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
2005.09862	A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition	Building a good speech recognition system usually requires large amounts of transcribed data, which is expensive to collect. To tackle this problem, many unsupervised pre-training methods have been proposed. Among these methods, Masked Predictive Coding achieved significant improvements on various speech recognition da...	false	false	true	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	178,021
2103.05028	Fast and Effective Biomedical Entity Linking Using a Dual Encoder	Biomedical entity linking is the task of identifying mentions of biomedical concepts in text documents and mapping them to canonical entities in a target thesaurus. Recent advancements in entity linking using BERT-based models follow a retrieve and rerank paradigm, where the candidate entities are first selected using ...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	223,829
1410.2386	Bayesian Robust Tensor Factorization for Incomplete Multiway Data	We propose a generative model for robust tensor factorization in the presence of both missing data and outliers. The objective is to explicitly infer the underlying low-CP-rank tensor capturing the global information and a sparse tensor capturing the local information (also considered as outliers), thus providing the r...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	36,612
0809.1257	The Golden Ratio Encoder	This paper proposes a novel Nyquist-rate analog-to-digital (A/D) conversion algorithm which achieves exponential accuracy in the bit-rate despite using imperfect components. The proposed algorithm is based on a robust implementation of a beta-encoder where the value of the base beta is equal to golden mean. It was prev...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	2,306
2203.01440	Near-Optimal Correlation Clustering with Privacy	Correlation clustering is a central problem in unsupervised learning, with applications spanning community detection, duplicate detection, automated labelling and many more. In the correlation clustering problem one receives as input a set of nodes and for each node a list of co-clustering preferences, and the goal is ...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	true	283,373
2209.01880	ScaleFace: Uncertainty-aware Deep Metric Learning	The performance of modern deep learning-based systems dramatically depends on the quality of input objects. For example, face recognition quality would be lower for blurry or corrupted inputs. However, it is hard to predict the influence of input quality on the resulting accuracy in more complex scenarios. We propose a...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	316,042
2212.03968	Multimodal Vision Transformers with Forced Attention for Behavior Analysis	Human behavior understanding requires looking at minute details in the large context of a scene containing multiple input modalities. It is necessary as it allows the design of more human-like machines. While transformer approaches have shown great improvements, they face multiple challenges such as lack of data or bac...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	335,278
2311.00233	Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions	While instruction-tuned language models have demonstrated impressive zero-shot generalization, these models often struggle to generate accurate responses when faced with instructions that fall outside their training set. This paper presents Instructive Decoding (ID), a simple yet effective approach that augments the ef...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	404,559
2306.05079	Enhancing Robustness of AI Offensive Code Generators via Data Augmentation	Since manually writing software exploits for offensive security is time-consuming and requires expert knowledge, AI-base code generators are an attractive solution to enhance security analysts' productivity by automatically crafting exploits for security testing. However, the variability in the natural language and tec...	false	false	false	false	false	false	true	false	true	false	false	false	true	false	false	false	false	false	372,045
0902.1080	A Model for Managing Collections of Patterns	Data mining algorithms are now able to efficiently deal with huge amount of data. Various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. In many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	3,120
1711.02783	Learning to Imagine Manipulation Goals for Robot Task Planning	Prospection is an important part of how humans come up with new task plans, but has not been explored in depth in robotics. Predicting multiple task-level is a challenging problem that involves capturing both task semantics and continuous variability over the state of the world. Ideally, we would combine the ability of...	false	false	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	84,116
2411.12154	Tangential Randomization in Linear Bandits (TRAiL): Guaranteed Inference and Regret Bounds	We propose and analyze TRAiL (Tangential Randomization in Linear Bandits), a computationally efficient regret-optimal forced exploration algorithm for linear bandits on action sets that are sublevel sets of strongly convex functions. TRAiL estimates the governing parameter of the linear bandit problem through a standar...	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	509,311
2309.13398	A mirror-Unet architecture for PET/CT lesion segmentation	Automatic lesion detection and segmentation from [${}^{18}$F]FDG PET/CT scans is a challenging task, due to the diversity of shapes, sizes, FDG uptake and location they may present, besides the fact that physiological uptake is also present on healthy tissues. In this work, we propose a deep learning method aimed at th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	394,190
