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
2011.06916	Predicting respondent difficulty in web surveys: A machine-learning approach based on mouse movement features	A central goal of survey research is to collect robust and reliable data from respondents. However, despite researchers' best efforts in designing questionnaires, respondents may experience difficulty understanding questions' intent and therefore may struggle to respond appropriately. If it were possible to detect such...	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	206,385
1804.03707	A Tamper-Free Semi-Universal Communication System for Deletion Channels	We investigate the problem of reliable communication between two legitimate parties over deletion channels under an active eavesdropping (aka jamming) adversarial model. To this goal, we develop a theoretical framework based on probabilistic finite-state automata to define novel encoding and decoding schemes that ensur...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	94,674
1911.10024	Spotting insects from satellites: modeling the presence of Culicoides imicola through Deep CNNs	Nowadays, Vector-Borne Diseases (VBDs) raise a severe threat for public health, accounting for a considerable amount of human illnesses. Recently, several surveillance plans have been put in place for limiting the spread of such diseases, typically involving on-field measurements. Such a systematic and effective plan s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	154,703
1204.6703	A Spectral Algorithm for Latent Dirichlet Allocation	The problem of topic modeling can be seen as a generalization of the clustering problem, in that it posits that observations are generated due to multiple latent factors (e.g., the words in each document are generated as a mixture of several active topics, as opposed to just one). This increased representational power ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	15,738
2408.11077	Characteristic Performance Study on Solving Oscillator ODEs via Soft-constrained Physics-informed Neural Network with Small Data	This paper compared physics-informed neural network (PINN), conventional neural network (NN) and traditional numerical discretization methods on solving differential equations (DEs) through literature investigation and experimental validation. We focused on the soft-constrained PINN approach and formalized its mathemat...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	482,141
2402.11398	Reasoning before Comparison: LLM-Enhanced Semantic Similarity Metrics for Domain Specialized Text Analysis	In this study, we leverage LLM to enhance the semantic analysis and develop similarity metrics for texts, addressing the limitations of traditional unsupervised NLP metrics like ROUGE and BLEU. We develop a framework where LLMs such as GPT-4 are employed for zero-shot text identification and label generation for radiol...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	430,362
1911.05075	Time-Dynamic Estimates of the Reliability of Deep Semantic Segmentation Networks	In the semantic segmentation of street scenes with neural networks, the reliability of predictions is of highest interest. The assessment of neural networks by means of uncertainties is a common ansatz to prevent safety issues. As in applications like automated driving, video streams of images are available, we present...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	153,161
2310.18384	MicroNAS: Memory and Latency Constrained Hardware-Aware Neural Architecture Search for Time Series Classification on Microcontrollers	Designing domain specific neural networks is a time-consuming, error-prone, and expensive task. Neural Architecture Search (NAS) exists to simplify domain-specific model development but there is a gap in the literature for time series classification on microcontrollers. Therefore, we adapt the concept of differentiable...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	403,523
1409.1143	Tunably Rugged Landscapes with Known Maximum and Minimum	We propose NM landscapes as a new class of tunably rugged benchmark problems. NM landscapes are well-defined on alphabets of any arity, including both discrete and real-valued alphabets, include epistasis in a natural and transparent manner, are proven to have known value and location of the global maximum and, with so...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	35,803
2210.00412	Observer-based Event-triggered Boundary Control of the One-phase Stefan Problem	This paper provides an observer-based event-triggered boundary control strategy for the one-phase Stefan problem using the position and velocity measurements of the moving interface. The infinite-dimensional backstepping approach is used to design the underlying observer and controller. For the event-triggered implemen...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	320,854
1703.10511	Multimodal Network Alignment	A multimodal network encodes relationships between the same set of nodes in multiple settings, and network alignment is a powerful tool for transferring information and insight between a pair of networks. We propose a method for multimodal network alignment that computes a matrix which indicates the alignment, but prod...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	70,921
2502.09299	Moving Matter: Efficient Reconfiguration of Tile Arrangements by a Single Active Robot	We consider the problem of reconfiguring a two-dimensional connected grid arrangement of passive building blocks from a start configuration to a goal configuration, using a single active robot that can move on the tiles, remove individual tiles from a given location and physically move them to a new position by walking...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	533,399
