id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.02605 | Interpretable Company Similarity with Sparse Autoencoders | [
"cs.CL",
"cs.LG",
"econ.GN",
"q-fin.EC"
] | Determining company similarity is a vital task in finance, underpinning hedging, risk management, portfolio diversification, and more. Practitioners often rely on sector and industry classifications to gauge similarity, such as SIC-codes and GICS-codes - the former being used by the U.S. Securities and Exchange Commiss... | {
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2412.02609 | Wasserstein Markets for Differentially-Private Data | [
"cs.LG",
"cs.CE",
"cs.CR",
"cs.GT",
"econ.GN",
"q-fin.EC"
] | Data is an increasingly vital component of decision making processes across industries. However, data access raises privacy concerns motivating the need for privacy-preserving techniques such as differential privacy. Data markets provide a means to enable wider access as well as determine the appropriate privacy-utilit... | {
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2412.02610 | AI-Driven Resource Allocation Framework for Microservices in Hybrid
Cloud Platforms | [
"cs.AI",
"cs.CE",
"cs.PF",
"cs.SE",
"cs.SY",
"eess.SY"
] | The increasing demand for scalable, efficient resource management in hybrid cloud environments has led to the exploration of AI-driven approaches for dynamic resource allocation. This paper presents an AI-driven framework for resource allocation among microservices in hybrid cloud platforms. The framework employs reinf... | {
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2412.02611 | AV-Odyssey Bench: Can Your Multimodal LLMs Really Understand
Audio-Visual Information? | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.MM",
"cs.SD",
"eess.AS"
] | Recently, multimodal large language models (MLLMs), such as GPT-4o, Gemini 1.5 Pro, and Reka Core, have expanded their capabilities to include vision and audio modalities. While these models demonstrate impressive performance across a wide range of audio-visual applications, our proposed DeafTest reveals that MLLMs oft... | {
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2412.02612 | GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken
Chatbot | [
"cs.CL",
"cs.SD",
"eess.AS"
] | We introduce GLM-4-Voice, an intelligent and human-like end-to-end spoken chatbot. It supports both Chinese and English, engages in real-time voice conversations, and varies vocal nuances such as emotion, intonation, speech rate, and dialect according to user instructions. GLM-4-Voice uses an ultra-low bitrate (175bps)... | {
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2412.02613 | Haptic Stiffness Perception Using Hand Exoskeletons in Tactile Robotic
Telemanipulation | [
"cs.RO"
] | Robotic telemanipulation - the human-guided manipulation of remote objects - plays a pivotal role in several applications, from healthcare to operations in harsh environments. While visual feedback from cameras can provide valuable information to the human operator, haptic feedback is essential for accessing specific o... | {
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2412.02615 | Projection Abstractions in Planning Under the Lenses of Abstractions for
MDPs | [
"cs.AI"
] | The concept of abstraction has been independently developed both in the context of AI Planning and discounted Markov Decision Processes (MDPs). However, the way abstractions are built and used in the context of Planning and MDPs is different even though lots of commonalities can be highlighted. To this day there is no ... | {
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2412.02617 | Improving Dynamic Object Interactions in Text-to-Video Generation with
AI Feedback | [
"cs.LG",
"cs.AI",
"cs.CV"
] | Large text-to-video models hold immense potential for a wide range of downstream applications. However, these models struggle to accurately depict dynamic object interactions, often resulting in unrealistic movements and frequent violations of real-world physics. One solution inspired by large language models is to ali... | {
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2412.02619 | Demonstrating the Advantages of Analog Wafer-Scale Neuromorphic Hardware | [
"cs.NE"
] | As numerical simulations grow in size and complexity, they become increasingly resource-intensive in terms of time and energy. While specialized hardware accelerators often provide order-of-magnitude gains and are state of the art in other scientific fields, their availability and applicability in computational neurosc... | {
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2412.02621 | Medical Multimodal Foundation Models in Clinical Diagnosis and
Treatment: Applications, Challenges, and Future Directions | [
"cs.AI",
"cs.LG"
] | Recent advancements in deep learning have significantly revolutionized the field of clinical diagnosis and treatment, offering novel approaches to improve diagnostic precision and treatment efficacy across diverse clinical domains, thus driving the pursuit of precision medicine. The growing availability of multi-organ ... | {
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2412.02623 | The effect of priors on Learning with Restricted Boltzmann Machines | [
"cond-mat.dis-nn",
"cs.LG"
] | Restricted Boltzmann Machines (RBMs) are generative models designed to learn from data with a rich underlying structure. In this work, we explore a teacher-student setting where a student RBM learns from examples generated by a teacher RBM, with a focus on the effect of the unit priors on learning efficiency. We consid... | {
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2412.02626 | Time-Reversal Provides Unsupervised Feedback to LLMs | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) are typically trained to predict in the forward direction of time. However, recent works have shown that prompting these models to look back and critique their own generations can produce useful feedback. Motivated by this, we explore the question of whether LLMs can be empowered to think (... | {
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2412.02627 | Continual Learning of Personalized Generative Face Models with
Experience Replay | [
"cs.CV"
] | We introduce a novel continual learning problem: how to sequentially update the weights of a personalized 2D and 3D generative face model as new batches of photos in different appearances, styles, poses, and lighting are captured regularly. We observe that naive sequential fine-tuning of the model leads to catastrophic... | {
