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
2408.11469	The Self-Contained Negation Test Set	Several methodologies have recently been proposed to evaluate the ability of Pretrained Language Models (PLMs) to interpret negation. In this article, we build on Gubelmann and Handschuh (2022), which studies the modification of PLMs' predictions as a function of the polarity of inputs, in English. Crucially, this test...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	482,309
2204.00172	A Unified Framework for Domain Adaptive Pose Estimation	While pose estimation is an important computer vision task, it requires expensive annotation and suffers from domain shift. In this paper, we investigate the problem of domain adaptive 2D pose estimation that transfers knowledge learned on a synthetic source domain to a target domain without supervision. While several ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	289,165
2309.03154	Optimal transmission switching and grid reconfiguration for transmission systems via convex relaxations	In this paper, we formulate optimization problems to perform optimal transmission switching (OTS) in order to operate power transmission grids most efficiently. In any given electrical network, several of the transmission lines are generally equipped with switches, circuit breakers, and/or reclosers. The conventional p...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	390,285
1702.05564	The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment	An original dataset for semantic segmentation, Ciona17, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species in a marine environment. Diverse outdoor illumination, a range of object shapes, colour, and severe occlusion p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	68,425
2007.00171	A General Control Framework for Boolean Networks	This paper focuses on proposing a general control framework for large-scale Boolean networks (\texttt{BNs}). Only by the network structure, the concept of structural controllability for \texttt{BNs} is formalized. A necessary and sufficient criterion is derived for the structural controllability of \texttt{BNs}; it can...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	185,032
2006.07841	Classify and Generate Reciprocally: Simultaneous Positive-Unlabelled Learning and Conditional Generation with Extra Data	The scarcity of class-labeled data is a ubiquitous bottleneck in many machine learning problems. While abundant unlabeled data typically exist and provide a potential solution, it is highly challenging to exploit them. In this paper, we address this problem by leveraging Positive-Unlabeled~(PU) classification and the c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	181,972
2206.10075	Counting Varying Density Crowds Through Density Guided Adaptive Selection CNN and Transformer Estimation	In real-world crowd counting applications, the crowd densities in an image vary greatly. When facing density variation, humans tend to locate and count the targets in low-density regions, and reason the number in high-density regions. We observe that CNN focus on the local information correlation using a fixed-size con...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	303,782
1608.02893	Syntactically Informed Text Compression with Recurrent Neural Networks	We present a self-contained system for constructing natural language models for use in text compression. Our system improves upon previous neural network based models by utilizing recent advances in syntactic parsing -- Google's SyntaxNet -- to augment character-level recurrent neural networks. RNNs have proven excepti...	false	false	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	59,613
2406.17119	Accelerating Phase Field Simulations Through a Hybrid Adaptive Fourier Neural Operator with U-Net Backbone	Prolonged contact between a corrosive liquid and metal alloys can cause progressive dealloying. For such liquid-metal dealloying (LMD) process, phase field models have been developed. However, the governing equations often involve coupled non-linear partial differential equations (PDE), which are challenging to solve n...	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	467,428
2308.14654	Joint Multiple Intent Detection and Slot Filling with Supervised Contrastive Learning and Self-Distillation	Multiple intent detection and slot filling are two fundamental and crucial tasks in spoken language understanding. Motivated by the fact that the two tasks are closely related, joint models that can detect intents and extract slots simultaneously are preferred to individual models that perform each task independently. ...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	388,407
2104.02415	Multi-Robot Pickup and Delivery via Distributed Resource Allocation	In this paper, we consider a large-scale instance of the classical Pickup-and-Delivery Vehicle Routing Problem (PDVRP) that must be solved by a network of mobile cooperating robots. Robots must self-coordinate and self-allocate a set of pickup/delivery tasks while minimizing a given cost figure. This results in a large...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	228,713
1906.09088	Meta-Model Framework for Surrogate-Based Parameter Estimation in Dynamical Systems	The central task in modeling complex dynamical systems is parameter estimation. This task involves numerous evaluations of a computationally expensive objective function. Surrogate-based optimization introduces a computationally efficient predictive model that approximates the value of the objective function. The stand...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	136,061
2211.09929	Contrastive Credibility Propagation for Reliable Semi-Supervised Learning	Producing labels for unlabeled data is error-prone, making semi-supervised learning (SSL) troublesome. Often, little is known about when and why an algorithm fails to outperform a supervised baseline. Using benchmark datasets, we craft five common real-world SSL data scenarios: few-label, open-set, noisy-label, and cla...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	331,148
