id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2411.14739 | IRLab@iKAT24: Learned Sparse Retrieval with Multi-aspect LLM Query
Generation for Conversational Search | [
"cs.IR",
"cs.CL"
] | The Interactive Knowledge Assistant Track (iKAT) 2024 focuses on advancing conversational assistants, able to adapt their interaction and responses from personalized user knowledge. The track incorporates a Personal Textual Knowledge Base (PTKB) alongside Conversational AI tasks, such as passage ranking and response ge... | {
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2411.14740 | TEXGen: a Generative Diffusion Model for Mesh Textures | [
"cs.CV",
"cs.AI",
"cs.GR"
] | While high-quality texture maps are essential for realistic 3D asset rendering, few studies have explored learning directly in the texture space, especially on large-scale datasets. In this work, we depart from the conventional approach of relying on pre-trained 2D diffusion models for test-time optimization of 3D text... | {
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2411.14743 | FOCUS: Knowledge-enhanced Adaptive Visual Compression for Few-shot Whole
Slide Image Classification | [
"cs.CV",
"cs.AI",
"q-bio.QM"
] | Few-shot learning presents a critical solution for cancer diagnosis in computational pathology (CPath), addressing fundamental limitations in data availability, particularly the scarcity of expert annotations and patient privacy constraints. A key challenge in this paradigm stems from the inherent disparity between the... | {
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2411.14744 | Point Cloud Understanding via Attention-Driven Contrastive Learning | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Recently Transformer-based models have advanced point cloud understanding by leveraging self-attention mechanisms, however, these methods often overlook latent information in less prominent regions, leading to increased sensitivity to perturbations and limited global comprehension. To solve this issue, we introduce Poi... | {
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2411.14748 | Cosmological Analysis with Calibrated Neural Quantile Estimation and
Approximate Simulators | [
"astro-ph.CO",
"astro-ph.IM",
"cs.LG"
] | A major challenge in extracting information from current and upcoming surveys of cosmological Large-Scale Structure (LSS) is the limited availability of computationally expensive high-fidelity simulations. We introduce Neural Quantile Estimation (NQE), a new Simulation-Based Inference (SBI) method that leverages a larg... | {
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2411.14750 | Ordinal Multiple-instance Learning for Ulcerative Colitis Severity
Estimation with Selective Aggregated Transformer | [
"cs.CV",
"cs.LG"
] | Patient-level diagnosis of severity in ulcerative colitis (UC) is common in real clinical settings, where the most severe score in a patient is recorded. However, previous UC classification methods (i.e., image-level estimation) mainly assumed the input was a single image. Thus, these methods can not utilize severity l... | {
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2411.14751 | TopoSD: Topology-Enhanced Lane Segment Perception with SDMap Prior | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.RO"
] | Recent advances in autonomous driving systems have shifted towards reducing reliance on high-definition maps (HDMaps) due to the huge costs of annotation and maintenance. Instead, researchers are focusing on online vectorized HDMap construction using on-board sensors. However, sensor-only approaches still face challeng... | {
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2411.14752 | Comparative Analysis of nnUNet and MedNeXt for Head and Neck Tumor
Segmentation in MRI-guided Radiotherapy | [
"eess.IV",
"cs.CV",
"cs.LG"
] | Radiation therapy (RT) is essential in treating head and neck cancer (HNC), with magnetic resonance imaging(MRI)-guided RT offering superior soft tissue contrast and functional imaging. However, manual tumor segmentation is time-consuming and complex, and therfore remains a challenge. In this study, we present our solu... | {
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2411.14754 | Subspace Collision: An Efficient and Accurate Framework for
High-dimensional Approximate Nearest Neighbor Search | [
"cs.DB"
] | Approximate Nearest Neighbor (ANN) search in high-dimensional Euclidean spaces is a fundamental problem with a wide range of applications. However, there is currently no ANN method that performs well in both indexing and query answering performance, while providing rigorous theoretical guarantees for the quality of the... | {
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2411.14755 | FairAdapter: Detecting AI-generated Images with Improved Fairness | [
"cs.CV",
"cs.CY"
] | The high-quality, realistic images generated by generative models pose significant challenges for exposing them.So far, data-driven deep neural networks have been justified as the most efficient forensics tools for the challenges. However, they may be over-fitted to certain semantics, resulting in considerable inconsis... | {
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2411.14756 | KPG 193: A Synthetic Korean Power Grid Test System for Decarbonization
Studies | [
"eess.SY",
"cs.SY"
] | This paper introduces the 193 bus synthetic Korean power grid (KPG 193), developed using open data sources to address recent challenges of the Korean power system. The KPG 193 test system serves as a valuable platform for decarbonization research, capturing Korean low renewable energy penetration, concentrated urban en... | {
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2411.14759 | Hammer: Towards Efficient Hot-Cold Data Identification via Online
Learning | [
"cs.LG",
"cs.AI"
] | Efficient management of storage resources in big data and cloud computing environments requires accurate identification of data's "cold" and "hot" states. Traditional methods, such as rule-based algorithms and early AI techniques, often struggle with dynamic workloads, leading to low accuracy, poor adaptability, and hi... | {
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2411.14760 | The 1st Workshop on Human-Centered Recommender Systems | [
"cs.IR"