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2412.02631 | Sharp-It: A Multi-view to Multi-view Diffusion Model for 3D Synthesis
and Manipulation | [
"cs.CV",
"cs.LG"
] | Advancements in text-to-image diffusion models have led to significant progress in fast 3D content creation. One common approach is to generate a set of multi-view images of an object, and then reconstruct it into a 3D model. However, this approach bypasses the use of a native 3D representation of the object and is hen... | {
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2412.02632 | Scaling Image Tokenizers with Grouped Spherical Quantization | [
"cs.CV",
"cs.AI"
] | Vision tokenizers have gained a lot of attraction due to their scalability and compactness; previous works depend on old-school GAN-based hyperparameters, biased comparisons, and a lack of comprehensive analysis of the scaling behaviours. To tackle those issues, we introduce Grouped Spherical Quantization (GSQ), featur... | {
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2412.02635 | MetaShadow: Object-Centered Shadow Detection, Removal, and Synthesis | [
"cs.CV"
] | Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one versatile framework that enables detection, removal, and controllable synthesis of shadows in natural images in an object-centered fashion.... | {
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2412.02637 | Words and Action: Modeling Linguistic Leadership in #BlackLivesMatter
Communities | [
"cs.CL",
"cs.SI"
] | In this project, we describe a method of modeling semantic leadership across a set of communities associated with the #BlackLivesMatter movement, which has been informed by qualitative research on the structure of social media and Black Twitter in particular. We describe our bespoke approaches to time-binning, communit... | {
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2412.02638 | QA-TOOLBOX: Conversational Question-Answering for process task guidance
in manufacturing | [
"cs.CL",
"cs.AI"
] | In this work we explore utilizing LLMs for data augmentation for manufacturing task guidance system. The dataset consists of representative samples of interactions with technicians working in an advanced manufacturing setting. The purpose of this work to explore the task, data augmentation for the supported tasks and e... | {
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2412.02639 | The Space Complexity of Approximating Logistic Loss | [
"cs.DS",
"cs.LG"
] | We provide space complexity lower bounds for data structures that approximate logistic loss up to $\epsilon$-relative error on a logistic regression problem with data $\mathbf{X} \in \mathbb{R}^{n \times d}$ and labels $\mathbf{y} \in \{-1,1\}^d$. The space complexity of existing coreset constructions depend on a natur... | {
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2412.02642 | Robust soybean seed yield estimation using high-throughput ground robot
videos | [
"cs.CV"
] | We present a novel method for soybean (Glycine max (L.) Merr.) yield estimation leveraging high throughput seed counting via computer vision and deep learning techniques. Traditional methods for collecting yield data are labor-intensive, costly, prone to equipment failures at critical data collection times, and require... | {
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2412.02643 | A Bidirectional Long Short Term Memory Approach for Infrastructure
Health Monitoring Using On-board Vibration Response | [
"cs.CV"
] | The growing volume of available infrastructural monitoring data enables the development of powerful datadriven approaches to estimate infrastructure health conditions using direct measurements. This paper proposes a deep learning methodology to estimate infrastructure physical parameters, such as railway track stiffnes... | {
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2412.02644 | Leveraging Tactile Sensing to Render both Haptic Feedback and Virtual
Reality 3D Object Reconstruction in Robotic Telemanipulation | [
"cs.RO"
] | Dexterous robotic manipulator teleoperation is widely used in many applications, either where it is convenient to keep the human inside the control loop, or to train advanced robot agents. So far, this technology has been used in combination with camera systems with remarkable success. On the other hand, only a limited... | {
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2412.02646 | Interpretable Generalized Additive Models for Datasets with Missing
Values | [
"cs.LG"
] | Many important datasets contain samples that are missing one or more feature values. Maintaining the interpretability of machine learning models in the presence of such missing data is challenging. Singly or multiply imputing missing values complicates the model's mapping from features to labels. On the other hand, rea... | {
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2412.02647 | Quaternary and Component-Binary Spreading Codes with Low Correlation for
Navigation Systems | [
"cs.IT",
"math.IT"
] | In the first part of this two-part paper, we construct a family MFD$_2$ of low-correlation quaternary spreading codes having period $2046$. By quaternary, we mean that the spreading code symbols are drawn from $Z_4$ and are designed to be used in conjunction with QPSK modulation. Apart from low auto and crosscorrelatio... | {
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2412.02649 | Communicate or Sense? AP Mode Selection in mmWave Cell-Free Massive
MIMO-ISAC | [
"eess.SP",
"cs.IT",
"math.IT"
] | Integrated sensing and communication (ISAC) is a promising technology for future mobile networks, enabling sensing applications to be performed by existing communication networks, consequently improving the system efficiency. Millimeter wave (mmWave) signals provide high sensing resolution and high data rate but suffer... | {
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2412.02650 | Bridging Hard and Soft: Mechanical Metamaterials Enable Rigid Torque
Transmission in Soft Robots | [
"cs.RO"
] | Torque and continuous rotation are fundamental methods of actuation and manipulation in rigid robots. Soft robot arms use soft materials and structures to mimic the passive compliance of biological arms that bend and extend. This use of compliance prevents soft arms from continuously transmitting and exerting torques t... | {