1903.10536	Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach	Cancer is one of the leading cause of death, worldwide. Many believe that genomic data will enable us to better predict the survival time of these patients, which will lead to better, more personalized treatment options and patient care. As standard survival prediction models have a hard time coping with the high-dimen...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	125,292
2308.10401	Model-Free Large-Scale Cloth Spreading With Mobile Manipulation: Initial Feasibility Study	Cloth manipulation is common in domestic and service tasks, and most studies use fixed-base manipulators to manipulate objects whose sizes are relatively small with respect to the manipulators' workspace, such as towels, shirts, and rags. In contrast, manipulation of large-scale cloth, such as bed making and tablecloth...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	386,709
0705.0081	Constructions of q-Ary Constant-Weight Codes	This paper introduces a new combinatorial construction for q-ary constant-weight codes which yields several families of optimal codes and asymptotically optimal codes. The construction reveals intimate connection between q-ary constant-weight codes and sets of pairwise disjoint combinatorial designs of various types.	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	128
1009.0906	Near-Oracle Performance of Greedy Block-Sparse Estimation Techniques from Noisy Measurements	This paper examines the ability of greedy algorithms to estimate a block sparse parameter vector from noisy measurements. In particular, block sparse versions of the orthogonal matching pursuit and thresholding algorithms are analyzed under both adversarial and Gaussian noise models. In the adversarial setting, it is s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,483
2404.18208	ROS 2 on a Chip, Achieving Brain-Like Speeds and Efficiency in Robotic Networking	The Robot Operating System (ROS) pubsub model played a pivotal role in developing sophisticated robotic applications. However, the complexities and real-time demands of modern robotics necessitate more efficient communication solutions that are deterministic and isochronous. This article introduces a groundbreaking app...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	450,168
1106.0346	Entropy-based Classification of 'Retweeting' Activity on Twitter	Twitter is used for a variety of reasons, including information dissemination, marketing, political organizing and to spread propaganda, spamming, promotion, conversations, and so on. Characterizing these activities and categorizing associated user generated content is a challenging task. We present a information-theor...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	10,675
2209.01028	MIMO-ISAC: Performance Analysis and Rate Region Characterization	This article analyzes the performance of sensing and communications (S\&C) achieved by a multiple-input multiple-output downlink integrated S\&C (ISAC) system. Three ISAC scenarios are analyzed, including the sensing-centric design, communications-centric design, and Pareto optimal design. For each scenario, diversity ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	315,760
2102.02155	Polar Codes for Channels with Insertions, Deletions, and Substitutions	This paper presents a coding scheme for an insertion deletion substitution channel. We extend a previous scheme for the deletion channel where polar codes are modified by adding "guard bands" between segments. In the new scheme, each guard band is comprised of a middle segment of '1' symbols, and left and right segment...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	218,340
2312.04825	Weighted Combinatorial Laplacian and its Application to Coverage Repair in Sensor Networks	We define the weighted combinatorial Laplacian operators on a simplicial complex and investigate their spectral properties. Eigenvalues close to zero and the corresponding eigenvectors of them are especially of our interest, and we show that they can detect almost $n$-dimensional holes in the given complex. Real-valued...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	413,846
2310.10274	No Compromise in Solution Quality: Speeding Up Belief-dependent Continuous POMDPs via Adaptive Multilevel Simplification	Continuous POMDPs with general belief-dependent rewards are notoriously difficult to solve online. In this paper, we present a complete provable theory of adaptive multilevel simplification for the setting of a given externally constructed belief tree and MCTS that constructs the belief tree on the fly using an explora...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	400,156
2304.07305	1-D Residual Convolutional Neural Network coupled with Data Augmentation and Regularization for the ICPHM 2023 Data Challenge	In this article, we present our contribution to the ICPHM 2023 Data Challenge on Industrial Systems' Health Monitoring using Vibration Analysis. For the task of classifying sun gear faults in a gearbox, we propose a residual Convolutional Neural Network that operates on raw three-channel time-domain vibration signals. ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	358,302
1011.2809	Multipath Parameter Estimation from OFDM Signals in Mobile Channels	We study multipath parameter estimation from orthogonal frequency division multiplex signals transmitted over doubly dispersive mobile radio channels. We are interested in cases where the transmission is long enough to suffer time selectivity, but short enough such that the time variation can be accurately modeled as d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,210