2302.13435	Scalable Weight Reparametrization for Efficient Transfer Learning	This paper proposes a novel, efficient transfer learning method, called Scalable Weight Reparametrization (SWR) that is efficient and effective for multiple downstream tasks. Efficient transfer learning involves utilizing a pre-trained model trained on a larger dataset and repurposing it for downstream tasks with the a...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	347,947
2105.13777	Linear Complexity of Binary Interleaved Sequences of Period 4n	Binary periodic sequences with good autocorrelation property have many applications in many aspects of communication. In past decades many series of such binary sequences have been constructed. In the application of cryptography, such binary sequences are required to have larger linear complexity. Tang and Ding \cite{X...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	237,400
2207.08303	A Novel Composite Resilience Indicator for Decentralized Infrastructure Systems (CRI-DS)	Resilience is a key driver for planning adaptation strategies to mitigate risks due to both natural and anthropogenic hazards. The effectiveness of a resilience-driven decision-making strategy for adapting systems against stressors depends on how resilience is mapped to decision variables. This requires a functional re...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	308,535
2403.01766	Improving Visual Perception of a Social Robot for Controlled and In-the-wild Human-robot Interaction	Social robots often rely on visual perception to understand their users and the environment. Recent advancements in data-driven approaches for computer vision have demonstrated great potentials for applying deep-learning models to enhance a social robot's visual perception. However, the high computational demands of de...	false	false	false	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	434,564
2302.01241	Diagrammatization: Rationalizing with diagrammatic AI explanations for abductive-deductive reasoning on hypotheses	Many visualizations have been developed for explainable AI (XAI), but they often require further reasoning by users to interpret. We argue that XAI should support diagrammatic and abductive reasoning for the AI to perform hypothesis generation and evaluation to reduce the interpretability gap. We propose Diagrammatizat...	true	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	343,531
2204.02824	ShowFace: Coordinated Face Inpainting with Memory-Disentangled Refinement Networks	Face inpainting aims to complete the corrupted regions of the face images, which requires coordination between the completed areas and the non-corrupted areas. Recently, memory-oriented methods illustrate great prospects in the generation related tasks by introducing an external memory module to improve image coordinat...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	290,098
1412.5718	Revisiting Non-Progressive Influence Models: Scalable Influence Maximization	While influence maximization in social networks has been studied extensively in computer science community for the last decade the focus has been on the progressive influence models, such as independent cascade (IC) and Linear threshold (LT) models, which cannot capture the reversibility of choices. In this paper, we p...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	38,521
2412.18380	RSGaussian:3D Gaussian Splatting with LiDAR for Aerial Remote Sensing Novel View Synthesis	This study presents RSGaussian, an innovative novel view synthesis (NVS) method for aerial remote sensing scenes that incorporate LiDAR point cloud as constraints into the 3D Gaussian Splatting method, which ensures that Gaussians grow and split along geometric benchmarks, addressing the overgrowth and floaters issues ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	520,401
2202.03631	Robotic Grasping from Classical to Modern: A Survey	Robotic Grasping has always been an active topic in robotics since grasping is one of the fundamental but most challenging skills of robots. It demands the coordination of robotic perception, planning, and control for robustness and intelligence. However, current solutions are still far behind humans, especially when c...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	279,282
2112.04720	Amicable Aid: Perturbing Images to Improve Classification Performance	While adversarial perturbation of images to attack deep image classification models pose serious security concerns in practice, this paper suggests a novel paradigm where the concept of image perturbation can benefit classification performance, which we call amicable aid. We show that by taking the opposite search dire...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	270,622
2304.04217	The Study of Highway for Lifelong Multi-Agent Path Finding	In modern fulfillment warehouses, agents traverse the map to complete endless tasks that arrive on the fly, which is formulated as a lifelong Multi-Agent Path Finding (lifelong MAPF) problem. The goal of tackling this challenging problem is to find the path for each agent in a finite runtime while maximizing the throug...	false	false	false	false	true	false	false	true	false	false	false	false	false	false	true	false	false	false	357,134
2406.07236	Let Go of Your Labels with Unsupervised Transfer	Foundation vision-language models have enabled remarkable zero-shot transferability of the pre-trained representations to a wide range of downstream tasks. However, to solve a new task, zero-shot transfer still necessitates human guidance to define visual categories that appear in the data. Here, we show that fully uns...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	462,956
