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
2408.12134	Machine Learning-based Channel Prediction in Wideband Massive MIMO Systems with Small Overhead for Online Training	Channel prediction compensates for outdated channel state information in multiple-input multiple-output (MIMO) systems. Machine learning (ML) techniques have recently been implemented to design channel predictors by leveraging the temporal correlation of wireless channels. However, most ML-based channel prediction tech...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	482,605
2305.17568	Scalable Primal-Dual Actor-Critic Method for Safe Multi-Agent RL with General Utilities	We investigate safe multi-agent reinforcement learning, where agents seek to collectively maximize an aggregate sum of local objectives while satisfying their own safety constraints. The objective and constraints are described by {\it general utilities}, i.e., nonlinear functions of the long-term state-action occupancy...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	368,655
1805.08168	"You Know What to Do": Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks	Video sharing platforms like YouTube are increasingly targeted by aggression and hate attacks. Prior work has shown how these attacks often take place as a result of "raids," i.e., organized efforts by ad-hoc mobs coordinating from third-party communities. Despite the increasing relevance of this phenomenon, however, o...	false	false	false	true	false	false	false	false	false	false	false	false	true	true	false	false	false	false	98,064
2303.09847	Empowering Young Learners to Explore Blockchain with User-Friendly Tools: A Method Using Google Blockly and NFTs	As blockchain technology continues to gain attention, there is a growing need to make it more accessible to young learners in K-12 education. However, the technical complexity and lack of accessible tools have been identified as significant barriers to adoption. Our paper proposes a new method for empowering NFTs by co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	352,215
2412.04067	Automated Medical Report Generation for ECG Data: Bridging Medical Text and Signal Processing with Deep Learning	Recent advances in deep learning and natural language generation have significantly improved image captioning, enabling automated, human-like descriptions for visual content. In this work, we apply these captioning techniques to generate clinician-like interpretations of ECG data. This study leverages existing ECG data...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	514,241
2107.11712	Efficient inference of interventional distributions	We consider the problem of efficiently inferring interventional distributions in a causal Bayesian network from a finite number of observations. Let $\mathcal{P}$ be a causal model on a set $\mathbf{V}$ of observable variables on a given causal graph $G$. For sets $\mathbf{X},\mathbf{Y}\subseteq \mathbf{V}$, and settin...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	247,667
1911.00153	On hybrid precoder/combiner for downlink mmWave massive MU-MIMO systems	We propose four hybrid combiner/precoder for downlink mmWave massive MU-MIMO systems. The design of a hybrid combiner/precoder is divided in two parts, analog and digital. The system baseband model shows that the signal processed by the mobile station can be interpreted as a received signal in the presence of colored G...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	151,738
1302.5955	Multi-Feedback Successive Interference Cancellation for Multiuser MIMO Systems	In this paper, a low-complexity multiple feedback successive interference cancellation (MF-SIC) strategy is proposed for the uplink of multiuser multiple-input multiple-output (MU-MIMO) systems. In the proposed MF-SIC {algorithm with shadow area constraints (SAC)}, an enhanced interference cancellation is achieved by i...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	22,337
2203.15331	CNN Filter DB: An Empirical Investigation of Trained Convolutional Filters	Currently, many theoretical as well as practically relevant questions towards the transferability and robustness of Convolutional Neural Networks (CNNs) remain unsolved. While ongoing research efforts are engaging these problems from various angles, in most computer vision related cases these approaches can be generali...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	288,350
1104.4249	Robustness and Contagion in the International Financial Network	The recent financial crisis of 2008 and the 2011 indebtedness of Greece highlight the importance of understanding the structure of the global financial network. In this paper we set out to analyze and characterize this network, as captured by the IMF Coordinated Portfolio Investment Survey (CPIS), in two ways. First, t...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	10,068
2410.19258	Not All Heads Matter: A Head-Level KV Cache Compression Method with Integrated Retrieval and Reasoning	Key-Value (KV) caching is a common technique to enhance the computational efficiency of Large Language Models (LLMs), but its memory overhead grows rapidly with input length. Prior work has shown that not all tokens are equally important for text generation, proposing layer-level KV cache compression to selectively ret...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	502,237
2410.14763	Enabling Scalable Evaluation of Bias Patterns in Medical LLMs	Large language models (LLMs) have shown impressive potential in helping with numerous medical challenges. Deploying LLMs in high-stakes applications such as medicine, however, brings in many concerns. One major area of concern relates to biased behaviors of LLMs in medical applications, leading to unfair treatment of i...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	500,201