] | Recommender systems are quintessential applications of human-computer interaction. Widely utilized in daily life, they offer significant convenience but also present numerous challenges, such as the information cocoon effect, privacy concerns, fairness issues, and more. Consequently, this workshop aims to provide a pla... | {
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2411.14762 | Efficient Long Video Tokenization via Coordinate-based Patch
Reconstruction | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Efficient tokenization of videos remains a challenge in training vision models that can process long videos. One promising direction is to develop a tokenizer that can encode long video clips, as it would enable the tokenizer to leverage the temporal coherence of videos better for tokenization. However, training existi... | {
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2411.14765 | An Attention-based Framework for Fair Contrastive Learning | [
"cs.LG"
] | Contrastive learning has proven instrumental in learning unbiased representations of data, especially in complex environments characterized by high-cardinality and high-dimensional sensitive information. However, existing approaches within this setting require predefined modelling assumptions of bias-causing interactio... | {
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2411.14768 | Grid and Road Expressions Are Complementary for Trajectory
Representation Learning | [
"cs.LG",
"cs.AI"
] | Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movement in free space, or road trajectories, capturing movement in a road network, as input. We observe that the two types of trajectories are c... | {
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2411.14770 | Aim My Robot: Precision Local Navigation to Any Object | [
"cs.RO"
] | Existing navigation systems mostly consider "success" when the robot reaches within 1m radius to a goal. This precision is insufficient for emerging applications where the robot needs to be positioned precisely relative to an object for downstream tasks, such as docking, inspection, and manipulation. To this end, we de... | {
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2411.14771 | Capacity Approximations for Insertion Channels with Small Insertion
Probabilities | [
"cs.IT",
"math.IT"
] | Channels with synchronization errors, exhibiting deletion and insertion errors, find practical applications in DNA storage, data reconstruction, and various other domains. Presence of insertions and deletions render the channel with memory, complicating capacity analysis. For instance, despite the formulation of an ind... | {
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2411.14773 | Mode-conditioned music learning and composition: a spiking neural
network inspired by neuroscience and psychology | [
"cs.SD",
"cs.AI",
"eess.AS",
"q-bio.NC"
] | Musical mode is one of the most critical element that establishes the framework of pitch organization and determines the harmonic relationships. Previous works often use the simplistic and rigid alignment method, and overlook the diversity of modes. However, in contrast to AI models, humans possess cognitive mechanisms... | {
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2411.14774 | Resolution-Agnostic Transformer-based Climate Downscaling | [
"cs.CV",
"cs.AI"
] | Understanding future weather changes at regional and local scales is crucial for planning and decision-making, particularly in the context of extreme weather events, as well as for broader applications in agriculture, insurance, and infrastructure development. However, the computational cost of downscaling Global Clima... | {
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2411.14775 | A Benchmark Dataset for Collaborative SLAM in Service Environments | [
"cs.RO",
"cs.CV"
] | As service environments have become diverse, they have started to demand complicated tasks that are difficult for a single robot to complete. This change has led to an interest in multiple robots instead of a single robot. C-SLAM, as a fundamental technique for multiple service robots, needs to handle diverse challenge... | {
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2411.14779 | New families of non-Reed-Solomon MDS codes | [
"cs.IT",
"math.IT"
] | MDS codes have garnered significant attention due to their wide applications in practice. To date, most known MDS codes are equivalent to Reed-Solomon codes. The construction of non-Reed-Solomon (non-RS) type MDS codes has emerged as an intriguing and important problem in both coding theory and finite geometry. Althoug... | {
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2411.14781 | Reconciling Semantic Controllability and Diversity for Remote Sensing
Image Synthesis with Hybrid Semantic Embedding | [
"cs.CV"
] | Significant advancements have been made in semantic image synthesis in remote sensing. However, existing methods still face formidable challenges in balancing semantic controllability and diversity. In this paper, we present a Hybrid Semantic Embedding Guided Generative Adversarial Network (HySEGGAN) for controllable a... | {
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2411.14783 | Segmenting Action-Value Functions Over Time-Scales in SARSA via
TD($\Delta$) | [
"cs.LG"
] | In numerous episodic reinforcement learning (RL) settings, SARSA-based methodologies are employed to enhance policies aimed at maximizing returns over long horizons. Conventional SARSA algorithms, however, have difficulties in balancing bias and variation due to the reliance on a singular, fixed discount factor. This s... | {
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2411.14786 | FastGrasp: Efficient Grasp Synthesis with Diffusion | [
"cs.RO",
"cs.CV"
] | Effectively modeling the interaction between human hands and objects is challenging due to the complex physical constraints and the requirement for high generation efficiency in applications. Prior approaches often employ computationally intensive two-stage approaches, which first generate an intermediate representatio... | {
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2411.14788 | Jovis: A Visualization Tool for PostgreSQL Query Optimizer | [
"cs.DB",
"cs.HC"
