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
1605.05711	The Information-Collecting Vehicle Routing Problem: Stochastic Optimization for Emergency Storm Response	Utilities face the challenge of responding to power outages due to storms and ice damage, but most power grids are not equipped with sensors to pinpoint the precise location of the faults causing the outage. Instead, utilities have to depend primarily on phone calls (trouble calls) from customers who have lost power to...	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	56,033
2211.03418	A Quantum-Powered Photorealistic Rendering	Achieving photorealistic rendering of real-world scenes poses a significant challenge with diverse applications, including mixed reality and virtual reality. Neural networks, extensively explored in solving differential equations, have previously been introduced as implicit representations for photorealistic rendering....	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	328,925
2205.13671	Transformer for Partial Differential Equations' Operator Learning	Data-driven learning of partial differential equations' solution operators has recently emerged as a promising paradigm for approximating the underlying solutions. The solution operators are usually parameterized by deep learning models that are built upon problem-specific inductive biases. An example is a convolutiona...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	299,029
2303.09455	Learning Cross-lingual Visual Speech Representations	Cross-lingual self-supervised learning has been a growing research topic in the last few years. However, current works only explored the use of audio signals to create representations. In this work, we study cross-lingual self-supervised visual representation learning. We use the recently-proposed Raw Audio-Visual Spee...	false	false	true	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	352,050
1912.10166	MedCAT -- Medical Concept Annotation Tool	Biomedical documents such as Electronic Health Records (EHRs) contain a large amount of information in an unstructured format. The data in EHRs is a hugely valuable resource documenting clinical narratives and decisions, but whilst the text can be easily understood by human doctors it is challenging to use in research ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	158,250
1910.10086	Meta Matrix Factorization for Federated Rating Predictions	Federated recommender systems have distinct advantages in terms of privacy protection over traditional recommender systems that are centralized at a data center. However, previous work on federated recommender systems does not fully consider the limitations of storage, RAM, energy and communication bandwidth in a mobil...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	150,392
2412.16979	A Conditional Diffusion Model for Electrical Impedance Tomography Image Reconstruction	Electrical impedance tomography (EIT) is a non-invasive imaging technique, capable of reconstructing images of the electrical conductivity of tissues and materials. It is popular in diverse application areas, from medical imaging to industrial process monitoring and tactile sensing, due to its low cost, real-time capab...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	519,781
2110.11226	Accelerating Genetic Programming using GPUs	Genetic Programming (GP), an evolutionary learning technique, has multiple applications in machine learning such as curve fitting, data modelling, feature selection, classification etc. GP has several inherent parallel steps, making it an ideal candidate for GPU based parallelization. This paper describes a GPU acceler...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	262,400
2101.02153	The Shapley Value of Classifiers in Ensemble Games	What is the value of an individual model in an ensemble of binary classifiers? We answer this question by introducing a class of transferable utility cooperative games called \textit{ensemble games}. In machine learning ensembles, pre-trained models cooperate to make classification decisions. To quantify the importance...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	false	true	214,541
1611.10248	Assessing pattern recognition or labeling in streams of temporal data	In the data deluge context, pattern recognition or labeling in streams is becoming quite an essential and pressing task as data flows inside always bigger streams. The assessment of such tasks is not so easy when dealing with temporal data, namely patterns that have a duration (a beginning and an end time-stamp). This ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	64,790
2105.02212	Inclusive Universities. Evidence from the Erasmus Program	The Erasmus Program is the main international mobility program in Europe and worldwide. Since its launch in 1987, it has been growing both in terms of participants and budget devoted to its activities. However, despite the possibility to obtain additional funding, the participation of students with special needs to the...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	233,757
1912.08969	Learning a Spatio-Temporal Embedding for Video Instance Segmentation	We present a novel embedding approach for video instance segmentation. Our method learns a spatio-temporal embedding integrating cues from appearance, motion, and geometry; a 3D causal convolutional network models motion, and a monocular self-supervised depth loss models geometry. In this embedding space, video-pixels ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	157,969
2307.02383	Floating-base manipulation on zero-perturbation manifolds	To achieve high-dexterity motion planning on floating-base systems, the base dynamics induced by arm motions must be treated carefully. In general, it is a significant challenge to establish a fixed-base frame during tasking due to forces and torques on the base that arise directly from arm motions (e.g. arm drag in lo...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	377,674
