id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.14950 | Generalizing Constraint Models in Constraint Acquisition | [
"cs.AI"
] | Constraint Acquisition (CA) aims to widen the use of constraint programming by assisting users in the modeling process. However, most CA methods suffer from a significant drawback: they learn a single set of individual constraints for a specific problem instance, but cannot generalize these constraints to the parameter... | {
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2412.14954 | Corn Ear Detection and Orientation Estimation Using Deep Learning | [
"cs.CV",
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] | Monitoring growth behavior of maize plants such as the development of ears can give key insights into the plant's health and development. Traditionally, the measurement of the angle of ears is performed manually, which can be time-consuming and prone to human error. To address these challenges, this paper presents a co... | {
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2412.14957 | Dream to Manipulate: Compositional World Models Empowering Robot
Imitation Learning with Imagination | [
"cs.RO",
"cs.CV"
] | A world model provides an agent with a representation of its environment, enabling it to predict the causal consequences of its actions. Current world models typically cannot directly and explicitly imitate the actual environment in front of a robot, often resulting in unrealistic behaviors and hallucinations that make... | {
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2412.14959 | Understanding the Dark Side of LLMs' Intrinsic Self-Correction | [
"cs.CL"
] | Intrinsic self-correction was proposed to improve LLMs' responses via feedback prompts solely based on their inherent capability. However, recent works show that LLMs' intrinsic self-correction fails without oracle labels as feedback prompts. In this paper, we aim to interpret LLMs' intrinsic self-correction for differ... | {
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2412.14961 | TDCNet: Transparent Objects Depth Completion with CNN-Transformer
Dual-Branch Parallel Network | [
"cs.CV"
] | The sensing and manipulation of transparent objects present a critical challenge in industrial and laboratory robotics. Conventional sensors face challenges in obtaining the full depth of transparent objects due to the refraction and reflection of light on their surfaces and their lack of visible texture. Previous rese... | {
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2412.14963 | IDOL: Instant Photorealistic 3D Human Creation from a Single Image | [
"cs.CV",
"cs.GR",
"cs.LG"
] | Creating a high-fidelity, animatable 3D full-body avatar from a single image is a challenging task due to the diverse appearance and poses of humans and the limited availability of high-quality training data. To achieve fast and high-quality human reconstruction, this work rethinks the task from the perspectives of dat... | {
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2412.14964 | Knowledge Injection via Prompt Distillation | [
"cs.CL",
"cs.LG"
] | In many practical applications, large language models (LLMs) need to incorporate new knowledge not present in their pre-training data. The primary methods for this are fine-tuning and retrieval-augmented generation (RAG). Although RAG has emerged as the industry standard for knowledge injection, fine-tuning has not yet... | {
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2412.14965 | Movie2Story: A framework for understanding videos and telling stories in
the form of novel text | [
"cs.CV",
"cs.AI",
"cs.CL"
] | In recent years, large-scale models have achieved significant advancements, accompanied by the emergence of numerous high-quality benchmarks for evaluating various aspects of their comprehension abilities. However, most existing benchmarks primarily focus on spatial understanding in static image tasks. While some bench... | {
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2412.14967 | ECLIPSE: Contrastive Dimension Importance Estimation with
Pseudo-Irrelevance Feedback for Dense Retrieval | [
"cs.IR"
] | Recent advances in Information Retrieval have leveraged high-dimensional embedding spaces to improve the retrieval of relevant documents. Moreover, the Manifold Clustering Hypothesis suggests that despite these high-dimensional representations, documents relevant to a query reside on a lower-dimensional, query-dependen... | {
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2412.14968 | An Overview on Over-the-air Electromagnetic Signal Processing | [
"eess.SP",
"cs.IT",
"math.IT"
] | This article provides a tutorial on over-the-air electromagnetic signal processing (ESP) for next-generation wireless networks, addressing the limitations of digital processing to enhance the efficiency and sustainability of future 6th Generation (6G) systems. It explores the integration of electromagnetism and signal ... | {
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2412.14969 | PhotoHolmes: a Python library for forgery detection in digital images | [
"cs.CV"
] | In this paper, we introduce PhotoHolmes, an open-source Python library designed to easily run and benchmark forgery detection methods on digital images. The library includes implementations of popular and state-of-the-art methods, dataset integration tools, and evaluation metrics. Utilizing the Benchmark tool in PhotoH... | {
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2412.14974 | Arti-PG: A Toolbox for Procedurally Synthesizing Large-Scale and Diverse
Articulated Objects with Rich Annotations | [
"cs.CV",
"cs.RO"
] | The acquisition of substantial volumes of 3D articulated object data is expensive and time-consuming, and consequently the scarcity of 3D articulated object data becomes an obstacle for deep learning methods to achieve remarkable performance in various articulated object understanding tasks. Meanwhile, pairing these ob... | {
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2412.14978 | Spectrum-based Modality Representation Fusion Graph Convolutional
Network for Multimodal Recommendation | [
"cs.IR",
"cs.MM"