] | In the world of relational database management, the query optimizer is a critical component that significantly impacts query performance. To address the challenge of optimizing query performance due to the complexity of optimizers -- especially with join operations -- we introduce Jovis. This novel visualization tool p... | {
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2411.14789 | Simplifying CLIP: Unleashing the Power of Large-Scale Models on
Consumer-level Computers | [
"cs.LG",
"cs.CV"
] | Contrastive Language-Image Pre-training (CLIP) has attracted a surge of attention for its superior zero-shot performance and excellent transferability to downstream tasks. However, training such large-scale models usually requires substantial computation and storage, which poses barriers for general users with consumer... | {
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2411.14790 | KBAlign: Efficient Self Adaptation on Specific Knowledge Bases | [
"cs.CL",
"cs.AI"
] | Humans can utilize techniques to quickly acquire knowledge from specific materials in advance, such as creating self-assessment questions, enabling us to achieving related tasks more efficiently. In contrast, large language models (LLMs) usually relies on retrieval-augmented generation to exploit knowledge materials in... | {
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2411.14793 | Style-Friendly SNR Sampler for Style-Driven Generation | [
"cs.CV"
] | Recent large-scale diffusion models generate high-quality images but struggle to learn new, personalized artistic styles, which limits the creation of unique style templates. Fine-tuning with reference images is the most promising approach, but it often blindly utilizes objectives and noise level distributions used for... | {
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2411.14794 | VideoEspresso: A Large-Scale Chain-of-Thought Dataset for Fine-Grained
Video Reasoning via Core Frame Selection | [
"cs.CV",
"cs.AI",
"cs.CL"
] | The advancement of Large Vision Language Models (LVLMs) has significantly improved multimodal understanding, yet challenges remain in video reasoning tasks due to the scarcity of high-quality, large-scale datasets. Existing video question-answering (VideoQA) datasets often rely on costly manual annotations with insuffi... | {
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2411.14795 | De-biased Multimodal Electrocardiogram Analysis | [
"cs.CL"
] | Multimodal large language models (MLLMs) are increasingly being applied in the medical field, particularly in medical imaging. However, developing MLLMs for ECG signals, which are crucial in clinical settings, has been a significant challenge beyond medical imaging. Previous studies have attempted to address this by co... | {
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2411.14796 | Adaptive Hyper-Graph Convolution Network for Skeleton-based Human Action
Recognition with Virtual Connections | [
"cs.CV",
"cs.LG"
] | The shared topology of human skeletons motivated the recent investigation of graph convolutional network (GCN) solutions for action recognition. However, the existing GCNs rely on the binary connection of two neighbouring vertices (joints) formed by an edge (bone), overlooking the potential of constructing multi-vertex... | {
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2411.14797 | Continual SFT Matches Multimodal RLHF with Negative Supervision | [
"cs.LG",
"cs.AI",
"cs.CL",
"cs.CV"
] | Multimodal RLHF usually happens after supervised finetuning (SFT) stage to continually improve vision-language models' (VLMs) comprehension. Conventional wisdom holds its superiority over continual SFT during this preference alignment stage. In this paper, we observe that the inherent value of multimodal RLHF lies in i... | {
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2411.14798 | Facial Features Matter: a Dynamic Watermark based Proactive Deepfake
Detection Approach | [
"cs.CV",
"cs.CR",
"cs.LG",
"eess.IV"
] | Current passive deepfake face-swapping detection methods encounter significance bottlenecks in model generalization capabilities. Meanwhile, proactive detection methods often use fixed watermarks which lack a close relationship with the content they protect and are vulnerable to security risks. Dynamic watermarks based... | {
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2411.14807 | Harlequin: Color-driven Generation of Synthetic Data for Referring
Expression Comprehension | [
"cs.CV",
"cs.CL",
"cs.LG"
] | Referring Expression Comprehension (REC) aims to identify a particular object in a scene by a natural language expression, and is an important topic in visual language understanding. State-of-the-art methods for this task are based on deep learning, which generally requires expensive and manually labeled annotations. S... | {
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2411.14808 | High-Resolution Image Synthesis via Next-Token Prediction | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Denoising with a Joint-Embedding Predictive Architecture (D-JEPA), an autoregressive model, has demonstrated outstanding performance in class-conditional image generation. However, the application of next-token prediction in high-resolution text-to-image generation remains underexplored. In this paper, we introduce D-J... | {
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2411.14811 | Fine-Grained Alignment in Vision-and-Language Navigation through
Bayesian Optimization | [
"cs.CV",
"cs.CL",
"cs.LG"
] | This paper addresses the challenge of fine-grained alignment in Vision-and-Language Navigation (VLN) tasks, where robots navigate realistic 3D environments based on natural language instructions. Current approaches use contrastive learning to align language with visual trajectory sequences. Nevertheless, they encounter... | {
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2411.14816 | Unsupervised Multi-view UAV Image Geo-localization via Iterative
Rendering | [
"cs.CV",
"cs.RO",
"eess.IV"
] | Unmanned Aerial Vehicle (UAV) Cross-View Geo-Localization (CVGL) presents significant challenges due to the view discrepancy between oblique UAV images and overhead satellite images. Existing methods heavily rely on the supervision of labeled datasets to extract viewpoint-invariant features for cross-view retrieval. Ho... | {
