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
1106.0224	Reasoning about Minimal Belief and Negation as Failure	We investigate the problem of reasoning in the propositional fragment of MBNF, the logic of minimal belief and negation as failure introduced by Lifschitz, which can be considered as a unifying framework for several nonmonotonic formalisms, including default logic, autoepistemic logic, circumscription, epistemic querie...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	10,638
1604.07224	The Manifold Particle Filter for State Estimation on High-dimensional Implicit Manifolds	We estimate the state a noisy robot arm and underactuated hand using an Implicit Manifold Particle Filter (MPF) informed by touch sensors. As the robot touches the world, its state space collapses to a contact manifold that we represent implicitly using a signed distance field. This allows us to extend the MPF to highe...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	55,063
2311.17320	Revisiting Single Image Reflection Removal In the Wild	This research focuses on the issue of single-image reflection removal (SIRR) in real-world conditions, examining it from two angles: the collection pipeline of real reflection pairs and the perception of real reflection locations. We devise an advanced reflection collection pipeline that is highly adaptable to a wide r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	411,249
2206.04967	Deep Learning-based Massive MIMO CSI Acquisition for 5G Evolution and 6G	Recently, inspired by successful applications in many fields, deep learning (DL) technologies for CSI acquisition have received considerable research interest from both academia and industry. Considering the practical feedback mechanism of 5th generation (5G) New radio (NR) networks, we propose two implementation schem...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	301,841
2302.05803	TPE-Net: Track Point Extraction and Association Network for Rail Path Proposal Generation	One essential feature of an autonomous train is minimizing collision risks with third-party objects. To estimate the risk, the control system must identify topological information of all the rail routes ahead on which the train can possibly move, especially within merging or diverging rails. This way, the train can fig...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	345,173
2103.12857	Embracing the Disharmony in Medical Imaging: A Simple and Effective Framework for Domain Adaptation	Domain shift, the mismatch between training and testing data characteristics, causes significant degradation in the predictive performance in multi-source imaging scenarios. In medical imaging, the heterogeneity of population, scanners and acquisition protocols at different sites presents a significant domain shift cha...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	226,301
2403.06070	Reframe Anything: LLM Agent for Open World Video Reframing	The proliferation of mobile devices and social media has revolutionized content dissemination, with short-form video becoming increasingly prevalent. This shift has introduced the challenge of video reframing to fit various screen aspect ratios, a process that highlights the most compelling parts of a video. Traditiona...	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	436,282
2301.01482	Underwater Object Tracker: UOSTrack for Marine Organism Grasping of Underwater Vehicles	A visual single-object tracker is an indispensable component of underwater vehicles (UVs) in marine organism grasping tasks. Its accuracy and stability are imperative to guide the UVs to perform grasping behavior. Although single-object trackers show competitive performance in the challenge of underwater image degradat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	339,252
2310.19626	Transformation vs Tradition: Artificial General Intelligence (AGI) for Arts and Humanities	Recent advances in artificial general intelligence (AGI), particularly large language models and creative image generation systems have demonstrated impressive capabilities on diverse tasks spanning the arts and humanities. However, the swift evolution of AGI has also raised critical questions about its responsible dep...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	404,060
1907.03960	Learning from Thresholds: Fully Automated Classification of Tumor Infiltrating Lymphocytes for Multiple Cancer Types	Deep learning classifiers for characterization of whole slide tissue morphology require large volumes of annotated data to learn variations across different tissue and cancer types. As is well known, manual generation of digital pathology training data is time consuming and expensive. In this paper, we propose a semi-a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	137,980
2208.02246	AdaCat: Adaptive Categorical Discretization for Autoregressive Models	Autoregressive generative models can estimate complex continuous data distributions, like trajectory rollouts in an RL environment, image intensities, and audio. Most state-of-the-art models discretize continuous data into several bins and use categorical distributions over the bins to approximate the continuous data d...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	311,416
2007.07085	Semi-supervised Collaborative Filtering by Text-enhanced Domain Adaptation	Data sparsity is an inherent challenge in the recommender systems, where most of the data is collected from the implicit feedbacks of users. This causes two difficulties in designing effective algorithms: first, the majority of users only have a few interactions with the system and there is no enough data for learning;...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	187,223