2310.04929	DISCOVER: Making Vision Networks Interpretable via Competition and Dissection	Modern deep networks are highly complex and their inferential outcome very hard to interpret. This is a serious obstacle to their transparent deployment in safety-critical or bias-aware applications. This work contributes to post-hoc interpretability, and specifically Network Dissection. Our goal is to present a framew...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	397,891
1506.05713	Destructive nodes in multi-agent controllability	In this paper, several necessary and sufficient graphical conditions are derived for the controllability of multi-agent systems by taking advantage of the proposed concept of controllability destructive nodes. A key step of arriving at this result is the establishment of a relationship between topology structures of th...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	44,331
1812.06135	Bias Mitigation Post-processing for Individual and Group Fairness	Whereas previous post-processing approaches for increasing the fairness of predictions of biased classifiers address only group fairness, we propose a method for increasing both individual and group fairness. Our novel framework includes an individual bias detector used to prioritize data samples in a bias mitigation a...	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	116,547
cs/0112005	Universal Model for Paraphrasing -- Using Transformation Based on a Defined Criteria --	This paper describes a universal model for paraphrasing that transforms according to defined criteria. We showed that by using different criteria we could construct different kinds of paraphrasing systems including one for answering questions, one for compressing sentences, one for polishing up, and one for transformin...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	537,467
2203.13457	Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap	Recently, contrastive learning has risen to be a promising approach for large-scale self-supervised learning. However, theoretical understanding of how it works is still unclear. In this paper, we propose a new guarantee on the downstream performance without resorting to the conditional independence assumption that is ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	287,635
1711.00888	Set-to-Set Hashing with Applications in Visual Recognition	Visual data, such as an image or a sequence of video frames, is often naturally represented as a point set. In this paper, we consider the fundamental problem of finding a nearest set from a collection of sets, to a query set. This problem has obvious applications in large-scale visual retrieval and recognition, and al...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	83,793
2501.15106	In-Context Operator Learning for Linear Propagator Models	We study operator learning in the context of linear propagator models for optimal order execution problems with transient price impact \`a la Bouchaud et al. (2004) and Gatheral (2010). Transient price impact persists and decays over time according to some propagator kernel. Specifically, we propose to use In-Context O...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	527,409
1801.04546	Evaluation of Machine Learning Fameworks on Finis Terrae II	Machine Learning (ML) and Deep Learning (DL) are two technologies used to extract representations of the data for a specific purpose. ML algorithms take a set of data as input to generate one or several predictions. To define the final version of one model, usually there is an initial step devoted to train the algorith...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	88,302
2411.06171	SEEKR: Selective Attention-Guided Knowledge Retention for Continual Learning of Large Language Models	Continual learning (CL) is crucial for language models to dynamically adapt to the evolving real-world demands. To mitigate the catastrophic forgetting problem in CL, data replay has been proven a simple and effective strategy, and the subsequent data-replay-based distillation can further enhance the performance. Howev...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	506,995
2104.00201	Graph-Based Intercategory and Intermodality Network for Multilabel Classification and Melanoma Diagnosis of Skin Lesions in Dermoscopy and Clinical Images	The identification of melanoma involves an integrated analysis of skin lesion images acquired using the clinical and dermoscopy modalities. Dermoscopic images provide a detailed view of the subsurface visual structures that supplement the macroscopic clinical images. Melanoma diagnosis is commonly based on the 7-point ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,909
2104.01409	Diff-TTS: A Denoising Diffusion Model for Text-to-Speech	Although neural text-to-speech (TTS) models have attracted a lot of attention and succeeded in generating human-like speech, there is still room for improvements to its naturalness and architectural efficiency. In this work, we propose a novel non-autoregressive TTS model, namely Diff-TTS, which achieves highly natural...	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	228,338
1606.03168	Finding Low-Rank Solutions via Non-Convex Matrix Factorization, Efficiently and Provably	A rank-$r$ matrix $X \in \mathbb{R}^{m \times n}$ can be written as a product $U V^\top$, where $U \in \mathbb{R}^{m \times r}$ and $V \in \mathbb{R}^{n \times r}$. One could exploit this observation in optimization: e.g., consider the minimization of a convex function $f(X)$ over rank-$r$ matrices, where the set of ra...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	57,062