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2411.14823 | Omni-IML: Towards Unified Image Manipulation Localization | [
"cs.CV",
"cs.CR",
"cs.LG"
] | Image manipulation can lead to misinterpretation of visual content, posing significant risks to information security. Image Manipulation Localization (IML) has thus received increasing attention. However, existing IML methods rely heavily on task-specific designs, making them perform well only on one target image type ... | {
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2411.14827 | Physically Interpretable Probabilistic Domain Characterization | [
"cs.CV",
"cs.AI",
"cs.LG",
"eess.IV"
] | Characterizing domains is essential for models analyzing dynamic environments, as it allows them to adapt to evolving conditions or to hand the task over to backup systems when facing conditions outside their operational domain. Existing solutions typically characterize a domain by solving a regression or classificatio... | {
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2411.14832 | VisGraphVar: A Benchmark Generator for Assessing Variability in Graph
Analysis Using Large Vision-Language Models | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.LG"
] | The fast advancement of Large Vision-Language Models (LVLMs) has shown immense potential. These models are increasingly capable of tackling abstract visual tasks. Geometric structures, particularly graphs with their inherent flexibility and complexity, serve as an excellent benchmark for evaluating these models' predic... | {
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2411.14833 | Cell as Point: One-Stage Framework for Efficient Cell Tracking | [
"eess.IV",
"cs.CV",
"q-bio.QM"
] | Cellular activities are dynamic and intricate, playing a crucial role in advancing diagnostic and therapeutic techniques, yet they often require substantial resources for accurate tracking. Despite recent progress, the conventional multi-stage cell tracking approaches not only heavily rely on detection or segmentation ... | {
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2411.14834 | Evaluating the Robustness of the "Ensemble Everything Everywhere"
Defense | [
"cs.LG",
"cs.CR"
] | Ensemble everything everywhere is a defense to adversarial examples that was recently proposed to make image classifiers robust. This defense works by ensembling a model's intermediate representations at multiple noisy image resolutions, producing a single robust classification. This defense was shown to be effective a... | {
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2411.14839 | Bayesian dynamic mode decomposition for real-time ship motion digital
twinning | [
"stat.AP",
"cs.LG",
"math.DS"
] | Digital twins are widely considered enablers of groundbreaking changes in the development, operation, and maintenance of novel generations of products. They are meant to provide reliable and timely predictions to inform decisions along the entire product life cycle. One of their most interesting applications in the nav... | {
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2411.14842 | Who Can Withstand Chat-Audio Attacks? An Evaluation Benchmark for Large
Language Models | [
"cs.SD",
"cs.AI",
"eess.AS"
] | Adversarial audio attacks pose a significant threat to the growing use of large language models (LLMs) in voice-based human-machine interactions. While existing research has primarily focused on model-specific adversarial methods, real-world applications demand a more generalizable and universal approach to audio adver... | {
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2411.14847 | Dynamics-Aware Gaussian Splatting Streaming Towards Fast On-the-Fly
Training for 4D Reconstruction | [
"cs.CV",
"cs.AI"
] | The recent development of 3D Gaussian Splatting (3DGS) has led to great interest in 4D dynamic spatial reconstruction from multi-view visual inputs. While existing approaches mainly rely on processing full-length multi-view videos for 4D reconstruction, there has been limited exploration of iterative online reconstruct... | {
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2411.14855 | Applications of fractional calculus in learned optimization | [
"cs.LG"
] | Fractional gradient descent has been studied extensively, with a focus on its ability to extend traditional gradient descent methods by incorporating fractional-order derivatives. This approach allows for more flexibility in navigating complex optimization landscapes and offers advantages in certain types of problems, ... | {
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2411.14858 | Domain and Range Aware Synthetic Negatives Generation for Knowledge
Graph Embedding Models | [
"cs.AI"
] | Knowledge Graph Embedding models, representing entities and edges in a low-dimensional space, have been extremely successful at solving tasks related to completing and exploring Knowledge Graphs (KGs). One of the key aspects of training most of these models is teaching to discriminate between true statements positives ... | {
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2411.14860 | Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems | [
"cs.LG"
] | While ensembling deep neural networks has shown promise in improving generalization performance, scaling current ensemble methods for large models remains challenging. Given that recent progress in deep learning is largely driven by the scale, exemplified by the widespread adoption of large-scale neural network archite... | {
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2411.14863 | Latent Schrodinger Bridge: Prompting Latent Diffusion for Fast Unpaired
Image-to-Image Translation | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Diffusion models (DMs), which enable both image generation from noise and inversion from data, have inspired powerful unpaired image-to-image (I2I) translation algorithms. However, they often require a larger number of neural function evaluations (NFEs), limiting their practical applicability. In this paper, we tackle ... | {
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2411.14865 | Benchmarking the Robustness of Optical Flow Estimation to Corruptions | [
"eess.IV",
"cs.CV",
"cs.RO"
