id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.09902 | One Node One Model: Featuring the Missing-Half for Graph Clustering | [
"cs.LG",
"cs.AI",
"cs.DC",
"cs.SI"
] | Most existing graph clustering methods primarily focus on exploiting topological structure, often neglecting the ``missing-half" node feature information, especially how these features can enhance clustering performance. This issue is further compounded by the challenges associated with high-dimensional features. Featu... | {
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2412.09906 | Enhancing the Reasoning Capabilities of Small Language Models via
Solution Guidance Fine-Tuning | [
"cs.CL"
] | Large language models (LLMs) have demonstrated remarkable performance across a wide range of tasks. Advances in prompt engineering and fine-tuning techniques have further enhanced their ability to address complex reasoning challenges. However, these advanced capabilities are often exclusive to models exceeding 100 bill... | {
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2412.09907 | IQViC: In-context, Question Adaptive Vision Compressor for Long-term
Video Understanding LMMs | [
"cs.CV"
] | With the increasing complexity of video data and the need for more efficient long-term temporal understanding, existing long-term video understanding methods often fail to accurately capture and analyze extended video sequences. These methods typically struggle to maintain performance over longer durations and to handl... | {
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2412.09910 | Prompt2Perturb (P2P): Text-Guided Diffusion-Based Adversarial Attacks on
Breast Ultrasound Images | [
"cs.CV"
] | Deep neural networks (DNNs) offer significant promise for improving breast cancer diagnosis in medical imaging. However, these models are highly susceptible to adversarial attacks--small, imperceptible changes that can mislead classifiers--raising critical concerns about their reliability and security. Traditional atta... | {
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2412.09912 | All-in-One: Transferring Vision Foundation Models into Stereo Matching | [
"cs.CV"
] | As a fundamental vision task, stereo matching has made remarkable progress. While recent iterative optimization-based methods have achieved promising performance, their feature extraction capabilities still have room for improvement. Inspired by the ability of vision foundation models (VFMs) to extract general represen... | {
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2412.09913 | Digital Twin Enabled Runtime Verification for Autonomous Mobile Robots
under Uncertainty | [
"cs.RO"
] | As autonomous robots increasingly navigate complex and unpredictable environments, ensuring their reliable behavior under uncertainty becomes a critical challenge. This paper introduces a digital twin-based runtime verification for an autonomous mobile robot to mitigate the impact posed by uncertainty in the deployment... | {
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2412.09915 | Two-dimensional Constacyclic Codes over $\mathbb{F}_q$ | [
"cs.IT",
"math.IT"
] | We consider two-dimensional $(\lambda_1, \lambda_2)$-constacyclic codes over $\mathbb{F}_{q}$ of area $M N$, where $q$ is some power of prime $p$ with $\gcd(M,p)=1$ and $\gcd(N,p)=1$. With the help of common zero (CZ) set, we characterize 2-D constacyclic codes. Further, we provide an algorithm to construct an ideal ba... | {
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2412.09919 | B-VLLM: A Vision Large Language Model with Balanced Spatio-Temporal
Tokens | [
"cs.CV",
"cs.AI"
] | Recently, Vision Large Language Models (VLLMs) integrated with vision encoders have shown promising performance in vision understanding. The key of VLLMs is to encode visual content into sequences of visual tokens, enabling VLLMs to simultaneously process both visual and textual content. However, understanding videos, ... | {
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2412.09920 | Precision-Enhanced Human-Object Contact Detection via Depth-Aware
Perspective Interaction and Object Texture Restoration | [
"cs.CV"
] | Human-object contact (HOT) is designed to accurately identify the areas where humans and objects come into contact. Current methods frequently fail to account for scenarios where objects are frequently blocking the view, resulting in inaccurate identification of contact areas. To tackle this problem, we suggest using a... | {
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2412.09921 | FaceShield: Defending Facial Image against Deepfake Threats | [
"cs.CV"
] | The rising use of deepfakes in criminal activities presents a significant issue, inciting widespread controversy. While numerous studies have tackled this problem, most primarily focus on deepfake detection. These reactive solutions are insufficient as a fundamental approach for crimes where authenticity verification i... | {
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2412.09922 | Low-Resource Fast Text Classification Based on Intra-Class and
Inter-Class Distance Calculation | [
"cs.CL"
] | In recent years, text classification methods based on neural networks and pre-trained models have gained increasing attention and demonstrated excellent performance. However, these methods still have some limitations in practical applications: (1) They typically focus only on the matching similarity between sentences. ... | {
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2412.09923 | On Eisenstein additive codes over chain rings and linear codes over
mixed alphabets | [
"cs.IT",
"math.IT"