1102.4873	Weighted Radial Variation for Node Feature Classification	Connections created from a node-edge matrix have been traditionally difficult to visualize and analyze because of the number of flows to be rendered in a limited feature or cartographic space. Because analyzing connectivity patterns is useful for understanding the complex dynamics of human and information flow that con...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	9,338
2501.12703	HEPPO: Hardware-Efficient Proximal Policy Optimization -- A Universal Pipelined Architecture for Generalized Advantage Estimation	This paper introduces HEPPO, an FPGA-based accelerator designed to optimize the Generalized Advantage Estimation (GAE) stage in Proximal Policy Optimization (PPO). Unlike previous approaches that focused on trajectory collection and actor-critic updates, HEPPO addresses GAE's computational demands with a parallel, pipe...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	526,409
2312.13377	SADA: Semantic adversarial unsupervised domain adaptation for Temporal Action Localization	Temporal Action Localization (TAL) is a complex task that poses relevant challenges, particularly when attempting to generalize on new -- unseen -- domains in real-world applications. These scenarios, despite realistic, are often neglected in the literature, exposing these solutions to important performance degradation...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,287
1906.07488	A One-step Pruning-recovery Framework for Acceleration of Convolutional Neural Networks	Acceleration of convolutional neural network has received increasing attention during the past several years. Among various acceleration techniques, filter pruning has its inherent merit by effectively reducing the number of convolution filters. However, most filter pruning methods resort to tedious and time-consuming ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	135,606
1911.02104	Perceived Intensities of Normal and Shear Skin Stimuli using a Wearable Haptic Bracelet	Our aim is to provide effective interaction with virtual objects, despite the lack of co-location of virtual and real-world contacts, while taking advantage of relatively large skin area and ease of mounting on the forearm. We performed two human participant studies to determine the effects of haptic feedback in the no...	true	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	152,276
1908.10198	Robust Tensor Recovery with Fiber Outliers for Traffic Events	Event detection is gaining increasing attention in smart cities research. Large-scale mobility data serves as an important tool to uncover the dynamics of urban transportation systems, and more often than not the dataset is incomplete. In this article, we develop a method to detect extreme events in large traffic datas...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	143,051
2108.00981	PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series	Realistic synthetic time series data of sufficient length enables practical applications in time series modeling tasks, such as forecasting, but remains a challenge. In this paper we present PSA-GAN, a generative adversarial network (GAN) that generates long time series samples of high quality using progressive growing...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,891
2309.02333	Resilient VAE: Unsupervised Anomaly Detection at the SLAC Linac Coherent Light Source	Significant advances in utilizing deep learning for anomaly detection have been made in recent years. However, these methods largely assume the existence of a normal training set (i.e., uncontaminated by anomalies) or even a completely labeled training set. In many complex engineering systems, such as particle accelera...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	390,011
cs/9904003	The Structure of Weighting Coefficient Matrices of Harmonic Differential Quadrature and Its Applications	The structure of weighting coefficient matrices of Harmonic Differential Quadrature (HDQ) is found to be either centrosymmetric or skew centrosymmetric depending on the order of the corresponding derivatives. The properties of both matrices are briefly discussed in this paper. It is noted that the computational effort ...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	540,492
2308.16085	State Estimation over Broadcast and Multi-Access Channels in an Unreliable Regime	This article examines the problem of state estimation over multi-terminal channels in an unreliable regime. More specifically, we consider two canonical settings. In the first setting, measurements of a common stochastic source need to be transmitted to two distinct remote monitors over a packet-erasure broadcast chann...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	388,896
2412.08562	An End-to-End Collaborative Learning Approach for Connected Autonomous Vehicles in Occluded Scenarios	Collaborative navigation becomes essential in situations of occluded scenarios in autonomous driving where independent driving policies are likely to lead to collisions. One promising approach to address this issue is through the use of Vehicle-to-Vehicle (V2V) networks that allow for the sharing of perception informat...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	516,141
1711.03243	Selecting Representative Examples for Program Synthesis	Program synthesis is a class of regression problems where one seeks a solution, in the form of a source-code program, mapping the inputs to their corresponding outputs exactly. Due to its precise and combinatorial nature, program synthesis is commonly formulated as a constraint satisfaction problem, where input-output ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	84,180