2408.15710	Conan-embedding: General Text Embedding with More and Better Negative Samples	With the growing popularity of RAG, the capabilities of embedding models are gaining increasing attention. Embedding models are primarily trained through contrastive loss learning, with negative examples being a key component. Previous work has proposed various hard negative mining strategies, but these strategies are ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	484,046
2407.08641	How more data can hurt: Instability and regularization in next-generation reservoir computing	It has been found recently that more data can, counter-intuitively, hurt the performance of deep neural networks. Here, we show that a more extreme version of the phenomenon occurs in data-driven models of dynamical systems. To elucidate the underlying mechanism, we focus on next-generation reservoir computing (NGRC) -...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	472,243
2010.09256	Diffusion in large networks	We investigate the phenomenon of diffusion in a countably infinite society of individuals interacting with their neighbors in a network. At a given time, each individual is either active or inactive. The diffusion is driven by two characteristics: the network structure and the diffusion mechanism represented by an aggr...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	201,466
2206.00850	Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LT$^2$LR-Net)	While low-rank matrix prior has been exploited in dynamic MR image reconstruction and has obtained satisfying performance, tensor low-rank models have recently emerged as powerful alternative representations for three-dimensional dynamic MR datasets. In this paper, we introduce a novel deep unrolling network for dynami...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	300,282
2406.16109	X-ray2CTPA: Generating 3D CTPA scans from 2D X-ray conditioning	Chest X-rays or chest radiography (CXR), commonly used for medical diagnostics, typically enables limited imaging compared to computed tomography (CT) scans, which offer more detailed and accurate three-dimensional data, particularly contrast-enhanced scans like CT Pulmonary Angiography (CTPA). However, CT scans entail...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	467,002
2406.12478	Accelerating Depthwise Separable Convolutions on Ultra-Low-Power Devices	Depthwise separable convolutions are a fundamental component in efficient Deep Neural Networks, as they reduce the number of parameters and operations compared to traditional convolutions while maintaining comparable accuracy. However, their low data reuse opportunities make deploying them notoriously difficult. In thi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	465,432
2011.04286	Simultaneous Data Communication and Channel Estimation in Multi-User Full Duplex MIMO Systems	In this paper, we study Simultaneous Communication of Data and Control (SCDC) information signals in Full Duplex (FD) Multiple-Input Multiple-Output (MIMO) wireless systems. In particular, considering an FD MIMO base station serving multiple single-antenna FD users, a novel multi-user communication scheme for simultane...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	205,538
2011.00515	On Signal-to-Noise Ratio Issues in Variational Inference for Deep Gaussian Processes	We show that the gradient estimates used in training Deep Gaussian Processes (DGPs) with importance-weighted variational inference are susceptible to signal-to-noise ratio (SNR) issues. Specifically, we show both theoretically and via an extensive empirical evaluation that the SNR of the gradient estimates for the late...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	204,249
2006.02876	Enhanced back-translation for low resource neural machine translation using self-training	Improving neural machine translation (NMT) models using the back-translations of the monolingual target data (synthetic parallel data) is currently the state-of-the-art approach for training improved translation systems. The quality of the backward system - which is trained on the available parallel data and used for t...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	180,160
2205.03143	How to Minimize the Weighted Sum AoI in Multi-Source Status Update Systems: OMA or NOMA?	In this paper, the minimization of the weighted sum average age of information (AoI) in a multi-source status update communication system is studied. Multiple independent sources send update packets to a common destination node in a time-slotted manner under the limit of maximum retransmission rounds. Different multipl...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	295,182
2309.01380	Understanding Video Scenes through Text: Insights from Text-based Video Question Answering	Researchers have extensively studied the field of vision and language, discovering that both visual and textual content is crucial for understanding scenes effectively. Particularly, comprehending text in videos holds great significance, requiring both scene text understanding and temporal reasoning. This paper focuses...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,666
1903.02120	Decoders Matter for Semantic Segmentation: Data-Dependent Decoding Enables Flexible Feature Aggregation	Recent semantic segmentation methods exploit encoder-decoder architectures to produce the desired pixel-wise segmentation prediction. The last layer of the decoders is typically a bilinear upsampling procedure to recover the final pixel-wise prediction. We empirically show that this oversimple and data-independent bili...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,425
