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
2010.04627	Learning Binary Decision Trees by Argmin Differentiation	We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node pruning) and continuous parameters (i.e., for tree split functions and prediction functions) simultaneously using argmin differentiation. We ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	199,811
2406.01649	CoLa-DCE -- Concept-guided Latent Diffusion Counterfactual Explanations	Recent advancements in generative AI have introduced novel prospects and practical implementations. Especially diffusion models show their strength in generating diverse and, at the same time, realistic features, positioning them well for generating counterfactual explanations for computer vision models. Answering "wha...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	460,419
2410.15921	Fully distributed and resilient source seeking for robot swarms	We propose a self-contained, resilient and fully distributed solution for locating the maximum of an unknown 3D scalar field using a swarm of robots that travel at constant speeds. Unlike conventional reactive methods relying on gradient information, our methodology enables the swarm to determine an ascending direction...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	500,793
2211.11962	Transformation-Equivariant 3D Object Detection for Autonomous Driving	3D object detection received increasing attention in autonomous driving recently. Objects in 3D scenes are distributed with diverse orientations. Ordinary detectors do not explicitly model the variations of rotation and reflection transformations. Consequently, large networks and extensive data augmentation are require...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,938
2204.12184	SkillNet-NLG: General-Purpose Natural Language Generation with a Sparsely Activated Approach	We present SkillNet-NLG, a sparsely activated approach that handles many natural language generation tasks with one model. Different from traditional dense models that always activate all the parameters, SkillNet-NLG selectively activates relevant parts of the parameters to accomplish a task, where the relevance is con...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	293,402
2411.13424	CAFE A Novel Code switching Dataset for Algerian Dialect French and English	The paper introduces and publicly releases (Data download link available after acceptance) CAFE -- the first Code-switching dataset between Algerian dialect, French, and english languages. The CAFE speech data is unique for (a) its spontaneous speaking style in vivo human-human conversation capturing phenomena like cod...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	509,782
2007.14997	Aggregate Analytic Window Query over Spatial Data	Analytic window query is a commonly used query in the relational databases. It answers the aggregations of data over a sliding window. For example, to get the average prices of a stock for each day. However, it is not supported in the spatial databases. Because the spatial data are not in a one-dimension space, there i...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	189,545
1511.06606	Data Representation and Compression Using Linear-Programming Approximations	We propose `Dracula', a new framework for unsupervised feature selection from sequential data such as text. Dracula learns a dictionary of $n$-grams that efficiently compresses a given corpus and recursively compresses its own dictionary; in effect, Dracula is a `deep' extension of Compressive Feature Learning. It requ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	49,287
1304.7284	Supervised Heterogeneous Multiview Learning for Joint Association Study and Disease Diagnosis	Given genetic variations and various phenotypical traits, such as Magnetic Resonance Imaging (MRI) features, we consider two important and related tasks in biomedical research: i)to select genetic and phenotypical markers for disease diagnosis and ii) to identify associations between genetic and phenotypical data. Thes...	false	true	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	24,243
2112.06011	Improving the Transferability of Adversarial Examples with Resized-Diverse-Inputs, Diversity-Ensemble and Region Fitting	We introduce a three stage pipeline: resized-diverse-inputs (RDIM), diversity-ensemble (DEM) and region fitting, that work together to generate transferable adversarial examples. We first explore the internal relationship between existing attacks, and propose RDIM that is capable of exploiting this relationship. Then w...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	271,023
2103.07893	DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network	Conditional generative adversarial networks (cGANs) target at synthesizing diverse images given the input conditions and latent codes, but unfortunately, they usually suffer from the issue of mode collapse. To solve this issue, previous works mainly focused on encouraging the correlation between the latent codes and th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	224,725
1605.00686	Adaptive Candidate Generation for Scalable Edge-discovery Tasks on Data Graphs	Several `edge-discovery' applications over graph-based data models are known to have worst-case quadratic time complexity in the nodes, even if the discovered edges are sparse. One example is the generic link discovery problem between two graphs, which has invited research interest in several communities. Specific vers...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	false	55,374
2407.16944	Adaptive Gradient Regularization: A Faster and Generalizable Optimization Technique for Deep Neural Networks	Stochastic optimization plays a crucial role in the advancement of deep learning technologies. Over the decades, significant effort has been dedicated to improving the training efficiency and robustness of deep neural networks, via various strategies including gradient normalization (GN) and gradient centralization (GC...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	475,792