] | Let $\mathcal{R}_e=GR(p^e,r)[y]/\langle g(y),p^{e-1}y^t\rangle$ be a finite commutative chain ring, where $p$ is a prime number, $GR(p^e,r)$ is the Galois ring of characteristic $p^e$ and rank $r,$ $t$ and $k$ are positive integers satisfying $1\leq t\leq k$ when $e \geq 2,$ while $t=k$ when $e=1,$ and $g(y)=y^k+p(g_{k... | {
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2412.09925 | Simulating Hard Attention Using Soft Attention | [
"cs.LG",
"cs.CL",
"cs.FL"
] | We study conditions under which transformers using soft attention can simulate hard attention, that is, effectively focus all attention on a subset of positions. First, we examine several variants of linear temporal logic, whose formulas have been previously been shown to be computable using hard attention transformers... | {
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2412.09927 | Neural Vector Tomography for Reconstructing a Magnetization Vector Field | [
"cond-mat.dis-nn",
"cs.CV"
] | Discretized techniques for vector tomographic reconstructions are prone to producing artifacts in the reconstructions. The quality of these reconstructions may further deteriorate as the amount of noise increases. In this work, we instead model the underlying vector fields using smooth neural fields. Owing to the fact ... | {
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2412.09936 | CaLoRAify: Calorie Estimation with Visual-Text Pairing and LoRA-Driven
Visual Language Models | [
"cs.CV"
] | The obesity phenomenon, known as the heavy issue, is a leading cause of preventable chronic diseases worldwide. Traditional calorie estimation tools often rely on specific data formats or complex pipelines, limiting their practicality in real-world scenarios. Recently, vision-language models (VLMs) have excelled in und... | {
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2412.09937 | On Galois LCD codes and LCPs of codes over mixed alphabets | [
"cs.IT",
"math.IT"
] | Let $\mathtt{R}$ be a finite commutative chain ring with the maximal ideal $\gamma\mathtt{R}$ of nilpotency index $e\geq 2,$ and let $\check{\mathtt{R}}=\mathtt{R}/\gamma^{s}\mathtt{R}$ for some positive integer $ s< e.$ In this paper, we study and characterize Galois $\mathtt{R}\check{\mathtt{R}}$-LCD codes of an arbi... | {
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2412.09938 | Pixel Intensity Tracking for Remote Respiratory Monitoring: A Study on
Indonesian Subject | [
"cs.CV"
] | Respiratory rate is a vital sign indicating various health conditions. Traditional contact-based measurement methods are often uncomfortable, and alternatives like respiratory belts and smartwatches have limitations in cost and operability. Therefore, a non-contact method based on Pixel Intensity Changes (PIC) with RGB... | {
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2412.09939 | Cooperative Target Defense under Communication and Sensing Constraints | [
"eess.SY",
"cs.SY"
] | We consider a variant of the target defense problems where a group of defenders are tasked to simultaneously capture an intruder. The intruder's objective is to reach a target without being simultaneously captured by the defender team. Some of the defenders are sensing-limited and do not have any information regarding ... | {
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2412.09940 | Predictive Query-based Pipeline for Graph Data | [
"cs.DB",
"cs.LG"
] | Graphs face challenges when dealing with massive datasets. They are essential tools for modeling interconnected data and often become computationally expensive. Graph embedding techniques, on the other hand, provide an efficient approach. By projecting complex graphs into a lower-dimensional space, these techniques sim... | {
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2412.09942 | Latent feedback control of distributed systems in multiple scenarios
through deep learning-based reduced order models | [
"math.OC",
"cs.LG",
"cs.NA",
"math.NA"
] | Continuous monitoring and real-time control of high-dimensional distributed systems are often crucial in applications to ensure a desired physical behavior, without degrading stability and system performances. Traditional feedback control design that relies on full-order models, such as high-dimensional state-space rep... | {
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2412.09945 | Going Beyond Feature Similarity: Effective Dataset distillation based on
Class-aware Conditional Mutual Information | [
"cs.CV"
] | Dataset distillation (DD) aims to minimize the time and memory consumption needed for training deep neural networks on large datasets, by creating a smaller synthetic dataset that has similar performance to that of the full real dataset. However, current dataset distillation methods often result in synthetic datasets t... | {
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2412.09946 | Enhancing Nursing and Elderly Care with Large Language Models: An
AI-Driven Framework | [
"cs.CL",
"cs.AI"
] | This paper explores the application of large language models (LLMs) in nursing and elderly care, focusing on AI-driven patient monitoring and interaction. We introduce a novel Chinese nursing dataset and implement incremental pre-training (IPT) and supervised fine-tuning (SFT) techniques to enhance LLM performance in s... | {
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2412.09947 | Towards Fair Graph Neural Networks via Graph Counterfactual without
Sensitive Attributes | [
"cs.LG"
] | Graph-structured data is ubiquitous in today's connected world, driving extensive research in graph analysis. Graph Neural Networks (GNNs) have shown great success in this field, leading to growing interest in developing fair GNNs for critical applications. However, most existing fair GNNs focus on statistical fairness... | {