2007.03960	On Entropy Regularized Path Integral Control for Trajectory Optimization	In this article we present a generalised view on Path Integral Control (PIC) methods. PIC refers to a particular class of policy search methods that are closely tied to the setting of Linearly Solvable Optimal Control (LSOC), a restricted subclass of nonlinear Stochastic Optimal Control (SOC) problems. This class is un...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	186,217
2210.06418	Relational Graph Convolutional Neural Networks for Multihop Reasoning: A Comparative Study	Multihop Question Answering is a complex Natural Language Processing task that requires multiple steps of reasoning to find the correct answer to a given question. Previous research has explored the use of models based on Graph Neural Networks for tackling this task. Various architectures have been proposed, including ...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	323,281
2201.12212	M\"obius Convolutions for Spherical CNNs	M\"obius transformations play an important role in both geometry and spherical image processing - they are the group of conformal automorphisms of 2D surfaces and the spherical equivalent of homographies. Here we present a novel, M\"obius-equivariant spherical convolution operator which we call M\"obius convolution, an...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	true	277,564
2306.16265	Reconfigurable Robot Control Using Flexible Coupling Mechanisms	Reconfigurable robot swarms are capable of connecting with each other to form complex structures. Current mechanical or magnetic connection mechanisms can be complicated to manufacture, consume high power, have a limited load-bearing capacity, or can only form rigid structures. In this paper, we present our low-cost so...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	376,323
2311.02482	Generalized zero-shot audio-to-intent classification	Spoken language understanding systems using audio-only data are gaining popularity, yet their ability to handle unseen intents remains limited. In this study, we propose a generalized zero-shot audio-to-intent classification framework with only a few sample text sentences per intent. To achieve this, we first train a s...	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	405,460
1205.1357	Detecting Spammers via Aggregated Historical Data Set	The battle between email service providers and senders of mass unsolicited emails (Spam) continues to gain traction. Vast numbers of Spam emails are sent mainly from automatic botnets distributed over the world. One method for mitigating Spam in a computationally efficient manner is fast and accurate blacklisting of th...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	15,820
0807.0942	Secrecy via Sources and Channels	Alice and Bob want to share a secret key and to communicate an independent message, both of which they desire to be kept secret from an eavesdropper Eve. We study this problem of secret communication and secret key generation when two resources are available -- correlated sources at Alice, Bob, and Eve, and a noisy bro...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,037
cs/0702130	Syndrome Decoding of Reed-Solomon Codes Beyond Half the Minimum Distance based on Shift-Register Synthesis	In this paper, a new approach for decoding low-rate Reed-Solomon codes beyond half the minimum distance is considered and analyzed. Unlike the Sudan algorithm published in 1997, this new approach is based on multi-sequence shift-register synthesis, which makes it easy to understand and simple to implement. The computat...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	540,185
2310.16924	Physician Detection of Clinical Harm in Machine Translation: Quality Estimation Aids in Reliance and Backtranslation Identifies Critical Errors	A major challenge in the practical use of Machine Translation (MT) is that users lack guidance to make informed decisions about when to rely on outputs. Progress in quality estimation research provides techniques to automatically assess MT quality, but these techniques have primarily been evaluated in vitro by comparis...	true	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	402,921
2208.09016	Improving Small Molecule Generation using Mutual Information Machine	We address the task of controlled generation of small molecules, which entails finding novel molecules with desired properties under certain constraints (e.g., similarity to a reference molecule). Here we introduce MolMIM, a probabilistic auto-encoder for small molecule drug discovery that learns an informative and clu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	313,563
2312.14828	Plan, Posture and Go: Towards Open-World Text-to-Motion Generation	Conventional text-to-motion generation methods are usually trained on limited text-motion pairs, making them hard to generalize to open-world scenarios. Some works use the CLIP model to align the motion space and the text space, aiming to enable motion generation from natural language motion descriptions. However, they...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	417,762
2402.06329	A Network for structural dense displacement based on 3D deformable mesh model and optical flow	This study proposes a Network to recognize displacement of a RC frame structure from a video by a monocular camera. The proposed Network consists of two modules which is FlowNet2 and POFRN-Net. FlowNet2 is used to generate dense optical flow as well as POFRN-Net is to extract pose parameter H. FlowNet2 convert two vide...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	428,263