2302.07453	Cooperative Driving for Speed Harmonization in Mixed-Traffic Environments	Autonomous driving systems present promising methods for congestion mitigation in mixed autonomy traffic control settings. In particular, when coupled with even modest traffic state estimates, such systems can plan and coordinate the behaviors of automated vehicles (AVs) in response to observed downstream events, there...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	345,736
2403.15855	Initialisation and Network Effects in Decentralised Federated Learning	Fully decentralised federated learning enables collaborative training of individual machine learning models on a distributed network of communicating devices while keeping the training data localised on each node. This approach avoids central coordination, enhances data privacy and eliminates the risk of a single point...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	true	440,775
2305.09276	Noise robust neural network architecture	In which we propose neural network architecture (dune neural network) for recognizing general noisy image without adding any artificial noise in the training data. By representing each free parameter of the network as an uncertainty interval, and applying a linear transformation to each input element, we show that the ...	false	false	false	false	true	false	true	false	false	false	false	true	false	false	false	false	false	false	364,584
2207.13779	Physical Pooling Functions in Graph Neural Networks for Molecular Property Prediction	Graph neural networks (GNNs) are emerging in chemical engineering for the end-to-end learning of physicochemical properties based on molecular graphs. A key element of GNNs is the pooling function which combines atom feature vectors into molecular fingerprints. Most previous works use a standard pooling function to pre...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	310,395
1805.11749	Unsupervised Text Style Transfer using Language Models as Discriminators	Binary classifiers are often employed as discriminators in GAN-based unsupervised style transfer systems to ensure that transferred sentences are similar to sentences in the target domain. One difficulty with this approach is that the error signal provided by the discriminator can be unstable and is sometimes insuffici...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	98,997
2007.03496	AutoAssign: Differentiable Label Assignment for Dense Object Detection	Determining positive/negative samples for object detection is known as label assignment. Here we present an anchor-free detector named AutoAssign. It requires little human knowledge and achieves appearance-aware through a fully differentiable weighting mechanism. During training, to both satisfy the prior distribution ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	186,071
2207.03197	SPR:Supervised Personalized Ranking Based on Prior Knowledge for Recommendation	The goal of a recommendation system is to model the relevance between each user and each item through the user-item interaction history, so that maximize the positive samples score and minimize negative samples. Currently, two popular loss functions are widely used to optimize recommender systems: the pointwise and the...	false	false	false	false	true	true	false	false	false	false	false	false	false	false	false	false	false	false	306,760
2308.03565	Topological Interpretations of GPT-3	This is an experiential study of investigating a consistent method for deriving the correlation between sentence vector and semantic meaning of a sentence. We first used three state-of-the-art word/sentence embedding methods including GPT-3, Word2Vec, and Sentence-BERT, to embed plain text sentence strings into high di...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	384,082
2407.12814	Computational Politeness in Natural Language Processing: A Survey	Computational approach to politeness is the task of automatically predicting and generating politeness in text. This is a pivotal task for conversational analysis, given the ubiquity and challenges of politeness in interactions. The computational approach to politeness has witnessed great interest from the conversation...	false	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	474,091
2209.12430	$O(T^{-1})$ Convergence of Optimistic-Follow-the-Regularized-Leader in Two-Player Zero-Sum Markov Games	We prove that optimistic-follow-the-regularized-leader (OFTRL), together with smooth value updates, finds an $O(T^{-1})$-approximate Nash equilibrium in $T$ iterations for two-player zero-sum Markov games with full information. This improves the $\tilde{O}(T^{-5/6})$ convergence rate recently shown in the paper Zhang e...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	319,534
2205.03676	Empathetic Response Generation with State Management	A good empathetic dialogue system should first track and understand a user's emotion and then reply with an appropriate emotion. However, current approaches to this task either focus on improving the understanding of users' emotion or on proposing better responding strategies, and very few works consider both at the sa...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	295,373
1712.04006	Training Ensembles to Detect Adversarial Examples	We propose a new ensemble method for detecting and classifying adversarial examples generated by state-of-the-art attacks, including DeepFool and C&W. Our method works by training the members of an ensemble to have low classification error on random benign examples while simultaneously minimizing agreement on examples ...	false	false	false	false	false	false	true	false	false	false	false	true	true	false	false	false	false	false	86,530
1905.01326	Single Image 3D Hand Reconstruction with Mesh Convolutions	Monocular 3D reconstruction of deformable objects, such as human body parts, has been typically approached by predicting parameters of heavyweight linear models. In this paper, we demonstrate an alternative solution that is based on the idea of encoding images into a latent non-linear representation of meshes. The prio...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	129,693
