a robotic platform to conduct research in the domain of self-driving cars and collabor...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	30,027
2306.00824	Zero and Few-shot Semantic Parsing with Ambiguous Inputs	Despite the frequent challenges posed by ambiguity when representing meaning via natural language, it is often ignored or deliberately removed in tasks mapping language to formally-designed representations, which generally assume a one-to-one mapping between linguistic and formal representations. We attempt to address ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	370,177

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