2302.08500	Auditing large language models: a three-layered approach	Large language models (LLMs) represent a major advance in artificial intelligence (AI) research. However, the widespread use of LLMs is also coupled with significant ethical and social challenges. Previous research has pointed towards auditing as a promising governance mechanism to help ensure that AI systems are desig...	false	false	false	false	true	false	false	false	true	false	false	false	false	true	false	false	false	false	346,069
1111.4052	A Facial Expression Classification System Integrating Canny, Principal Component Analysis and Artificial Neural Network	Facial Expression Classification is an interesting research problem in recent years. There are a lot of methods to solve this problem. In this research, we propose a novel approach using Canny, Principal Component Analysis (PCA) and Artificial Neural Network. Firstly, in preprocessing phase, we use Canny for local regi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	13,066
2301.10174	Analysis of Arrhythmia Classification on ECG Dataset	The heart is one of the most vital organs in the human body. It supplies blood and nutrients in other parts of the body. Therefore, maintaining a healthy heart is essential. As a heart disorder, arrhythmia is a condition in which the heart's pumping mechanism becomes aberrant. The Electrocardiogram is used to analyze t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	341,728
2107.05043	A Projector-Camera System Using Hybrid Pixels with Projection and Capturing Capabilities	We propose a novel projector-camera system (ProCams) in which each pixel has both projection and capturing capabilities. Our proposed ProCams solves the difficulty of obtaining precise pixel correspondence between the projector and the camera. We implemented a proof-of-concept ProCams prototype and demonstrated its app...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	245,648
1906.04338	SALT: Subspace Alignment as an Auxiliary Learning Task for Domain Adaptation	Unsupervised domain adaptation aims to transfer and adapt knowledge learned from a labeled source domain to an unlabeled target domain. Key components of unsupervised domain adaptation include: (a) maximizing performance on the target, and (b) aligning the source and target domains. Traditionally, these tasks have eith...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	134,681
1807.02617	Predicting Infant Motor Development Status using Day Long Movement Data from Wearable Sensors	Infants with a variety of complications at or before birth are classified as being at risk for developmental delays (AR). As they grow older, they are followed by healthcare providers in an effort to discern whether they are on a typical or impaired developmental trajectory. Often, it is difficult to make an accurate d...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	102,308
1912.11947	Colorectal Polyp Segmentation by U-Net with Dilation Convolution	Colorectal cancer (CRC) is one of the most commonly diagnosed cancers and a leading cause of cancer deaths in the United States. Colorectal polyps that grow on the intima of the colon or rectum is an important precursor for CRC. Currently, the most common way for colorectal polyp detection and precancerous pathology is...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	158,706
2412.14233	Descriptive Caption Enhancement with Visual Specialists for Multimodal Perception	Training Large Multimodality Models (LMMs) relies on descriptive image caption that connects image and language. Existing methods either distill the caption from the LMM models or construct the captions from the internet images or by human. We propose to leverage off-the-shelf visual specialists, which were trained fro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	518,632
2005.09561	Normalized Attention Without Probability Cage	Attention architectures are widely used; they recently gained renewed popularity with Transformers yielding a streak of state of the art results. Yet, the geometrical implications of softmax-attention remain largely unexplored. In this work we highlight the limitations of constraining attention weights to the probabili...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	177,956
1812.00306	Unilateral Left-Tail Anderson Darling Test Based Spectrum Sensing with Laplacian Noise	This paper focuses on spectrum sensing under Laplacian noise. To remit the negative effects caused by heavy-tailed behavior of Laplacian noise, the fractional lower order moments (FLOM) technology is employed to pre-process the received samples before spectrum sensing. Via exploiting the asymmetrical difference between...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	115,219
2410.05045	Can LLMs plan paths with extra hints from solvers?	Large Language Models (LLMs) have shown remarkable capabilities in natural language processing, mathematical problem solving, and tasks related to program synthesis. However, their effectiveness in long-term planning and higher-order reasoning has been noted to be limited and fragile. This paper explores an approach fo...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	495,541
2110.00934	Bounding Box Tightness Prior for Weakly Supervised Image Segmentation	This paper presents a weakly supervised image segmentation method that adopts tight bounding box annotations. It proposes generalized multiple instance learning (MIL) and smooth maximum approximation to integrate the bounding box tightness prior into the deep neural network in an end-to-end manner. In generalized MIL, ...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	258,592
1902.08648	Scalable Hyperbolic Recommender Systems	We present a large scale hyperbolic recommender system. We discuss why hyperbolic geometry is a more suitable underlying geometry for many recommendation systems and cover the fundamental milestones and insights that we have gained from its development. In doing so, we demonstrate the viability of hyperbolic geometry f...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	122,234