2005.06282	Smart To-Do : Automatic Generation of To-Do Items from Emails	Intelligent features in email service applications aim to increase productivity by helping people organize their folders, compose their emails and respond to pending tasks. In this work, we explore a new application, Smart-To-Do, that helps users with task management over emails. We introduce a new task and dataset for...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	176,968
2402.07095	Does ChatGPT and Whisper Make Humanoid Robots More Relatable?	Humanoid robots are designed to be relatable to humans for applications such as customer support and helpdesk services. However, many such systems, including Softbank's Pepper, fall short because they fail to communicate effectively with humans. The advent of Large Language Models (LLMs) shows the potential to solve th...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	428,565
2309.05239	HAT: Hybrid Attention Transformer for Image Restoration	Transformer-based methods have shown impressive performance in image restoration tasks, such as image super-resolution and denoising. However, we find that these networks can only utilize a limited spatial range of input information through attribution analysis. This implies that the potential of Transformer is still n...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	391,011
2111.14156	Waveform Optimization for Wireless Power Transfer with Power Amplifier and Energy Harvester Non-Linearities	Waveform optimization has recently been shown to be a key technique to boost the efficiency and range of far-field wireless power transfer (WPT). Current research has optimized transmit waveform adaptive to channel state information (CSI) and accounting for energy harvester (EH)'s non-linearity but under the assumption...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	268,508
2210.13732	Evaluating and Optimizing Hearing-Aid Self-Fitting Methods using Population Coverage	Adults with mild-to-moderate hearing loss can use over-the-counter hearing aids to treat their hearing loss at a fraction of traditional hearing care costs. These products incorporate self-fitting methods that allow end-users to configure their hearing aids without the help of an audiologist. A self-fitting method help...	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	326,284
2410.18210	Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks	Recent advancements in Large Language Models (LLMs) have sparked widespread concerns about their safety. Recent work demonstrates that safety alignment of LLMs can be easily removed by fine-tuning with a few adversarially chosen instruction-following examples, i.e., fine-tuning attacks. We take a further step to unders...	false	false	false	false	true	false	true	false	true	false	false	false	true	false	false	false	false	false	501,793
2202.01747	The Met Dataset: Instance-level Recognition for Artworks	This work introduces a dataset for large-scale instance-level recognition in the domain of artworks. The proposed benchmark exhibits a number of different challenges such as large inter-class similarity, long tail distribution, and many classes. We rely on the open access collection of The Met museum to form a large tr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	278,572
2501.04661	Assessing Language Comprehension in Large Language Models Using Construction Grammar	Large Language Models, despite their significant capabilities, are known to fail in surprising and unpredictable ways. Evaluating their true `understanding' of language is particularly challenging due to the extensive web-scale data they are trained on. Therefore, we construct an evaluation to systematically assess nat...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	523,293
1212.2529	On The Delays In Spiking Neural P Systems	In this work we extend and improve the results done in a previous work on simulating Spiking Neural P systems (SNP systems in short) with delays using SNP systems without delays. We simulate the former with the latter over sequential, iteration, join, and split routing. Our results provide constructions so that both sy...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	true	20,323
2004.01572	Worst-Case Sensitivity of DC Optimal Power Flow Problems	In this paper we consider the problem of analyzing the effect a change in the load vector can have on the optimal power generation in a DC power flow model. The methodology is based upon the recently introduced concept of the $\mathcal{OPF}$ operator. It is shown that for general network topologies computing the worst-...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	170,948
1504.00952	Energy-efficient hybrid spintronic-straintronic reconfigurable bit comparator	We propose a reconfigurable bit comparator implemented with a nanowire spin valve whose two contacts are magnetostrictive with bistable magnetization. Reference and input bits are "written" into the magnetization states of the two contacts with electrically generated strain and the spin-valve's resistance is lowered if...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	41,743
2211.12112	Human Evaluation of Text-to-Image Models on a Multi-Task Benchmark	We provide a new multi-task benchmark for evaluating text-to-image models. We perform a human evaluation comparing the most common open-source (Stable Diffusion) and commercial (DALL-E 2) models. Twenty computer science AI graduate students evaluated the two models, on three tasks, at three difficulty levels, across te...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	331,999
1409.0473	Neural Machine Translation by Jointly Learning to Align and Translate	Neural machine translation is a recently proposed approach to machine translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. The models proposed recently for neural ma...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	true	false	false	35,733