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2412.02653 | Scaffold or Crutch? Examining College Students' Use and Views of
Generative AI Tools for STEM Education | [
"physics.ed-ph",
"cs.AI"
] | Developing problem-solving competency is central to Science, Technology, Engineering, and Mathematics (STEM) education, yet translating this priority into effective approaches to problem-solving instruction and assessment remain a significant challenge. The recent proliferation of generative artificial intelligence (ge... | {
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2412.02655 | LLM-Enhanced Path Planning: Safe and Efficient Autonomous Navigation
with Instructional Inputs | [
"cs.RO",
"cs.SY",
"eess.SY"
] | Autonomous navigation guided by natural language instructions is essential for improving human-robot interaction and enabling complex operations in dynamic environments. While large language models (LLMs) are not inherently designed for planning, they can significantly enhance planning efficiency by providing guidance ... | {
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2412.02659 | Adaptive Informed Deep Neural Networks for Power Flow Analysis | [
"eess.SY",
"cs.AI",
"cs.SY",
"eess.SP"
] | This study introduces PINN4PF, an end-to-end deep learning architecture for power flow (PF) analysis that effectively captures the nonlinear dynamics of large-scale modern power systems. The proposed neural network (NN) architecture consists of two important advancements in the training pipeline: (A) a double-head feed... | {
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2412.02661 | Efficient Graph Matching for Correlated Stochastic Block Models | [
"cs.DS",
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"math.PR",
"math.ST",
"stat.ML",
"stat.TH"
] | We study learning problems on correlated stochastic block models with two balanced communities. Our main result gives the first efficient algorithm for graph matching in this setting. In the most interesting regime where the average degree is logarithmic in the number of vertices, this algorithm correctly matches all b... | {
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2412.02664 | Probing the statistical properties of enriched co-occurrence networks | [
"cs.CL",
"cs.SI"
] | Recent studies have explored the addition of virtual edges to word co-occurrence networks using word embeddings to enhance graph representations, particularly for short texts. While these enriched networks have demonstrated some success, the impact of incorporating semantic edges into traditional co-occurrence networks... | {
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2412.02665 | A Dissipativity Approach to Analyzing Composite Spreading Networks | [
"physics.soc-ph",
"cs.SY",
"eess.SY"
] | The study of spreading processes often analyzes networks at different resolutions, e.g., at the level of individuals or countries, but it is not always clear how properties at one resolution can carry over to another. Accordingly, in this work we use dissipativity theory from control system analysis to characterize com... | {
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2412.02670 | The Broader Landscape of Robustness in Algorithmic Statistics | [
"stat.ML",
"cs.CR",
"cs.DS",
"cs.IT",
"math.IT",
"math.ST",
"stat.TH"
] | The last decade has seen a number of advances in computationally efficient algorithms for statistical methods subject to robustness constraints. An estimator may be robust in a number of different ways: to contamination of the dataset, to heavy-tailed data, or in the sense that it preserves privacy of the dataset. We s... | {
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2412.02674 | Mind the Gap: Examining the Self-Improvement Capabilities of Large
Language Models | [
"cs.CL",
"cs.LG"
] | Self-improvement is a mechanism in Large Language Model (LLM) pre-training, post-training and test-time inference. We explore a framework where the model verifies its own outputs, filters or reweights data based on this verification, and distills the filtered data. Despite several empirical successes, a fundamental und... | {
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2412.02676 | Planning-Guided Diffusion Policy Learning for Generalizable Contact-Rich
Bimanual Manipulation | [
"cs.RO",
"cs.CV",
"cs.LG"
] | Contact-rich bimanual manipulation involves precise coordination of two arms to change object states through strategically selected contacts and motions. Due to the inherent complexity of these tasks, acquiring sufficient demonstration data and training policies that generalize to unseen scenarios remain a largely unre... | {
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2412.02682 | The Asymptotic Behavior of Attention in Transformers | [
"cs.AI",
"cs.LG",
"cs.SY",
"eess.SY",
"math.DS",
"math.OC"
] | A key component of transformers is the attention mechanism orchestrating how each token influences the propagation of every other token through a transformer. In this paper we provide a rigorous, mathematical analysis of the asymptotic properties of attention in transformers. Although we present several results based o... | {
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2412.02684 | AniGS: Animatable Gaussian Avatar from a Single Image with Inconsistent
Gaussian Reconstruction | [
"cs.CV",
"cs.AI"
] | Generating animatable human avatars from a single image is essential for various digital human modeling applications. Existing 3D reconstruction methods often struggle to capture fine details in animatable models, while generative approaches for controllable animation, though avoiding explicit 3D modeling, suffer from ... | {
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2412.02685 | T-REG: Preference Optimization with Token-Level Reward Regularization | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Reinforcement learning from human feedback (RLHF) has been crucial in aligning large language models (LLMs) with human values. Traditionally, RLHF involves generating responses to a query and using a reward model to assign a reward to the entire response. However, this approach faces challenges due to its reliance on a... | {
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2412.02687 | SNOOPI: Supercharged One-step Diffusion Distillation with Proper