2106.01779	Preparation of Many-body Ground States by Time Evolution with Variational Microscopic Magnetic Fields and Incomplete Interactions	State preparation is of fundamental importance in quantum physics, which can be realized by constructing the quantum circuit as a unitary that transforms the initial state to the target, or implementing a quantum control protocol to evolve to the target state with a designed Hamiltonian. In this work, we study the latt...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	238,622
2103.14660	Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models	Preventable or undiagnosed visual impairment and blindness affect billion of people worldwide. Automated multi-disease detection models offer great potential to address this problem via clinical decision support in diagnosis. In this work, we proposed an innovative multi-disease detection pipeline for retinal imaging w...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	226,932
1401.5871	Serefind: A Social Networking Website for Classifieds	This paper presents the design and implementation of a social networking website for classifieds, called Serefind. We designed search interfaces with focus on security, privacy, usability, design, ranking, and communications. We deployed this site at the Johns Hopkins University, and the results show it can be used as ...	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	false	30,264
2105.09858	Low-Latency Real-Time Non-Parallel Voice Conversion based on Cyclic Variational Autoencoder and Multiband WaveRNN with Data-Driven Linear Prediction	This paper presents a low-latency real-time (LLRT) non-parallel voice conversion (VC) framework based on cyclic variational autoencoder (CycleVAE) and multiband WaveRNN with data-driven linear prediction (MWDLP). CycleVAE is a robust non-parallel multispeaker spectral model, which utilizes a speaker-independent latent ...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	236,186
2412.20807	Two Heads Are Better Than One: Averaging along Fine-Tuning to Improve Targeted Transferability	With much longer optimization time than that of untargeted attacks notwithstanding, the transferability of targeted attacks is still far from satisfactory. Recent studies reveal that fine-tuning an existing adversarial example (AE) in feature space can efficiently boost its targeted transferability. However, existing f...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	521,365
2201.01203	Quantifying Uncertainty in Deep Learning Approaches to Radio Galaxy Classification	In this work we use variational inference to quantify the degree of uncertainty in deep learning model predictions of radio galaxy classification. We show that the level of model posterior variance for individual test samples is correlated with human uncertainty when labelling radio galaxies. We explore the model perfo...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	274,181
1911.05377	CSPN++: Learning Context and Resource Aware Convolutional Spatial Propagation Networks for Depth Completion	Depth Completion deals with the problem of converting a sparse depth map to a dense one, given the corresponding color image. Convolutional spatial propagation network (CSPN) is one of the state-of-the-art (SoTA) methods of depth completion, which recovers structural details of the scene. In this paper, we propose CSPN...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	153,244
2009.08720	Contextual Semantic Interpretability	Convolutional neural networks (CNN) are known to learn an image representation that captures concepts relevant to the task, but do so in an implicit way that hampers model interpretability. However, one could argue that such a representation is hidden in the neurons and can be made explicit by teaching the model to rec...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	196,331
2109.14259	Hierarchical Character Tagger for Short Text Spelling Error Correction	State-of-the-art approaches to spelling error correction problem include Transformer-based Seq2Seq models, which require large training sets and suffer from slow inference time; and sequence labeling models based on Transformer encoders like BERT, which involve token-level label space and therefore a large pre-defined ...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	257,915
2108.12276	End-To-End Anomaly Detection for Identifying Malicious Cyber Behavior through NLP-Based Log Embeddings	Rule-based IDS (intrusion detection systems) are being replaced by more robust neural IDS, which demonstrate great potential in the field of Cybersecurity. However, these ML approaches continue to rely on ad-hoc feature engineering techniques, which lack the capacity to vectorize inputs in ways that are fully relevant ...	false	false	false	false	true	false	false	false	false	false	false	false	true	false	false	false	false	false	252,452
1701.08608	Peduncle Detection of Sweet Pepper for Autonomous Crop Harvesting - Combined Colour and 3D Information	This paper presents a 3D visual detection method for the challenging task of detecting peduncles of sweet peppers (Capsicum annuum) in the field. Cutting the peduncle cleanly is one of the most difficult stages of the harvesting process, where the peduncle is the part of the crop that attaches it to the main stem of th...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	67,491
0909.1771	The Role of Schema Matching in Large Enterprises	To date, the principal use case for schema matching research has been as a precursor for code generation, i.e., constructing mappings between schema elements with the end goal of data transfer. In this paper, we argue that schema matching plays valuable roles independent of mapping construction, especially as schemata ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	4,449