0906.4764	A Novel Bid Optimizer for Sponsored Search Auctions based on Cooperative Game Theory	In this paper, we propose a bid optimizer for sponsored keyword search auctions which leads to better retention of advertisers by yielding attractive utilities to the advertisers without decreasing the revenue to the search engine. The bid optimizer is positioned as a key value added tool the search engine provides to ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	3,969
2502.00089	Ensembles of Low-Rank Expert Adapters	The training and fine-tuning of large language models (LLMs) often involve diverse textual data from multiple sources, which poses challenges due to conflicting gradient directions, hindering optimization and specialization. These challenges can undermine model generalization across tasks, resulting in reduced downstre...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	529,214
2406.08909	A Label-Free and Non-Monotonic Metric for Evaluating Denoising in Event Cameras	Event cameras are renowned for their high efficiency due to outputting a sparse, asynchronous stream of events. However, they are plagued by noisy events, especially in low light conditions. Denoising is an essential task for event cameras, but evaluating denoising performance is challenging. Label-dependent denoising ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	463,685
1709.01784	Cross-Domain Image Retrieval with Attention Modeling	With the proliferation of e-commerce websites and the ubiquitousness of smart phones, cross-domain image retrieval using images taken by smart phones as queries to search products on e-commerce websites is emerging as a popular application. One challenge of this task is to locate the attention of both the query and dat...	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	true	80,152
2301.09930	Quadruple-star systems are not always nested triples: a machine learning approach to dynamical stability	The dynamical stability of quadruple-star systems has traditionally been treated as a problem involving two `nested' triples which constitute a quadruple. In this novel study, we employed a machine learning algorithm, the multi-layer perceptron (MLP), to directly classify 2+2 and 3+1 quadruples based on their stability...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,651
2102.11560	SISE-PC: Semi-supervised Image Subsampling for Explainable Pathology	Although automated pathology classification using deep learning (DL) has proved to be predictively efficient, DL methods are found to be data and compute cost intensive. In this work, we aim to reduce DL training costs by pre-training a Resnet feature extractor using SimCLR contrastive loss for latent encoding of OCT i...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	221,468
2309.08464	Differentially Private Average Consensus with Improved Accuracy-Privacy Trade-off	This paper studies the average consensus problem with differential privacy of initial states, for which it is widely recognized that there is a trade-off between the mean-square computation accuracy and privacy level. Considering the trade-off gap between the average consensus algorithm and the centralized averaging ap...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	392,179
1303.1477	Valuation Networks and Conditional Independence	Valuation networks have been proposed as graphical representations of valuation-based systems (VBSs). The VBS framework is able to capture many uncertainty calculi including probability theory, Dempster-Shafer's belief-function theory, Spohn's epistemic belief theory, and Zadeh's possibility theory. In this paper, we s...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	22,692
1603.04981	An Approximate Dynamic Programming Approach to Adversarial Online Learning	We describe an approximate dynamic programming (ADP) approach to compute approximations of the optimal strategies and of the minimal losses that can be guaranteed in discounted repeated games with vector-valued losses. Such games prominently arise in the analysis of regret in repeated decision-making in adversarial env...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	53,311
2310.01164	Segment Any Building	The task of identifying and segmenting buildings within remote sensing imagery has perennially stood at the forefront of scholarly investigations. This manuscript accentuates the potency of harnessing diversified datasets in tandem with cutting-edge representation learning paradigms for building segmentation in such im...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	396,308
1901.11397	Hotels-50K: A Global Hotel Recognition Dataset	Recognizing a hotel from an image of a hotel room is important for human trafficking investigations. Images directly link victims to places and can help verify where victims have been trafficked, and where their traffickers might move them or others in the future. Recognizing the hotel from images is challenging becaus...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	120,243
2005.04097	Delay-aware Resource Allocation in Fog-assisted IoT Networks Through Reinforcement Learning	Fog nodes in the vicinity of IoT devices are promising to provision low latency services by offloading tasks from IoT devices to them. Mobile IoT is composed by mobile IoT devices such as vehicles, wearable devices and smartphones. Owing to the time-varying channel conditions, traffic loads and computing loads, it is c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	176,355
1703.02222	Preliminary Study on Bit-String Modelling of Opinion Formation in Complex Networks	Opinion formation has been gaining increasing research interests recently, and various models have been proposed. These models, however, have their limitations, among which noticeably include (i) it is generally assumed that adjacent nodes holding similar opinions will further reduce their difference in between, while ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	69,518