1609.05113	Bleach: A Distributed Stream Data Cleaning System	In this paper we address the problem of rule-based stream data cleaning, which sets stringent requirements on latency, rule dynamics and ability to cope with the unbounded nature of data streams. We design a system, called Bleach, which achieves real-time violation detection and data repair on a dirty data stream. Bl...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	true	61,075
2304.14446	HyperMODEST: Self-Supervised 3D Object Detection with Confidence Score Filtering	Current LiDAR-based 3D object detectors for autonomous driving are almost entirely trained on human-annotated data collected in specific geographical domains with specific sensor setups, making it difficult to adapt to a different domain. MODEST is the first work to train 3D object detectors without any labels. Our wor...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	360,961
2306.01945	Efficient Spoken Language Recognition via Multilabel Classification	Spoken language recognition (SLR) is the task of automatically identifying the language present in a speech signal. Existing SLR models are either too computationally expensive or too large to run effectively on devices with limited resources. For real-world deployment, a model should also gracefully handle unseen lang...	false	false	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	370,687
1505.00217	The Fractured Nature of British Politics	The outcome of the British General Election to be held in just over one week's time is widely regarded as the most difficult in living memory to predict. Current polls suggest that the two main parties are neck and neck but that there will be a landslide to the Scottish Nationalist Party with that party taking most of ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	42,684
1908.06083	Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack	The detection of offensive language in the context of a dialogue has become an increasingly important application of natural language processing. The detection of trolls in public forums (Gal\'an-Garc\'ia et al., 2016), and the deployment of chatbots in the public domain (Wolf et al., 2017) are two examples that show t...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	141,907
1109.4994	The finite-state character of physical dynamics	Finite physical systems have only a finite amount of distinct state. This finiteness is fundamental in statistical mechanics, where the maximum number of distinct states compatible with macroscopic constraints defines entropy. Here we show that finiteness of distinct state is similarly fundamental in ordinary mechanics...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	12,283
2402.05650	Rocks Coding, Not Development--A Human-Centric, Experimental Evaluation of LLM-Supported SE Tasks	Recently, large language models (LLM) based generative AI has been gaining momentum for their impressive high-quality performances in multiple domains, particularly after the release of the ChatGPT. Many believe that they have the potential to perform general-purpose problem-solving in software development and replace ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	427,950
2108.13083	An Introduction to Variational Inference	Approximating complex probability densities is a core problem in modern statistics. In this paper, we introduce the concept of Variational Inference (VI), a popular method in machine learning that uses optimization techniques to estimate complex probability densities. This property allows VI to converge faster than cla...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	252,706
2412.04727	Learning to Translate Noise for Robust Image Denoising	Deep learning-based image denoising techniques often struggle with poor generalization performance to out-of-distribution real-world noise. To tackle this challenge, we propose a novel noise translation framework that performs denoising on an image with translated noise rather than directly denoising an original noisy ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	514,532
2405.10512	In-context Contrastive Learning for Event Causality Identification	Event Causality Identification (ECI) aims at determining the existence of a causal relation between two events. Although recent prompt learning-based approaches have shown promising improvements on the ECI task, their performance are often subject to the delicate design of multiple prompts and the positive correlations...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	454,784
2303.01249	Language-Universal Adapter Learning with Knowledge Distillation for End-to-End Multilingual Speech Recognition	In this paper, we propose a language-universal adapter learning framework based on a pre-trained model for end-to-end multilingual automatic speech recognition (ASR). For acoustic modeling, the wav2vec 2.0 pre-trained model is fine-tuned by inserting language-specific and language-universal adapters. An online knowledg...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	348,894
2402.01160	Truncated Non-Uniform Quantization for Distributed SGD	To address the communication bottleneck challenge in distributed learning, our work introduces a novel two-stage quantization strategy designed to enhance the communication efficiency of distributed Stochastic Gradient Descent (SGD). The proposed method initially employs truncation to mitigate the impact of long-tail n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	425,891
1507.02086	The Role of Pragmatics in Legal Norm Representation	Despite the 'apparent clarity' of a given legal provision, its application may result in an outcome that does not exactly conform to the semantic level of a statute. The vagueness within a legal text is induced intentionally to accommodate all possible scenarios under which such norms should be applied, thus making the...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	44,942