2207.05289	PLM-ICD: Automatic ICD Coding with Pretrained Language Models	Automatically classifying electronic health records (EHRs) into diagnostic codes has been challenging to the NLP community. State-of-the-art methods treated this problem as a multilabel classification problem and proposed various architectures to model this problem. However, these systems did not leverage the superb pe...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	307,483
2208.13314	Fluorescence molecular optomic signatures improve identification of tumors in head and neck specimens	In this study, a radiomics approach was extended to optical fluorescence molecular imaging data for tissue classification, termed 'optomics'. Fluorescence molecular imaging is emerging for precise surgical guidance during head and neck squamous cell carcinoma (HNSCC) resection. However, the tumor-to-normal tissue contr...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	315,021
2501.04698	ConceptMaster: Multi-Concept Video Customization on Diffusion Transformer Models Without Test-Time Tuning	Text-to-video generation has made remarkable advancements through diffusion models. However, Multi-Concept Video Customization (MCVC) remains a significant challenge. We identify two key challenges in this task: 1) the identity decoupling problem, where directly adopting existing customization methods inevitably mix at...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	523,312
2211.01298	Contract Composition for Dynamical Control Systems: Definition and Verification using Linear Programming	Designing large-scale control systems to satisfy complex specifications is hard in practice, as most formal methods are limited to systems of modest size. Contract theory has been proposed as a modular alternative to formal methods in control, in which specifications are defined by assumptions on the input to a compone...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	328,175
2410.20540	Automatic Estimation of Singing Voice Musical Dynamics	Musical dynamics form a core part of expressive singing voice performances. However, automatic analysis of musical dynamics for singing voice has received limited attention partly due to the scarcity of suitable datasets and a lack of clear evaluation frameworks. To address this challenge, we propose a methodology for ...	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	502,856
1908.03738	Personalized Music Recommendation with Triplet Network	Since many online music services emerged in recent years so that effective music recommendation systems are desirable. Some common problems in recommendation system like feature representations, distance measure and cold start problems are also challenges for music recommendation. In this paper, I proposed a triplet ne...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	141,309
2502.06836	CAST: Cross Attention based multimodal fusion of Structure and Text for materials property prediction	Recent advancements in AI have revolutionized property prediction in materials science and accelerating material discovery. Graph neural networks (GNNs) stand out due to their ability to represent crystal structures as graphs, effectively capturing local interactions and delivering superior predictions. However, these ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	532,281
1407.7790	Spectral and Energy Spectral Efficiency Optimization of Joint Transmit and Receive Beamforming Based Multi-Relay MIMO-OFDMA Cellular Networks	We first conceive a novel transmission protocol for a multi-relay multiple-input--multiple-output orthogonal frequency-division multiple-access (MIMO-OFDMA) cellular network based on joint transmit and receive beamforming. We then address the associated network-wide spectral efficiency (SE) and energy spectral efficien...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	34,979
2405.07399	Semi-Supervised Weed Detection for Rapid Deployment and Enhanced Efficiency	Weeds present a significant challenge in agriculture, causing yield loss and requiring expensive control measures. Automatic weed detection using computer vision and deep learning offers a promising solution. However, conventional deep learning methods often require large amounts of labelled training data, which can be...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	453,695
1910.14552	On the Interaction Between Deep Detectors and Siamese Trackers in Video Surveillance	Visual object tracking is an important function in many real-time video surveillance applications, such as localization and spatio-temporal recognition of persons. In real-world applications, an object detector and tracker must interact on a periodic basis to discover new objects, and thereby to initiate tracks. Period...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	151,680
2107.14574	Surrogate Modelling for Injection Molding Processes using Machine Learning	Injection molding is one of the most popular manufacturing methods for the modeling of complex plastic objects. Faster numerical simulation of the technological process would allow for faster and cheaper design cycles of new products. In this work, we propose a baseline for a data processing pipeline that includes the ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	248,502
2411.04130	ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design	Engineering molecules to exhibit precise 3D intermolecular interactions with their environment forms the basis of chemical design. In ligand-based drug design, bioisosteric analogues of known bioactive hits are often identified by virtually screening chemical libraries with shape, electrostatic, and pharmacophore simil...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,160