] | Optical flow estimation is extensively used in autonomous driving and video editing. While existing models demonstrate state-of-the-art performance across various benchmarks, the robustness of these methods has been infrequently investigated. Despite some research focusing on the robustness of optical flow models again... | {
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2411.14868 | Defective Edge Detection Using Cascaded Ensemble Canny Operator | [
"cs.CV"
] | Edge detection has been one of the most difficult challenges in computer vision because of the difficulty in identifying the borders and edges from the real-world images including objects of varying kinds and sizes. Methods based on ensemble learning, which use a combination of backbones and attention modules, outperfo... | {
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2411.14869 | BIP3D: Bridging 2D Images and 3D Perception for Embodied Intelligence | [
"cs.CV",
"cs.AI",
"cs.LG"
] | In embodied intelligence systems, a key component is 3D perception algorithm, which enables agents to understand their surrounding environments. Previous algorithms primarily rely on point cloud, which, despite offering precise geometric information, still constrain perception performance due to inherent sparsity, nois... | {
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2411.14870 | Application of AI to formal methods -- an analysis of current trends | [
"cs.LO",
"cs.AI",
"cs.LG"
] | With artificial intelligence (AI) being well established within the daily lives of research communities, we turn our gaze toward an application area that appears intuitively unsuited for probabilistic decision-making: the area of formal methods (FM). FM aim to provide sound and understandable reasoning about problems i... | {
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2411.14871 | Prioritize Denoising Steps on Diffusion Model Preference Alignment via
Explicit Denoised Distribution Estimation | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.LG"
] | Diffusion models have shown remarkable success in text-to-image generation, making alignment methods for these models increasingly important. A key challenge is the sparsity of preference labels, which are typically available only at the terminal of denoising trajectories. This raises the issue of how to assign credit ... | {
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2411.14873 | Implementation of Real-Time Lane Detection on Autonomous Mobile Robot | [
"cs.RO",
"cs.CV"
] | This paper describes the implementation of a learning-based lane detection algorithm on an Autonomous Mobile Robot. It aims to implement the Ultra Fast Lane Detection algorithm for real-time application on the SEATER P2MC-BRIN prototype using a camera and optimize its performance on the Jetson Nano platform. Preliminar... | {
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2411.14875 | Iterative Reweighted Framework Based Algorithms for Sparse Linear
Regression with Generalized Elastic Net Penalty | [
"stat.ML",
"cs.LG",
"math.ST",
"stat.TH"
] | The elastic net penalty is frequently employed in high-dimensional statistics for parameter regression and variable selection. It is particularly beneficial compared to lasso when the number of predictors greatly surpasses the number of observations. However, empirical evidence has shown that the $\ell_q$-norm penalty ... | {
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2411.14877 | Astro-HEP-BERT: A bidirectional language model for studying the meanings
of concepts in astrophysics and high energy physics | [
"cs.CL",
"physics.hist-ph"
] | I present Astro-HEP-BERT, a transformer-based language model specifically designed for generating contextualized word embeddings (CWEs) to study the meanings of concepts in astrophysics and high-energy physics. Built on a general pretrained BERT model, Astro-HEP-BERT underwent further training over three epochs using t... | {
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2411.14879 | Random Permutation Codes: Lossless Source Coding of Non-Sequential Data | [
"cs.IT",
"eess.SP",
"math.IT"
] | This thesis deals with the problem of communicating and storing non-sequential data. We investigate this problem through the lens of lossless source coding, also sometimes referred to as lossless compression, from both an algorithmic and information-theoretic perspective. Lossless compression algorithms typically pre... | {
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2411.14880 | Leveraging Hierarchical Prototypes as the Verbalizer for Implicit
Discourse Relation Recognition | [
"cs.CL"
] | Implicit discourse relation recognition involves determining relationships that hold between spans of text that are not linked by an explicit discourse connective. In recent years, the pre-train, prompt, and predict paradigm has emerged as a promising approach for tackling this task. However, previous work solely relie... | {
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2411.14883 | Boundless Across Domains: A New Paradigm of Adaptive Feature and
Cross-Attention for Domain Generalization in Medical Image Segmentation | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Domain-invariant representation learning is a powerful method for domain generalization. Previous approaches face challenges such as high computational demands, training instability, and limited effectiveness with high-dimensional data, potentially leading to the loss of valuable features. To address these issues, we h... | {
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2411.14886 | CardioLab: Laboratory Values Estimation and Monitoring from
Electrocardiogram Signals -- A Multimodal Deep Learning Approach | [
"eess.SP",
"cs.LG"
] | Background: Laboratory values are fundamental to medical diagnosis and management, but acquiring these values can be costly, invasive, and time-consuming. While electrocardiogram (ECG) patterns have been linked to certain laboratory abnormalities, the comprehensive modeling of these relationships remains underexplored.... | {
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2411.14894 | The Dynamics of Innovation in Open Source Software Ecosystems | [
"cs.SE",
"cs.SI"
] | Software libraries are the elementary building blocks of open source software ecosystems, extending the capabilities of programming languages beyond their standard libraries. Although ecosystem health is often quantified using data on libraries and their interdependencies, we know little about the rate at which new lib... | {