2405.05945	Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers	Sora unveils the potential of scaling Diffusion Transformer for generating photorealistic images and videos at arbitrary resolutions, aspect ratios, and durations, yet it still lacks sufficient implementation details. In this technical report, we introduce the Lumina-T2X family - a series of Flow-based Large Diffusion ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,116
1708.05582	Agree to Disagree: Improving Disagreement Detection with Dual GRUs	This paper presents models for detecting agreement/disagreement in online discussions. In this work we show that by using a Siamese inspired architecture to encode the discussions, we no longer need to rely on hand-crafted features to exploit the meta thread structure. We evaluate our model on existing online discussio...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	79,164
1202.6404	Signal Shaping for BICM at Low SNR	The mutual information of bit-interleaved coded modulation (BICM) systems, sometimes called the BICM capacity, is investigated at low signal-to-noise ratio (SNR), i.e., in the wideband regime. A new linear transform that depends on bits' probabilities is introduced. This transform is used to prove the asymptotical equi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	14,633
2006.02689	Solving Hard AI Planning Instances Using Curriculum-Driven Deep Reinforcement Learning	Despite significant progress in general AI planning, certain domains remain out of reach of current AI planning systems. Sokoban is a PSPACE-complete planning task and represents one of the hardest domains for current AI planners. Even domain-specific specialized search methods fail quickly due to the exponential searc...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	180,116
2305.20018	Scalable Learning of Latent Language Structure With Logical Offline Cycle Consistency	We introduce Logical Offline Cycle Consistency Optimization (LOCCO), a scalable, semi-supervised method for training a neural semantic parser. Conceptually, LOCCO can be viewed as a form of self-learning where the semantic parser being trained is used to generate annotations for unlabeled text that are then used as new...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	369,775
2105.07086	Divergence Estimation in Message Passing algorithms	Many modern imaging applications can be modeled as compressed sensing linear inverse problems. When the measurement operator involved in the inverse problem is sufficiently random, denoising Scalable Message Passing (SMP) algorithms have a potential to demonstrate high efficiency in recovering compressed data. One of t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	235,311
2203.12057	Cat-inspired Gaits for A Tilt-rotor -- from Symmetrical to Asymmetrical	Among the tilt-rotors (quadrotors) developed in the last decades, Rylls model with eight inputs (four magnitudes of the thrusts and four tilting angles) attracted great attention. Typical feedback linearization maneuvers all the eight inputs with a united control rule to stabilize this tilt-rotor. Instead of assigning ...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	287,120
1909.10307	Human Synthesis and Scene Compositing	Generating good quality and geometrically plausible synthetic images of humans with the ability to control appearance, pose and shape parameters, has become increasingly important for a variety of tasks ranging from photo editing, fashion virtual try-on, to special effects and image compression. In this paper, we propo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	146,511
1705.05637	Text-based Adventures of the Golovin AI Agent	The domain of text-based adventure games has been recently established as a new challenge of creating the agent that is both able to understand natural language, and acts intelligently in text-described environments. In this paper, we present our approach to tackle the problem. Our agent, named Golovin, takes advanta...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	73,527
1903.12344	Learning Good Representation via Continuous Attention	In this paper we present our scientific discovery that good representation can be learned via continuous attention during the interaction between Unsupervised Learning(UL) and Reinforcement Learning(RL) modules driven by intrinsic motivation. Specifically, we designed intrinsic rewards generated from UL modules for dri...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	125,702
2001.00942	Simple explanation of Landauer's bound and its ineffectiveness for multivalued logic	We discuss, using recent results on the Landauer's bound in multivalued logic, the difficulties and pitfalls of how to apply this principle. The presentation is based on Szilard's version of Maxwell's demon experiment and use of equilibrium Thermodynamics. Different versions of thermodynamical/mechanical memory are pre...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	159,359
2109.09267	Intelligent Reflecting Surfaces and Classical Relays: Coexistence and Co-Design	This paper investigates a multiuser downlink communication system with coexisting intelligent reflecting surface (IRS) and classical half-duplex decode-and-forward (DF) relay. In this system, the IRS and the DF relay interact with each other and assist transmission simultaneously. In particular, active beamforming at t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	256,216
2202.06022	Fun Selfie Filters in Face Recognition: Impact Assessment and Removal	This work investigates the impact of fun selfie filters, which are frequently used to modify selfies, on face recognition systems. Based on a qualitative assessment and classification of freely available mobile applications, ten relevant fun selfie filters are selected to create a database. To this end, the selected fi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	280,064