2005.10406	Training Keyword Spotting Models on Non-IID Data with Federated Learning	We demonstrate that a production-quality keyword-spotting model can be trained on-device using federated learning and achieve comparable false accept and false reject rates to a centrally-trained model. To overcome the algorithmic constraints associated with fitting on-device data (which are inherently non-independent ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	178,165
2203.06425	VAFO-Loss: VAscular Feature Optimised Loss Function for Retinal Artery/Vein Segmentation	Estimating clinically-relevant vascular features following vessel segmentation is a standard pipeline for retinal vessel analysis, which provides potential ocular biomarkers for both ophthalmic disease and systemic disease. In this work, we integrate these clinical features into a novel vascular feature optimised loss ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	285,110
2302.08710	Cross-Domain Label Propagation for Domain Adaptation with Discriminative Graph Self-Learning	Domain adaptation manages to transfer the knowledge of well-labeled source data to unlabeled target data. Many recent efforts focus on improving the prediction accuracy of target pseudo-labels to reduce conditional distribution shift. In this paper, we propose a novel domain adaptation method, which infers target pseud...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	346,153
2406.07287	Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot Learning	Sexism in online content is a pervasive issue that necessitates effective classification techniques to mitigate its harmful impact. Online platforms often have sexist comments and posts that create a hostile environment, especially for women and minority groups. This content not only spreads harmful stereotypes but als...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	462,981
cmp-lg/9509004	The Development and Migration of Concepts from Donor to Borrower Disciplines: Sublanguage Term Use in Hard & Soft Sciences	Academic disciplines, often divided into hard and soft sciences, may be understood as "donor disciplines" if they produce more concepts than they borrow from other disciplines, or "borrower disciplines" if they import more than they originate. Terms used to describe these concepts can be used to distinguish between har...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	536,460
1606.03066	The Effects of Latency Penalties in Evaluating Push Notification Systems	We examine the effects of different latency penalties in the evaluation of push notification systems, as operationalized in the TREC 2015 Microblog track evaluation. The purpose of this study is to inform the design of metrics for the TREC 2016 Real-Time Summarization track, which is largely modeled after the TREC 2015...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	57,050
1912.00772	E-Stitchup: Data Augmentation for Pre-Trained Embeddings	In this work, we propose data augmentation methods for embeddings from pre-trained deep learning models that take a weighted combination of a pair of input embeddings, as inspired by Mixup, and combine such augmentation with extra label softening. These methods are shown to significantly increase classification accurac...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	155,884
1812.05256	Learning to Communicate: A Machine Learning Framework for Heterogeneous Multi-Agent Robotic Systems	We present a machine learning framework for multi-agent systems to learn both the optimal policy for maximizing the rewards and the encoding of the high dimensional visual observation. The encoding is useful for sharing local visual observations with other agents under communication resource constraints. The actor-enco...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	false	116,380
1706.05544	Rgtsvm: Support Vector Machines on a GPU in R	Rgtsvm provides a fast and flexible support vector machine (SVM) implementation for the R language. The distinguishing feature of Rgtsvm is that support vector classification and support vector regression tasks are implemented on a graphical processing unit (GPU), allowing the libraries to scale to millions of examples...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	75,527
2411.15604	FATE: Full-head Gaussian Avatar with Textural Editing from Monocular Video	Reconstructing high-fidelity, animatable 3D head avatars from effortlessly captured monocular videos is a pivotal yet formidable challenge. Although significant progress has been made in rendering performance and manipulation capabilities, notable challenges remain, including incomplete reconstruction and inefficient G...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	510,683
1111.3846	No Free Lunch versus Occam's Razor in Supervised Learning	The No Free Lunch theorems are often used to argue that domain specific knowledge is required to design successful algorithms. We use algorithmic information theory to argue the case for a universal bias allowing an algorithm to succeed in all interesting problem domains. Additionally, we give a new algorithm for off-l...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	13,057
2311.11796	Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems	Artificial Intelligence (AI) systems such as autonomous vehicles, facial recognition, and speech recognition systems are increasingly integrated into our daily lives. However, despite their utility, these AI systems are vulnerable to a wide range of attacks such as adversarial, backdoor, data poisoning, membership infe...	false	false	false	false	true	false	false	false	true	false	false	true	true	false	false	false	false	false	409,074
2502.05349	Contextual Scenario Generation for Two-Stage Stochastic Programming	Two-stage stochastic programs (2SPs) are important tools for making decisions under uncertainty. Decision-makers use contextual information to generate a set of scenarios to represent the true conditional distribution. However, the number of scenarios required is a barrier to implementing 2SPs, motivating the problem o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	531,563