2409.14778	Human Hair Reconstruction with Strand-Aligned 3D Gaussians	We introduce a new hair modeling method that uses a dual representation of classical hair strands and 3D Gaussians to produce accurate and realistic strand-based reconstructions from multi-view data. In contrast to recent approaches that leverage unstructured Gaussians to model human avatars, our method reconstructs th...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	true	490,627
2409.19587	Efficient Quality Control of Whole Slide Pathology Images with Human-in-the-loop Training	Histopathology whole slide images (WSIs) are being widely used to develop deep learning-based diagnostic solutions, especially for precision oncology. Most of these diagnostic softwares are vulnerable to biases and impurities in the training and test data which can lead to inaccurate diagnoses. For instance, WSIs conta...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	492,754
1711.09057	Cooperative Multi-Agent Planning: A Survey	Cooperative multi-agent planning (MAP) is a relatively recent research field that combines technologies, algorithms and techniques developed by the Artificial Intelligence Planning and Multi-Agent Systems communities. While planning has been generally treated as a single-agent task, MAP generalizes this concept by cons...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	true	false	false	false	85,316
2411.01248	Guiding Neural Collapse: Optimising Towards the Nearest Simplex Equiangular Tight Frame	Neural Collapse (NC) is a recently observed phenomenon in neural networks that characterises the solution space of the final classifier layer when trained until zero training loss. Specifically, NC suggests that the final classifier layer converges to a Simplex Equiangular Tight Frame (ETF), which maximally separates t...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	504,983
2412.11763	QUENCH: Measuring the gap between Indic and Non-Indic Contextual General Reasoning in LLMs	The rise of large language models (LLMs) has created a need for advanced benchmarking systems beyond traditional setups. To this end, we introduce QUENCH, a novel text-based English Quizzing Benchmark manually curated and transcribed from YouTube quiz videos. QUENCH possesses masked entities and rationales for the LLMs...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	517,573
2501.04719	Calculating Customer Lifetime Value and Churn using Beta Geometric Negative Binomial and Gamma-Gamma Distribution in a NFT based setting	Customer Lifetime Value (CLV) is an important metric that measures the total value a customer will bring to a business over their lifetime. The Beta Geometric Negative Binomial Distribution (BGNBD) and Gamma Gamma Distribution are two models that can be used to calculate CLV, taking into account both the frequency and ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	523,317
2408.03754	A Soft Robotic System Automatically Learns Precise Agile Motions Without Model Information	Many application domains, e.g., in medicine and manufacturing, can greatly benefit from pneumatic Soft Robots (SRs). However, the accurate control of SRs has remained a significant challenge to date, mainly due to their nonlinear dynamics and viscoelastic material properties. Conventional control design methods often r...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	479,141
2502.04419	Understanding and Mitigating the Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks	Generating synthetic datasets via large language models (LLMs) themselves has emerged as a promising approach to improve LLM performance. However, LLMs inherently reflect biases present in their training data, leading to a critical challenge: when these models generate synthetic data for training, they may propagate an...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	531,155
2308.10592	BAN-PL: a Novel Polish Dataset of Banned Harmful and Offensive Content from Wykop.pl web service	Since the Internet is flooded with hate, it is one of the main tasks for NLP experts to master automated online content moderation. However, advancements in this field require improved access to publicly available accurate and non-synthetic datasets of social media content. For the Polish language, such resources are v...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	386,798
1905.10601	TableNet: a multiplier-less implementation of neural networks for inferencing	We consider the use of look-up tables (LUT) to simplify the hardware implementation of a deep learning network for inferencing after weights have been successfully trained. The use of LUT replaces the matrix multiply and add operations with a small number of LUTs and addition operations resulting in a completely multip...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	132,116
2104.01672	Topological Information Retrieval with Dilation-Invariant Bottleneck Comparative Measures	Appropriately representing elements in a database so that queries may be accurately matched is a central task in information retrieval; recently, this has been achieved by embedding the graphical structure of the database into a manifold in a hierarchy-preserving manner using a variety of metrics. Persistent homology i...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	228,431
1412.1340	On spin scale-discretised wavelets on the sphere for the analysis of CMB polarisation	A new spin wavelet transform on the sphere is proposed to analyse the polarisation of the cosmic microwave background (CMB), a spin $\pm 2$ signal observed on the celestial sphere. The scalar directional scale-discretised wavelet transform on the sphere is extended to analyse signals of arbitrary spin. The resulting sp...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	38,095