] | Incorporating multi-modal features as side information has recently become a trend in recommender systems. To elucidate user-item preferences, recent studies focus on fusing modalities via concatenation, element-wise sum, or attention mechanisms. Despite having notable success, existing approaches do not account for th... | {
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2412.14982 | Efficient Motion Sickness Assessment: Recreation of On-Road Driving on a
Compact Test Track | [
"cs.RO",
"cs.ET",
"cs.HC"
] | The ability to engage in other activities during the ride is considered by consumers as one of the key reasons for the adoption of automated vehicles. However, engagement in non-driving activities will provoke occupants' motion sickness, deteriorating their overall comfort and thereby risking acceptance of automated dr... | {
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2412.14984 | Co-optimization of Vehicle Dynamics and Powertrain Management for
Connected and Automated Electric Vehicles | [
"eess.SY",
"cs.SY"
] | Connected and automated vehicles (CAVs) represent the future of transportation, utilizing detailed traffic information to enhance control and decision-making. Eco-driving of CAVs has the potential to significantly improve energy efficiency, and the benefits are maximized when both vehicle speed and powertrain operation... | {
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2412.14986 | Chain-of-MetaWriting: Linguistic and Textual Analysis of How Small
Language Models Write Young Students Texts | [
"cs.CL"
] | Large Language Models (LLMs) have been used to generate texts in response to different writing tasks: reports, essays, story telling. However, language models do not have a meta-representation of the text writing process, nor inherent communication learning needs, comparable to those of young human students. This paper... | {
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2412.14988 | Stitch Contrast and Segment_Learning a Human Action Segmentation Model
Using Trimmed Skeleton Videos | [
"cs.CV",
"cs.LG"
] | Existing skeleton-based human action classification models rely on well-trimmed action-specific skeleton videos for both training and testing, precluding their scalability to real-world applications where untrimmed videos exhibiting concatenated actions are predominant. To overcome this limitation, recently introduced ... | {
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2412.14989 | RoboCup@Home 2024 OPL Winner NimbRo: Anthropomorphic Service Robots
using Foundation Models for Perception and Planning | [
"cs.RO"
] | We present the approaches and contributions of the winning team NimbRo@Home at the RoboCup@Home 2024 competition in the Open Platform League held in Eindhoven, NL. Further, we describe our hardware setup and give an overview of the results for the task stages and the final demonstration. For this year's competition, we... | {
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2412.14995 | HSEvo: Elevating Automatic Heuristic Design with Diversity-Driven
Harmony Search and Genetic Algorithm Using LLMs | [
"cs.NE",
"cs.AI"
] | Automatic Heuristic Design (AHD) is an active research area due to its utility in solving complex search and NP-hard combinatorial optimization problems in the real world. The recent advancements in Large Language Models (LLMs) introduce new possibilities by coupling LLMs with evolutionary computation to automatically ... | {
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2412.15000 | Autonomous Navigation in Dynamic Human Environments with an Embedded 2D
LiDAR-based Person Tracker | [
"cs.RO",
"cs.SY",
"eess.SY"
] | In the rapidly evolving landscape of autonomous mobile robots, the emphasis on seamless human-robot interactions has shifted towards autonomous decision-making. This paper delves into the intricate challenges associated with robotic autonomy, focusing on navigation in dynamic environments shared with humans. It introdu... | {
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2412.15004 | Large Language Models and Code Security: A Systematic Literature Review | [
"cs.CR",
"cs.AI",
"cs.CL"
] | Large Language Models (LLMs) have emerged as powerful tools for automating various programming tasks, including security-related ones, such as detecting and fixing vulnerabilities. Despite their promising capabilities, when required to produce or modify pre-existing code, LLMs could introduce vulnerabilities unbeknown ... | {
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2412.15005 | DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start
Cross-Domain Recommendation | [
"cs.IR",
"cs.LG"
] | Recommender systems are widely used in various real-world applications, but they often encounter the persistent challenge of the user cold-start problem. Cross-domain recommendation (CDR), which leverages user interactions from one domain to improve prediction performance in another, has emerged as a promising solution... | {
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2412.15010 | Robust Federated Learning in the Face of Covariate Shift: A Magnitude
Pruning with Hybrid Regularization Framework for Enhanced Model Aggregation | [
"cs.LG",
"cs.CV"
] | The development of highly sophisticated neural networks has allowed for fast progress in every field of computer vision, however, applications where annotated data is prohibited due to privacy or security concerns remain challenging. Federated Learning (FL) offers a promising framework for individuals aiming to collabo... | {
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2412.15021 | Event-based backpropagation on the neuromorphic platform SpiNNaker2 | [
"cs.NE",
"cs.AR",
"cs.ET"
] | Neuromorphic computing aims to replicate the brain's capabilities for energy efficient and parallel information processing, promising a solution to the increasing demand for faster and more efficient computational systems. Efficient training of neural networks on neuromorphic hardware requires the development of traini... | {
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2412.15023 | Stable-V2A: Synthesis of Synchronized Sound Effects with Temporal and
Semantic Controls | [
"cs.SD",
"cs.CV",
"cs.LG",
"cs.MM",
"eess.AS"