2101.06417	Bayesian Inference Forgetting	The right to be forgotten has been legislated in many countries but the enforcement in machine learning would cause unbearable costs: companies may need to delete whole models learned from massive resources due to single individual requests. Existing works propose to remove the knowledge learned from the requested data...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	215,709
2005.11757	Req2Lib: A Semantic Neural Model for Software Library Recommendation	Third-party libraries are crucial to the development of software projects. To get suitable libraries, developers need to search through millions of libraries by filtering, evaluating, and comparing. The vast number of libraries places a barrier for programmers to locate appropriate ones. To help developers, researchers...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	178,565
2306.15552	A Survey on Deep Learning Hardware Accelerators for Heterogeneous HPC Platforms	Recent trends in deep learning (DL) imposed hardware accelerators as the most viable solution for several classes of high-performance computing (HPC) applications such as image classification, computer vision, and speech recognition. This survey summarizes and classifies the most recent advances in designing DL acceler...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	376,060
2109.01100	How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology?	Data-driven subword segmentation has become the default strategy for open-vocabulary machine translation and other NLP tasks, but may not be sufficiently generic for optimal learning of non-concatenative morphology. We design a test suite to evaluate segmentation strategies on different types of morphological phenomena...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	253,340
2005.08598	Sequential Recommender via Time-aware Attentive Memory Network	Recommendation systems aim to assist users to discover most preferred contents from an ever-growing corpus of items. Although recommenders have been greatly improved by deep learning, they still faces several challenges: (1) Behaviors are much more complex than words in sentences, so traditional attentive and recurrent...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	177,664
cs/9902002	Automatic Identification of Subjects for Textual Documents in Digital Libraries	The amount of electronic documents in the Internet grows very quickly. How to effectively identify subjects for documents becomes an important issue. In past, the researches focus on the behavior of nouns in documents. Although subjects are composed of nouns, the constituents that determine which nouns are subjects are...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	540,469
1106.1250	Optimal Repair of MDS Codes in Distributed Storage via Subspace Interference Alignment	It is well known that an (n,k) code can be used to store 'k' units of information in 'n' unit-capacity disks of a distributed data storage system. If the code used is maximum distance separable (MDS), then the system can tolerate any (n-k) disk failures, since the original information can be recovered from any k surviv...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	10,748
2307.13639	Fake It Without Making It: Conditioned Face Generation for Accurate 3D Face Reconstruction	Accurate 3D face reconstruction from 2D images is an enabling technology with applications in healthcare, security, and creative industries. However, current state-of-the-art methods either rely on supervised training with very limited 3D data or self-supervised training with 2D image data. To bridge this gap, we prese...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	381,651
2210.00935	Analysis of (sub-)Riemannian PDE-G-CNNs	Group equivariant convolutional neural networks (G-CNNs) have been successfully applied in geometric deep learning. Typically, G-CNNs have the advantage over CNNs that they do not waste network capacity on training symmetries that should have been hard-coded in the network. The recently introduced framework of PDE-base...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	321,063
2301.04906	Practical challenges in data-driven interpolation: dealing with noise, enforcing stability, and computing realizations	In this contribution, we propose a detailed study of interpolation-based data-driven methods that are of relevance in the model reduction and also in the systems and control communities. The data are given by samples of the transfer function of the underlying (unknown) model, i.e., we analyze frequency-response data. W...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	340,209
2210.11750	Generative Range Imaging for Learning Scene Priors of 3D LiDAR Data	3D LiDAR sensors are indispensable for the robust vision of autonomous mobile robots. However, deploying LiDAR-based perception algorithms often fails due to a domain gap from the training environment, such as inconsistent angular resolution and missing properties. Existing studies have tackled the issue by learning in...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	325,438
2403.12659	Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites	The ability to efficiently predict adsorption properties of zeolites can be of large benefit in accelerating the design process of novel materials. The existing configuration space for these materials is wide, while existing molecular simulation methods are computationally expensive. In this work, we propose a model wh...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	439,283