2209.14926	Domain-Unified Prompt Representations for Source-Free Domain Generalization	Domain generalization (DG), aiming to make models work on unseen domains, is a surefire way toward general artificial intelligence. Limited by the scale and diversity of current DG datasets, it is difficult for existing methods to scale to diverse domains in open-world scenarios (e.g., science fiction and pixelate styl...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	320,398
1406.2022	Two-dimensional Sentiment Analysis of text	Sentiment Analysis aims to get the underlying viewpoint of the text, which could be anything that holds a subjective opinion, such as an online review, Movie rating, Comments on Blog posts etc. This paper presents a novel approach that classify text in two-dimensional Emotional space, based on the sentiments of the aut...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	33,702
2408.00690	Improving Text Embeddings for Smaller Language Models Using Contrastive Fine-tuning	While Large Language Models show remarkable performance in natural language understanding, their resource-intensive nature makes them less accessible. In contrast, smaller language models such as MiniCPM offer more sustainable scalability, but often underperform without specialized optimization. In this paper, we explo...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	477,935
2211.03818	Retrieval augmentation of large language models for lay language generation	Recent lay language generation systems have used Transformer models trained on a parallel corpus to increase health information accessibility. However, the applicability of these models is constrained by the limited size and topical breadth of available corpora. We introduce CELLS, the largest (63k pairs) and broadest-...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	329,047
2409.16001	Artificial Human Intelligence: The role of Humans in the Development of Next Generation AI	Human intelligence, the most evident and accessible form of source of reasoning, hosted by biological hardware, has evolved and been refined over thousands of years, positioning itself today to create new artificial forms and preparing to self--design their evolutionary path forward. Beginning with the advent of founda...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	491,162
2404.16139	A Survey on Intermediate Fusion Methods for Collaborative Perception Categorized by Real World Challenges	This survey analyzes intermediate fusion methods in collaborative perception for autonomous driving, categorized by real-world challenges. We examine various methods, detailing their features and the evaluation metrics they employ. The focus is on addressing challenges like transmission efficiency, localization errors,...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	449,368
2006.00592	Predicting Engagement in Video Lectures	The explosion of Open Educational Resources (OERs) in the recent years creates the demand for scalable, automatic approaches to process and evaluate OERs, with the end goal of identifying and recommending the most suitable educational materials for learners. We focus on building models to find the characteristics and f...	true	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	179,515
1709.04794	Fast semi-supervised discriminant analysis for binary classification of large data-sets	High-dimensional data requires scalable algorithms. We propose and analyze three scalable and related algorithms for semi-supervised discriminant analysis (SDA). These methods are based on Krylov subspace methods which exploit the data sparsity and the shift-invariance of Krylov subspaces. In addition, the problem defi...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	80,732
2402.11769	Connection-Aware P2P Trading: Simultaneous Trading and Peer Selection	Peer-to-peer (P2P) trading is seen as a viable solution to handle the growing number of distributed energy resources in distribution networks. However, when dealing with large-scale consumers, there are several challenges that must be addressed. One of these challenges is limited communication capabilities. Additionall...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	430,559
2501.08950	Computing Approximated Fixpoints via Dampened Mann Iteration	Fixpoints are ubiquitous in computer science and when dealing with quantitative semantics and verification one is commonly led to consider least fixpoints of (higher-dimensional) functions over the nonnegative reals. We show how to approximate the least fixpoint of such functions, focusing on the case in which they are...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	524,954
2008.04107	Phonological Features for 0-shot Multilingual Speech Synthesis	Code-switching---the intra-utterance use of multiple languages---is prevalent across the world. Within text-to-speech (TTS), multilingual models have been found to enable code-switching. By modifying the linguistic input to sequence-to-sequence TTS, we show that code-switching is possible for languages unseen during tr...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	191,134
2409.08516	AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation	Class Incremental Semantic Segmentation (CISS) aims to mitigate catastrophic forgetting by maintaining a balance between previously learned and newly introduced knowledge. Existing methods, primarily based on regularization techniques like knowledge distillation, help preserve old knowledge but often face challenges in...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	487,940