] | Sound designers and Foley artists usually sonorize a scene, such as from a movie or video game, by manually annotating and sonorizing each action of interest in the video. In our case, the intent is to leave full creative control to sound designers with a tool that allows them to bypass the more repetitive parts of the... | {
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2412.15032 | DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT
Space | [
"cs.CV",
"cs.LG",
"eess.IV"
] | This paper explores image modeling from the frequency space and introduces DCTdiff, an end-to-end diffusion generative paradigm that efficiently models images in the discrete cosine transform (DCT) space. We investigate the design space of DCTdiff and reveal the key design factors. Experiments on different frameworks (... | {
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2412.15035 | LLMs Lost in Translation: M-ALERT uncovers Cross-Linguistic Safety Gaps | [
"cs.CL"
] | Building safe Large Language Models (LLMs) across multiple languages is essential in ensuring both safe access and linguistic diversity. To this end, we introduce M-ALERT, a multilingual benchmark that evaluates the safety of LLMs in five languages: English, French, German, Italian, and Spanish. M-ALERT includes 15k hi... | {
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2412.15040 | Noise Analysis and Modeling of the PMD Flexx2 Depth Camera for Robotic
Applications | [
"eess.IV",
"cs.RO"
] | Time of Flight ToF cameras renowned for their ability to capture realtime 3D information have become indispensable for agile mobile robotics These cameras utilize light signals to accurately measure distances enabling robots to navigate complex environments with precision Innovative depth cameras characterized by their... | {
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2412.15047 | Measuring, Modeling, and Helping People Account for Privacy Risks in
Online Self-Disclosures with AI | [
"cs.HC",
"cs.AI"
] | In pseudonymous online fora like Reddit, the benefits of self-disclosure are often apparent to users (e.g., I can vent about my in-laws to understanding strangers), but the privacy risks are more abstract (e.g., will my partner be able to tell that this is me?). Prior work has sought to develop natural language process... | {
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2412.15050 | Uni-Renderer: Unifying Rendering and Inverse Rendering Via Dual Stream
Diffusion | [
"cs.CV"
] | Rendering and inverse rendering are pivotal tasks in both computer vision and graphics. The rendering equation is the core of the two tasks, as an ideal conditional distribution transfer function from intrinsic properties to RGB images. Despite achieving promising results of existing rendering methods, they merely appr... | {
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2412.15054 | GIRAFE: Glottal Imaging Dataset for Advanced Segmentation, Analysis, and
Facilitative Playbacks Evaluation | [
"cs.CV",
"cs.AI",
"cs.SD",
"eess.AS"
] | The advances in the development of Facilitative Playbacks extracted from High-Speed videoendoscopic sequences of the vocal folds are hindered by a notable lack of publicly available datasets annotated with the semantic segmentations corresponding to the area of the glottal gap. This fact also limits the reproducibility... | {
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2412.15058 | MultiverSeg: Scalable Interactive Segmentation of Biomedical Imaging
Datasets with In-Context Guidance | [
"cs.CV",
"cs.LG",
"eess.IV"
] | Medical researchers and clinicians often need to perform novel segmentation tasks on a set of related images. Existing methods for segmenting a new dataset are either interactive, requiring substantial human effort for each image, or require an existing set of manually labeled images. We introduce a system, MultiverSeg... | {
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2412.15060 | ConfliBERT: A Language Model for Political Conflict | [
"cs.CL"
] | Conflict scholars have used rule-based approaches to extract information about political violence from news reports and texts. Recent Natural Language Processing developments move beyond rigid rule-based approaches. We review our recent ConfliBERT language model (Hu et al. 2022) to process political and violence relate... | {
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2412.15075 | DroughtSet: Understanding Drought Through Spatial-Temporal Learning | [
"cs.LG"
] | Drought is one of the most destructive and expensive natural disasters, severely impacting natural resources and risks by depleting water resources and diminishing agricultural yields. Under climate change, accurately predicting drought is critical for mitigating drought-induced risks. However, the intricate interplay ... | {
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2412.15077 | Till the Layers Collapse: Compressing a Deep Neural Network through the
Lenses of Batch Normalization Layers | [
"cs.LG",
"cs.CL",
"cs.CV"
] | Today, deep neural networks are widely used since they can handle a variety of complex tasks. Their generality makes them very powerful tools in modern technology. However, deep neural networks are often overparameterized. The usage of these large models consumes a lot of computation resources. In this paper, we introd... | {
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2412.15078 | Novel Conditions for the Finite-Region Stability of 2D-Systems with
Application to Iterative Learning Control | [
"eess.SY",
"cs.SY",
"math.OC"
] | Some recent papers have extended the concept of finite-time stability (FTS) to the context of 2D linear systems, where it has been referred to as finite-region stability (FRS). FRS methodologies make even more sense than the classical FTS approach developed for 1D-systems, since, typically, at least one of the state va... | {
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2412.15079 | A Traffic Adapative Physics-informed Learning Control for Energy Savings
of Connected and Automated Vehicles | [
"eess.SY",
"cs.SY"
] | Model predictive control has emerged as an effective approach for real-time optimal control of connected and automated vehicles. However, nonlinear dynamics of vehicle and traffic systems make accurate modeling and real-time optimization challenging. Learning-based control offer a promising alternative, as they adapt t... | {