Guidance | [
"cs.CV"
] | Recent approaches have yielded promising results in distilling multi-step text-to-image diffusion models into one-step ones. The state-of-the-art efficient distillation technique, i.e., SwiftBrushv2 (SBv2), even surpasses the teacher model's performance with limited resources. However, our study reveals its instability... | {
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2412.02689 | Preliminary Investigation into Data Scaling Laws for Imitation
Learning-Based End-to-End Autonomous Driving | [
"cs.RO"
] | The end-to-end autonomous driving paradigm has recently attracted lots of attention due to its scalability. However, existing methods are constrained by the limited scale of real-world data, which hinders a comprehensive exploration of the scaling laws associated with end-to-end autonomous driving. To address this issu... | {
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2412.02690 | FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand
Image Generation | [
"cs.CV"
] | Despite remarkable progress in image generation models, generating realistic hands remains a persistent challenge due to their complex articulation, varying viewpoints, and frequent occlusions. We present FoundHand, a large-scale domain-specific diffusion model for synthesizing single and dual hand images. To train our... | {
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2412.02692 | Taming Scalable Visual Tokenizer for Autoregressive Image Generation | [
"cs.CV",
"cs.AI"
] | Existing vector quantization (VQ) methods struggle with scalability, largely attributed to the instability of the codebook that undergoes partial updates during training. The codebook is prone to collapse as utilization decreases, due to the progressively widening distribution gap between non-activated codes and visual... | {
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2412.02693 | Diffusion-based Visual Anagram as Multi-task Learning | [
"cs.CV"
] | Visual anagrams are images that change appearance upon transformation, like flipping or rotation. With the advent of diffusion models, generating such optical illusions can be achieved by averaging noise across multiple views during the reverse denoising process. However, we observe two critical failure modes in this a... | {
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2412.02695 | An ADHD Diagnostic Interface Based on EEG Spectrograms and Deep Learning
Techniques | [
"cs.CY",
"cs.LG",
"eess.SP"
] | This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) diagnosis by employing deep learning (DL) techniques on electroencephalography (EEG) signals. This method addresses the limitations of current behavior-based diagnostic methods, which often lead to misdiagnosis and gender bi... | {
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2412.02698 | Scaling BERT Models for Turkish Automatic Punctuation and Capitalization
Correction | [
"cs.CL",
"cs.AI",
"cs.LG"
] | This paper investigates the effectiveness of BERT based models for automated punctuation and capitalization corrections in Turkish texts across five distinct model sizes. The models are designated as Tiny, Mini, Small, Medium, and Base. The design and capabilities of each model are tailored to address the specific chal... | {
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2412.02699 | UniGraspTransformer: Simplified Policy Distillation for Scalable
Dexterous Robotic Grasping | [
"cs.RO"
] | We introduce UniGraspTransformer, a universal Transformer-based network for dexterous robotic grasping that simplifies training while enhancing scalability and performance. Unlike prior methods such as UniDexGrasp++, which require complex, multi-step training pipelines, UniGraspTransformer follows a streamlined process... | {
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2412.02700 | Motion Prompting: Controlling Video Generation with Motion Trajectories | [
"cs.CV"
] | Motion control is crucial for generating expressive and compelling video content; however, most existing video generation models rely mainly on text prompts for control, which struggle to capture the nuances of dynamic actions and temporal compositions. To this end, we train a video generation model conditioned on spat... | {
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2412.02702 | Fine Tuning Swimming Locomotion Learned from Mosquito Larvae | [
"cs.NE",
"cs.AI"
] | In prior research, we analyzed the backwards swimming motion of mosquito larvae, parameterized it, and replicated it in a Computational Fluid Dynamics (CFD) model. Since the parameterized swimming motion is copied from observed larvae, it is not necessarily the most efficient locomotion for the model of the swimmer. In... | {
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2412.02704 | Correlation Clustering with Overlap: a Heuristic Graph Editing Approach | [
"cs.SI"
] | Correlation clustering seeks a partition of the vertex set of a given graph/network into groups of closely related, or just close enough, vertices so that elements of different groups are not close to each other. The problem has been previously modeled and studied as a graph editing problem, namely Cluster Editing, whi... | {
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2412.02708 | Nutzung von Massespeichern zur Flexibilisierung des Energieverbrauchs:
Kosteneffizienter Anlagenbetrieb durch Anpassung an Marktpreise | [
"eess.SY",
"cs.SY"
] | The increasing share of renewable energy sources and necessitate new concepts for energy flexible operation of industrial production resources. In this paper, we demonstrate the potential of mass storage to increase energy flexibility in industrial operations through the application of optimized operational planning ba... | {
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} |
2412.02711 | Community Detection of Complex Network Based on Graph Convolution
Iterative Algorithm | [
"cs.SI"
] | Community detection can reveal the underlying structure and patterns of complex networks, identify sets of nodes with specific functions or similar characteristics, and study the evolution process and development trends of networks. Despite the myriad community detection methods that have been proposed, researchers con... | {
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2412.02712 | Analyzing political stances on Twitter in the lead-up to the 2024 U.S.