2302.06810	Learning from Noisy Labels with Decoupled Meta Label Purifier	Training deep neural networks(DNN) with noisy labels is challenging since DNN can easily memorize inaccurate labels, leading to poor generalization ability. Recently, the meta-learning based label correction strategy is widely adopted to tackle this problem via identifying and correcting potential noisy labels with the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	345,535
2006.06885	Uncovering the Folding Landscape of RNA Secondary Structure with Deep Graph Embeddings	Biomolecular graph analysis has recently gained much attention in the emerging field of geometric deep learning. Here we focus on organizing biomolecular graphs in ways that expose meaningful relations and variations between them. We propose a geometric scattering autoencoder (GSAE) network for learning such graph embe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,593
1512.02005	Three Tier Network Architecture to mitigate DDoS Attacks on Hybrid Cloud Environments	Connecting the wired and wireless networks particularly the Mobile ad hoc Network is interesting in real world situations due to its usefulness and practicality. Different mechanisms have been proposed to integrate MANETs and the Internet. These strategies differ in gateway discovery mechanism, cell switching criteria,...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	true	49,892
2105.06092	Voltage Regulation Support Along a Distribution Line by a Virtual Power Plant Based on a Center of Mass Load Modeling	A voltage regulation method for slow voltage variations at distribution level is proposed, based on a view of the loads, generators and storage along a distribution line as point weights. The "centers of mass" of the absorbed and injected currents (loads & generation, respectively) are compensated by minimizing the dis...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	235,020
2302.06006	Slepian Scale-Discretised Wavelets on Manifolds	Inspired by recent interest in geometric deep learning, this work generalises the recently developed Slepian scale-discretised wavelets on the sphere to Riemannian manifolds. Through the sifting convolution, one may define translations and, thus, convolutions on manifolds - which are otherwise not well-defined in gener...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	345,252
2411.03535	The Differentiable Feasibility Pump	Although nearly 20 years have passed since its conception, the feasibility pump algorithm remains a widely used heuristic to find feasible primal solutions to mixed-integer linear problems. Many extensions of the initial algorithm have been proposed. Yet, its core algorithm remains centered around two key steps: solvin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	505,935
2102.08201	Improper Reinforcement Learning with Gradient-based Policy Optimization	We consider an improper reinforcement learning setting where a learner is given $M$ base controllers for an unknown Markov decision process, and wishes to combine them optimally to produce a potentially new controller that can outperform each of the base ones. This can be useful in tuning across controllers, learnt pos...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	220,375
1910.12027	Consistency Regularization for Generative Adversarial Networks	Generative Adversarial Networks (GANs) are known to be difficult to train, despite considerable research effort. Several regularization techniques for stabilizing training have been proposed, but they introduce non-trivial computational overheads and interact poorly with existing techniques like spectral normalization....	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	150,943
1907.00686	Sparse regular variation	Regular variation provides a convenient theoretical framework to study large events. In the multivariate setting, the dependence structure of the positive extremes is characterized by a measure - the spectral measure - defined on the positive orthant of the unit sphere. This measure gathers information on the localizat...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	137,116
2107.14658	Task 1A DCASE 2021: Acoustic Scene Classification with mismatch-devices using squeeze-excitation technique and low-complexity constraint	Acoustic scene classification (ASC) is one of the most popular problems in the field of machine listening. The objective of this problem is to classify an audio clip into one of the predefined scenes using only the audio data. This problem has considerably progressed over the years in the different editions of DCASE. I...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,535
1909.08112	Spherical View Synthesis for Self-Supervised 360 Depth Estimation	Learning based approaches for depth perception are limited by the availability of clean training data. This has led to the utilization of view synthesis as an indirect objective for learning depth estimation using efficient data acquisition procedures. Nonetheless, most research focuses on pinhole based monocular visio...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	145,871
2408.00695	Accelerating Full Waveform Inversion By Transfer Learning	Full waveform inversion (FWI) is a powerful tool for reconstructing material fields based on sparsely measured data obtained by wave propagation. For specific problems, discretizing the material field with a neural network (NN) improves the robustness and reconstruction quality of the corresponding optimization problem...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	477,936
cs/0703134	Automatic Generation of Benchmarks for Plagiarism Detection Tools using Grammatical Evolution	This paper has been withdrawn by the authors due to a major rewriting.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	540,268