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2412.15084 | AceMath: Advancing Frontier Math Reasoning with Post-Training and Reward
Modeling | [
"cs.CL",
"cs.AI",
"cs.LG"
] | In this paper, we introduce AceMath, a suite of frontier math models that excel in solving complex math problems, along with highly effective reward models capable of evaluating generated solutions and reliably identifying the correct ones. To develop the instruction-tuned math models, we propose a supervised fine-tuni... | {
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2412.15086 | Learning Disentangled Equivariant Representation for Explicitly
Controllable 3D Molecule Generation | [
"cs.LG",
"cs.AI"
] | We consider the conditional generation of 3D drug-like molecules with \textit{explicit control} over molecular properties such as drug-like properties (e.g., Quantitative Estimate of Druglikeness or Synthetic Accessibility score) and effectively binding to specific protein sites. To tackle this problem, we propose an E... | {
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2412.15093 | Nano-ESG: Extracting Corporate Sustainability Information from News
Articles | [
"cs.IR"
] | Determining the sustainability impact of companies is a highly complex subject which has garnered more and more attention over the past few years. Today, investors largely rely on sustainability-ratings from established rating-providers in order to analyze how responsibly a company acts. However, those ratings have rec... | {
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2412.15095 | A Full Transformer-based Framework for Automatic Pain Estimation using
Videos | [
"cs.CV",
"cs.AI",
"cs.LG"
] | The automatic estimation of pain is essential in designing an optimal pain management system offering reliable assessment and reducing the suffering of patients. In this study, we present a novel full transformer-based framework consisting of a Transformer in Transformer (TNT) model and a Transformer leveraging cross-a... | {
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2412.15098 | A Cross-Domain Study of the Use of Persuasion Techniques in Online
Disinformation | [
"cs.CY",
"cs.AI",
"cs.CL"
] | Disinformation, irrespective of domain or language, aims to deceive or manipulate public opinion, typically through employing advanced persuasion techniques. Qualitative and quantitative research on the weaponisation of persuasion techniques in disinformation has been mostly topic-specific (e.g., COVID-19) with limited... | {
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2412.15100 | Tests for model misspecification in simulation-based inference: from
local distortions to global model checks | [
"astro-ph.IM",
"astro-ph.CO",
"cs.LG",
"gr-qc"
] | Model misspecification analysis strategies, such as anomaly detection, model validation, and model comparison are a key component of scientific model development. Over the last few years, there has been a rapid rise in the use of simulation-based inference (SBI) techniques for Bayesian parameter estimation, applied to ... | {
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2412.15101 | Review-Then-Refine: A Dynamic Framework for Multi-Hop Question Answering
with Temporal Adaptability | [
"cs.CL"
] | Retrieve-augmented generation (RAG) frameworks have emerged as a promising solution to multi-hop question answering(QA) tasks since it enables large language models (LLMs) to incorporate external knowledge and mitigate their inherent knowledge deficiencies. Despite this progress, existing RAG frameworks, which usually ... | {
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2412.15105 | Exploiting sparse structures and synergy designs to advance situational
awareness of electrical power grid | [
"eess.SP",
"cs.AI"
] | The growing threats of uncertainties, anomalies, and cyberattacks on power grids are driving a critical need to advance situational awareness which allows system operators to form a complete and accurate picture of the present and future state. Simulation and estimation are foundational tools in this process. However, ... | {
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2412.15106 | Knowing Where to Focus: Attention-Guided Alignment for Text-based Person
Search | [
"cs.CV"
] | In the realm of Text-Based Person Search (TBPS), mainstream methods aim to explore more efficient interaction frameworks between text descriptions and visual data. However, recent approaches encounter two principal challenges. Firstly, the widely used random-based Masked Language Modeling (MLM) considers all the words ... | {
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2412.15109 | Predictive Inverse Dynamics Models are Scalable Learners for Robotic
Manipulation | [
"cs.RO"
] | Current efforts to learn scalable policies in robotic manipulation primarily fall into two categories: one focuses on "action," which involves behavior cloning from extensive collections of robotic data, while the other emphasizes "vision," enhancing model generalization by pre-training representations or generative mo... | {
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2412.15113 | Associative memory inspires improvements for in-context learning using a
novel attention residual stream architecture | [
"cs.NE",
"cs.AI",
"cs.CL"
] | Large language models (LLMs) demonstrate an impressive ability to utilise information within the context of their input sequences to appropriately respond to data unseen by the LLM during its training procedure. This ability is known as in-context learning (ICL). Humans and non-human animals demonstrate similar abiliti... | {
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2412.15114 | Towards Friendly AI: A Comprehensive Review and New Perspectives on
Human-AI Alignment | [
"cs.AI",
"cs.CY"
] | As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been proposed to advocate for more equitable and fair development of AI. Despite its importance, there is a lack of comprehensive reviews examining FAI from an ethical perspective, as well as limited discussion on its potential applicat... | {
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2412.15115 | Qwen2.5 Technical Report | [