election | [
"cs.SI",
"cs.CY"
] | Social media platforms play a pivotal role in shaping public opinion and amplifying political discourse, particularly during elections. However, the same dynamics that foster democratic engagement can also exacerbate polarization. To better understand these challenges, here, we investigate the ideological positioning o... | {
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2412.02713 | Applying IRT to Distinguish Between Human and Generative AI Responses to
Multiple-Choice Assessments | [
"cs.AI"
] | Generative AI is transforming the educational landscape, raising significant concerns about cheating. Despite the widespread use of multiple-choice questions in assessments, the detection of AI cheating in MCQ-based tests has been almost unexplored, in contrast to the focus on detecting AI-cheating on text-rich student... | {
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2412.02714 | Nuevo modelo para el dimensionamiento de lotes de pedidos en funci\'on
del volumen de compra y deterioro temporal de los art\'iculos | [
"math.OC",
"cs.SY",
"eess.SY"
] | This research presents the development of a new simulation model to determine the optimal order lot sizes in Material Requirements Planning, based on purchase volume and the temporal deterioration of items. The scientific novelty lies in the exhaustive enumeration of all supply strategies, considering when and how much... | {
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2412.02715 | Scalar embedding of temporal network trajectories | [
"physics.soc-ph",
"cs.SI",
"physics.data-an"
] | A temporal network -- a collection of snapshots recording the evolution of a network whose links appear and disappear dynamically -- can be interpreted as a trajectory in graph space. In order to characterize the complex dynamics of such trajectory via the tools of time series analysis and signal processing, it is sens... | {
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2412.02720 | Quantum Annealing based Hybrid Strategies for Real Time Route
Optimization | [
"quant-ph",
"cs.CE",
"cs.ET"
] | One of the most well-known problems in transportation and logistics is the Capacitated Vehicle Routing Problem (CVRP). It involves optimizing a set of truck routes to service a set of customers, subject to limits on truck capacity, to reduce travel costs. The biggest challenge faced whilst attempting to solve the issue... | {
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2412.02722 | Enhanced N-BEATS for Mid-Term Electricity Demand Forecasting | [
"cs.LG",
"cs.AI"
] | This paper presents an enhanced N-BEATS model, N-BEATS*, for improved mid-term electricity load forecasting (MTLF). Building on the strengths of the original N-BEATS architecture, which excels in handling complex time series data without requiring preprocessing or domain-specific knowledge, N-BEATS* introduces two key ... | {
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2412.02723 | DYffCast: Regional Precipitation Nowcasting Using IMERG Satellite Data.
A case study over South America | [
"cs.LG",
"cs.AI"
] | Climate change is increasing the frequency of extreme precipitation events, making weather disasters such as flooding and landslides more likely. The ability to accurately nowcast precipitation is therefore becoming more critical for safeguarding society by providing immediate, accurate information to decision makers. ... | {
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} |
2412.02725 | emg2pose: A Large and Diverse Benchmark for Surface Electromyographic
Hand Pose Estimation | [
"cs.CV",
"cs.HC",
"cs.LG"
] | Hands are the primary means through which humans interact with the world. Reliable and always-available hand pose inference could yield new and intuitive control schemes for human-computer interactions, particularly in virtual and augmented reality. Computer vision is effective but requires one or multiple cameras and ... | {
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} |
2412.02729 | Resource-Adaptive Successive Doubling for Hyperparameter Optimization
with Large Datasets on High-Performance Computing Systems | [
"cs.LG",
"cs.DC"
] | On High-Performance Computing (HPC) systems, several hyperparameter configurations can be evaluated in parallel to speed up the Hyperparameter Optimization (HPO) process. State-of-the-art HPO methods follow a bandit-based approach and build on top of successive halving, where the final performance of a combination is e... | {
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2412.02730 | Shaping AI's Impact on Billions of Lives | [
"cs.AI",
"cs.CY",
"cs.ET",
"cs.LG"
] | Artificial Intelligence (AI), like any transformative technology, has the potential to be a double-edged sword, leading either toward significant advancements or detrimental outcomes for society as a whole. As is often the case when it comes to widely-used technologies in market economies (e.g., cars and semiconductor ... | {
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2412.02732 | Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth
Observation Applications | [
"cs.CV"
] | This technical report presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2M global time series samples from NASA's Harmonized Landsat and Sentinel-2 data archive at 30m resolution, the new 300M and 600M parameter models inco... | {
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2412.02734 | MVCTrack: Boosting 3D Point Cloud Tracking via Multimodal-Guided Virtual
Cues | [
"cs.CV",
"cs.RO"
] | 3D single object tracking is essential in autonomous driving and robotics. Existing methods often struggle with sparse and incomplete point cloud scenarios. To address these limitations, we propose a Multimodal-guided Virtual Cues Projection (MVCP) scheme that generates virtual cues to enrich sparse point clouds. Addit... | {
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2412.02735 | CPP-UT-Bench: Can LLMs Write Complex Unit Tests in C++? | [
"cs.SE",
"cs.LG"
] | We introduce CPP-UT-Bench, a benchmark dataset to measure C++ unit test generation capability of a large language model (LLM). CPP-UT-Bench aims to reflect a broad and diverse set of C++ codebases found in the real world. The dataset includes 2,653 {code, unit test} pairs drawn from 14 different opensource C++ codebase... | {