1402.1270	Vers une interface pour l enrichissement des requetes en arabe dans un systeme de recherche d information	This presentation focuses on the automatic expansion of Arabic request using morphological analyzer and Arabic Wordnet. The expanded request is sent to Google.	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	30,653
2502.10725	PropNet: a White-Box and Human-Like Network for Sentence Representation	Transformer-based embedding methods have dominated the field of sentence representation in recent years. Although they have achieved remarkable performance on NLP missions, such as semantic textual similarity (STS) tasks, their black-box nature and large-data-driven training style have raised concerns, including issues...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	534,024
2402.13804	Reconfigurable Intelligent Surfaces for THz: Hardware Impairments and Switching Technologies	The demand for unprecedented performance in the upcoming 6G wireless networks is fomenting the research on THz communications empowered by Reconfigurable Inteligent Surfaces (RISs). A wide range of use cases have been proposed, most of them, assuming high-level RIS models that overlook some of the hardware impairments ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	431,419
2207.10409	Sequence Models for Drone vs Bird Classification	Drone detection has become an essential task in object detection as drone costs have decreased and drone technology has improved. It is, however, difficult to detect distant drones when there is weak contrast, long range, and low visibility. In this work, we propose several sequence classification architectures to redu...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	309,257
2403.05788	On the Benefits of Fine-Grained Loss Truncation: A Case Study on Factuality in Summarization	Text summarization and simplification are among the most widely used applications of AI. However, models developed for such tasks are often prone to hallucination, which can result from training on unaligned data. One efficient approach to address this issue is Loss Truncation (LT) (Kang and Hashimoto, 2020), an approa...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	436,156
2308.14484	Multimodal Detection of Bots on X (Twitter) using Transformers	Although not all bots are malicious, the vast majority of them are responsible for spreading misinformation and manipulating the public opinion about several issues, i.e., elections and many more. Therefore, the early detection of bots is crucial. Although there have been proposed methods for detecting bots in social m...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	388,348
1904.02817	Unsupervised Domain Adaptation of Contextualized Embeddings for Sequence Labeling	Contextualized word embeddings such as ELMo and BERT provide a foundation for strong performance across a wide range of natural language processing tasks by pretraining on large corpora of unlabeled text. However, the applicability of this approach is unknown when the target domain varies substantially from the pretrai...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	126,534
2404.10419	MAD Speech: Measures of Acoustic Diversity of Speech	Generative spoken language models produce speech in a wide range of voices, prosody, and recording conditions, seemingly approaching the diversity of natural speech. However, the extent to which generated speech is acoustically diverse remains unclear due to a lack of appropriate metrics. We address this gap by develop...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	447,095
cs/0411011	Capacity Analysis for Continuous Alphabet Channels with Side Information, Part I: A General Framework	Capacity analysis for channels with side information at the receiver has been an active area of interest. This problem is well investigated for the case of finite alphabet channels. However, the results are not easily generalizable to the case of continuous alphabet channels due to analytic difficulties inherent with c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	538,387
1710.09485	Signed Network Modeling Based on Structural Balance Theory	The modeling of networks, specifically generative models, have been shown to provide a plethora of information about the underlying network structures, as well as many other benefits behind their construction. Recently there has been a considerable increase in interest for the better understanding and modeling of netwo...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	83,211
2406.19272	Stochastic Concept Bottleneck Models	Concept Bottleneck Models (CBMs) have emerged as a promising interpretable method whose final prediction is based on intermediate, human-understandable concepts rather than the raw input. Through time-consuming manual interventions, a user can correct wrongly predicted concept values to enhance the model's downstream p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	468,361
2403.20085	OmniNxt: A Fully Open-source and Compact Aerial Robot with Omnidirectional Visual Perception	Adopting omnidirectional Field of View (FoV) cameras in aerial robots vastly improves perception ability, significantly advancing aerial robotics's capabilities in inspection, reconstruction, and rescue tasks. However, such sensors also elevate system complexity, e.g., hardware design, and corresponding algorithm, whic...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	442,602
2407.21174	AI Safety in Practice: Enhancing Adversarial Robustness in Multimodal Image Captioning	Multimodal machine learning models that combine visual and textual data are increasingly being deployed in critical applications, raising significant safety and security concerns due to their vulnerability to adversarial attacks. This paper presents an effective strategy to enhance the robustness of multimodal image ca...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	477,432