"cs.CL"
] | In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been significantly improved during both the pre-training and post-training stages. In terms of pre-training, we have scaled the high-quality pre-trai... | {
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2412.15118 | Outcome-Refining Process Supervision for Code Generation | [
"cs.CL",
"cs.AI",
"cs.LG",
"cs.SE"
] | Large Language Models have demonstrated remarkable capabilities in code generation, yet they often struggle with complex programming tasks that require deep algorithmic reasoning. While process supervision through learned reward models shows promise in guiding reasoning steps, it requires expensive training data and su... | {
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2412.15119 | Parallelized Autoregressive Visual Generation | [
"cs.CV"
] | Autoregressive models have emerged as a powerful approach for visual generation but suffer from slow inference speed due to their sequential token-by-token prediction process. In this paper, we propose a simple yet effective approach for parallelized autoregressive visual generation that improves generation efficiency ... | {
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2412.15127 | Adaptive Pruning for Large Language Models with Structural Importance
Awareness | [
"cs.CL",
"cs.AI",
"cs.LG"
] | The recent advancements in large language models (LLMs) have significantly improved language understanding and generation capabilities. However, it is difficult to deploy LLMs on resource-constrained edge devices due to their high computational and storage resource demands. To address this issue, we propose a novel LLM... | {
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2412.15129 | Jet: A Modern Transformer-Based Normalizing Flow | [
"cs.CV",
"cs.AI",
"cs.LG"
] | In the past, normalizing generative flows have emerged as a promising class of generative models for natural images. This type of model has many modeling advantages: the ability to efficiently compute log-likelihood of the input data, fast generation and simple overall structure. Normalizing flows remained a topic of a... | {
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2412.15135 | Probabilistic Strategy Logic with Degrees of Observability | [
"cs.AI",
"cs.LO"
] | There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are unable to express properties relating to information transparency. Information transparency concerns the extent to which agents' actions and ... | {
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2412.15137 | Hydrogen in Aviation: Evaluating the Feasibility and Benefits of a Green
Fuel Alternative | [
"eess.SY",
"cs.SY"
] | Growing concerns regarding environmental health have highlighted the aviation industry's impact and potential mitigation strategies. Previous research has indicated hydrogen's significant potential for reducing the industry's environmental impact, yet implementation challenges remain. Through analysis of light aircraft... | {
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2412.15150 | Leveraging Color Channel Independence for Improved Unsupervised Object
Detection | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Object-centric architectures can learn to extract distinct object representations from visual scenes, enabling downstream applications on the object level. Similarly to autoencoder-based image models, object-centric approaches have been trained on the unsupervised reconstruction loss of images encoded by RGB color spac... | {
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2412.15151 | Language Models as Continuous Self-Evolving Data Engineers | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) have demonstrated remarkable capabilities on various tasks, while the further evolvement is limited to the lack of high-quality training data. In addition, traditional training approaches rely too much on expert-labeled data, setting a ceiling on the performance of LLMs. To address this iss... | {
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2412.15152 | Measuring DNA Microswimmer Locomotion in Complex Flow Environments | [
"cs.RO"
] | Microswimmers are sub-millimeter swimming microrobots that show potential as a platform for controllable locomotion in applications including targeted cargo delivery and minimally invasive surgery. To be viable for these target applications, microswimmers will eventually need to be able to navigate in environments with... | {
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2412.15156 | Prompt-A-Video: Prompt Your Video Diffusion Model via Preference-Aligned
LLM | [
"cs.CV",
"cs.CL",
"cs.MM"
] | Text-to-video models have made remarkable advancements through optimization on high-quality text-video pairs, where the textual prompts play a pivotal role in determining quality of output videos. However, achieving the desired output often entails multiple revisions and iterative inference to refine user-provided prom... | {
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2412.15159 | OnlineVPO: Align Video Diffusion Model with Online Video-Centric
Preference Optimization | [
"cs.CV"
] | In recent years, the field of text-to-video (T2V) generation has made significant strides. Despite this progress, there is still a gap between theoretical advancements and practical application, amplified by issues like degraded image quality and flickering artifacts. Recent advancements in enhancing the video diffusio... | {
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2412.15160 | On the structure of the Schur squares of Twisted Generalized
Reed-Solomon codes and application to cryptanalysis | [
"cs.IT",
"math.IT"
] | Twisted generalized Reed-Solomon (TGRS) codes constitute an interesting family of evaluation codes, containing a large class of maximum distance separable codes non-equivalent to generalized Reed-Solomon (GRS) ones. Moreover, the Schur squares of TGRS codes may be much larger than those of GRS codes with same dimension... | {
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2412.15163 | Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents | [
"cs.MA",
"cs.AI",
"cs.LG"