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2412.02758 | Data-Driven LQR with Finite-Time Experiments via Extremum-Seeking Policy
Iteration | [
"math.OC",
"cs.SY",
"eess.SY"
] | In this paper, we address Linear Quadratic Regulator (LQR) problems through a novel iterative algorithm named EXtremum-seeking Policy iteration LQR (EXP-LQR). The peculiarity of EXP-LQR is that it only needs access to a truncated approximation of the infinite-horizon cost associated to a given policy. Hence, EXP-LQR do... | {
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2412.02759 | Mixture of Physical Priors Adapter for Parameter-Efficient Fine-Tuning | [
"cs.CV"
] | Most parameter-efficient fine-tuning (PEFT) methods rely on low-rank representations to adapt models. However, these approaches often oversimplify representations, particularly when the underlying data has high-rank or high-frequency components. This limitation hinders the model's ability to capture complex data intera... | {
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2412.02760 | Cosmos-LLaVA: Chatting with the Visual Cosmos-LLaVA: G\"orselle Sohbet
Etmek | [
"cs.AI",
"cs.CL",
"cs.CV",
"cs.LG"
] | In this study, a Turkish visual instruction model was developed and various model architectures and dataset combinations were analysed to improve the performance of this model. The Cosmos-LLaVA model, which is built by combining different large language models and image coders, is designed to overcome the deficiencies ... | {
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2412.02764 | Drawing Pandas: A Benchmark for LLMs in Generating Plotting Code | [
"cs.SE",
"cs.AI",
"cs.LG"
] | This paper introduces the human-curated PandasPlotBench dataset, designed to evaluate language models' effectiveness as assistants in visual data exploration. Our benchmark focuses on generating code for visualizing tabular data - such as a Pandas DataFrame - based on natural language instructions, complementing curren... | {
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2412.02768 | Quaternion-based Unscented Kalman Filter for 6-DoF Vision-based Inertial
Navigation in GPS-denied Regions | [
"cs.RO",
"cs.SY",
"eess.SY"
] | This paper investigates the orientation, position, and linear velocity estimation problem of a rigid-body moving in three-dimensional (3D) space with six degrees-of-freedom (6 DoF). The highly nonlinear navigation kinematics are formulated to ensure global representation of the navigation problem. A computationally eff... | {
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2412.02775 | Optimizing Large Language Models for Turkish: New Methodologies in
Corpus Selection and Training | [
"cs.CL",
"cs.AI",
"cs.LG"
] | In this study, we develop and assess new corpus selection and training methodologies to improve the effectiveness of Turkish language models. Specifically, we adapted Large Language Model generated datasets and translated English datasets into Turkish, integrating these resources into the training process. This approac... | {
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2412.02776 | Hacking CTFs with Plain Agents | [
"cs.CR",
"cs.AI"
] | We saturate a high-school-level hacking benchmark with plain LLM agent design. Concretely, we obtain 95% performance on InterCode-CTF, a popular offensive security benchmark, using prompting, tool use, and multiple attempts. This beats prior work by Phuong et al. 2024 (29%) and Abramovich et al. 2024 (72%). Our resul... | {
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2412.02779 | Synergistic Development of Perovskite Memristors and Algorithms for
Robust Analog Computing | [
"cs.LG",
"cs.AI",
"cs.ET"
] | Analog computing using non-volatile memristors has emerged as a promising solution for energy-efficient deep learning. New materials, like perovskites-based memristors are recently attractive due to their cost-effectiveness, energy efficiency and flexibility. Yet, challenges in material diversity and immature fabricati... | {
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2412.02780 | WxC-Bench: A Novel Dataset for Weather and Climate Downstream Tasks | [
"cs.LG",
"cs.AI"
] | High-quality machine learning (ML)-ready datasets play a foundational role in developing new artificial intelligence (AI) models or fine-tuning existing models for scientific applications such as weather and climate analysis. Unfortunately, despite the growing development of new deep learning models for weather and cli... | {
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2412.02781 | Methods with Local Steps and Random Reshuffling for Generally Smooth
Non-Convex Federated Optimization | [
"math.OC",
"cs.LG"
] | Non-convex Machine Learning problems typically do not adhere to the standard smoothness assumption. Based on empirical findings, Zhang et al. (2020b) proposed a more realistic generalized $(L_0, L_1)$-smoothness assumption, though it remains largely unexplored. Many existing algorithms designed for standard smooth prob... | {
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2412.02784 | FathomGPT: A Natural Language Interface for Interactively Exploring
Ocean Science Data | [
"cs.HC",
"cs.AI"
] | We introduce FathomGPT, an open source system for the interactive investigation of ocean science data via a natural language interface. FathomGPT was developed in close collaboration with marine scientists to enable researchers to explore and analyze the FathomNet image database. FathomGPT provides a custom information... | {
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2412.02788 | Hybrid-SQuAD: Hybrid Scholarly Question Answering Dataset | [
"cs.CL",
"cs.AI"
] | Existing Scholarly Question Answering (QA) methods typically target homogeneous data sources, relying solely on either text or Knowledge Graphs (KGs). However, scholarly information often spans heterogeneous sources, necessitating the development of QA systems that integrate information from multiple heterogeneous data... | {