1805.07862	Featurized Bidirectional GAN: Adversarial Defense via Adversarially Learned Semantic Inference	Deep neural networks have been demonstrated to be vulnerable to adversarial attacks, where small perturbations intentionally added to the original inputs can fool the classifier. In this paper, we propose a defense method, Featurized Bidirectional Generative Adversarial Networks (FBGAN), to extract the semantic feature...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	97,966
1703.06108	Global Entity Ranking Across Multiple Languages	We present work on building a global long-tailed ranking of entities across multiple languages using Wikipedia and Freebase knowledge bases. We identify multiple features and build a model to rank entities using a ground-truth dataset of more than 10 thousand labels. The final system ranks 27 million entities with 75% ...	false	false	false	true	false	true	false	false	true	false	false	false	false	false	false	false	false	false	70,176
1701.07485	Relay-Assisted Mixed FSO/RF Systems over M\'alaga-$\mathcal{M}$ and $\kappa$-$\mu$ Shadowed Fading Channels	This letter presents a unified analytical framework for relay-assisted mixed FSO/RF transmission. In addition to accounting for different FSO detection techniques, the mathematical model offers a twofold unification of mixed FSO/RF systems by considering mixed M\'alaga-$\mathcal{M}$/$\kappa$-$\mu$ shadowed fading, whic...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	67,299
2410.01818	Integrating AI's Carbon Footprint into Risk Management Frameworks: Strategies and Tools for Sustainable Compliance in Banking Sector	This paper examines the integration of AI's carbon footprint into the risk management frameworks (RMFs) of the banking sector, emphasising its importance in aligning with sustainability goals and regulatory requirements. As AI becomes increasingly central to banking operations, its energy-intensive processes contribute...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	493,970
1111.3376	Fingerprinting with Equiangular Tight Frames	Digital fingerprinting is a framework for marking media files, such as images, music, or movies, with user-specific signatures to deter illegal distribution. Multiple users can collude to produce a forgery that can potentially overcome a fingerprinting system. This paper proposes an equiangular tight frame fingerprint ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	13,028
2106.05365	DESCGEN: A Distantly Supervised Dataset for Generating Abstractive Entity Descriptions	Short textual descriptions of entities provide summaries of their key attributes and have been shown to be useful sources of background knowledge for tasks such as entity linking and question answering. However, generating entity descriptions, especially for new and long-tail entities, can be challenging since relevant...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	240,063
2102.01646	Online Learning with Simple Predictors and a Combinatorial Characterization of Minimax in 0/1 Games	Which classes can be learned properly in the online model? -- that is, by an algorithm that at each round uses a predictor from the concept class. While there are simple and natural cases where improper learning is necessary, it is natural to ask how complex must the improper predictors be in such cases. Can one always...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	218,182
1608.08967	Robustness of classifiers: from adversarial to random noise	Several recent works have shown that state-of-the-art classifiers are vulnerable to worst-case (i.e., adversarial) perturbations of the datapoints. On the other hand, it has been empirically observed that these same classifiers are relatively robust to random noise. In this paper, we propose to study a \textit{semi-ran...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	60,415
2402.03284	Deal, or no deal (or who knows)? Forecasting Uncertainty in Conversations using Large Language Models	Effective interlocutors account for the uncertain goals, beliefs, and emotions of others. But even the best human conversationalist cannot perfectly anticipate the trajectory of a dialogue. How well can language models represent inherent uncertainty in conversations? We propose FortUne Dial, an expansion of the long-st...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	426,938
2304.12995	AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head	Large language models (LLMs) have exhibited remarkable capabilities across a variety of domains and tasks, challenging our understanding of learning and cognition. Despite the recent success, current LLMs are not capable of processing complex audio information or conducting spoken conversations (like Siri or Alexa). In...	false	false	true	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	360,415
2105.07383	Dimensioning an Indoor SISO RIS-system: Approximations and Equivalence Models	We provide closed-form approximations to the performance gain achieved in a RIS-assisted communication. We then consider a network deployment of RIS and Transmitter-Receiver pairs and use these approximate expressions to provide equivalence models which state that the performance of a RIS-equipped network is similar to...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	235,414
2311.05152	Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks	In recent years, the deployment of large-scale pre-trained models in audio-visual downstream tasks has yielded remarkable outcomes. However, these models, primarily trained on single-modality unconstrained datasets, still encounter challenges in feature extraction for multi-modal tasks, leading to suboptimal performanc...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	true	406,494