] | Social norms are standards of behaviour common in a society. However, when agents make decisions without considering how others are impacted, norms can emerge that lead to the subjugation of certain agents. We present RAWL-E, a method to create ethical norm-learning agents. RAWL-E agents operationalise maximin, a fairn... | {
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2412.15166 | Human-Humanoid Robots Cross-Embodiment Behavior-Skill Transfer Using
Decomposed Adversarial Learning from Demonstration | [
"cs.RO",
"cs.AI"
] | Humanoid robots are envisioned as embodied intelligent agents capable of performing a wide range of human-level loco-manipulation tasks, particularly in scenarios requiring strenuous and repetitive labor. However, learning these skills is challenging due to the high degrees of freedom of humanoid robots, and collecting... | {
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2412.15171 | SqueezeMe: Mobile-Ready Distillation of Gaussian Full-Body Avatars | [
"cs.CV"
] | Gaussian-based human avatars have achieved an unprecedented level of visual fidelity. However, existing approaches based on high-capacity neural networks typically require a desktop GPU to achieve real-time performance for a single avatar, and it remains non-trivial to animate and render such avatars on mobile devices ... | {
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2412.15176 | Rethinking Uncertainty Estimation in Natural Language Generation | [
"cs.LG"
] | Large Language Models (LLMs) are increasingly employed in real-world applications, driving the need to evaluate the trustworthiness of their generated text. To this end, reliable uncertainty estimation is essential. Since current LLMs generate text autoregressively through a stochastic process, the same prompt can lead... | {
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2412.15177 | Critical-Questions-of-Thought: Steering LLM reasoning with Argumentative
Querying | [
"cs.AI",
"cs.CL"
] | Studies have underscored how, regardless of the recent breakthrough and swift advances in AI research, even state-of-the-art Large Language models (LLMs) continue to struggle when performing logical and mathematical reasoning. The results seem to suggest that LLMs still work as (highly advanced) data pattern identifier... | {
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2412.15178 | HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages | [
"cs.DC",
"cs.LG",
"cs.SE"
] | Large Language Model (LLM) based coding tools have been tremendously successful as software development assistants, yet they are often designed for general purpose programming tasks and perform poorly for more specialized domains such as high performance computing. Creating specialized models and tools for these domain... | {
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2412.15182 | STRAP: Robot Sub-Trajectory Retrieval for Augmented Policy Learning | [
"cs.RO",
"cs.LG",
"cs.SY",
"eess.SY"
] | Robot learning is witnessing a significant increase in the size, diversity, and complexity of pre-collected datasets, mirroring trends in domains such as natural language processing and computer vision. Many robot learning methods treat such datasets as multi-task expert data and learn a multi-task, generalist policy b... | {
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2412.15184 | Data for Mathematical Copilots: Better Ways of Presenting Proofs for
Machine Learning | [
"cs.LG"
] | The suite of datasets commonly used to train and evaluate the mathematical capabilities of AI-based mathematical copilots (primarily large language models) exhibit several shortcomings. These limitations include a restricted scope of mathematical complexity, typically not exceeding lower undergraduate-level mathematics... | {
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2412.15185 | Tiled Diffusion | [
"cs.CV"
] | Image tiling -- the seamless connection of disparate images to create a coherent visual field -- is crucial for applications such as texture creation, video game asset development, and digital art. Traditionally, tiles have been constructed manually, a method that poses significant limitations in scalability and flexib... | {
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2412.15188 | LMFusion: Adapting Pretrained Language Models for Multimodal Generation | [
"cs.CL",
"cs.AI",
"cs.CV",
"cs.LG"
] | We present LMFusion, a framework for empowering pretrained text-only large language models (LLMs) with multimodal generative capabilities, enabling them to understand and generate both text and images in arbitrary sequences. LMFusion leverages existing Llama-3's weights for processing texts autoregressively while intro... | {
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2412.15189 | Face the Facts! Evaluating RAG-based Fact-checking Pipelines in
Realistic Settings | [
"cs.CL",
"cs.CY"
] | Natural Language Processing and Generation systems have recently shown the potential to complement and streamline the costly and time-consuming job of professional fact-checkers. In this work, we lift several constraints of current state-of-the-art pipelines for automated fact-checking based on the Retrieval-Augmented ... | {
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2412.15190 | EarthDial: Turning Multi-sensory Earth Observations to Interactive
Dialogues | [
"cs.CV"
] | Automated analysis of vast Earth observation data via interactive Vision-Language Models (VLMs) can unlock new opportunities for environmental monitoring, disaster response, and resource management. Existing generic VLMs do not perform well on Remote Sensing data, while the recent Geo-spatial VLMs remain restricted to ... | {
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2412.15191 | AV-Link: Temporally-Aligned Diffusion Features for Cross-Modal
Audio-Video Generation | [
"cs.CV",
"cs.LG",
"cs.SD",
"eess.AS"
] | We propose AV-Link, a unified framework for Video-to-Audio and Audio-to-Video generation that leverages the activations of frozen video and audio diffusion models for temporally-aligned cross-modal conditioning. The key to our framework is a Fusion Block that enables bidirectional information exchange between our backb... | {