2104.08404	Wireless Information and Power Transfer for IoT: Pulse Position Modulation, Integrated Receiver, and Experimental Validation	Simultaneous wireless information and power transfer (SWIPT) has emerged as a viable technique to energize and connect low-power autonomous devices and enable future Internet of Things (IoT). A major challenge of SWIPT is the energy consumption of the receiver of such low-power devices. An attractive low-power solution...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	230,780
2404.06700	Scaling Multi-Camera 3D Object Detection through Weak-to-Strong Eliciting	The emergence of Multi-Camera 3D Object Detection (MC3D-Det), facilitated by bird's-eye view (BEV) representation, signifies a notable progression in 3D object detection. Scaling MC3D-Det training effectively accommodates varied camera parameters and urban landscapes, paving the way for the MC3D-Det foundation model. H...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	445,563
1902.07669	ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing	Despite recent advances in natural language processing, many statistical models for processing text perform extremely poorly under domain shift. Processing biomedical and clinical text is a critically important application area of natural language processing, for which there are few robust, practical, publicly availabl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	122,035
1808.00639	Sequence Discriminative Training for Deep Learning based Acoustic Keyword Spotting	Speech recognition is a sequence prediction problem. Besides employing various deep learning approaches for framelevel classification, sequence-level discriminative training has been proved to be indispensable to achieve the state-of-the-art performance in large vocabulary continuous speech recognition (LVCSR). However...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	104,428
1812.01947	Channel Shortening by Large Multiantenna Precoding in OFDM	A channel delay spread larger than the cyclic prefix (CP) creates inter-carrier/symbol interference (ISI/ICI) in orthogonal frequency-division multiplexing (OFDM). Recent interests in low-latency applications have motivated the usage of shorter OFDM symbols where one can either downscale the CP at the cost of interfere...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	115,657
1903.03736	How Effectively Can Indoor Wireless Positioning Relieve Visual Tracking Pains: A Camera-Rao Bound Viewpoint	Visual tracking is fragile in some difficult scenarios, for instance, appearance ambiguity and variation, occlusion can easily degrade most of visual trackers to some extent. In this paper, visual tracking is empowered with wireless positioning to achieve high accuracy while maintaining robustness. Fundamentally differ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	123,805
2304.02410	STRV -- A radiation hard RISC-V microprocessor for high-energy physics applications	While microprocessors are used in various applications, they are precluded from the use in high-energy physics applications due to the harsh radiation present. To overcome this limitation a microprocessor design must withstand high doses of radiation and mitigate radiation induced soft errors. A TMR protection scheme i...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	356,427
2103.02800	Hardware Acceleration of Fully Quantized BERT for Efficient Natural Language Processing	BERT is the most recent Transformer-based model that achieves state-of-the-art performance in various NLP tasks. In this paper, we investigate the hardware acceleration of BERT on FPGA for edge computing. To tackle the issue of huge computational complexity and memory footprint, we propose to fully quantize the BERT (F...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	223,068
1804.04378	Fast Gaussian Process Based Gradient Matching for Parameter Identification in Systems of Nonlinear ODEs	Parameter identification and comparison of dynamical systems is a challenging task in many fields. Bayesian approaches based on Gaussian process regression over time-series data have been successfully applied to infer the parameters of a dynamical system without explicitly solving it. While the benefits in computationa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	94,837
2406.04273	ELFS: Enhancing Label-Free Coreset Selection via Clustering-based Pseudo-Labeling	High-quality human-annotated data is crucial for modern deep learning pipelines, yet the human annotation process is both costly and time-consuming. Given a constrained human labeling budget, selecting an informative and representative data subset for labeling can significantly reduce human annotation effort. Well-perf...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	461,595
2208.02129	SC6D: Symmetry-agnostic and Correspondence-free 6D Object Pose Estimation	This paper presents an efficient symmetry-agnostic and correspondence-free framework, referred to as SC6D, for 6D object pose estimation from a single monocular RGB image. SC6D requires neither the 3D CAD model of the object nor any prior knowledge of the symmetries. The pose estimation is decomposed into three sub-tas...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	311,385
2407.19869	Distances Between Partial Preference Orderings	This paper proposes to establish the distance between partial preference orderings based on two very different approaches. The first approach corresponds to the brute force method based on combinatorics. It generates all possible complete preference orderings compatible with the partial preference orderings and calcula...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	476,963