2403.18569	PDNNet: PDN-Aware GNN-CNN Heterogeneous Network for Dynamic IR Drop Prediction	IR drop on the power delivery network (PDN) is closely related to PDN's configuration and cell current consumption. As the integrated circuit (IC) design is growing larger, dynamic IR drop simulation becomes computationally unaffordable and machine learning based IR drop prediction has been explored as a promising solu...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	441,993
2002.10200	ABCNet: Real-time Scene Text Spotting with Adaptive Bezier-Curve Network	Scene text detection and recognition has received increasing research attention. Existing methods can be roughly categorized into two groups: character-based and segmentation-based. These methods either are costly for character annotation or need to maintain a complex pipeline, which is often not suitable for real-time...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	165,318
1911.09807	Multi-Objective Multi-Agent Planning for Jointly Discovering and Tracking Mobile Object	We consider the challenging problem of online planning for a team of agents to autonomously search and track a time-varying number of mobile objects under the practical constraint of detection range limited onboard sensors. A standard POMDP with a value function that either encourages discovery or accurate tracking of ...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	true	false	false	false	154,621
2502.02582	Open Materials Generation with Stochastic Interpolants	The discovery of new materials is essential for enabling technological advancements. Computational approaches for predicting novel materials must effectively learn the manifold of stable crystal structures within an infinite design space. We introduce Open Materials Generation (OMG), a unifying framework for the genera...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	530,381
2005.04680	Optimizing Deep Learning Recommender Systems' Training On CPU Cluster Architectures	During the last two years, the goal of many researchers has been to squeeze the last bit of performance out of HPC system for AI tasks. Often this discussion is held in the context of how fast ResNet50 can be trained. Unfortunately, ResNet50 is no longer a representative workload in 2020. Thus, we focus on Recommender ...	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	true	176,533
2403.08370	SMART: Submodular Data Mixture Strategy for Instruction Tuning	Instruction Tuning involves finetuning a language model on a collection of instruction-formatted datasets in order to enhance the generalizability of the model to unseen tasks. Studies have shown the importance of balancing different task proportions during finetuning, but finding the right balance remains challenging....	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	437,314
1705.07057	Masked Autoregressive Flow for Density Estimation	Autoregressive models are among the best performing neural density estimators. We describe an approach for increasing the flexibility of an autoregressive model, based on modelling the random numbers that the model uses internally when generating data. By constructing a stack of autoregressive models, each modelling th...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	73,734
2311.04517	High-Performance Hybrid Algorithm for Minimum Sum-of-Squares Clustering of Infinitely Tall Data	This paper introduces a novel formulation of the clustering problem, namely the Minimum Sum-of-Squares Clustering of Infinitely Tall Data (MSSC-ITD), and presents HPClust, an innovative set of hybrid parallel approaches for its effective solution. By utilizing modern high-performance computing techniques, HPClust enhan...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	406,253
2309.01420	Unified Pre-training with Pseudo Texts for Text-To-Image Person Re-identification	The pre-training task is indispensable for the text-to-image person re-identification (T2I-ReID) task. However, there are two underlying inconsistencies between these two tasks that may impact the performance; i) Data inconsistency. A large domain gap exists between the generic images/texts used in public pre-trained m...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	389,681
2201.10602	Jacobian Computation for Cumulative B-Splines on SE(3) and Application to Continuous-Time Object Tracking	In this paper we propose a method that estimates the $SE(3)$ continuous trajectories (orientation and translation) of the dynamic rigid objects present in a scene, from multiple RGB-D views. Specifically, we fit the object trajectories to cumulative B-Splines curves, which allow us to interpolate, at any intermediate t...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	277,040
2202.12594	Complexity of Deliberative Coalition Formation	Elkind et al. (AAAI, 2021) introduced a model for deliberative coalition formation, where a community wishes to identify a strongly supported proposal from a space of alternatives, in order to change the status quo. In their model, agents and proposals are points in a metric space, agents' preferences are determined by...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	282,302
2306.10955	Semi-Supervised Learning for hyperspectral images by non parametrically predicting view assignment	Hyperspectral image (HSI) classification is gaining a lot of momentum in present time because of high inherent spectral information within the images. However, these images suffer from the problem of curse of dimensionality and usually require a large number samples for tasks such as classification, especially in super...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	374,424