1004.1743	An Analytical Study on Behavior of Clusters Using K Means, EM and K* Means Algorithm	Clustering is an unsupervised learning method that constitutes a cornerstone of an intelligent data analysis process. It is used for the exploration of inter-relationships among a collection of patterns, by organizing them into homogeneous clusters. Clustering has been dynamically applied to a variety of tasks in the f...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	6,130
2010.05337	DistDGL: Distributed Graph Neural Network Training for Billion-Scale Graphs	Graph neural networks (GNN) have shown great success in learning from graph-structured data. They are widely used in various applications, such as recommendation, fraud detection, and search. In these domains, the graphs are typically large, containing hundreds of millions of nodes and several billions of edges. To tac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	200,080
2308.12747	An Information-Theoretic Approach for Detecting Edits in AI-Generated Text	We propose a method to determine whether a given article was written entirely by a generative language model or perhaps contains edits by a different author, possibly a human. Our process involves multiple tests for the origin of individual sentences or other pieces of text and combining these tests using a method that...	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	387,663
2310.02246	Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances	Solving a linear system $Ax=b$ is a fundamental scientific computing primitive for which numerous solvers and preconditioners have been developed. These come with parameters whose optimal values depend on the system being solved and are often impossible or too expensive to identify; thus in practice sub-optimal heurist...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	396,766
2008.07560	Modeling of Natural Disasters and Extreme Events in Power System Resilience Enhancement and Evaluation Methods	The frequency of disruptive and newly emerging threats (e.g. man-made attacks--cyber and physical attacks; extreme natural events--hurricanes, earthquakes, and floods) has escalated dramatically in the last decade. Impacts of these events are very severe ranging from long power outage duration, major power system equip...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	192,141
2501.15754	Weight-based Analysis of Detokenization in Language Models: Understanding the First Stage of Inference Without Inference	According to the stages-of-inference hypothesis, early layers of language models map their subword-tokenized input, which does not necessarily correspond to a linguistically meaningful segmentation, to more meaningful representations that form the model's "inner vocabulary". Prior analysis of this detokenization stage ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	527,696
2012.00425	Edge-assisted Democratized Learning Towards Federated Analytics	A recent take towards Federated Analytics (FA), which allows analytical insights of distributed datasets, reuses the Federated Learning (FL) infrastructure to evaluate the summary of model performances across the training devices. However, the current realization of FL adopts single server-multiple client architecture ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	209,133
2012.14672	Tips and Tricks for Webly-Supervised Fine-Grained Recognition: Learning from the WebFG 2020 Challenge	WebFG 2020 is an international challenge hosted by Nanjing University of Science and Technology, University of Edinburgh, Nanjing University, The University of Adelaide, Waseda University, etc. This challenge mainly pays attention to the webly-supervised fine-grained recognition problem. In the literature, existing dee...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	213,579
1709.07114	Cost Adaptation for Robust Decentralized Swarm Behaviour	Decentralized receding horizon control (D-RHC) provides a mechanism for coordination in multi-agent settings without a centralized command center. However, combining a set of different goals, costs, and constraints to form an efficient optimization objective for D-RHC can be difficult. To allay this problem, we use a m...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	81,225
2403.20020	Nonparametric Bellman Mappings for Reinforcement Learning: Application to Robust Adaptive Filtering	This paper designs novel nonparametric Bellman mappings in reproducing kernel Hilbert spaces (RKHSs) for reinforcement learning (RL). The proposed mappings benefit from the rich approximating properties of RKHSs, adopt no assumptions on the statistics of the data owing to their nonparametric nature, require no knowledg...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	442,581
2012.03033	Branching Process with Attack: Viral Competing Markets	The marked increase in advertisements over online social networks (OSNs) necessitates the study of content propagation. We analyse the viral markets with content providers competing for the propagation of similar posts over OSNs. Towards this, we required a new variant of the branching process (BP), which we named as "...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	209,961
1904.08721	Societal Controversies in Wikipedia Articles	Collaborative content creation inevitably reaches situations where different points of view lead to conflict. We focus on Wikipedia, the free encyclopedia anyone may edit, where disputes about content in controversial articles often reflect larger societal debates. While Wikipedia has a public edit history and discussi...	false	false	false	true	false	false	false	false	true	false	false	false	false	true	false	false	false	false	128,161
1906.10155	Machine Learning Phase Transitions with a Quantum Processor	Machine learning has emerged as a promising approach to study the properties of many-body systems. Recently proposed as a tool to classify phases of matter, the approach relies on classical simulation methods$-$such as Monte Carlo$-$which are known to experience an exponential slowdown when simulating certain quantum s...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	136,367