2004.07300	Gumbel-softmax-based Optimization: A Simple General Framework for Optimization Problems on Graphs	In computer science, there exist a large number of optimization problems defined on graphs, that is to find a best node state configuration or a network structure such that the designed objective function is optimized under some constraints. However, these problems are notorious for their hardness to solve because most...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	172,740
1301.6956	The Capacity of Wireless Channels: A Physical Approach	In this paper, the capacity of wireless channels is characterized based on electromagnetic and antenna theories with only minimal assumptions. We assume the transmitter can generate an arbitrary current distribution inside a spherical region and the receive antennas are uniformly distributed on a bigger sphere surround...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	21,570
2409.01957	Power Control and Random Serving Mode Allocation for CJT-NCJT Hybrid Mode Enabled Cell-Free Massive MIMO With Limited Fronthauls	With a great potential of improving the service fairness and quality for user equipments (UEs), cell-free massive multiple-input multiple-output (mMIMO) has been regarded as an emerging candidate for 6G network architectures. Under ideal assumptions, the coherent joint transmission (CJT) serving mode has been considere...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	485,522
2303.09117	Cross-Modal Causal Intervention for Medical Report Generation	Medical report generation (MRG) is essential for computer-aided diagnosis and medication guidance, which can relieve the heavy burden of radiologists by automatically generating the corresponding medical reports according to the given radiology image. However, due to the spurious correlations within image-text data ind...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	351,918
2402.14411	J-UniMorph: Japanese Morphological Annotation through the Universal Feature Schema	We introduce a Japanese Morphology dataset, J-UniMorph, developed based on the UniMorph feature schema. This dataset addresses the unique and rich verb forms characteristic of the language's agglutinative nature. J-UniMorph distinguishes itself from the existing Japanese subset of UniMorph, which is automatically extra...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	431,678
2303.13948	Knowledge Graphs: Opportunities and Challenges	With the explosive growth of artificial intelligence (AI) and big data, it has become vitally important to organize and represent the enormous volume of knowledge appropriately. As graph data, knowledge graphs accumulate and convey knowledge of the real world. It has been well-recognized that knowledge graphs effective...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	353,895
2303.13479	IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformation	Category-level 6D pose estimation aims to predict the poses and sizes of unseen objects from a specific category. Thanks to prior deformation, which explicitly adapts a category-specific 3D prior (i.e., a 3D template) to a given object instance, prior-based methods attained great success and have become a major researc...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	353,680
2305.00646	Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction	Direct mesh fitting for 3D hand shape reconstruction is highly accurate. However, the reconstructed meshes are prone to artifacts and do not appear as plausible hand shapes. Conversely, parametric models like MANO ensure plausible hand shapes but are not as accurate as the non-parametric methods. In this work, we intro...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	361,411
cs/0602014	Game theoretic aspects of distributed spectral coordination with application to DSL networks	In this paper we use game theoretic techniques to study the value of cooperation in distributed spectrum management problems. We show that the celebrated iterative water-filling algorithm is subject to the prisoner's dilemma and therefore can lead to severe degradation of the achievable rate region in an interference c...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,252
1912.12367	Illumination Robust Loop Closure Detection with the Constraint of Pose	Background: Loop closure detection is a crucial part in robot navigation and simultaneous location and mapping (SLAM). Appearance-based loop closure detection still faces many challenges, such as illumination changes, perceptual aliasing and increasing computational complexity. Method: In this paper, we proposed a visu...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	158,825
1710.03575	A Multi-Objective DIRECT Algorithm Towards Structural Damage Identification with Limited Dynamic Response Information	A major challenge in Structural Health Monitoring (SHM) is to accurately identify both the location and severity of damage using the dynamic response information acquired. While in theory the vibration-based and impedance-based methods may facilitate damage identification with the assistance of a credible baseline fini...	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	false	82,345
2502.10003	SciClaimHunt: A Large Dataset for Evidence-based Scientific Claim Verification	Verifying scientific claims presents a significantly greater challenge than verifying political or news-related claims. Unlike the relatively broad audience for political claims, the users of scientific claim verification systems can vary widely, ranging from researchers testing specific hypotheses to everyday users se...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	533,698
1109.0762	Tunable Dual-band IFA Antenna using LC Resonators	A tunable dual-band inverted F antenna (IFA) is presented in this paper. By placing a LC resonator on the radiating arm, dual-band characteristic is achieved. Especially, the capacitor in the resonator is a tunable thin-film BST capacitor, which has a 3.3:1 tuning ratio. The capacitance of the BST capacitors can be tun...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	11,964