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2411.14896 | Evaluating LLM Prompts for Data Augmentation in Multi-label
Classification of Ecological Texts | [
"cs.CL",
"cs.CY",
"cs.SI"
] | Large language models (LLMs) play a crucial role in natural language processing (NLP) tasks, improving the understanding, generation, and manipulation of human language across domains such as translating, summarizing, and classifying text. Previous studies have demonstrated that instruction-based LLMs can be effectivel... | {
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2411.14901 | ReVisionLLM: Recursive Vision-Language Model for Temporal Grounding in
Hour-Long Videos | [
"cs.CV",
"cs.CL"
] | Large language models (LLMs) excel at retrieving information from lengthy text, but their vision-language counterparts (VLMs) face difficulties with hour-long videos, especially for temporal grounding. Specifically, these VLMs are constrained by frame limitations, often losing essential temporal details needed for accu... | {
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2411.14904 | Exploring Kolmogorov-Arnold Networks for Interpretable Time Series
Classification | [
"cs.LG"
] | Time series classification is a relevant step supporting decision-making processes in various domains, and deep neural models have shown promising performance. Despite significant advancements in deep learning, the theoretical understanding of how and why complex architectures function remains limited, prompting the ... | {
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2411.14907 | DAIRHuM: A Platform for Directly Aligning AI Representations with Human
Musical Judgments applied to Carnatic Music | [
"cs.SD",
"cs.AI",
"eess.AS"
] | Quantifying and aligning music AI model representations with human behavior is an important challenge in the field of MIR. This paper presents a platform for exploring the Direct alignment between AI music model Representations and Human Musical judgments (DAIRHuM). It is designed to enable musicians and experimentalis... | {
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2411.14908 | Reactive Robot Navigation Using Quasi-conformal Mappings and Control
Barrier Functions | [
"cs.RO",
"math.DS",
"math.OC"
] | This paper presents a robot control algorithm suitable for safe reactive navigation tasks in cluttered environments. The proposed approach consists of transforming the robot workspace into the \emph{ball world}, an artificial representation where all obstacle regions are closed balls. Starting from a polyhedral represe... | {
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2411.14913 | Enhancing Exploration with Diffusion Policies in Hybrid Off-Policy RL:
Application to Non-Prehensile Manipulation | [
"cs.RO"
] | Learning diverse policies for non-prehensile manipulation is essential for improving skill transfer and generalization to out-of-distribution scenarios. In this work, we enhance exploration through a two-fold approach within a hybrid framework that tackles both discrete and continuous action spaces. First, we model the... | {
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2411.14914 | A Reproducibility and Generalizability Study of Large Language Models
for Query Generation | [
"cs.IR"
] | Systematic literature reviews (SLRs) are a cornerstone of academic research, yet they are often labour-intensive and time-consuming due to the detailed literature curation process. The advent of generative AI and large language models (LLMs) promises to revolutionize this process by assisting researchers in several ted... | {
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2411.14917 | Task-Aware Robotic Grasping by evaluating Quality Diversity Solutions
through Foundation Models | [
"cs.RO"
] | Task-aware robotic grasping is a challenging problem that requires the integration of semantic understanding and geometric reasoning. Traditional grasp planning approaches focus on stable or feasible grasps, often disregarding the specific tasks the robot needs to accomplish. This paper proposes a novel framework that ... | {
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2411.14919 | Optimal Beamforming for Multi-User Continuous Aperture Array (CAPA)
Systems | [
"cs.IT",
"eess.SP",
"math.IT"
] | The optimal beamforming design for multi-user continuous aperture array (CAPA) systems is proposed. In contrast to conventional spatially discrete array (SPDA), the beamformer for CAPA is a continuous function rather than a discrete vector or matrix, rendering beamforming optimization a non-convex integral-based functi... | {
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2411.14922 | GOT4Rec: Graph of Thoughts for Sequential Recommendation | [
"cs.IR",
"cs.AI"
] | With the advancement of large language models (LLMs), researchers have explored various methods to optimally leverage their comprehension and generation capabilities in sequential recommendation scenarios. However, several challenges persist in this endeavor. Firstly, most existing approaches rely on the input-output p... | {
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2411.14923 | Predictive Modeling For Real-Time Personalized Health Monitoring in
Muscular Dystrophy Management | [
"cs.LG"
] | Muscular Dystrophy is a group of genetic disorders that progressively affect the strength and functioning of muscles, thereby affecting millions of people worldwide. The lifetime nature of MD requires continuous follow-up care due to its progressive nature. This conceptual paper proposes an Internet of Things-based sys... | {
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2411.14925 | Purrfessor: A Fine-tuned Multimodal LLaVA Diet Health Chatbot | [
"cs.HC",
"cs.AI"
] | This study introduces Purrfessor, an innovative AI chatbot designed to provide personalized dietary guidance through interactive, multimodal engagement. Leveraging the Large Language-and-Vision Assistant (LLaVA) model fine-tuned with food and nutrition data and a human-in-the-loop approach, Purrfessor integrates visual... | {
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2411.14927 | LiDAR-based End-to-end Temporal Perception for Vehicle-Infrastructure