1911.03852	HAWQ-V2: Hessian Aware trace-Weighted Quantization of Neural Networks	Quantization is an effective method for reducing memory footprint and inference time of Neural Networks, e.g., for efficient inference in the cloud, especially at the edge. However, ultra low precision quantization could lead to significant degradation in model generalization. A promising method to address this is to p...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	152,789
1911.01143	Application of Gaussian Process Regression to Koopman Mode Decomposition for Noisy Dynamic Data	Koopman Mode Decomposition (KMD) is a technique of nonlinear time-series analysis that originates from point spectrum of the Koopman operator defined for an underlying nonlinear dynamical system. We present a numerical algorithm of KMD based on Gaussian process regression that is capable of handling noisy finite-time d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	152,024
2108.05523	Fair Decision-Making for Food Inspections	Data and algorithms are essential and complementary parts of a large-scale decision-making process. However, their injudicious use can lead to unforeseen consequences, as has been observed by researchers and activists alike in the recent past. In this paper, we revisit the application of predictive models by the Chicag...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	250,321
2210.00834	Merging Classification Predictions with Sequential Information for Lightweight Visual Place Recognition in Changing Environments	Low-overhead visual place recognition (VPR) is a highly active research topic. Mobile robotics applications often operate under low-end hardware, and even more hardware capable systems can still benefit from freeing up onboard system resources for other navigation tasks. This work addresses lightweight VPR by proposing...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	321,019
1907.06607	Agglomerative Attention	Neural networks using transformer-based architectures have recently demonstrated great power and flexibility in modeling sequences of many types. One of the core components of transformer networks is the attention layer, which allows contextual information to be exchanged among sequence elements. While many of the prev...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,666
2406.08045	A novel approach to graph distinction through GENEOs and permutants	The theory of Group Equivariant Non-Expansive Operators (GENEOs) was initially developed in Topological Data Analysis for the geometric approximation of data observers, including their invariances and symmetries. This paper departs from that line of research and explores the use of GENEOs for distinguishing $r$-regular...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	463,329
2306.01753	Preconditioned Visual Language Inference with Weak Supervision	Humans can infer the affordance of objects by extracting related contextual preconditions for each scenario. For example, upon seeing an image of a broken cup, we can infer that this precondition prevents the cup from being used for drinking. Reasoning with preconditions of commonsense is studied in NLP where the model...	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	false	false	false	370,585
2407.10062	SpikeGS: 3D Gaussian Splatting from Spike Streams with High-Speed Camera Motion	Novel View Synthesis plays a crucial role by generating new 2D renderings from multi-view images of 3D scenes. However, capturing high-speed scenes with conventional cameras often leads to motion blur, hindering the effectiveness of 3D reconstruction. To address this challenge, high-frame-rate dense 3D reconstruction e...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	472,824
2012.09421	Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning	We consider the problem of learning fair policies in (deep) cooperative multi-agent reinforcement learning (MARL). We formalize it in a principled way as the problem of optimizing a welfare function that explicitly encodes two important aspects of fairness: efficiency and equity. As a solution method, we propose a nove...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	212,071
1911.04759	Prediction of Missing Semantic Relations in Lexical-Semantic Network using Random Forest Classifier	This study focuses on the prediction of missing six semantic relations (such as is_a and has_part) between two given nodes in RezoJDM a French lexical-semantic network. The output of this prediction is a set of pairs in which the first entries are semantic relations and the second entries are the probabilities of exist...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	153,074
2406.14066	Optimizing Speculative Decoding for Serving Large Language Models Using Goodput	Reducing the inference latency of large language models (LLMs) is crucial, and speculative decoding (SD) stands out as one of the most effective techniques. Rather than letting the LLM generate all tokens directly, speculative decoding employs effective proxies to predict potential outputs, which are then verified by t...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	466,136
1403.2360	Matching theory for priority-based cell association in the downlink of wireless small cell networks	The deployment of small cells, overlaid on existing cellular infrastructure, is seen as a key feature in next-generation cellular systems. In this paper, the problem of user association in the downlink of small cell networks (SCNs) is considered. The problem is formulated as a many-to-one matching game in which the use...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	31,478