1902.00585	Incremental Techniques for Large-Scale Dynamic Query Processing	Many applications from various disciplines are now required to analyze fast evolving big data in real time. Various approaches for incremental processing of queries have been proposed over the years. Traditional approaches rely on updating the results of a query when updates are streamed rather than re-computing these ...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	120,437
2202.05756	A Novel Speech Intelligibility Enhancement Model based on CanonicalCorrelation and Deep Learning	Current deep learning (DL) based approaches to speech intelligibility enhancement in noisy environments are often trained to minimise the feature distance between noise-free speech and enhanced speech signals. Despite improving the speech quality, such approaches do not deliver required levels of speech intelligibility...	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	279,974
2004.06750	SI-spreading-based network embedding in static and temporal networks	Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a simi...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	172,590
1806.08690	Is the 1-norm the best convex sparse regularization?	The 1-norm is a good convex regularization for the recovery of sparse vectors from under-determined linear measurements. No other convex regularization seems to surpass its sparse recovery performance. How can this be explained? To answer this question, we define several notions of "best" (convex) regulariza-tion in th...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	101,198
1903.06694	Tuning Hyperparameters without Grad Students: Scalable and Robust Bayesian Optimisation with Dragonfly	Bayesian Optimisation (BO) refers to a suite of techniques for global optimisation of expensive black box functions, which use introspective Bayesian models of the function to efficiently search for the optimum. While BO has been applied successfully in many applications, modern optimisation tasks usher in new challeng...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	124,443
1512.02968	Predicting Online Protest Participation of Social Media Users	Social media has emerged to be a popular platform for people to express their viewpoints on political protests like the Arab Spring. Millions of people use social media to communicate and mobilize their viewpoints on protests. Hence, it is a valuable tool for organizing social movements. However, the mechanisms by whic...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	49,985
1210.4614	Random Sequences Based on the Divisor Pairs Function	This paper investigates the randomness properties of a function of the divisor pairs of a natural number. This function, the antecedents of which go to very ancient times, has randomness properties that can find applications in cryptography, key distribution, and other problems of computer science. It is shown that the...	false	false	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	19,152
2211.16029	Diverse Multi-Answer Retrieval with Determinantal Point Processes	Often questions provided to open-domain question answering systems are ambiguous. Traditional QA systems that provide a single answer are incapable of answering ambiguous questions since the question may be interpreted in several ways and may have multiple distinct answers. In this paper, we address multi-answer retrie...	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	false	false	333,493
2402.07878	Using Graph Theory for Improving Machine Learning-based Detection of Cyber Attacks	Early detection of network intrusions and cyber threats is one of the main pillars of cybersecurity. One of the most effective approaches for this purpose is to analyze network traffic with the help of artificial intelligence algorithms, with the aim of detecting the possible presence of an attacker by distinguishing i...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	428,881
1011.0786	Gaussian Process Techniques for Wireless Communications	Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. Classical solutions such that Kalman filter and Particle filter are introduced in this report. Gaussian processes have been introduced as a non-parametric technique for system estimation from supervision learning. For ...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	8,125
1207.4860	Inference of Extreme Synchrony with an Entropy Measure on a Bipartite Network	This article proposes a method to quantify the structure of a bipartite graph using a network entropy per link. The network entropy of a bipartite graph with random links is calculated both numerically and theoretically. As an application of the proposed method to analyze collective behavior, the affairs in which parti...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	17,675
2002.09056	Contact-less manipulation of millimeter-scale objects via ultrasonic levitation	Although general purpose robotic manipulators are becoming more capable at manipulating various objects, their ability to manipulate millimeter-scale objects are usually very limited. On the other hand, ultrasonic levitation devices have been shown to levitate a large range of small objects, from polystyrene balls to l...	false	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	164,952
2211.16234	SimCS: Simulation for Domain Incremental Online Continual Segmentation	Continual Learning is a step towards lifelong intelligence where models continuously learn from recently collected data without forgetting previous knowledge. Existing continual learning approaches mostly focus on image classification in the class-incremental setup with clear task boundaries and unlimited computational...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	333,566
1903.01552	1D Convolutional Neural Network Models for Sleep Arousal Detection	Sleep arousals transition the depth of sleep to a more superficial stage. The occurrence of such events is often considered as a protective mechanism to alert the body of harmful stimuli. Thus, accurate sleep arousal detection can lead to an enhanced understanding of the underlying causes and influencing the assessment...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	123,281