2404.15823	A Configurable and Efficient Memory Hierarchy for Neural Network Hardware Accelerator	As machine learning applications continue to evolve, the demand for efficient hardware accelerators, specifically tailored for deep neural networks (DNNs), becomes increasingly vital. In this paper, we propose a configurable memory hierarchy framework tailored for per layer adaptive memory access patterns of DNNs. The ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	449,256
1910.01531	Modeling Color Terminology Across Thousands of Languages	There is an extensive history of scholarship into what constitutes a "basic" color term, as well as a broadly attested acquisition sequence of basic color terms across many languages, as articulated in the seminal work of Berlin and Kay (1969). This paper employs a set of diverse measures on massively cross-linguistic ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	147,966
2104.03902	The Autodidactic Universe	We present an approach to cosmology in which the Universe learns its own physical laws. It does so by exploring a landscape of possible laws, which we express as a certain class of matrix models. We discover maps that put each of these matrix models in correspondence with both a gauge/gravity theory and a mathematical ...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	229,217
2407.05233	Advancing Prompt Recovery in NLP: A Deep Dive into the Integration of Gemma-2b-it and Phi2 Models	Prompt recovery, a crucial task in natural language processing, entails the reconstruction of prompts or instructions that language models use to convert input text into a specific output. Although pivotal, the design and effectiveness of prompts represent a challenging and relatively untapped field within NLP research...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	470,879
1703.09928	Bundle Optimization for Multi-aspect Embedding	Understanding semantic similarity among images is the core of a wide range of computer vision applications. An important step towards this goal is to collect and learn human perceptions. Interestingly, the semantic context of images is often ambiguous as images can be perceived with emphasis on different aspects, which...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	70,832
2111.06524	An Enhanced Adaptive Bi-clustering Algorithm through Building a Shielding Complex Sub-Matrix	Bi-clustering refers to the task of finding sub-matrices (indexed by a group of columns and a group of rows) within a matrix of data such that the elements of each sub-matrix (data and features) are related in a particular way, for instance, that they are similar with respect to some metric. In this paper, after analyz...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	266,098
2309.04161	Performance Analysis of OTSM under Hardware Impairments and Imperfect CSI	Orthogonal time sequency multiplexing (OTSM) has been recently proposed as a single-carrier waveform offering similar bit error rate to orthogonal time frequency space (OTFS) and outperforms orthogonal frequency division multiplexing (OFDM) in doubly-spread channels (DSCs); however, with a much lower complexity making ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	390,630
2206.06888	CERT: Continual Pre-Training on Sketches for Library-Oriented Code Generation	Code generation is a longstanding challenge, aiming to generate a code snippet based on a natural language description. Usually, expensive text-code paired data is essential for training a code generation model. Recently, thanks to the success of pre-training techniques, large language models are trained on large-scale...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	302,533
2212.03120	Towards a Better Understanding of the Characteristics of Fractal Networks	The fractal nature of complex networks has received a great deal of research interest in the last two decades. Similarly to geometric fractals, the fractality of networks can also be defined with the so-called box-covering method. A network is called fractal if the minimum number of boxes needed to cover the entire net...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	335,004
1802.03803	FlipDial: A Generative Model for Two-Way Visual Dialogue	We present FlipDial, a generative model for visual dialogue that simultaneously plays the role of both participants in a visually-grounded dialogue. Given context in the form of an image and an associated caption summarising the contents of the image, FlipDial learns both to answer questions and put forward questions, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	90,070
2408.11138	Target-Oriented Object Grasping via Multimodal Human Guidance	In the context of human-robot interaction and collaboration scenarios, robotic grasping still encounters numerous challenges. Traditional grasp detection methods generally analyze the entire scene to predict grasps, leading to redundancy and inefficiency. In this work, we reconsider 6-DoF grasp detection from a target-...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	482,153
2102.12736	Time-Series Imputation with Wasserstein Interpolation for Optimal Look-Ahead-Bias and Variance Tradeoff	Missing time-series data is a prevalent practical problem. Imputation methods in time-series data often are applied to the full panel data with the purpose of training a model for a downstream out-of-sample task. For example, in finance, imputation of missing returns may be applied prior to training a portfolio optimiz...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	221,834
2012.06777	Uncalibrated Neural Inverse Rendering for Photometric Stereo of General Surfaces	This paper presents an uncalibrated deep neural network framework for the photometric stereo problem. For training models to solve the problem, existing neural network-based methods either require exact light directions or ground-truth surface normals of the object or both. However, in practice, it is challenging to pr...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	211,222