2001.01168	Facial Action Unit Detection via Adaptive Attention and Relation	Facial action unit (AU) detection is challenging due to the difficulty in capturing correlated information from subtle and dynamic AUs. Existing methods often resort to the localization of correlated regions of AUs, in which predefining local AU attentions by correlated facial landmarks often discards essential parts, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	159,423
2006.02244	SimPool: Towards Topology Based Graph Pooling with Structural Similarity Features	Deep learning methods for graphs have seen rapid progress in recent years with much focus awarded to generalising Convolutional Neural Networks (CNN) to graph data. CNNs are typically realised by alternating convolutional and pooling layers where the pooling layers subsample the grid and exchange spatial or temporal re...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	179,992
1301.2275	Causes and Explanations: A Structural-Model Approach --- Part 1: Causes	We propose a new definition of actual causes, using structural equations to model counterfactuals.We show that the definitions yield a plausible and elegant account ofcausation that handles well examples which have caused problems forother definitions and resolves major difficulties in the traditionalaccount. In a comp...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	20,951
2006.04105	Kafka-ML: connecting the data stream with ML/AI frameworks	Machine Learning (ML) and Artificial Intelligence (AI) have a dependency on data sources to train, improve and make predictions through their algorithms. With the digital revolution and current paradigms like the Internet of Things, this information is turning from static data into continuous data streams. However, mos...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	180,564
2306.03072	Explore to Generalize in Zero-Shot RL	We study zero-shot generalization in reinforcement learning-optimizing a policy on a set of training tasks to perform well on a similar but unseen test task. To mitigate overfitting, previous work explored different notions of invariance to the task. However, on problems such as the ProcGen Maze, an adequate solution t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	371,178
2009.11440	Graph-Based Intrusion Detection System for Controller Area Networks	The controller area network (CAN) is the most widely used intra-vehicular communication network in the automotive industry. Because of its simplicity in design, it lacks most of the requirements needed for a security-proven communication protocol. However, a safe and secured environment is imperative for autonomous as ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	197,170
1908.03632	Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants	Voice-enabled interactions provide more human-like experiences in many popular IoT systems. Cloud-based speech analysis services extract useful information from voice input using speech recognition techniques. The voice signal is a rich resource that discloses several possible states of a speaker, such as emotional sta...	false	false	true	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	141,280
2203.03962	Generative Cooperative Learning for Unsupervised Video Anomaly Detection	Video anomaly detection is well investigated in weakly-supervised and one-class classification (OCC) settings. However, unsupervised video anomaly detection methods are quite sparse, likely because anomalies are less frequent in occurrence and usually not well-defined, which when coupled with the absence of ground trut...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	284,293
2108.13637	When are Deep Networks really better than Decision Forests at small sample sizes, and how?	Deep networks and decision forests (such as random forests and gradient boosted trees) are the leading machine learning methods for structured and tabular data, respectively. Many papers have empirically compared large numbers of classifiers on one or two different domains (e.g., on 100 different tabular data settings)...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	252,856
2407.17412	(PASS) Visual Prompt Locates Good Structure Sparsity through a Recurrent HyperNetwork	Large-scale neural networks have demonstrated remarkable performance in different domains like vision and language processing, although at the cost of massive computation resources. As illustrated by compression literature, structural model pruning is a prominent algorithm to encourage model efficiency, thanks to its a...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	475,958
2212.02251	Multiscale Graph Neural Networks for Protein Residue Contact Map Prediction	Machine learning (ML) is revolutionizing protein structural analysis, including an important subproblem of predicting protein residue contact maps, i.e., which amino-acid residues are in close spatial proximity given the amino-acid sequence of a protein. Despite recent progresses in ML-based protein contact prediction,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	334,738
2112.11602	Causal Inference Despite Limited Global Confounding via Mixture Models	A Bayesian Network is a directed acyclic graph (DAG) on a set of $n$ random variables (the vertices); a Bayesian Network Distribution (BND) is a probability distribution on the random variables that is Markovian on the graph. A finite $k$-mixture of such models is graphically represented by a larger graph which has an ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	272,743