2304.12949	eFAT: Improving the Effectiveness of Fault-Aware Training for Mitigating Permanent Faults in DNN Hardware Accelerators	Fault-Aware Training (FAT) has emerged as a highly effective technique for addressing permanent faults in DNN accelerators, as it offers fault mitigation without significant performance or accuracy loss, specifically at low and moderate fault rates. However, it leads to very high retraining overheads, especially when u...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	360,398
2006.07869	Benchmarking Multi-Agent Deep Reinforcement Learning Algorithms in Cooperative Tasks	Multi-agent deep reinforcement learning (MARL) suffers from a lack of commonly-used evaluation tasks and criteria, making comparisons between approaches difficult. In this work, we provide a systematic evaluation and comparison of three different classes of MARL algorithms (independent learning, centralised multi-agent...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	false	181,984
2412.17109	Similarity Trajectories: Linking Sampling Process to Artifacts in Diffusion-Generated Images	Artifact detection algorithms are crucial to correcting the output generated by diffusion models. However, because of the variety of artifact forms, existing methods require substantial annotated data for training. This requirement limits their scalability and efficiency, which restricts their wide application. This pa...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	519,832
2405.03351	Modality Prompts for Arbitrary Modality Salient Object Detection	This paper delves into the task of arbitrary modality salient object detection (AM SOD), aiming to detect salient objects from arbitrary modalities, eg RGB images, RGB-D images, and RGB-D-T images. A novel modality-adaptive Transformer (MAT) will be proposed to investigate two fundamental challenges of AM SOD, ie more ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	452,151
2410.05982	DeMo: Decoupling Motion Forecasting into Directional Intentions and Dynamic States	Accurate motion forecasting for traffic agents is crucial for ensuring the safety and efficiency of autonomous driving systems in dynamically changing environments. Mainstream methods adopt a one-query-one-trajectory paradigm, where each query corresponds to a unique trajectory for predicting multi-modal trajectories. ...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	495,997
2203.11987	PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers	Vision Transformers (ViTs) are built on the assumption of treating image patches as ``visual tokens" and learn patch-to-patch attention. The patch embedding based tokenizer has a semantic gap with respect to its counterpart, the textual tokenizer. The patch-to-patch attention suffers from the quadratic complexity issue...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	287,102
2406.06455	A Large Language Model Pipeline for Breast Cancer Oncology	Large language models (LLMs) have demonstrated potential in the innovation of many disciplines. However, how they can best be developed for oncology remains underdeveloped. State-of-the-art OpenAI models were fine-tuned on a clinical dataset and clinical guidelines text corpus for two important cancer treatment factors...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	462,583
2106.07387	An SMT Based Compositional Algorithm to Solve a Conflict-Free Electric Vehicle Routing Problem	The Vehicle Routing Problem (VRP) is the combinatorial optimization problem of designing routes for vehicles to visit customers in such a fashion that a cost function, typically the number of vehicles, or the total travelled distance is minimized. The problem finds applications in industrial scenarios, for example wher...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	240,910
0711.1038	Am\'elioration des Performances des Syst\`emes Automatiques de Reconnaissance de la Parole pour la Parole Non Native	In this article, we present an approach for non native automatic speech recognition (ASR). We propose two methods to adapt existing ASR systems to the non-native accents. The first method is based on the modification of acoustic models through integration of acoustic models from the mother tong. The phonemes of the tar...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	875
2107.00769	Enhancing Multi-Robot Perception via Learned Data Association	In this paper, we address the multi-robot collaborative perception problem, specifically in the context of multi-view infilling for distributed semantic segmentation. This setting entails several real-world challenges, especially those relating to unregistered multi-agent image data. Solutions must effectively leverage...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	true	false	false	false	244,262
2209.12309	Feature Encodings for Gradient Boosting with Automunge	Automunge is a tabular preprocessing library that encodes dataframes for supervised learning. When selecting a default feature encoding strategy for gradient boosted learning, one may consider metrics of training duration and achieved predictive performance associated with the feature representations. Automunge offers ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,488
2312.04764	First Attempt at Building Parallel Corpora for Machine Translation of Northeast India's Very Low-Resource Languages	This paper presents the creation of initial bilingual corpora for thirteen very low-resource languages of India, all from Northeast India. It also presents the results of initial translation efforts in these languages. It creates the first-ever parallel corpora for these languages and provides initial benchmark neural ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	413,815
1608.09010	Statistical physics of vaccination	Historically, infectious diseases caused considerable damage to human societies, and they continue to do so today. To help reduce their impact, mathematical models of disease transmission have been studied to help understand disease dynamics and inform prevention strategies. Vaccination - one of the most important prev...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	60,421