2412.05216	ColonNet: A Hybrid Of DenseNet121 And U-NET Model For Detection And Segmentation Of GI Bleeding	This study presents an integrated deep learning model for automatic detection and classification of Gastrointestinal bleeding in the frames extracted from Wireless Capsule Endoscopy (WCE) videos. The dataset has been released as part of Auto-WCBleedGen Challenge Version V2 hosted by the MISAHUB team. Our model attained...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	514,739
1810.07942	Semantic Parsing for Task Oriented Dialog using Hierarchical Representations	Task oriented dialog systems typically first parse user utterances to semantic frames comprised of intents and slots. Previous work on task oriented intent and slot-filling work has been restricted to one intent per query and one slot label per token, and thus cannot model complex compositional requests. Alternative se...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	110,728
2401.11488	HARDCORE: H-field and power loss estimation for arbitrary waveforms with residual, dilated convolutional neural networks in ferrite cores	The MagNet Challenge 2023 calls upon competitors to develop data-driven models for the material-specific, waveform-agnostic estimation of steady-state power losses in toroidal ferrite cores. The following HARDCORE (H-field and power loss estimation for Arbitrary waveforms with Residual, Dilated convolutional neural net...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	423,024
2412.09937	On Galois LCD codes and LCPs of codes over mixed alphabets	Let $\mathtt{R}$ be a finite commutative chain ring with the maximal ideal $\gamma\mathtt{R}$ of nilpotency index $e\geq 2,$ and let $\check{\mathtt{R}}=\mathtt{R}/\gamma^{s}\mathtt{R}$ for some positive integer $ s< e.$ In this paper, we study and characterize Galois $\mathtt{R}\check{\mathtt{R}}$-LCD codes of an arbi...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	516,715
2501.09532	AdaFV: Rethinking of Visual-Language alignment for VLM acceleration	The success of VLMs often relies on the dynamic high-resolution schema that adaptively augments the input images to multiple crops, so that the details of the images can be retained. However, such approaches result in a large number of redundant visual tokens, thus significantly reducing the efficiency of the VLMs. To ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	525,180
2002.00270	A New Derivative-Free Linear Approximation for Solving the Network Water Flow Problem with Convergence Guarantees	Addressing challenges in urban water infrastructure systems including aging infrastructure, supply uncertainty, extreme events, and security threats, depend highly on water distribution networks modeling emphasizing the importance of realistic assumptions, modeling complexities, and scalable solutions. In this study, w...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	162,311
2401.10660	Accelerating Multilingual Language Model for Excessively Tokenized Languages	Recent advancements in large language models (LLMs) have remarkably enhanced performances on a variety of tasks in multiple languages. However, tokenizers in LLMs trained primarily on English-centric corpora often overly fragment a text into character or Unicode-level tokens in non-Roman alphabetic languages, leading t...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	422,726
1303.0157	Scalable Cost-Aware Multi-Way Influence Maximization	Viral marketing is different from other marketing strategies since it leverages the influence power in intimate relationship, e.g., close friends, family members, couples. Due to the development and popularity of social networking services, such as Facebook, Twitter, and Pinterest, the new notion of "social media marke...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	true	22,540
2011.14073	On Performance Comparison of Multi-Antenna HD-NOMA, SCMA and PD-NOMA Schemes	In this paper, we study the uplink channel throughput performance of a proposed novel multiple-antenna hybrid-domain non-orthogonal multiple access (MA-HD-NOMA) scheme. This scheme combines the conventional sparse code multiple access (SCMA) and power-domain NOMA (PD-NOMA) schemes in order to increase the number of use...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	208,661
2010.08238	Toward Evaluating Re-identification Risks in the Local Privacy Model	LDP (Local Differential Privacy) has recently attracted much attention as a metric of data privacy that prevents the inference of personal data from obfuscated data in the local model. However, there are scenarios in which the adversary wants to perform re-identification attacks to link the obfuscated data to users in ...	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	true	false	201,118
2012.04276	Revisiting Iterative Back-Translation from the Perspective of Compositional Generalization	Human intelligence exhibits compositional generalization (i.e., the capacity to understand and produce unseen combinations of seen components), but current neural seq2seq models lack such ability. In this paper, we revisit iterative back-translation, a simple yet effective semi-supervised method, to investigate whether...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	210,405
2312.09791	Network Members Can Hide from Group Centrality Measures	Group centrality measures are a generalization of standard centrality, designed to quantify the importance of not just a single node (as is the case with standard measures) but rather that of a group of nodes. Some nodes may have an incentive to evade such measures, i.e., to hide their actual importance, in order to co...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	415,884