2206.07745	When to intervene? Prescriptive Process Monitoring Under Uncertainty and Resource Constraints	Prescriptive process monitoring approaches leverage historical data to prescribe runtime interventions that will likely prevent negative case outcomes or improve a process's performance. A centerpiece of a prescriptive process monitoring method is its intervention policy: a decision function determining if and when to ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	302,865
2410.06424	Restructuring Vector Quantization with the Rotation Trick	Vector Quantized Variational AutoEncoders (VQ-VAEs) are designed to compress a continuous input to a discrete latent space and reconstruct it with minimal distortion. They operate by maintaining a set of vectors -- often referred to as the codebook -- and quantizing each encoder output to the nearest vector in the code...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	496,195
1612.00132	CDVAE: Co-embedding Deep Variational Auto Encoder for Conditional Variational Generation	Problems such as predicting a new shading field (Y) for an image (X) are ambiguous: many very distinct solutions are good. Representing this ambiguity requires building a conditional model P(Y\|X) of the prediction, conditioned on the image. Such a model is difficult to train, because we do not usually have training dat...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	true	64,829
2004.14581	Feedback U-net for Cell Image Segmentation	Human brain is a layered structure, and performs not only a feedforward process from a lower layer to an upper layer but also a feedback process from an upper layer to a lower layer. The layer is a collection of neurons, and neural network is a mathematical model of the function of neurons. Although neural network imit...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	174,942
1805.02919	Learning Short-Cut Connections for Object Counting	Object counting is an important task in computer vision due to its growing demand in applications such as traffic monitoring or surveillance. In this paper, we consider object counting as a learning problem of a joint feature extraction and pixel-wise object density estimation with Convolutional-Deconvolutional network...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	96,950
2309.06192	Improving and Evaluating the Detection of Fragmentation in News Recommendations with the Clustering of News Story Chains	News recommender systems play an increasingly influential role in shaping information access within democratic societies. However, tailoring recommendations to users' specific interests can result in the divergence of information streams. Fragmented access to information poses challenges to the integrity of the public ...	false	false	false	false	false	true	false	false	true	false	false	false	false	true	false	false	false	false	391,342
2104.01027	Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training	Self-supervised learning of speech representations has been a very active research area but most work is focused on a single domain such as read audio books for which there exist large quantities of labeled and unlabeled data. In this paper, we explore more general setups where the domain of the unlabeled data for pre-...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	228,208
2407.05619	AIRA: A Low-cost IR-based Approach Towards Autonomous Precision Drone Landing and NLOS Indoor Navigation	Automatic drone landing is an important step for achieving fully autonomous drones. Although there are many works that leverage GPS, video, wireless signals, and active acoustic sensing to perform precise landing, autonomous drone landing remains an unsolved challenge for palm-sized microdrones that may not be able to ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	471,058
1908.07841	Ranking Viscous Finger Simulations to an Acquired Ground Truth with Topology-aware Matchings	This application paper presents a novel framework based on topological data analysis for the automatic evaluation and ranking of viscous finger simulation runs in an ensemble with respect to a reference acquisition. Individual fingers in a given time-step are associated with critical point pairs in the distance field t...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	142,394
2306.08737	A Networked Multi-Agent System for Mobile Wireless Infrastructure on Demand	Despite the prevalence of wireless connectivity in urban areas around the globe, there remain numerous and diverse situations where connectivity is insufficient or unavailable. To address this, we introduce mobile wireless infrastructure on demand, a system of UAVs that can be rapidly deployed to establish an ad-hoc wi...	false	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	373,519
2106.12417	False perfection in machine prediction: Detecting and assessing circularity problems in machine learning	This paper is an excerpt of an early version of Chapter 2 of the book "Validity, Reliability, and Significance. Empirical Methods for NLP and Data Science", by Stefan Riezler and Michael Hagmann, published in December 2021 by Morgan & Claypool. Please see the book's homepage at https://www.morganclaypoolpublishers.com/...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	242,721
2310.17753	Bin Assignment and Decentralized Path Planning for Multi-Robot Parcel Sorting	At modern warehouses, mobile robots transport packages and drop them into collection bins/chutes based on shipping destinations grouped by, e.g., the ZIP code. System throughput, measured as the number of packages sorted per unit of time, determines the efficiency of the warehouse. This research develops a scalable, hi...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	403,273