2406.11256	Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts	Mixture-of-Experts (MoE) models have shown remarkable capability in instruction tuning, especially when the number of tasks scales. However, previous methods simply merge all training tasks (e.g. creative writing, coding, and mathematics) and apply fixed sampling weights, without considering the importance of different...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	464,801
1702.03812	Reservoir Computing Using Non-Uniform Binary Cellular Automata	The Reservoir Computing (RC) paradigm utilizes a dynamical system, i.e., a reservoir, and a linear classifier, i.e., a read-out layer, to process data from sequential classification tasks. In this paper the usage of Cellular Automata (CA) as a reservoir is investigated. The use of CA in RC has been showing promising re...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	68,186
2203.00461	JOINED : Prior Guided Multi-task Learning for Joint Optic Disc/Cup Segmentation and Fovea Detection	Fundus photography has been routinely used to document the presence and severity of various retinal degenerative diseases such as age-related macula degeneration, glaucoma, and diabetic retinopathy, for which the fovea, optic disc (OD), and optic cup (OC) are important anatomical landmarks. Identification of those anat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	283,009
1506.06343	Mining Mid-level Visual Patterns with Deep CNN Activations	The purpose of mid-level visual element discovery is to find clusters of image patches that are both representative and discriminative. Here we study this problem from the prospective of pattern mining while relying on the recently popularized Convolutional Neural Networks (CNNs). We observe that a fully-connected CNN ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	44,410
1609.00081	All Fingers are not Equal: Intensity of References in Scientific Articles	Research accomplishment is usually measured by considering all citations with equal importance, thus ignoring the wide variety of purposes an article is being cited for. Here, we posit that measuring the intensity of a reference is crucial not only to perceive better understanding of research endeavor, but also to impr...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	60,435
2112.03350	Test-Time Detection of Backdoor Triggers for Poisoned Deep Neural Networks	Backdoor (Trojan) attacks are emerging threats against deep neural networks (DNN). A DNN being attacked will predict to an attacker-desired target class whenever a test sample from any source class is embedded with a backdoor pattern; while correctly classifying clean (attack-free) test samples. Existing backdoor defen...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	270,166
2312.04333	Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers	This paper presents an in-depth analysis of Large Language Models (LLMs), focusing on LLaMA, a prominent open-source foundational model in natural language processing. Instead of assessing LLaMA through its generative output, we design multiple-choice tasks to probe its intrinsic understanding in high-order tasks such ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	413,640
2210.04887	In-Hand Object Rotation via Rapid Motor Adaptation	Generalized in-hand manipulation has long been an unsolved challenge of robotics. As a small step towards this grand goal, we demonstrate how to design and learn a simple adaptive controller to achieve in-hand object rotation using only fingertips. The controller is trained entirely in simulation on only cylindrical ob...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	322,617
2303.11428	Lamarr: LHCb ultra-fast simulation based on machine learning models deployed within Gauss	About 90% of the computing resources available to the LHCb experiment has been spent to produce simulated data samples for Run 2 of the Large Hadron Collider at CERN. The upgraded LHCb detector will be able to collect larger data samples, requiring many more simulated events to analyze the data to be collected in Run 3...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	352,844
2409.14702	Rate-Splitting for Cell-Free Massive MIMO: Performance Analysis and Generative AI Approach	Cell-free (CF) massive multiple-input multipleoutput (MIMO) provides a ubiquitous coverage to user equipments (UEs) but it is also susceptible to interference. Ratesplitting (RS) effectively extracts data by decoding interference, yet its effectiveness is limited by the weakest UE. In this paper, we investigate an RS-b...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	490,591
2105.12457	ReStore -- Neural Data Completion for Relational Databases	Classical approaches for OLAP assume that the data of all tables is complete. However, in case of incomplete tables with missing tuples, classical approaches fail since the result of a SQL aggregate query might significantly differ from the results computed on the full dataset. Today, the only way to deal with missing ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	237,017
2107.01982	The DCU-EPFL Enhanced Dependency Parser at the IWPT 2021 Shared Task	We describe the DCU-EPFL submission to the IWPT 2021 Shared Task on Parsing into Enhanced Universal Dependencies. The task involves parsing Enhanced UD graphs, which are an extension of the basic dependency trees designed to be more facilitative towards representing semantic structure. Evaluation is carried out on 29 t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	244,661
1710.02437	Learning Word Embeddings for Hyponymy with Entailment-Based Distributional Semantics	Lexical entailment, such as hyponymy, is a fundamental issue in the semantics of natural language. This paper proposes distributional semantic models which efficiently learn word embeddings for entailment, using a recently-proposed framework for modelling entailment in a vector-space. These models postulate a latent ve...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	82,171