1807.08221	A Preliminary Study On the Sustainability of Android Malware Detection	Machine learning-based malware detection dominates current security defense approaches for Android apps. However, due to the evolution of Android platforms and malware, existing such techniques are widely limited by their need for constant retraining that are costly, and reliance on new malware samples that may not be ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	103,485
2403.11729	Hardware Design and Learning-Based Software Architecture of Musculoskeletal Wheeled Robot Musashi-W for Real-World Applications	Various musculoskeletal humanoids have been developed so far. While these humanoids have the advantage of their flexible and redundant bodies that mimic the human body, they are still far from being applied to real-world tasks. One of the reasons for this is the difficulty of bipedal walking in a flexible body. Thus, w...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	438,830
1811.06930	Pre-training Graph Neural Networks with Kernels	Many machine learning techniques have been proposed in the last few years to process data represented in graph-structured form. Graphs can be used to model several scenarios, from molecules and materials to RNA secondary structures. Several kernel functions have been defined on graphs that coupled with kernelized learn...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	113,621
2301.10443	Learning to Rank Normalized Entropy Curves with Differentiable Window Transformation	Recent automated machine learning systems often use learning curves ranking models to inform decisions about when to stop unpromising trials and identify better model configurations. In this paper, we present a novel learning curve ranking model specifically tailored for ranking normalized entropy (NE) learning curves,...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	341,805
2211.11983	Weakly-supervised Pre-training for 3D Human Pose Estimation via Perspective Knowledge	Modern deep learning-based 3D pose estimation approaches require plenty of 3D pose annotations. However, existing 3D datasets lack diversity, which limits the performance of current methods and their generalization ability. Although existing methods utilize 2D pose annotations to help 3D pose estimation, they mainly fo...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	331,950
1905.00322	Multi-level Encoder-Decoder Architectures for Image Restoration	Many real-world solutions for image restoration are learning-free and based on handcrafted image priors such as self-similarity. Recently, deep-learning methods that use training data have achieved state-of-the-art results in various image restoration tasks (e.g., super-resolution and inpainting). Ulyanov et al. bridge...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,442
2009.00210	Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition	Existing vision-based action recognition is susceptible to occlusion and appearance variations, while wearable sensors can alleviate these challenges by capturing human motion with one-dimensional time-series signal. For the same action, the knowledge learned from vision sensors and wearable sensors, may be related and...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	193,987
2203.12857	Local Measurement Based Robust Voltage Stability Index & Identification of Voltage Collapse Onset	This paper addresses the problem of real-time monitoring of long-term voltage instability (LTVI) by using local field measurements. Existing local measurement-based methods use Thevenin equivalent parameter estimation that is sensitive to the noise in measurements. For solving this issue, we avoid the Thevenin approach...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	287,422
2107.07040	Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations	Robust physics discovery is of great interest for many scientific and engineering fields. Inspired by the principle that a representative model is the one simplest possible, a new model selection criteria considering both model's Parsimony and Sparsity is proposed. A Parsimony Enhanced Sparse Bayesian Learning (PeSBL) ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	246,285
2412.11177	A Progressive Transformer for Unifying Binary Code Embedding and Knowledge Transfer	Language model approaches have recently been integrated into binary analysis tasks, such as function similarity detection and function signature recovery. These models typically employ a two-stage training process: pre-training via Masked Language Modeling (MLM) on machine code and fine-tuning for specific tasks. While...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	517,297
2501.16507	Characterizing Network Structure of Anti-Trans Actors on TikTok	The recent proliferation of short form video social media sites such as TikTok has been effectively utilized for increased visibility, communication, and community connection amongst trans/nonbinary creators online. However, these same platforms have also been exploited by right-wing actors targeting trans/nonbinary pe...	true	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	false	527,989
1907.04067	Impact of climate change on the cost-optimal mix of decentralised heat pump and gas boiler technologies in Europe	Residential demands for space heating and hot water account for 31% of the total European energy demand. Space heating is highly dependent on ambient conditions and susceptible to climate change. We adopt a techno-economic standpoint and assess the impact of climate change on decentralised heating demand and the cost-o...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	138,013
2105.11903	Towards an Online Empathetic Chatbot with Emotion Causes	Existing emotion-aware conversational models usually focus on controlling the response contents to align with a specific emotion class, whereas empathy is the ability to understand and concern the feelings and experience of others. Hence, it is critical to learn the causes that evoke the users' emotion for empathetic r...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	236,858