1301.1395	Extending FO(ID) with Knowledge Producing Definitions: Preliminary Results	Previous research into the relation between ASP and classical logic has identified at least two different ways in which the former extends the latter. First, ASP program typically contain sets of rules that can be naturally interpreted as inductive definitions, and the language FO(ID) has shown that such inductive defi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	20,855
2403.12848	Planner3D: LLM-enhanced graph prior meets 3D indoor scene explicit regularization	Compositional 3D scene synthesis has diverse applications across a spectrum of industries such as robotics, films, and video games, as it closely mirrors the complexity of real-world multi-object environments. Conventional works typically employ shape retrieval based frameworks which naturally suffer from limited shape...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	439,358
1311.1053	Guessing a password over a wireless channel (on the effect of noise non-uniformity)	A string is sent over a noisy channel that erases some of its characters. Knowing the statistical properties of the string's source and which characters were erased, a listener that is equipped with an ability to test the veracity of a string, one string at a time, wishes to fill in the missing pieces. Here we characte...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	28,202
2307.05093	Forward Dynamics Estimation from Data-Driven Inverse Dynamics Learning	In this paper, we propose to estimate the forward dynamics equations of mechanical systems by learning a model of the inverse dynamics and estimating individual dynamics components from it. We revisit the classical formulation of rigid body dynamics in order to extrapolate the physical dynamical components, such as ine...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	378,621
2311.13445	Transfer Attacks and Defenses for Large Language Models on Coding Tasks	Modern large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities for coding tasks including writing and reasoning about code. They improve upon previous neural network models of code, such as code2seq or seq2seq, that already demonstrated competitive results when performing tasks such as ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	409,740
2311.18364	Hubness Reduction Improves Sentence-BERT Semantic Spaces	Semantic representations of text, i.e. representations of natural language which capture meaning by geometry, are essential for areas such as information retrieval and document grouping. High-dimensional trained dense vectors have received much attention in recent years as such representations. We investigate the struc...	false	false	false	true	false	false	true	false	true	false	false	false	false	false	false	false	false	false	411,659
1911.09753	Reinforcing an Image Caption Generator Using Off-Line Human Feedback	Human ratings are currently the most accurate way to assess the quality of an image captioning model, yet most often the only used outcome of an expensive human rating evaluation is a few overall statistics over the evaluation dataset. In this paper, we show that the signal from instance-level human caption ratings can...	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	154,599
2408.05477	Scene123: One Prompt to 3D Scene Generation via Video-Assisted and Consistency-Enhanced MAE	As Artificial Intelligence Generated Content (AIGC) advances, a variety of methods have been developed to generate text, images, videos, and 3D objects from single or multimodal inputs, contributing efforts to emulate human-like cognitive content creation. However, generating realistic large-scale scenes from a single ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	479,806
2201.01800	KUDO Interpreter Assist: Automated Real-time Support for Remote Interpretation	High-quality human interpretation requires linguistic and factual preparation as well as the ability to retrieve information in real-time. This situation becomes particularly relevant in the context of remote simultaneous interpreting (RSI) where time-to-event may be short, posing new challenges to professional interpr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	274,349
1405.0455	Epidemic and Cascading Survivability of Complex Networks	Our society nowadays is governed by complex networks, examples being the power grids, telecommunication networks, biological networks, and social networks. It has become of paramount importance to understand and characterize the dynamic events (e.g. failures) that might happen in these complex networks. For this reason...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	32,766
2310.05401	Entropy-MCMC: Sampling from Flat Basins with Ease	Bayesian deep learning counts on the quality of posterior distribution estimation. However, the posterior of deep neural networks is highly multi-modal in nature, with local modes exhibiting varying generalization performance. Given a practical budget, targeting at the original posterior can lead to suboptimal performa...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	398,138
2411.07015	Leveraging LSTM for Predictive Modeling of Satellite Clock Bias	Satellite clock bias prediction plays a crucial role in enhancing the accuracy of satellite navigation systems. In this paper, we propose an approach utilizing Long Short-Term Memory (LSTM) networks to predict satellite clock bias. We gather data from the PRN 8 satellite of the Galileo and preprocess it to obtain a sin...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	507,353
1501.05992	The Murchison Widefield Array Correlator	The Murchison Widefield Array (MWA) is a Square Kilometre Array (SKA) Precursor. The telescope is located at the Murchison Radio--astronomy Observatory (MRO) in Western Australia (WA). The MWA consists of 4096 dipoles arranged into 128 dual polarisation aperture arrays forming a connected element interferometer that cr...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	39,553