2402.01579	Are Paralinguistic Representations all that is needed for Speech Emotion Recognition?	Availability of representations from pre-trained models (PTMs) have facilitated substantial progress in speech emotion recognition (SER). Particularly, representations from PTM trained for paralinguistic speech processing have shown state-of-the-art (SOTA) performance for SER. However, such paralinguistic PTM represent...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	426,085
1807.07203	Few-Shot Adaptation for Multimedia Semantic Indexing	We propose a few-shot adaptation framework, which bridges zero-shot learning and supervised many-shot learning, for semantic indexing of image and video data. Few-shot adaptation provides robust parameter estimation with few training examples, by optimizing the parameters of zero-shot learning and supervised many-shot ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	103,275
1903.11059	AlphaX: eXploring Neural Architectures with Deep Neural Networks and Monte Carlo Tree Search	Neural Architecture Search (NAS) has shown great success in automating the design of neural networks, but the prohibitive amount of computations behind current NAS methods requires further investigations in improving the sample efficiency and the network evaluation cost to get better results in a shorter time. In this ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	125,427
1806.05620	DynaSLAM: Tracking, Mapping and Inpainting in Dynamic Scenes	The assumption of scene rigidity is typical in SLAM algorithms. Such a strong assumption limits the use of most visual SLAM systems in populated real-world environments, which are the target of several relevant applications like service robotics or autonomous vehicles. In this paper we present DynaSLAM, a visual SLAM s...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	100,519
2012.13539	A GCICA Grant-Free Random Access Scheme for M2M Communications in Crowded Massive MIMO Systems	A high success rate of grant-free random access scheme is proposed to support massive access for machine-to-machine communications in massive multipleinput multiple-output systems. This scheme allows active user equipments (UEs) to transmit their modulated uplink messages along with super pilots consisting of multiple ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	213,244
2003.13896	Robust Multiple-Path Orienteering Problem: Securing Against Adversarial Attacks	The multiple-path orienteering problem asks for paths for a team of robots that maximize the total reward collected while satisfying budget constraints on the path length. This problem models many multi-robot routing tasks such as exploring unknown environments and information gathering for environmental monitoring. In...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	170,344
2211.02716	NLP Inspired Training Mechanics For Modeling Transient Dynamics	In recent years, Machine learning (ML) techniques developed for Natural Language Processing (NLP) have permeated into developing better computer vision algorithms. In this work, we use such NLP-inspired techniques to improve the accuracy, robustness and generalizability of ML models for simulating transient dynamics. W...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	328,673
2209.12948	Developing Machine-Learned Potentials for Coarse-Grained Molecular Simulations: Challenges and Pitfalls	Coarse graining (CG) enables the investigation of molecular properties for larger systems and at longer timescales than the ones attainable at the atomistic resolution. Machine learning techniques have been recently proposed to learn CG particle interactions, i.e. develop CG force fields. Graph representations of molec...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	319,715
2309.04503	Quantum Algorithm for Maximum Biclique Problem	Identifying a biclique with the maximum number of edges bears considerable implications for numerous fields of application, such as detecting anomalies in E-commerce transactions, discerning protein-protein interactions in biology, and refining the efficacy of social network recommendation algorithms. However, the inhe...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	390,748
2007.05335	Robust Classification under Class-Dependent Domain Shift	Investigation of machine learning algorithms robust to changes between the training and test distributions is an active area of research. In this paper we explore a special type of dataset shift which we call class-dependent domain shift. It is characterized by the following features: the input data causally depends on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	186,643
2309.13035	PyPose v0.6: The Imperative Programming Interface for Robotics	PyPose is an open-source library for robot learning. It combines a learning-based approach with physics-based optimization, which enables seamless end-to-end robot learning. It has been used in many tasks due to its meticulously designed application programming interface (API) and efficient implementation. From its ini...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	394,016
1506.01072	Homogeneous Spiking Neuromorphic System for Real-World Pattern Recognition	A neuromorphic chip that combines CMOS analog spiking neurons and memristive synapses offers a promising solution to brain-inspired computing, as it can provide massive neural network parallelism and density. Previous hybrid analog CMOS-memristor approaches required extensive CMOS circuitry for training, and thus elimi...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	true	false	true	43,754
2206.03603	A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images	Background: The assessment of left ventricular (LV) function by myocardial perfusion SPECT (MPS) relies on accurate myocardial segmentation. The purpose of this paper is to develop and validate a new method incorporating deep learning with shape priors to accurately extract the LV myocardium for automatic measurement o...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	301,340

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