1703.10663	Near Perfect Protein Multi-Label Classification with Deep Neural Networks	Artificial neural networks (ANNs) have gained a well-deserved popularity among machine learning tools upon their recent successful applications in image- and sound processing and classification problems. ANNs have also been applied for predicting the family or function of a protein, knowing its residue sequence. Here w...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	70,950
2308.01966	DCTM: Dilated Convolutional Transformer Model for Multimodal Engagement Estimation in Conversation	Conversational engagement estimation is posed as a regression problem, entailing the identification of the favorable attention and involvement of the participants in the conversation. This task arises as a crucial pursuit to gain insights into human's interaction dynamics and behavior patterns within a conversation. In...	false	false	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	true	383,434
2412.09173	ReFF: Reinforcing Format Faithfulness in Language Models across Varied Tasks	Following formatting instructions to generate well-structured content is a fundamental yet often unmet capability for large language models (LLMs). To study this capability, which we refer to as format faithfulness, we present FormatBench, a comprehensive format-related benchmark. Compared to previous format-related be...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	516,385
2304.14824	A noise-robust acoustic method for recognizing foraging activities of grazing cattle	Farmers must continuously improve their livestock production systems to remain competitive in the growing dairy market. Precision livestock farming technologies provide individualized monitoring of animals on commercial farms, optimizing livestock production. Continuous acoustic monitoring is a widely accepted sensing ...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,105
1809.07978	Paraphrase Detection on Noisy Subtitles in Six Languages	We perform automatic paraphrase detection on subtitle data from the Opusparcus corpus comprising six European languages: German, English, Finnish, French, Russian, and Swedish. We train two types of supervised sentence embedding models: a word-averaging (WA) model and a gated recurrent averaging network (GRAN) model. W...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	108,401
1802.07452	Spatial Morphing Kernel Regression For Feature Interpolation	In recent years, geotagged social media has become popular as a novel source for geographic knowledge discovery. Ground-level images and videos provide a different perspective than overhead imagery and can be applied to a range of applications such as land use mapping, activity detection, pollution mapping, etc. The sp...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	90,898
2303.18083	Analysis and Comparison of Two-Level KFAC Methods for Training Deep Neural Networks	As a second-order method, the Natural Gradient Descent (NGD) has the ability to accelerate training of neural networks. However, due to the prohibitive computational and memory costs of computing and inverting the Fisher Information Matrix (FIM), efficient approximations are necessary to make NGD scalable to Deep Neura...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	355,456
2006.13527	Adversarial Model for Rotated Indoor Scenes Planning	In this paper, we propose an adversarial model for producing furniture layout for interior scene synthesis when the interior room is rotated. The proposed model combines a conditional adversarial network, a rotation module, a mode module, and a rotation discriminator module. As compared with the prior work on scene syn...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	183,946
2208.00584	A sensitivity-based approach to optimal sensor selection for process networks	Sensor selection is critical for state estimation, control and monitoring of nonlinear processes. However, evaluating the performance of each possible combination of $m$ out of $n$ sensors is impractical unless $m$ and $n$ are small. In this paper, we propose a sensitivity-based approach to determine the minimum number...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	310,902
2205.07430	Optimizing the optimizer for data driven deep neural networks and physics informed neural networks	We investigate the role of the optimizer in determining the quality of the model fit for neural networks with a small to medium number of parameters. We study the performance of Adam, an algorithm for first-order gradient-based optimization that uses adaptive momentum, the Levenberg and Marquardt (LM) algorithm a secon...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	296,597
2410.19055	Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms	When training neural networks with custom objectives, such as ranking losses and shortest-path losses, a common problem is that they are, per se, non-differentiable. A popular approach is to continuously relax the objectives to provide gradients, enabling learning. However, such differentiable relaxations are often non...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	502,140
2411.18266	Wearable intelligent throat enables natural speech in stroke patients with dysarthria	Wearable silent speech systems hold significant potential for restoring communication in patients with speech impairments. However, seamless, coherent speech remains elusive, and clinical efficacy is still unproven. Here, we present an AI-driven intelligent throat (IT) system that integrates throat muscle vibrations an...	false	false	true	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	511,799