2103.15436	Transformer Tracking	Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the search region. However, the correlation operation itself is a local linear matching process, leading...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	227,203
2402.00623	Bayesian Causal Inference with Gaussian Process Networks	Causal discovery and inference from observational data is an essential problem in statistics posing both modeling and computational challenges. These are typically addressed by imposing strict assumptions on the joint distribution such as linearity. We consider the problem of the Bayesian estimation of the effects of h...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	425,659
2206.08894	Scaling multi-species occupancy models to large citizen science datasets	Citizen science datasets can be very large and promise to improve species distribution modelling, but detection is imperfect, risking bias when fitting models. In particular, observers may not detect species that are actually present. Occupancy models can estimate and correct for this observation process, and multi-spe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	303,342
1912.01411	A New Approach to Pinning Control of Boolean Networks	Boolean networks (BNs) are discrete-time systems where nodes are inter-connected (here we call such connection rule among nodes as network structure), and the dynamics of each gene node is determined by logical functions. In this paper, we propose a new approach on pinning control design for global stabilization of BNs...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	156,078
1708.05868	Outage Performance Analysis of Multicarrier Relay Selection for Cooperative Networks	In this paper, we analyze the outage performance of two multicarrier relay selection schemes, i.e. bulk and per-subcarrier selections, for two-hop orthogonal frequency-division multiplexing (OFDM) systems. To provide a comprehensive analysis, three forwarding protocols: decode-and-forward (DF), fixed-gain (FG) amplify-...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	79,211
2412.20231	How To Think About End-To-End Encryption and AI: Training, Processing, Disclosure, and Consent	End-to-end encryption (E2EE) has become the gold standard for securing communications, bringing strong confidentiality and privacy guarantees to billions of users worldwide. However, the current push towards widespread integration of artificial intelligence (AI) models, including in E2EE systems, raises some serious se...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	521,144
2207.11126	Optimism in Face of a Context: Regret Guarantees for Stochastic Contextual MDP	We present regret minimization algorithms for stochastic contextual MDPs under minimum reachability assumption, using an access to an offline least square regression oracle. We analyze three different settings: where the dynamics is known, where the dynamics is unknown but independent of the context and the most challe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	309,509
0806.1144	GRID-Launcher v.1.0	GRID-launcher-1.0 was built within the VO-Tech framework, as a software interface between the UK-ASTROGRID and a generic GRID infrastructures in order to allow any ASTROGRID user to launch on the GRID computing intensive tasks from the ASTROGRID Workbench or Desktop. Even though of general application, so far the Grid-...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	1,881
cs/0601132	A Study on the Global Convergence Time Complexity of Estimation of Distribution Algorithms	The Estimation of Distribution Algorithm is a new class of population based search methods in that a probabilistic model of individuals is estimated based on the high quality individuals and used to generate the new individuals. In this paper we compute 1) some upper bounds on the number of iterations required for glob...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	539,247
2008.10427	How To Evaluate Your Dialogue System: Probe Tasks as an Alternative for Token-level Evaluation Metrics	Though generative dialogue modeling is widely seen as a language modeling task, the task demands an agent to have a complex natural language understanding of its input text to carry a meaningful interaction with an user. The automatic metrics used evaluate the quality of the generated text as a proxy to the holistic in...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	192,994
2208.06866	HyP$^2$ Loss: Beyond Hypersphere Metric Space for Multi-label Image Retrieval	Image retrieval has become an increasingly appealing technique with broad multimedia application prospects, where deep hashing serves as the dominant branch towards low storage and efficient retrieval. In this paper, we carried out in-depth investigations on metric learning in deep hashing for establishing a powerful m...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	312,849
2303.11860	Online Transformers with Spiking Neurons for Fast Prosthetic Hand Control	Transformers are state-of-the-art networks for most sequence processing tasks. However, the self-attention mechanism often used in Transformers requires large time windows for each computation step and thus makes them less suitable for online signal processing compared to Recurrent Neural Networks (RNNs). In this paper...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	false	353,039