1009.4610	Performance Analysis and Design of Two Edge Type LDPC Codes for the BEC Wiretap Channel	We consider transmission over a wiretap channel where both the main channel and the wiretapper's channel are Binary Erasure Channels (BEC). We propose a code construction method using two edge type LDPC codes based on the coset encoding scheme. Using a standard LDPC ensemble with a given threshold over the BEC, we give...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	7,638
2406.04268	Open-Endedness is Essential for Artificial Superhuman Intelligence	In recent years there has been a tremendous surge in the general capabilities of AI systems, mainly fuelled by training foundation models on internetscale data. Nevertheless, the creation of openended, ever self-improving AI remains elusive. In this position paper, we argue that the ingredients are now in place to achi...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	461,593
1905.12660	Training Generative Adversarial Networks from Incomplete Observations using Factorised Discriminators	Generative adversarial networks (GANs) have shown great success in applications such as image generation and inpainting. However, they typically require large datasets, which are often not available, especially in the context of prediction tasks such as image segmentation that require labels. Therefore, methods such as...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,828
2007.16150	Network connectivity optimization: An evaluation of heuristics applied to complex networks and a transportation case study	Network optimization has generally been focused on solving network flow problems, but recently there have been investigations into optimizing network characteristics. Optimizing network connectivity to maximize the number of nodes within a given distance to a focal node and then minimizing the number and length of addi...	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	189,861
2205.00541	COUCH: Towards Controllable Human-Chair Interactions	Humans interact with an object in many different ways by making contact at different locations, creating a highly complex motion space that can be difficult to learn, particularly when synthesizing such human interactions in a controllable manner. Existing works on synthesizing human scene interaction focus on the high...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	294,297
2008.01883	When is invariance useful in an Out-of-Distribution Generalization problem ?	The goal of Out-of-Distribution (OOD) generalization problem is to train a predictor that generalizes on all environments. Popular approaches in this field use the hypothesis that such a predictor shall be an \textit{invariant predictor} that captures the mechanism that remains constant across environments. While these...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	190,457
2206.13238	SR-DEM: an efficient discrete element method for particles with surface of revolution	In this paper, the surface of revolution discrete element method (SR-DEM) is introduced to simulate systems of particles with closed surfaces of revolution. Due to the cylindrical symmetry of a surface of revolution, the geometry of any cross-section about the axis of rotation remains the same. Taking advantage of this...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	304,886
2305.02309	CodeGen2: Lessons for Training LLMs on Programming and Natural Languages	Large language models (LLMs) have demonstrated remarkable abilities in representation learning for program synthesis and understanding tasks. The quality of the learned representations appears to be dictated by the neural scaling laws as a function of the number of model parameters and observations, while imposing uppe...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	361,988
2312.03558	When an Image is Worth 1,024 x 1,024 Words: A Case Study in Computational Pathology	This technical report presents LongViT, a vision Transformer that can process gigapixel images in an end-to-end manner. Specifically, we split the gigapixel image into a sequence of millions of patches and project them linearly into embeddings. LongNet is then employed to model the extremely long sequence, generating r...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	413,304
1803.04474	Predicting Crime Using Spatial Features	Our study aims to build a machine learning model for crime prediction using geospatial features for different categories of crime. The reverse geocoding technique is applied to retrieve open street map (OSM) spatial data. This study also proposes finding hotpoints extracted from crime hotspots area found by Hierarchica...	false	false	false	false	true	false	false	false	false	false	false	false	false	true	false	false	false	false	92,458
1707.05720	Grounding Spatio-Semantic Referring Expressions for Human-Robot Interaction	The human language is one of the most natural interfaces for humans to interact with robots. This paper presents a robot system that retrieves everyday objects with unconstrained natural language descriptions. A core issue for the system is semantic and spatial grounding, which is to infer objects and their spatial rel...	false	false	false	false	true	false	false	true	true	false	false	false	false	false	false	false	false	false	77,285
1910.12074	Intrusion Detection using Sequential Hybrid Model	A large amount of work has been done on the KDD 99 dataset, most of which includes the use of a hybrid anomaly and misuse detection model done in parallel with each other. In order to further classify the intrusions, our approach to network intrusion detection includes use of two different anomaly detection models foll...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	150,965