2310.16560	Resurrecting Label Propagation for Graphs with Heterophily and Label Noise	Label noise is a common challenge in large datasets, as it can significantly degrade the generalization ability of deep neural networks. Most existing studies focus on noisy labels in computer vision; however, graph models encompass both node features and graph topology as input, and become more susceptible to label no...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	402,777
2110.01161	Enhance Images as You Like with Unpaired Learning	Low-light image enhancement exhibits an ill-posed nature, as a given image may have many enhanced versions, yet recent studies focus on building a deterministic mapping from input to an enhanced version. In contrast, we propose a lightweight one-path conditional generative adversarial network (cGAN) to learn a one-to-m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	258,666
2405.16436	Provably Mitigating Overoptimization in RLHF: Your SFT Loss is Implicitly an Adversarial Regularizer	Aligning generative models with human preference via RLHF typically suffers from overoptimization, where an imperfectly learned reward model can misguide the generative model to output undesired responses. We investigate this problem in a principled manner by identifying the source of the misalignment as a form of dist...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	457,422
1602.04630	Content Delivery in Erasure Broadcast Channels with Cache and Feedback	We study a content delivery problem in a K-user erasure broadcast channel such that a content providing server wishes to deliver requested files to users, each equipped with a cache of a finite memory. Assuming that the transmitter has state feedback and user caches can be filled during off-peak hours reliably by the d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	52,169
2103.01303	Exploring the high dimensional geometry of HSI features	We explore feature space geometries induced by the 3-D Fourier scattering transform and deep neural network with extended attribute profiles on four standard hyperspectral images. We examine the distances and angles of class means, the variability of classes, and their low-dimensional structures. These statistics are c...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	222,573
2211.07723	An online algorithm for contrastive Principal Component Analysis	Finding informative low-dimensional representations that can be computed efficiently in large datasets is an important problem in data analysis. Recently, contrastive Principal Component Analysis (cPCA) was proposed as a more informative generalization of PCA that takes advantage of contrastive learning. However, the p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	330,346
2110.02719	The Information Geometry of Unsupervised Reinforcement Learning	How can a reinforcement learning (RL) agent prepare to solve downstream tasks if those tasks are not known a priori? One approach is unsupervised skill discovery, a class of algorithms that learn a set of policies without access to a reward function. Such algorithms bear a close resemblance to representation learning a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	259,222
1910.04104	Vehicle Re-identification with Viewpoint-aware Metric Learning	This paper considers vehicle re-identification (re-ID) problem. The extreme viewpoint variation (up to 180 degrees) poses great challenges for existing approaches. Inspired by the behavior in human's recognition process, we propose a novel viewpoint-aware metric learning approach. It learns two metrics for similar view...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	148,684
2003.05131	Efficient Linear Transmission Strategy for MIMO Relaying Broadcast Channels with Direct Links	In this letter, a novel linear transmission strategy to design the linear precoding matrix~(PM) at base station~(BS) and the beamforming matrix~(BM) at relay station~(RS) for multiple-input multiple-output~(MIMO) relaying broadcast channels with direct channel (DC) is proposed, in which a linear PM is designed at BS ba...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	167,784
2105.01883	RepMLP: Re-parameterizing Convolutions into Fully-connected Layers for Image Recognition	We propose RepMLP, a multi-layer-perceptron-style neural network building block for image recognition, which is composed of a series of fully-connected (FC) layers. Compared to convolutional layers, FC layers are more efficient, better at modeling the long-range dependencies and positional patterns, but worse at captur...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	233,659
1909.10340	AHA! an 'Artificial Hippocampal Algorithm' for Episodic Machine Learning	The majority of ML research concerns slow, statistical learning of i.i.d. samples from large, labelled datasets. Animals do not learn this way. An enviable characteristic of animal learning is `episodic' learning - the ability to memorise a specific experience as a composition of existing concepts, after just one exper...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	146,518
2304.03526	Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field	This work explores the use of 3D generative models to synthesize training data for 3D vision tasks. The key requirements of the generative models are that the generated data should be photorealistic to match the real-world scenarios, and the corresponding 3D attributes should be aligned with given sampling labels. Howe...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	356,847
2405.08329	Cross-Dataset Generalization For Retinal Lesions Segmentation	Identifying lesions in fundus images is an important milestone toward an automated and interpretable diagnosis of retinal diseases. To support research in this direction, multiple datasets have been released, proposing groundtruth maps for different lesions. However, important discrepancies exist between the annotation...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	454,062

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