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2412.15194 | MMLU-CF: A Contamination-free Multi-task Language Understanding
Benchmark | [
"cs.CL"
] | Multiple-choice question (MCQ) datasets like Massive Multitask Language Understanding (MMLU) are widely used to evaluate the commonsense, understanding, and problem-solving abilities of large language models (LLMs). However, the open-source nature of these benchmarks and the broad sources of training data for LLMs have... | {
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2412.15195 | Preventing Local Pitfalls in Vector Quantization via Optimal Transport | [
"cs.CV",
"cs.LG"
] | Vector-quantized networks (VQNs) have exhibited remarkable performance across various tasks, yet they are prone to training instability, which complicates the training process due to the necessity for techniques such as subtle initialization and model distillation. In this study, we identify the local minima issue as t... | {
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2412.15199 | LiDAR-RT: Gaussian-based Ray Tracing for Dynamic LiDAR Re-simulation | [
"cs.CV",
"cs.LG",
"cs.RO"
] | This paper targets the challenge of real-time LiDAR re-simulation in dynamic driving scenarios. Recent approaches utilize neural radiance fields combined with the physical modeling of LiDAR sensors to achieve high-fidelity re-simulation results. Unfortunately, these methods face limitations due to high computational de... | {
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2412.15200 | DI-PCG: Diffusion-based Efficient Inverse Procedural Content Generation
for High-quality 3D Asset Creation | [
"cs.CV",
"cs.AI",
"cs.GR"
] | Procedural Content Generation (PCG) is powerful in creating high-quality 3D contents, yet controlling it to produce desired shapes is difficult and often requires extensive parameter tuning. Inverse Procedural Content Generation aims to automatically find the best parameters under the input condition. However, existing... | {
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2412.15204 | LongBench v2: Towards Deeper Understanding and Reasoning on Realistic
Long-context Multitasks | [
"cs.CL",
"cs.AI"
] | This paper introduces LongBench v2, a benchmark designed to assess the ability of LLMs to handle long-context problems requiring deep understanding and reasoning across real-world multitasks. LongBench v2 consists of 503 challenging multiple-choice questions, with contexts ranging from 8k to 2M words, across six major ... | {
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2412.15205 | FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching | [
"cs.CV"
] | Autoregressive (AR) modeling has achieved remarkable success in natural language processing by enabling models to generate text with coherence and contextual understanding through next token prediction. Recently, in image generation, VAR proposes scale-wise autoregressive modeling, which extends the next token predicti... | {
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2412.15206 | AutoTrust: Benchmarking Trustworthiness in Large Vision Language Models
for Autonomous Driving | [
"cs.CV",
"cs.LG",
"cs.RO"
] | Recent advancements in large vision language models (VLMs) tailored for autonomous driving (AD) have shown strong scene understanding and reasoning capabilities, making them undeniable candidates for end-to-end driving systems. However, limited work exists on studying the trustworthiness of DriveVLMs -- a critical fact... | {
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2412.15208 | OpenEMMA: Open-Source Multimodal Model for End-to-End Autonomous Driving | [
"cs.CV",
"cs.LG",
"cs.RO"
] | Since the advent of Multimodal Large Language Models (MLLMs), they have made a significant impact across a wide range of real-world applications, particularly in Autonomous Driving (AD). Their ability to process complex visual data and reason about intricate driving scenarios has paved the way for a new paradigm in end... | {
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2412.15209 | PRIMA: Multi-Image Vision-Language Models for Reasoning Segmentation | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Despite significant advancements in Large Vision-Language Models (LVLMs), existing pixel-grounding models operate on single-image settings, limiting their ability to perform detailed, fine-grained comparisons across multiple images. Conversely, current multi-image understanding models lack pixel-level grounding. Our wo... | {
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2412.15210 | Tokenisation is NP-Complete | [
"cs.DS",
"cs.CL",
"cs.FL"
] | In this work, we prove the NP-completeness of two variants of tokenisation, defined as the problem of compressing a dataset to at most $\delta$ symbols by either finding a vocabulary directly (direct tokenisation), or selecting a sequence of merge operations (bottom-up tokenisation). | {
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2412.15211 | Generative Multiview Relighting for 3D Reconstruction under Extreme
Illumination Variation | [
"cs.CV"
] | Reconstructing the geometry and appearance of objects from photographs taken in different environments is difficult as the illumination and therefore the object appearance vary across captured images. This is particularly challenging for more specular objects whose appearance strongly depends on the viewing direction. ... | {
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2412.15212 | Scaling 4D Representations | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Scaling has not yet been convincingly demonstrated for pure self-supervised learning from video. However, prior work has focused evaluations on semantic-related tasks $\unicode{x2013}$ action classification, ImageNet classification, etc. In this paper we focus on evaluating self-supervised learning on non-semantic visi... | {
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2412.15213 | Flowing from Words to Pixels: A Framework for Cross-Modality Evolution | [
"cs.CV"
] | Diffusion models, and their generalization, flow matching, have had a remarkable impact on the field of media generation. Here, the conventional approach is to learn the complex mapping from a simple source distribution of Gaussian noise to the target media distribution. For cross-modal tasks such as text-to-image gene... | {