2404.15352	TransfoRhythm: A Transformer Architecture Conductive to Blood Pressure Estimation via Solo PPG Signal Capturing	Recent statistics indicate that approximately 1.3 billion individuals worldwide suffer from hypertension, a leading cause of premature death globally. Blood Pressure (BP) serves as a critical health indicator for accurate and timely diagnosis and/or treatment of hypertension. Traditional BP measurement methods rely on ...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,062
2409.11634	Learning-accelerated A* Search for Risk-aware Path Planning	Safety is a critical concern for urban flights of autonomous Unmanned Aerial Vehicles. In populated environments, risk should be accounted for to produce an effective and safe path, known as risk-aware path planning. Risk-aware path planning can be modeled as a Constrained Shortest Path (CSP) problem, aiming to identif...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	489,243
1905.10194	Memorized Sparse Backpropagation	Neural network learning is usually time-consuming since backpropagation needs to compute full gradients and backpropagate them across multiple layers. Despite its success of existing works in accelerating propagation through sparseness, the relevant theoretical characteristics remain under-researched and empirical stud...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	131,987
2107.01833	Age of Information in Relay-Assisted Status Updating Systems	In this paper we consider the age of information (AoI) of a status updating system with a relay, where the updates are delivered to destination either from the direct line or the two-hop link via the relay. An updating packet generated at source is sent to receiver and the relay simultaneously. When the direct packet t...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	244,611
1902.00679	Natural Language Processing, Sentiment Analysis and Clinical Analytics	Recent advances in Big Data has prompted health care practitioners to utilize the data available on social media to discern sentiment and emotions expression. Health Informatics and Clinical Analytics depend heavily on information gathered from diverse sources. Traditionally, a healthcare practitioner will ask a patien...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	120,476
2406.15085	Evaluating Input Feature Explanations through a Unified Diagnostic Evaluation Framework	Explaining the decision-making process of machine learning models is crucial for ensuring their reliability and transparency for end users. One popular explanation form highlights key input features, such as i) tokens (e.g., Shapley Values and Integrated Gradients), ii) interactions between tokens (e.g., Bivariate Shap...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	466,611
1904.08760	Cursive Multilingual Characters Recognition Based on Hard Geometric Features	The cursive nature of multilingual characters segmentation and recognition of Arabic, Persian, Urdu languages have attracted researchers from academia and industry. However, despite several decades of research, still multilingual characters classification accuracy is not up to the mark. This paper presents an automated...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	128,170
2403.12471	Theoretical Modeling and Bio-inspired Trajectory Optimization of A Multiple-locomotion Origami Robot	Recent research on mobile robots has focused on increasing their adaptability to unpredictable and unstructured environments using soft materials and structures. However, the determination of key design parameters and control over these compliant robots are predominantly iterated through experiments, lacking a solid th...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	439,201
2108.03632	Deep Neural Network for DrawiNg Networks, (DNN)^2	By leveraging recent progress of stochastic gradient descent methods, several works have shown that graphs could be efficiently laid out through the optimization of a tailored objective function. In the meantime, Deep Learning (DL) techniques achieved great performances in many applications. We demonstrate that it is p...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	249,730
1905.10672	Signaling Friends and Head-Faking Enemies Simultaneously: Balancing Goal Obfuscation and Goal Legibility	In order to be useful in the real world, AI agents need to plan and act in the presence of others, who may include adversarial and cooperative entities. In this paper, we consider the problem where an autonomous agent needs to act in a manner that clarifies its objectives to cooperative entities while preventing advers...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	132,142
1912.04138	A Weak Supervision Approach to Detecting Visual Anomalies for Automated Testing of Graphics Units	We present a deep learning system for testing graphics units by detecting novel visual corruptions in videos. Unlike previous work in which manual tagging was required to collect labeled training data, our weak supervision method is fully automatic and needs no human labelling. This is achieved by reproducing driver bu...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	156,772
1705.04402	Negative Results in Computer Vision: A Perspective	A negative result is when the outcome of an experiment or a model is not what is expected or when a hypothesis does not hold. Despite being often overlooked in the scientific community, negative results are results and they carry value. While this topic has been extensively discussed in other fields such as social scie...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	73,328
1910.05653	Model Fusion via Optimal Transport	Combining different models is a widely used paradigm in machine learning applications. While the most common approach is to form an ensemble of models and average their individual predictions, this approach is often rendered infeasible by given resource constraints in terms of memory and computation, which grow linearl...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	149,133