1912.12325	ODE-based Deep Network for MRI Reconstruction	Fast data acquisition in Magnetic Resonance Imaging (MRI) is vastly in demand and scan time directly depends on the number of acquired k-space samples. The data-driven methods based on deep neural networks have resulted in promising improvements, compared to the conventional methods, in image reconstruction algorithms....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,818
2401.04749	LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection	Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps). Considering log data of variant domains, retraining the whole network for unknown domains is inefficient in real industrial scenarios. However, previous deep models merely focused on extracting the semantics of l...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	420,531
1312.6410	A Survey on Eye-Gaze Tracking Techniques	Study of eye-movement is being employed in Human Computer Interaction (HCI) research. Eye - gaze tracking is one of the most challenging problems in the area of computer vision. The goal of this paper is to present a review of latest research in this continued growth of remote eye-gaze tracking. This overview includes ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	29,362
2412.00928	A Deep Generative Model for the Design of Synthesizable Ionizable Lipids	Lipid nanoparticles (LNPs) are vital in modern biomedicine, enabling the effective delivery of mRNA for vaccines and therapies by protecting it from rapid degradation. Among the components of LNPs, ionizable lipids play a key role in RNA protection and facilitate its delivery into the cytoplasm. However, designing ioni...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	512,871
2207.01424	On MDS Codes With Galois Hulls of Arbitrary Dimensions	The Galois hulls of linear codes are a generalization of the Euclidean and Hermitian hulls of linear codes. In this paper, we study the Galois hulls of (extended) GRS codes and present several new constructions of MDS codes with Galois hulls of arbitrary dimensions via (extended) GRS codes. Two general methods of const...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	306,172
2303.04548	Estimation of the qualification and behavior of a contributor and aggregation of his answers in a crowdsourcing context	Crowdsourcing is the outsourcing of tasks to a crowd of contributors on a dedicated platform. The crowd on these platforms is very diversified and includes various profiles of contributors which generates data of uneven quality. However, majority voting, which is the aggregating method commonly used in platforms, gives...	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	350,129
2004.14487	Teaching Cameras to Feel: Estimating Tactile Physical Properties of Surfaces From Images	The connection between visual input and tactile sensing is critical for object manipulation tasks such as grasping and pushing. In this work, we introduce the challenging task of estimating a set of tactile physical properties from visual information. We aim to build a model that learns the complex mapping between visu...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	174,898
2106.01972	SOCCER: An Information-Sparse Discourse State Tracking Collection in the Sports Commentary Domain	In the pursuit of natural language understanding, there has been a long standing interest in tracking state changes throughout narratives. Impressive progress has been made in modeling the state of transaction-centric dialogues and procedural texts. However, this problem has been less intensively studied in the realm o...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	238,680
1401.3477	Solving Weighted Constraint Satisfaction Problems with Memetic/Exact Hybrid Algorithms	A weighted constraint satisfaction problem (WCSP) is a constraint satisfaction problem in which preferences among solutions can be expressed. Bucket elimination is a complete technique commonly used to solve this kind of constraint satisfaction problem. When the memory required to apply bucket elimination is too high, ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	29,882
1604.08076	The algebro-geometric study of range maps	Localizing a radiant source is a widespread problem to many scientific and technological research areas. E.g. localization based on range measurements stays at the core of technologies like radar, sonar and wireless sensors networks. In this manuscript we study in depth the model for source localization based on range ...	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	55,162
1605.01478	Modeling Rich Contexts for Sentiment Classification with LSTM	Sentiment analysis on social media data such as tweets and weibo has become a very important and challenging task. Due to the intrinsic properties of such data, tweets are short, noisy, and of divergent topics, and sentiment classification on these data requires to modeling various contexts such as the retweet/reply hi...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	55,486
1607.03260	Modified LLL algorithm with shifted start column	Multiple-input multiple-output (MIMO) systems are playing an important role in the recent wireless communication. The complexity of the different systems models challenge different researches to get a good complexity to performance balance. Lattices Reduction Techniques and Lenstra-Lenstra-Lovasz (LLL) algorithm bring ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	58,480
2410.10247	LOBG:Less Overfitting for Better Generalization in Vision-Language Model	Existing prompt learning methods in Vision-Language Models (VLM) have effectively enhanced the transfer capability of VLM to downstream tasks, but they suffer from a significant decline in generalization due to severe overfitting. To address this issue, we propose a framework named LOBG for vision-language models. Spec...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	497,981

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