Cooperation | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.RO"
] | Temporal perception, the ability to detect and track objects over time, is critical in autonomous driving for maintaining a comprehensive understanding of dynamic environments. However, this task is hindered by significant challenges, including incomplete perception caused by occluded objects and observational blind sp... | {
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2411.14937 | Geminio: Language-Guided Gradient Inversion Attacks in Federated
Learning | [
"cs.LG",
"cs.AI",
"cs.CR"
] | Foundation models that bridge vision and language have made significant progress, inspiring numerous life-enriching applications. However, their potential for misuse to introduce new threats remains largely unexplored. This paper reveals that vision-language models (VLMs) can be exploited to overcome longstanding limit... | {
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2411.14939 | Many happy returns: machine learning to support platelet issuing and
waste reduction in hospital blood banks | [
"cs.LG"
] | Efforts to reduce platelet wastage in hospital blood banks have focused on ordering policies, but the predominant practice of issuing the oldest unit first may not be optimal when some units are returned unused. We propose a novel, machine learning (ML)-guided issuing policy to increase the likelihood of returned units... | {
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2411.14942 | Comparative Study of Neural Network Methods for Solving Topological
Solitons | [
"hep-th",
"cs.AI",
"cs.LG"
] | Topological solitons, which are stable, localized solutions of nonlinear differential equations, are crucial in various fields of physics and mathematics, including particle physics and cosmology. However, solving these solitons presents significant challenges due to the complexity of the underlying equations and the c... | {
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2411.14946 | Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based
Approach | [
"cs.CV",
"cs.AI",
"cs.LG"
] | In this paper, we present an approach for evaluating attribution maps, which play a central role in interpreting the predictions of convolutional neural networks (CNNs). We show that the widely used insertion/deletion metrics are susceptible to distribution shifts that affect the reliability of the ranking. Our method ... | {
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2411.14950 | Trajectory Planning and Control for Robotic Magnetic Manipulation | [
"cs.RO",
"cs.SY",
"eess.SY"
] | Robotic magnetic manipulation offers a minimally invasive approach to gastrointestinal examinations through capsule endoscopy. However, controlling such systems using external permanent magnets (EPM) is challenging due to nonlinear magnetic interactions, especially when there are complex navigation requirements such as... | {
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2411.14951 | Morph: A Motion-free Physics Optimization Framework for Human Motion
Generation | [
"cs.CV"
] | Human motion generation plays a vital role in applications such as digital humans and humanoid robot control. However, most existing approaches disregard physics constraints, leading to the frequent production of physically implausible motions with pronounced artifacts such as floating and foot sliding. In this paper, ... | {
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2411.14953 | Evaluating Vision Transformer Models for Visual Quality Control in
Industrial Manufacturing | [
"cs.CV",
"cs.AI",
"cs.LG"
] | One of the most promising use-cases for machine learning in industrial manufacturing is the early detection of defective products using a quality control system. Such a system can save costs and reduces human errors due to the monotonous nature of visual inspections. Today, a rich body of research exists which employs ... | {
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2411.14957 | Information Extraction from Heterogeneous Documents without Ground Truth
Labels using Synthetic Label Generation and Knowledge Distillation | [
"cs.CL"
] | Invoices and receipts submitted by employees are visually rich documents (VRDs) with textual, visual and layout information. To protect against the risk of fraud and abuse, it is crucial for organizations to efficiently extract desired information from submitted receipts. This helps in the assessment of key factors suc... | {
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2411.14959 | Design-o-meter: Towards Evaluating and Refining Graphic Designs | [
"cs.CV",
"cs.AI",
"cs.HC"
] | Graphic designs are an effective medium for visual communication. They range from greeting cards to corporate flyers and beyond. Off-late, machine learning techniques are able to generate such designs, which accelerates the rate of content production. An automated way of evaluating their quality becomes critical. Towar... | {
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2411.14961 | LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and
Initialization Refinement | [
"cs.LG",
"cs.CV"
] | Foundation models (FMs) achieve strong performance across diverse tasks with task-specific fine-tuning, yet full parameter fine-tuning is often computationally prohibitive for large models. Parameter-efficient fine-tuning (PEFT) methods like Low-Rank Adaptation (LoRA) reduce this cost by introducing low-rank matrices f... | {
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2411.14962 | LLM for Barcodes: Generating Diverse Synthetic Data for Identity
Documents | [
"cs.CL",
"cs.AI",
"cs.CR"
] | Accurate barcode detection and decoding in Identity documents is crucial for applications like security, healthcare, and education, where reliable data extraction and verification are essential. However, building robust detection models is challenging due to the lack of diverse, realistic datasets an issue often tied t... | {
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2411.14967 | SwissADT: An Audio Description Translation System for Swiss Languages | [
"cs.CL",
"cs.AI",
"cs.CV",
"cs.HC"