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2412.02790 | An Evolutionary Large Language Model for Hallucination Mitigation | [
"cs.CL",
"cs.AI"
] | The emergence of LLMs, like ChatGPT and Gemini, has marked the modern era of artificial intelligence applications characterized by high-impact applications generating text, images, and videos. However, these models usually ensue with one critical challenge called hallucination: confident presentation of inaccurate or f... | {
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2412.02792 | Taurus Database: How to be Fast, Available, and Frugal in the Cloud | [
"cs.DB",
"cs.DC"
] | Using cloud Database as a Service (DBaaS) offerings instead of on-premise deployments is increasingly common. Key advantages include improved availability and scalability at a lower cost than on-premise alternatives. In this paper, we describe the design of Taurus, a new multi-tenant cloud database system. Taurus separ... | {
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2412.02795 | Hijacking Vision-and-Language Navigation Agents with Adversarial
Environmental Attacks | [
"cs.CV",
"cs.RO"
] | Assistive embodied agents that can be instructed in natural language to perform tasks in open-world environments have the potential to significantly impact labor tasks like manufacturing or in-home care -- benefiting the lives of those who come to depend on them. In this work, we consider how this benefit might be hija... | {
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2412.02796 | Harnessing Multiple Correlated Networks for Exact Community Recovery | [
"math.ST",
"cs.IT",
"cs.LG",
"cs.SI",
"math.IT",
"math.PR",
"stat.TH"
] | We study the problem of learning latent community structure from multiple correlated networks, focusing on edge-correlated stochastic block models with two balanced communities. Recent work of Gaudio, R\'acz, and Sridhar (COLT 2022) determined the precise information-theoretic threshold for exact community recovery usi... | {
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2412.02798 | Grayscale to Hyperspectral at Any Resolution Using a Phase-Only Lens | [
"cs.CV",
"eess.IV",
"physics.optics"
] | We consider the problem of reconstructing a $H\times W\times 31$ hyperspectral image from a $H\times W$ grayscale snapshot measurement that is captured using a single diffractive optic and a filterless panchromatic photosensor. This problem is severely ill-posed, and we present the first model that is able to produce h... | {
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2412.02799 | QPET: A Versatile and Portable Quantity-of-Interest-preservation
Framework for Error-Bounded Lossy Compression | [
"cs.DB",
"cs.CE",
"cs.DC"
] | Error-bounded lossy compression has been widely adopted in many scientific domains because it can address the challenges in storing, transferring, and analyzing the unprecedented amount of scientific data. Although error-bounded lossy compression offers general data distortion control by enforcing strict error bounds o... | {
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2412.02801 | Optimization of Transformer heart disease prediction model based on
particle swarm optimization algorithm | [
"cs.AI"
] | Aiming at the latest particle swarm optimization algorithm, this paper proposes an improved Transformer model to improve the accuracy of heart disease prediction and provide a new algorithm idea. We first use three mainstream machine learning classification algorithms - decision tree, random forest and XGBoost, and the... | {
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2412.02802 | Flattering to Deceive: The Impact of Sycophantic Behavior on User Trust
in Large Language Model | [
"cs.AI"
] | Sycophancy refers to the tendency of a large language model to align its outputs with the user's perceived preferences, beliefs, or opinions, in order to look favorable, regardless of whether those statements are factually correct. This behavior can lead to undesirable consequences, such as reinforcing discriminatory b... | {
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2412.02803 | Gaussian Splatting Under Attack: Investigating Adversarial Noise in 3D
Objects | [
"cs.CV",
"cs.AI",
"eess.IV"
] | 3D Gaussian Splatting has advanced radiance field reconstruction, enabling high-quality view synthesis and fast rendering in 3D modeling. While adversarial attacks on object detection models are well-studied for 2D images, their impact on 3D models remains underexplored. This work introduces the Masked Iterative Fast G... | {
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2412.02805 | STORM: Strategic Orchestration of Modalities for Rare Event
Classification | [
"cs.CV"
] | In domains such as biomedical, expert insights are crucial for selecting the most informative modalities for artificial intelligence (AI) methodologies. However, using all available modalities poses challenges, particularly in determining the impact of each modality on performance and optimizing their combinations for ... | {
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2412.02807 | Learning Koopman-based Stability Certificates for Unknown Nonlinear
Systems | [
"eess.SY",
"cs.LG",
"cs.SY",
"math.DS"
] | Koopman operator theory has gained significant attention in recent years for identifying discrete-time nonlinear systems by embedding them into an infinite-dimensional linear vector space. However, providing stability guarantees while learning the continuous-time dynamics, especially under conditions of relatively low ... | {
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2412.02808 | Temporally Consistent Dynamic Scene Graphs: An End-to-End Approach for
Action Tracklet Generation | [
"cs.CV",
"cs.LG"
] | Understanding video content is pivotal for advancing real-world applications like activity recognition, autonomous systems, and human-computer interaction. While scene graphs are adept at capturing spatial relationships between objects in individual frames, extending these representations to capture dynamic interaction... | {
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2412.02809 | The origin, consequence, and visibility of criticism in science | [