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2412.15214 | LeviTor: 3D Trajectory Oriented Image-to-Video Synthesis | [
"cs.CV"
] | The intuitive nature of drag-based interaction has led to its growing adoption for controlling object trajectories in image-to-video synthesis. Still, existing methods that perform dragging in the 2D space usually face ambiguity when handling out-of-plane movements. In this work, we augment the interaction with a new d... | {
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2412.15215 | EnvGS: Modeling View-Dependent Appearance with Environment Gaussian | [
"cs.CV"
] | Reconstructing complex reflections in real-world scenes from 2D images is essential for achieving photorealistic novel view synthesis. Existing methods that utilize environment maps to model reflections from distant lighting often struggle with high-frequency reflection details and fail to account for near-field reflec... | {
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} |
2412.15216 | UIP2P: Unsupervised Instruction-based Image Editing via Cycle Edit
Consistency | [
"cs.CV"
] | We propose an unsupervised model for instruction-based image editing that eliminates the need for ground-truth edited images during training. Existing supervised methods depend on datasets containing triplets of input image, edited image, and edit instruction. These are generated by either existing editing methods or h... | {
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} |
2412.15218 | Investigating the importance of social vulnerability in opioid-related
mortality across the United States | [
"cs.CY",
"cs.LG"
] | The opioid crisis remains a critical public health challenge in the United States. Despite national efforts to reduce opioid prescribing rates by nearly 45\% between 2011 and 2021, opioid overdose deaths more than tripled during this same period. This alarming trend reflects a major shift in the crisis, with illegal op... | {
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} |
2412.15222 | Leveraging Generative Adversarial Networks for Addressing Data Imbalance
in Financial Market Supervision | [
"q-fin.CP",
"cs.LG"
] | This study explores the application of generative adversarial networks in financial market supervision, especially for solving the problem of data imbalance to improve the accuracy of risk prediction. Since financial market data are often imbalanced, especially high-risk events such as market manipulation and systemic ... | {
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} |
2412.15224 | Multi-Branch Mutual-Distillation Transformer for EEG-Based Seizure
Subtype Classification | [
"eess.SP",
"cs.LG"
] | Cross-subject electroencephalogram (EEG) based seizure subtype classification is very important in precise epilepsy diagnostics. Deep learning is a promising solution, due to its ability to automatically extract latent patterns. However, it usually requires a large amount of training data, which may not always be avail... | {
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} |
2412.15226 | Learning-by-teaching with ChatGPT: The effect of teachable ChatGPT agent
on programming education | [
"cs.CY",
"cs.AI",
"stat.AP"
] | This study investigates the potential of using ChatGPT as a teachable agent to support students' learning by teaching process, specifically in programming education. While learning by teaching is an effective pedagogical strategy for promoting active learning, traditional teachable agents have limitations, particularly... | {
"Other": 0,
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} |
2412.15229 | Building an Explainable Graph-based Biomedical Paper Recommendation
System (Technical Report) | [
"cs.IR"
] | Digital libraries provide different access paths, allowing users to explore their collections. For instance, paper recommendation suggests literature similar to some selected paper. Their implementation is often cost-intensive, especially if neural methods are applied. Additionally, it is hard for users to understand o... | {
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} |
2412.15230 | Early Dementia Detection Using Multiple Spontaneous Speech Prompts: The
PROCESS Challenge | [
"cs.SD",
"cs.CL",
"eess.AS"
] | Dementia is associated with various cognitive impairments and typically manifests only after significant progression, making intervention at this stage often ineffective. To address this issue, the Prediction and Recognition of Cognitive Decline through Spontaneous Speech (PROCESS) Signal Processing Grand Challenge inv... | {
"Other": 0,
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} |
2412.15232 | Ranking Narrative Query Graphs for Biomedical Document Retrieval
(Technical Report) | [
"cs.IR"
] | Keyword-based searches are today's standard in digital libraries. Yet, complex retrieval scenarios like in scientific knowledge bases, need more sophisticated access paths. Although each document somewhat contributes to a domain's body of knowledge, the exact structure between keywords, i.e., their possible relationshi... | {
"Other": 0,
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} |
2412.15235 | OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large
Language Models | [
"cs.CL",
"cs.AI"
] | This paper presents OG-RAG, an Ontology-Grounded Retrieval Augmented Generation method designed to enhance LLM-generated responses by anchoring retrieval processes in domain-specific ontologies. While LLMs are widely used for tasks like question answering and search, they struggle to adapt to specialized knowledge, suc... | {
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} |
2412.15236 | CareBot: A Pioneering Full-Process Open-Source Medical Language Model | [
"cs.CL",
"cs.AI"
] | Recently, both closed-source LLMs and open-source communities have made significant strides, outperforming humans in various general domains. However, their performance in specific professional domains such as medicine, especially within the open-source community, remains suboptimal due to the complexity of medical kno... | {
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} |
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