1907.04483	Copula Representations and Error Surface Projections for the Exclusive Or Problem	The exclusive or (xor) function is one of the simplest examples that illustrate why nonlinear feedforward networks are superior to linear regression for machine learning applications. We review the xor representation and approximation problems and discuss their solutions in terms of probabilistic logic and associative ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	138,119
1705.07877	Block building programming for symbolic regression	Symbolic regression that aims to detect underlying data-driven models has become increasingly important for industrial data analysis. For most existing algorithms such as genetic programming (GP), the convergence speed might be too slow for large-scale problems with a large number of variables. This situation may becom...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	73,912
2002.08679	Neural Network Compression Framework for fast model inference	In this work we present a new framework for neural networks compression with fine-tuning, which we called Neural Network Compression Framework (NNCF). It leverages recent advances of various network compression methods and implements some of them, such as sparsity, quantization, and binarization. These methods allow ge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	164,836
2405.06278	Exploring the Interplay of Interpretability and Robustness in Deep Neural Networks: A Saliency-guided Approach	Adversarial attacks pose a significant challenge to deploying deep learning models in safety-critical applications. Maintaining model robustness while ensuring interpretability is vital for fostering trust and comprehension in these models. This study investigates the impact of Saliency-guided Training (SGT) on model r...	false	false	false	false	false	false	false	false	false	false	false	true	true	false	false	false	false	false	453,239
2408.14008	LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models	The explosive growth of videos on streaming media platforms has underscored the urgent need for effective video quality assessment (VQA) algorithms to monitor and perceptually optimize the quality of streaming videos. However, VQA remains an extremely challenging task due to the diverse video content and the complex sp...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	483,382
2406.04737	Fast-Fading Channel and Power Optimization of the Magnetic Inductive Cellular Network	The cellular network of magnetic Induction (MI) communication holds promise in long-distance underground environments. In the traditional MI communication, there is no fast-fading channel since the MI channel is treated as a quasi-static channel. However, for the vehicle (mobile) MI (VMI) communication, the unpredictab...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	461,817
0910.3275	Degrees of Freedom of Multi-Source Relay Networks	We study a multi-source Gaussian relay network consisting of $K$ source--destination pairs having $K$ unicast sessions. We assume $M$ layers of relays between the sources and the destinations. We find achievable degrees of freedom of the network. Our schemes are based on interference alignment at the transmitters and s...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	4,751
2406.06106	Testably Learning Polynomial Threshold Functions	Rubinfeld & Vasilyan recently introduced the framework of testable learning as an extension of the classical agnostic model. It relaxes distributional assumptions which are difficult to verify by conditions that can be checked efficiently by a tester. The tester has to accept whenever the data truly satisfies the origi...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	462,442
2404.15269	Aligning LLM Agents by Learning Latent Preference from User Edits	We study interactive learning of LLM-based language agents based on user edits made to the agent's output. In a typical setting such as writing assistants, the user interacts with a language agent to generate a response given a context, and may optionally edit the agent response to personalize it based on their latent ...	false	false	false	false	true	true	true	false	true	false	false	false	false	false	false	false	false	false	449,017
2007.07222	Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis	Deep learning based medical image diagnosis has shown great potential in clinical medicine. However, it often suffers two major difficulties in real-world applications: 1) only limited labels are available for model training, due to expensive annotation costs over medical images; 2) labeled images may contain considera...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	187,269
2501.19125	Upper Bounds on the Minimum Distance of Structured LDPC Codes	We investigate the minimum distance of structured binary Low-Density Parity-Check (LDPC) codes whose parity-check matrices are of the form $[\mathbf{C} \vert \mathbf{M}]$ where $\mathbf{C}$ is circulant and of column weight $2$, and $\mathbf{M}$ has fixed column weight $r \geq 3$ and row weight at least $1$. These code...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	529,023
2312.07252	Identifying Drivers of Predictive Aleatoric Uncertainty	Explainability and uncertainty quantification are two pillars of trustable artificial intelligence. However, the reasoning behind uncertainty estimates is generally left unexplained. Identifying the drivers of uncertainty complements explanations of point predictions in recognizing model limitations and enhances trust ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	414,853

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