2305.12231	Bi-VLGM : Bi-Level Class-Severity-Aware Vision-Language Graph Matching for Text Guided Medical Image Segmentation	Medical reports with substantial information can be naturally complementary to medical images for computer vision tasks, and the modality gap between vision and language can be solved by vision-language matching (VLM). However, current vision-language models distort the intra-model relation and mainly include class inf...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	365,898
2210.04705	Readability Controllable Biomedical Document Summarization	Different from general documents, it is recognised that the ease with which people can understand a biomedical text is eminently varied, owing to the highly technical nature of biomedical documents and the variance of readers' domain knowledge. However, existing biomedical document summarization systems have paid littl...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	322,554
2305.13713	CALLS: Japanese Empathetic Dialogue Speech Corpus of Complaint Handling and Attentive Listening in Customer Center	We present CALLS, a Japanese speech corpus that considers phone calls in a customer center as a new domain of empathetic spoken dialogue. The existing STUDIES corpus covers only empathetic dialogue between a teacher and student in a school. To extend the application range of empathetic dialogue speech synthesis (EDSS),...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	366,645
2005.10831	Repurpose Open Data to Discover Therapeutics for COVID-19 using Deep Learning	There have been more than 850,000 confirmed cases and over 48,000 deaths from the human coronavirus disease 2019 (COVID-19) pandemic, caused by novel severe acute respiratory syndrome coronavirus (SARS-CoV-2), in the United States alone. However, there are currently no proven effective medications against COVID-19. Dru...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	178,296
1002.2654	Assessment Of The Wind Farm Impact On The Radar	This study shows the means to evaluate the wind farm impact on the radar. It proposes the set of tools, which can be used to realise this objective. The big part of report covers the study of complex pattern propagation factor as the critical issue of the Advanced Propagation Model (APM). Finally, the reader can find h...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	5,695
2406.04472	On the Hardness of Probabilistic Neurosymbolic Learning	The limitations of purely neural learning have sparked an interest in probabilistic neurosymbolic models, which combine neural networks with probabilistic logical reasoning. As these neurosymbolic models are trained with gradient descent, we study the complexity of differentiating probabilistic reasoning. We prove that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	461,693
1904.09664	Deep Hough Voting for 3D Object Detection in Point Clouds	Current 3D object detection methods are heavily influenced by 2D detectors. In order to leverage architectures in 2D detectors, they often convert 3D point clouds to regular grids (i.e., to voxel grids or to bird's eye view images), or rely on detection in 2D images to propose 3D boxes. Few works have attempted to dire...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,447
2408.03195	RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuning	The advent of the "pre-train, prompt" paradigm has recently extended its generalization ability and data efficiency to graph representation learning, following its achievements in Natural Language Processing (NLP). Initial graph prompt tuning approaches tailored specialized prompting functions for Graph Neural Network ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	478,928
2303.01139	RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing	Data management on GPUs has become increasingly relevant due to a tremendous rise in processing power and available GPU memory. Similar to main-memory systems, there is a need for performant GPU-resident index structures to speed up query processing. Unfortunately, mapping indexes efficiently to the highly parallel and...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	348,844
1502.03487	Weakening the Isolation Assumption of Tamper-proof Hardware Tokens	Recent results have shown the usefulness of tamper-proof hardware tokens as a setup assumption for building UC-secure two-party computation protocols, thus providing broad security guarantees and allowing the use of such protocols as buildings blocks in the modular design of complex cryptography protocols. All these wo...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	40,149
2208.07023	Acceleration of Subspace Learning Machine via Particle Swarm Optimization and Parallel Processing	Built upon the decision tree (DT) classification and regression idea, the subspace learning machine (SLM) has been recently proposed to offer higher performance in general classification and regression tasks. Its performance improvement is reached at the expense of higher computational complexity. In this work, we inve...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	312,916
1811.00613	Shifting the Baseline: Single Modality Performance on Visual Navigation & QA	We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research. Where existing work often compares against random or majority class baselines, we argue that unimodal approaches better capture and reflect dataset biases and ther...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	112,138
2401.00900	Detecting the presence of sperm whales echolocation clicks in noisy environments	Sperm whales (Physeter macrocephalus) navigate underwater with a series of impulsive, click-like sounds known as echolocation clicks. These clicks are characterized by a multipulse structure (MPS) that serves as a distinctive pattern. In this work, we use the stability of the MPS as a detection metric for recognizing a...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	419,149

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