2405.02191	Non-Destructive Peat Analysis using Hyperspectral Imaging and Machine Learning	Peat, a crucial component in whisky production, imparts distinctive and irreplaceable flavours to the final product. However, the extraction of peat disrupts ancient ecosystems and releases significant amounts of carbon, contributing to climate change. This paper aims to address this issue by conducting a feasibility s...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	451,662
1711.00832	A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning	To achieve general intelligence, agents must learn how to interact with others in a shared environment: this is the challenge of multiagent reinforcement learning (MARL). The simplest form is independent reinforcement learning (InRL), where each agent treats its experience as part of its (non-stationary) environment. I...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	true	false	false	true	83,786
1903.02908	Locating Transparent Objects to Millimetre Accuracy	Transparent surfaces, such as glass, transmit most of the visible light that falls on them, making accurate pose estimation challenging. We propose a method to locate glass objects to millimetre accuracy using a simple Laser Range Finder (LRF) attached to the robot end-effector. The method, derived from a physical unde...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	123,595
2209.07348	Coupled Evolutionary Behavioral and Disease Dynamics under Reinfection Risk	We study the interplay between epidemic dynamics and human decision making for epidemics that involve reinfection risk; in particular, the susceptible-infected-susceptible (SIS) and the susceptible-infected-recovered-infected (SIRI) epidemic models. In the proposed game-theoretic setting, individuals choose whether to ...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	true	317,711
cs/0602074	The entropy rate of the binary symmetric channel in the rare transitions regime	This note has been withdrawn by the author as the more complete result was recently proved by A.Quas and Y.Peres	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	539,287
1304.5878	Visual Room-Awareness for Humanoid Robot Self-Localization	Humanoid robots without internal sensors such as a compass tend to lose their orientation after a fall. Furthermore, re-initialisation is often ambiguous due to symmetric man-made environments. The room-awareness module proposed here is inspired by the results of psychological experiments and improves existing self-loc...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	24,127
1112.4164	A Geometric Approach For Fully Automatic Chromosome Segmentation	A fundamental task in human chromosome analysis is chromosome segmentation. Segmentation plays an important role in chromosome karyotyping. The first step in segmentation is to remove intrusive objects such as stain debris and other noises. The next step is detection of touching and overlapping chromosomes, and the fin...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	13,510
2410.21280	TraderTalk: An LLM Behavioural ABM applied to Simulating Human Bilateral Trading Interactions	We introduce a novel hybrid approach that augments Agent-Based Models (ABMs) with behaviors generated by Large Language Models (LLMs) to simulate human trading interactions. We call our model TraderTalk. Leveraging LLMs trained on extensive human-authored text, we capture detailed and nuanced representations of bilater...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	503,168
2402.18995	Negative-Binomial Randomized Gamma Markov Processes for Heterogeneous Overdispersed Count Time Series	Modeling count-valued time series has been receiving increasing attention since count time series naturally arise in physical and social domains. Poisson gamma dynamical systems (PGDSs) are newly-developed methods, which can well capture the expressive latent transition structure and bursty dynamics behind count sequen...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	false	false	433,644
2307.10093	Revisiting invariances and introducing priors in Gromov-Wasserstein distances	Gromov-Wasserstein distance has found many applications in machine learning due to its ability to compare measures across metric spaces and its invariance to isometric transformations. However, in certain applications, this invariance property can be too flexible, thus undesirable. Moreover, the Gromov-Wasserstein dist...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	380,413
2302.10980	MultiRobustBench: Benchmarking Robustness Against Multiple Attacks	The bulk of existing research in defending against adversarial examples focuses on defending against a single (typically bounded Lp-norm) attack, but for a practical setting, machine learning (ML) models should be robust to a wide variety of attacks. In this paper, we present the first unified framework for considering...	false	false	false	false	false	false	true	false	false	false	false	false	true	false	false	false	false	false	347,038
2410.10546	Graph Classification Gaussian Processes via Hodgelet Spectral Features	The problem of classifying graphs is ubiquitous in machine learning. While it is standard to apply graph neural networks or graph kernel methods, Gaussian processes can be employed by transforming spatial features from the graph domain into spectral features in the Euclidean domain, and using them as the input points o...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	498,126