] | Audio description (AD) is a crucial accessibility service provided to blind persons and persons with visual impairment, designed to convey visual information in acoustic form. Despite recent advancements in multilingual machine translation research, the lack of well-crafted and time-synchronized AD data impedes the dev... | {
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2411.14968 | Optimization Strategies for Parallel Computation of Skylines | [
"cs.DB"
] | Skyline queries are one of the most widely adopted tools for Multi-Criteria Analysis, with applications covering diverse domains, including, e.g., Database Systems, Data Mining, and Decision Making. Skylines indeed offer a useful overview of the most suitable alternatives in a dataset, while discarding all the options ... | {
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2411.14971 | Leveraging LLMs for Legacy Code Modernization: Challenges and
Opportunities for LLM-Generated Documentation | [
"cs.LG",
"cs.SE"
] | Legacy software systems, written in outdated languages like MUMPS and mainframe assembly, pose challenges in efficiency, maintenance, staffing, and security. While LLMs offer promise for modernizing these systems, their ability to understand legacy languages is largely unknown. This paper investigates the utilization o... | {
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} |
2411.14972 | Open-Amp: Synthetic Data Framework for Audio Effect Foundation Models | [
"eess.AS",
"cs.AI",
"cs.LG",
"cs.SD"
] | This paper introduces Open-Amp, a synthetic data framework for generating large-scale and diverse audio effects data. Audio effects are relevant to many musical audio processing and Music Information Retrieval (MIR) tasks, such as modelling of analog audio effects, automatic mixing, tone matching and transcription. Exi... | {
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2411.14974 | 3D Convex Splatting: Radiance Field Rendering with 3D Smooth Convexes | [
"cs.CV"
] | Recent advances in radiance field reconstruction, such as 3D Gaussian Splatting (3DGS), have achieved high-quality novel view synthesis and fast rendering by representing scenes with compositions of Gaussian primitives. However, 3D Gaussians present several limitations for scene reconstruction. Accurately capturing har... | {
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} |
2411.14975 | Exploring Foundation Models Fine-Tuning for Cytology Classification | [
"eess.IV",
"cs.AI",
"cs.CV",
"q-bio.QM"
] | Cytology slides are essential tools in diagnosing and staging cancer, but their analysis is time-consuming and costly. Foundation models have shown great potential to assist in these tasks. In this paper, we explore how existing foundation models can be applied to cytological classification. More particularly, we focus... | {
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} |
2411.14980 | Generalized Multivariate Polynomial Codes for Distributed Matrix-Matrix
Multiplication | [
"cs.IT",
"math.IT"
] | Supporting multiple partial computations efficiently at each of the workers is a keystone in distributed coded computing in order to speed up computations and to fully exploit the resources of heterogeneous workers in terms of communication, storage, or computation capabilities. Multivariate polynomial coding schemes h... | {
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} |
2411.14982 | Large Multi-modal Models Can Interpret Features in Large Multi-modal
Models | [
"cs.CV",
"cs.CL"
] | Recent advances in Large Multimodal Models (LMMs) lead to significant breakthroughs in both academia and industry. One question that arises is how we, as humans, can understand their internal neural representations. This paper takes an initial step towards addressing this question by presenting a versatile framework to... | {
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} |
2411.14984 | Adaptive Group Robust Ensemble Knowledge Distillation | [
"cs.LG"
] | Neural networks can learn spurious correlations in the data, often leading to performance disparity for underrepresented subgroups. Studies have demonstrated that the disparity is amplified when knowledge is distilled from a complex teacher model to a relatively "simple" student model. Prior work has shown that ensembl... | {
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} |
2411.14986 | Generative AI may backfire for counterspeech | [
"cs.SI",
"cs.CY"
] | Online hate speech poses a serious threat to individual well-being and societal cohesion. A promising solution to curb online hate speech is counterspeech. Counterspeech is aimed at encouraging users to reconsider hateful posts by direct replies. However, current methods lack scalability due to the need for human inter... | {
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} |
2411.14991 | Free Energy Projective Simulation (FEPS): Active inference with
interpretability | [
"cs.AI",
"cs.LG",
"q-bio.NC",
"stat.ML"
] | In the last decade, the free energy principle (FEP) and active inference (AIF) have achieved many successes connecting conceptual models of learning and cognition to mathematical models of perception and action. This effort is driven by a multidisciplinary interest in understanding aspects of self-organizing complex ad... | {
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} |
2411.14992 | Differentiable Biomechanics for Markerless Motion Capture in Upper Limb
Stroke Rehabilitation: A Comparison with Optical Motion Capture | [
"cs.CV"
] | Marker-based Optical Motion Capture (OMC) paired with biomechanical modeling is currently considered the most precise and accurate method for measuring human movement kinematics. However, combining differentiable biomechanical modeling with Markerless Motion Capture (MMC) offers a promising approach to motion capture i... | {
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} |
2411.14995 | Learning Lifted STRIPS Models from Action Traces Alone: A Simple,
General, and Scalable Solution | [
"cs.AI"
] | Learning STRIPS action models from action traces alone is a challenging problem as it involves learning the domain predicates as well. In this work, a novel approach is introduced which, like the well-known LOCM systems, is scalable, but like SAT approaches, is sound and complete. Furthermore, the approach is general a... | {
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} |
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