1902.00163	Lift-the-flap: what, where and when for context reasoning	Context reasoning is critical in a wide variety of applications where current inputs need to be interpreted in the light of previous experience and knowledge. Both spatial and temporal contextual information play a critical role in the domain of visual recognition. Here we investigate spatial constraints (what image fe...	false	false	false	false	true	false	false	false	false	false	false	true	false	false	false	false	false	false	120,337
1602.03348	Iterative Hierarchical Optimization for Misspecified Problems (IHOMP)	For complex, high-dimensional Markov Decision Processes (MDPs), it may be necessary to represent the policy with function approximation. A problem is misspecified whenever, the representation cannot express any policy with acceptable performance. We introduce IHOMP : an approach for solving misspecified problems. IHOMP...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	51,989
1909.11074	Power Allocation in Cache-Aided NOMA Systems: Optimization and Deep Reinforcement Learning Approaches	This work exploits the advantages of two prominent techniques in future communication networks, namely caching and non-orthogonal multiple access (NOMA). Particularly, a system with Rayleigh fading channels and cache-enabled users is analyzed. It is shown that the caching-NOMA combination provides a new opportunity of ...	false	false	false	false	false	false	true	false	false	true	false	false	false	false	false	false	false	true	146,705
2302.12251	VoxFormer: Sparse Voxel Transformer for Camera-based 3D Semantic Scene Completion	Humans can easily imagine the complete 3D geometry of occluded objects and scenes. This appealing ability is vital for recognition and understanding. To enable such capability in AI systems, we propose VoxFormer, a Transformer-based semantic scene completion framework that can output complete 3D volumetric semantics fr...	false	false	false	false	true	false	true	true	false	false	false	true	false	false	false	false	false	false	347,496
2408.11554	Differentiating Choices via Commonality for Multiple-Choice Question Answering	Multiple-choice question answering (MCQA) becomes particularly challenging when all choices are relevant to the question and are semantically similar. Yet this setting of MCQA can potentially provide valuable clues for choosing the right answer. Existing models often rank each choice separately, overlooking the context...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	482,341
0911.5508	Codes on graphs: Duality and MacWilliams identities	A conceptual framework involving partition functions of normal factor graphs is introduced, paralleling a similar recent development by Al-Bashabsheh and Mao. The partition functions of dual normal factor graphs are shown to be a Fourier transform pair, whether or not the graphs have cycles. The original normal graph d...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	5,044
2201.11181	Searching, Learning, and Subtopic Ordering: A Simulation-based Analysis	Complex search tasks - such as those from the Search as Learning (SAL) domain - often result in users developing an information need composed of several aspects. However, current models of searcher behaviour assume that individuals have an atomic need, regardless of the task. While these models generally work well for ...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	277,208
2011.12785	Regret-optimal measurement-feedback control	We consider measurement-feedback control in linear dynamical systems from the perspective of regret minimization. Unlike most prior work in this area, we focus on the problem of designing an online controller which competes with the optimal dynamic sequence of control actions selected in hindsight, instead of the best ...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	208,268
2010.12970	Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy	Denoising is a fundamental challenge in scientific imaging. Deep convolutional neural networks (CNNs) provide the current state of the art in denoising natural images, where they produce impressive results. However, their potential has barely been explored in the context of scientific imaging. Denoising CNNs are typica...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	202,947
2012.10959	Physical Implementability of Linear Maps and Its Application in Error Mitigation	Completely positive and trace-preserving maps characterize physically implementable quantum operations. On the other hand, general linear maps, such as positive but not completely positive maps, which can not be physically implemented, are fundamental ingredients in quantum information, both in theoretical and practica...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	212,492
2401.01575	Enhancing Generalization of Invisible Facial Privacy Cloak via Gradient Accumulation	The blooming of social media and face recognition (FR) systems has increased people's concern about privacy and security. A new type of adversarial privacy cloak (class-universal) can be applied to all the images of regular users, to prevent malicious FR systems from acquiring their identity information. In this work, ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	419,415
2106.04172	Contention-based Grant-free Transmission with Extremely Sparse Orthogonal Pilot Scheme	Due to the limited number of traditional orthogonal pilots, pilot collision will severely degrade the performance of contention-based grant-free transmission. To alleviate the pilot collision and exploit the spatial degree of freedom as much as possible, an extremely sparse orthogonal pilot scheme is proposed for uplin...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	239,616