1510.03125	Fast detection of multiple objects in traffic scenes with a common detection framework	Traffic scene perception (TSP) aims to real-time extract accurate on-road environment information, which in- volves three phases: detection of objects of interest, recognition of detected objects, and tracking of objects in motion. Since recognition and tracking often rely on the results from detection, the ability to ...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	47,811
1602.06561	Deep Learning in Finance	We explore the use of deep learning hierarchical models for problems in financial prediction and classification. Financial prediction problems -- such as those presented in designing and pricing securities, constructing portfolios, and risk management -- often involve large data sets with complex data interactions that...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	52,388
2502.12771	Mind the Gap: Aligning the Brain with Language Models Requires a Nonlinear and Multimodal Approach	Self-supervised language and audio models effectively predict brain responses to speech. However, traditional prediction models rely on linear mappings from unimodal features, despite the complex integration of auditory signals with linguistic and semantic information across widespread brain networks during speech comp...	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	535,043
1402.4576	On the Average Performance of Caching and Coded Multicasting with Random Demands	For a network with one sender, $n$ receivers (users) and $m$ possible messages (files), caching side information at the users allows to satisfy arbitrary simultaneous demands by sending a common (multicast) coded message. In the worst-case demand setting, explicit deterministic and random caching strategies and explici...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	30,978
1908.08792	Beating the probabilistic lower bound on $q$-perfect hashing	For an integer $q\ge 2$, a perfect $q$-hash code $C$ is a block code over $[q]:=\{1,\ldots,q\}$ of length $n$ in which every subset $\{\mathbf{c}_1,\mathbf{c}_2,\dots,\mathbf{c}_q\}$ of $q$ elements is separated, i.e., there exists $i\in[n]$ such that $\{\mathrm{proj}_i(\mathbf{c}_1),\dots,\mathrm{proj}_i(\mathbf{c}_q)...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	142,652
2006.12226	Hierarchical Patch VAE-GAN: Generating Diverse Videos from a Single Sample	We consider the task of generating diverse and novel videos from a single video sample. Recently, new hierarchical patch-GAN based approaches were proposed for generating diverse images, given only a single sample at training time. Moving to videos, these approaches fail to generate diverse samples, and often collapse ...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	183,515
2309.03535	Feature Enhancer Segmentation Network (FES-Net) for Vessel Segmentation	Diseases such as diabetic retinopathy and age-related macular degeneration pose a significant risk to vision, highlighting the importance of precise segmentation of retinal vessels for the tracking and diagnosis of progression. However, existing vessel segmentation methods that heavily rely on encoder-decoder structure...	false	false	false	false	false	false	true	false	false	false	false	true	false	false	false	false	false	false	390,415
2311.13160	Large Language Models in Education: Vision and Opportunities	With the rapid development of artificial intelligence technology, large language models (LLMs) have become a hot research topic. Education plays an important role in human social development and progress. Traditional education faces challenges such as individual student differences, insufficient allocation of teaching ...	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	false	409,643
1912.11730	Memory Augmented Graph Neural Networks for Sequential Recommendation	The chronological order of user-item interactions can reveal time-evolving and sequential user behaviors in many recommender systems. The items that users will interact with may depend on the items accessed in the past. However, the substantial increase of users and items makes sequential recommender systems still face...	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	false	158,647
2305.12574	Atomic Anatomy of Low-Inertia Power Systems	In this article, we determine a fundamental anatomical modeling parallelism between low-inertia power systems and Bohr's atomic model. The proposed atomic architecture will serve as a microscopic building block, where we validate the structural analogy of low-inertia power systems using semi-classical quantum approxima...	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	366,066
2406.04851	Digital assistant in a point of sales	This article investigates the deployment of a Voice User Interface (VUI)-powered digital assistant in a retail setting and assesses its impact on customer engagement and service efficiency. The study explores how digital assistants can enhance user interactions through advanced conversational capabilities with multilin...	true	false	false	false	true	false	false	false	true	false	false	false	false	false	false	false	false	false	461,876
2102.05414	Manipulability optimization for multi-arm teleoperation	Teleoperation provides a way for human operators to guide robots in situations where full autonomy is challenging or where direct human intervention is required. It can also be an important tool to teach robots in order to achieve autonomous behaviour later on. The increased availability of collaborative robot arms and...	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	219,430
2204.13983	AdaInt: Learning Adaptive Intervals for 3D Lookup Tables on Real-time Image Enhancement	The 3D Lookup Table (3D LUT) is a highly-efficient tool for real-time image enhancement tasks, which models a non-linear 3D color transform by sparsely sampling it into a discretized 3D lattice. Previous works have made efforts to learn image-adaptive output color values of LUTs for flexible enhancement but neglect the...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	294,012