"cs.DL",
"cs.SI"
] | Critique between peers plays a vital role in the production of scientific knowledge. Yet, there is limited empirical evidence on the origins of criticism, its effects on the papers and individuals involved, and its visibility within the scientific literature. Here, we address these gaps through a data-driven analysis o... | {
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} |
2412.02810 | Universal Rates of Empirical Risk Minimization | [
"stat.ML",
"cs.LG"
] | The well-known empirical risk minimization (ERM) principle is the basis of many widely used machine learning algorithms, and plays an essential role in the classical PAC theory. A common description of a learning algorithm's performance is its so-called "learning curve", that is, the decay of the expected error as a fu... | {
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} |
2412.02811 | Kernel-based Koopman approximants for control: Flexible sampling, error
analysis, and stability | [
"math.OC",
"cs.SY",
"eess.SY"
] | Data-driven techniques for analysis, modeling, and control of complex dynamical systems are on the uptake. Koopman theory provides the theoretical foundation for the extremely popular kernel extended dynamic mode decomposition (kEDMD). In this work we propose a novel kEDMD scheme to approximate nonlinear control system... | {
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} |
2412.02818 | From Mystery to Mastery: Failure Diagnosis for Improving Manipulation
Policies | [
"cs.RO",
"cs.LG"
] | Robot manipulation policies often fail for unknown reasons, posing significant challenges for real-world deployment. Researchers and engineers typically address these failures using heuristic approaches, which are not only labor-intensive and costly but also prone to overlooking critical failure modes (FMs). This paper... | {
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} |
2412.02819 | CNNSum: Exploring Long-Context Summarization with Large Language Models
in Chinese Novels | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) have been well-researched in various long-context tasks. However, the scarcity of high-quality long-context summarization datasets has hindered further advancements in this area. To address this, we introduce CNNSum, a multi-scale long-context summarization benchmark based on Chinese novels... | {
"Other": 0,
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"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.02823 | Minimization of Boolean Complexity in In-Context Concept Learning | [
"cs.CL",
"cs.AI"
] | What factors contribute to the relative success and corresponding difficulties of in-context learning for Large Language Models (LLMs)? Drawing on insights from the literature on human concept learning, we test LLMs on carefully designed concept learning tasks, and show that task performance highly correlates with the ... | {
"Other": 0,
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} |
2412.02825 | Many-MobileNet: Multi-Model Augmentation for Robust Retinal Disease
Classification | [
"cs.CV"
] | In this work, we propose Many-MobileNet, an efficient model fusion strategy for retinal disease classification using lightweight CNN architecture. Our method addresses key challenges such as overfitting and limited dataset variability by training multiple models with distinct data augmentation strategies and different ... | {
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} |
2412.02830 | RARE: Retrieval-Augmented Reasoning Enhancement for Large Language
Models | [
"cs.CL"
] | This work introduces RARE (Retrieval-Augmented Reasoning Enhancement), a versatile extension to the mutual reasoning framework (rStar), aimed at enhancing reasoning accuracy and factual integrity across large language models (LLMs) for complex, knowledge-intensive tasks such as commonsense and medical reasoning. RARE i... | {
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} |
2412.02831 | FLAME 3 Dataset: Unleashing the Power of Radiometric Thermal UAV Imagery
for Wildfire Management | [
"cs.CV",
"cs.AI"
] | The increasing accessibility of radiometric thermal imaging sensors for unmanned aerial vehicles (UAVs) offers significant potential for advancing AI-driven aerial wildfire management. Radiometric imaging provides per-pixel temperature estimates, a valuable improvement over non-radiometric data that requires irradiance... | {
"Other": 0,
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"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.02833 | Economic Hubs and the Domination of Inter-Regional Ties in World City
Networks | [
"physics.soc-ph",
"cs.SI"
] | Cities are widely considered the lifeblood of a nations economy housing the bulk of industries, commercial and trade activities, and employment opportunities. Within this economic context, multinational corporations play an important role in this economic development of cities in particular, and subsequently the countr... | {
"Other": 0,
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} |
2412.02835 | CAISSON: Concept-Augmented Inference Suite of Self-Organizing Neural
Networks | [
"cs.CL",
"cs.AI",
"cs.IR",
"cs.LG"
] | We present CAISSON, a novel hierarchical approach to Retrieval-Augmented Generation (RAG) that transforms traditional single-vector search into a multi-view clustering framework. At its core, CAISSON leverages dual Self-Organizing Maps (SOMs) to create complementary organizational views of the document space, where eac... | {
"Other": 0,
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} |
2412.02837 | Enhancing Robustness of CLIP to Common Corruptions through Bimodal
Test-Time Adaptation | [
"cs.CV"
] | Although open-vocabulary classification models like Contrastive Language Image Pretraining (CLIP) have demonstrated strong zero-shot learning capabilities, their robustness to common image corruptions remains poorly understood. Through extensive experiments, we show that zero-shot CLIP lacks robustness to common image ... | {
"Other": 0,
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"cs.SY": 0
} |
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