2410.19414	Motion Planning for Robotics: A Review for Sampling-based Planners	Recent advancements in robotics have transformed industries such as manufacturing, logistics, surgery, and planetary exploration. A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex environments while avoiding collisions and optimizing metrics like path length, sweep...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	502,301
2412.09224	DASK: Distribution Rehearsing via Adaptive Style Kernel Learning for Exemplar-Free Lifelong Person Re-Identification	Lifelong person re-identification (LReID) is an important but challenging task that suffers from catastrophic forgetting due to significant domain gaps between training steps. Existing LReID approaches typically rely on data replay and knowledge distillation to mitigate this issue. However, data replay methods compromi...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	516,403
1808.08983	NeuralCubes: Deep Representations for Visual Data Exploration	Visual exploration of large multidimensional datasets has seen tremendous progress in recent years, allowing users to express rich data queries that produce informative visual summaries, all in real time. Techniques based on data cubes are some of the most promising approaches. However, these techniques usually require...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	106,077
2207.05837	Learning Bellman Complete Representations for Offline Policy Evaluation	We study representation learning for Offline Reinforcement Learning (RL), focusing on the important task of Offline Policy Evaluation (OPE). Recent work shows that, in contrast to supervised learning, realizability of the Q-function is not enough for learning it. Two sufficient conditions for sample-efficient OPE are B...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	307,681
2302.09959	Price of Anarchy in a Double-Sided Critical Distribution System	Measures of allocation optimality differ significantly when distributing standard tradable goods in peaceful times and scarce resources in crises. While realistic markets offer asymptotic efficiency, they may not necessarily guarantee fair allocation desirable when distributing the critical resources. To achieve fairne...	false	false	false	false	false	false	false	false	false	false	false	false	false	false	true	false	false	true	346,638
1810.11152	Efficient and High-Quality Seeded Graph Matching: Employing High Order Structural Information	Driven by many real applications, we study the problem of seeded graph matching. Given two graphs $G_1 = (V_1, E_1)$ and $G_2 = (V_2, E_2)$, and a small set $S$ of pre-matched node pairs $[u, v]$ where $u \in V_1$ and $v \in V_2$, the problem is to identify a matching between $V_1$ and $V_2$ growing from $S$, such that...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	true	true	111,438
1306.5707	Synthesizing Manipulation Sequences for Under-Specified Tasks using Unrolled Markov Random Fields	Many tasks in human environments require performing a sequence of navigation and manipulation steps involving objects. In unstructured human environments, the location and configuration of the objects involved often change in unpredictable ways. This requires a high-level planning strategy that is robust and flexible i...	false	false	false	false	true	false	true	true	false	false	false	false	false	false	false	false	false	false	25,427
2206.12562	PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance	Large Transformer-based models have exhibited superior performance in various natural language processing and computer vision tasks. However, these models contain enormous amounts of parameters, which restrict their deployment to real-world applications. To reduce the model size, researchers prune these models based on...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	304,648
1605.01207	Ontology-Mediated Queries: Combined Complexity and Succinctness of Rewritings via Circuit Complexity	We give solutions to two fundamental computational problems in ontology-based data access with the W3C standard ontology language OWL 2 QL: the succinctness problem for first-order rewritings of ontology-mediated queries (OMQs), and the complexity problem for OMQ answering. We classify OMQs according to the shape of th...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	true	true	55,451
1806.01044	A Desirability-Based Axiomatisation for Coherent Choice Functions	Choice functions constitute a simple, direct and very general mathematical framework for modelling choice under uncertainty. In particular, they are able to represent the set-valued choices that typically arise from applying decision rules to imprecise-probabilistic uncertainty models. We provide them with a clear inte...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	99,468
2007.15602	Heatmap-based Vanishing Point boosts Lane Detection	Vision-based lane detection (LD) is a key part of autonomous driving technology, and it is also a challenging problem. As one of the important constraints of scene composition, vanishing point (VP) may provide a useful clue for lane detection. In this paper, we proposed a new multi-task fusion network architecture for ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	189,709
1804.09364	Driving Policy Transfer via Modularity and Abstraction	End-to-end approaches to autonomous driving have high sample complexity and are difficult to scale to realistic urban driving. Simulation can help end-to-end driving systems by providing a cheap, safe, and diverse training environment. Yet training driving policies in simulation brings up the problem of transferring su...	false	false	false	false	false	false	true	true	false	false	false	true	false	false	false	false	false	false	95,961

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