2405.20868	Responsible AI for Earth Observation	The convergence of artificial intelligence (AI) and Earth observation (EO) technologies has brought geoscience and remote sensing into an era of unparalleled capabilities. AI's transformative impact on data analysis, particularly derived from EO platforms, holds great promise in addressing global challenges such as env...	false	false	false	false	false	false	false	false	false	false	false	true	false	true	false	false	false	false	459,556
2404.15673	Augmented CARDS: A machine learning approach to identifying triggers of climate change misinformation on Twitter	Misinformation about climate change poses a significant threat to societal well-being, prompting the urgent need for effective mitigation strategies. However, the rapid proliferation of online misinformation on social media platforms outpaces the ability of fact-checkers to debunk false claims. Automated detection of c...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	449,189
2304.01926	High-Throughput Vector Similarity Search in Knowledge Graphs	There is an increasing adoption of machine learning for encoding data into vectors to serve online recommendation and search use cases. As a result, recent data management systems propose augmenting query processing with online vector similarity search. In this work, we explore vector similarity search in the context o...	false	false	false	false	true	false	true	false	false	false	false	false	false	false	false	false	true	false	356,258
1704.01917	Downlink Power Optimization for Heterogeneous Networks with Time Reversal-based Transmission under Backhaul Limitation	In this paper, we investigate an application of two different beamforming techniques and propose a novel downlink power minimization scheme for a two-tier heterogeneous network (HetNet) model. In this context, we employ time reversal (TR) technique to a femtocell base station (FBS) whereas we assume that a macrocell ba...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	71,346
1912.08243	Competitive Contagion with Sparse Seeding	This paper studies a strategic model of marketing and product diffusion in social networks. We consider two firms offering substitutable products which can improve their market share by seeding the key individuals in the market. Consumers update their consumption level for each of the two products as the best response ...	false	false	false	true	false	false	false	false	false	false	false	false	false	false	true	false	false	false	157,785
1810.00368	Deep Quality-Value (DQV) Learning	We introduce a novel Deep Reinforcement Learning (DRL) algorithm called Deep Quality-Value (DQV) Learning. DQV uses temporal-difference learning to train a Value neural network and uses this network for training a second Quality-value network that learns to estimate state-action values. We first test DQV's update rules...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	109,167
1410.7895	Effect of Degradation in Molecular Communication: Impairment or Enhancement?	In the nanonetworking literature, many solutions have been suggested to enable the nanomachine-to-nanomachine communication. Among these solutions, we focus on what constitutes the basis for molecular communication paradigms --molecular communication via diffusion (MCvD). In this paper, we start with an analytical mode...	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	false	true	37,115
2304.10769	Deep Multiview Clustering by Contrasting Cluster Assignments	Multiview clustering (MVC) aims to reveal the underlying structure of multiview data by categorizing data samples into clusters. Deep learning-based methods exhibit strong feature learning capabilities on large-scale datasets. For most existing deep MVC methods, exploring the invariant representations of multiple views...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	359,552
2411.04036	Stepping Forward on the Last Mile	Continuously adapting pre-trained models to local data on resource constrained edge devices is the $\emph{last mile}$ for model deployment. However, as models increase in size and depth, backpropagation requires a large amount of memory, which becomes prohibitive for edge devices. In addition, most existing low power n...	false	false	false	false	false	false	true	false	false	false	false	false	false	false	false	false	false	false	506,128
2403.03173	Solving the Clustering Reasoning Problems by Modeling a Deep-Learning-Based Probabilistic Model	Visual abstract reasoning problems pose significant challenges to the perception and cognition abilities of artificial intelligence algorithms, demanding deeper pattern recognition and inductive reasoning beyond mere identification of explicit image features. Research advancements in this field often provide insights a...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	435,089
2402.10412	Measuring and Reducing LLM Hallucination without Gold-Standard Answers	LLM hallucination, i.e. generating factually incorrect yet seemingly convincing answers, is currently a major threat to the trustworthiness and reliability of LLMs. The first step towards solving this complicated problem is to measure it. However, existing hallucination metrics require having a benchmark dataset with g...	false	false	false	false	true	false	true	false	true	false	false	false	false	false	false	false	false	false	429,950
2308.02177	Scene-aware Human Pose Generation using Transformer	Affordance learning considers the interaction opportunities for an actor in the scene and thus has wide application in scene understanding and intelligent robotics. In this paper, we focus on contextual affordance learning, i.e., using affordance as context to generate a reasonable human pose in a scene. Existing scene...	false	false	false	false	false	false	false	false	false	false	false	true	false	false	false	false	false	false	383,525

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