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2412.09950 | Hesitation and Tolerance in Recommender Systems | [
"cs.IR"
] | User interactions in recommender systems are inherently complex, often involving behaviors that go beyond simple acceptance or rejection. One particularly common behavior is hesitation, where users deliberate over recommended items, signaling uncertainty. Our large-scale surveys, with 6,644 and 3,864 responses respecti... | {
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2412.09951 | WiseAD: Knowledge Augmented End-to-End Autonomous Driving with
Vision-Language Model | [
"cs.CV"
] | The emergence of general human knowledge and impressive logical reasoning capacity in rapidly progressed vision-language models (VLMs) have driven increasing interest in applying VLMs to high-level autonomous driving tasks, such as scene understanding and decision-making. However, an in-depth study on the relationship ... | {
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2412.09952 | Llama 3 Meets MoE: Efficient Upcycling | [
"cs.LG"
] | Scaling large language models (LLMs) significantly improves performance but comes with prohibitive computational costs. Mixture-of-Experts (MoE) models offer an efficient alternative, increasing capacity without a proportional rise in compute requirements. However, training MoE models from scratch poses challenges like... | {
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2412.09953 | Dual-Zone Hard-Core Model for RTS/CTS Handshake Analysis in WLANs | [
"cs.NI",
"cs.IT",
"math.IT"
] | This paper introduces a new stochastic geometry-based model to analyze the Request-to-Send/Clear-to-Send (RTS/CTS) handshake mechanism in wireless local area networks (WLANs). We develop an advanced hard-core point process model, termed the dual-zone hard-core process (DZHCP), which extends traditional hard-core models... | {
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2412.09954 | $\textrm{A}^{\textrm{2}}$RNet: Adversarial Attack Resilient Network for
Robust Infrared and Visible Image Fusion | [
"cs.CV"
] | Infrared and visible image fusion (IVIF) is a crucial technique for enhancing visual performance by integrating unique information from different modalities into one fused image. Exiting methods pay more attention to conducting fusion with undisturbed data, while overlooking the impact of deliberate interference on the... | {
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2412.09957 | Romanized to Native Malayalam Script Transliteration Using an
Encoder-Decoder Framework | [
"cs.CL"
] | In this work, we present the development of a reverse transliteration model to convert romanized Malayalam to native script using an encoder-decoder framework built with attention-based bidirectional Long Short Term Memory (Bi-LSTM) architecture. To train the model, we have used curated and combined collection of 4.3 m... | {
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2412.09959 | Efficient Dataset Distillation via Diffusion-Driven Patch Selection for
Improved Generalization | [
"cs.CV"
] | Dataset distillation offers an efficient way to reduce memory and computational costs by optimizing a smaller dataset with performance comparable to the full-scale original. However, for large datasets and complex deep networks (e.g., ImageNet-1K with ResNet-101), the extensive optimization space limits performance, re... | {
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2412.09960 | END$^2$: Robust Dual-Decoder Watermarking Framework Against
Non-Differentiable Distortions | [
"cs.CV",
"eess.IV"
] | DNN-based watermarking methods have rapidly advanced, with the ``Encoder-Noise Layer-Decoder'' (END) framework being the most widely used. To ensure end-to-end training, the noise layer in the framework must be differentiable. However, real-world distortions are often non-differentiable, leading to challenges in end-to... | {
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2412.09961 | What constitutes a Deep Fake? The blurry line between legitimate
processing and manipulation under the EU AI Act | [
"cs.LG",
"cs.AI",
"cs.CY"
] | When does a digital image resemble reality? The relevance of this question increases as the generation of synthetic images -- so called deep fakes -- becomes increasingly popular. Deep fakes have gained much attention for a number of reasons -- among others, due to their potential to disrupt the political climate. In o... | {
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2412.09965 | Exploiting structural observability and graph colorability for optimal
sensor placement in water distribution networks | [
"eess.SY",
"cs.SY"
] | Water distribution networks (WDNs) are critical systems for our society and detecting leakages is important for minimizing losses and water waste. This makes optimal sensor placement for leakage detection very relevant. Existing sensor placement methods rely on simulation-based scenarios, often lacking structure and ge... | {
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2412.09966 | EP-CFG: Energy-Preserving Classifier-Free Guidance | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Classifier-free guidance (CFG) is widely used in diffusion models but often introduces over-contrast and over-saturation artifacts at higher guidance strengths. We present EP-CFG (Energy-Preserving Classifier-Free Guidance), which addresses these issues by preserving the energy distribution of the conditional predictio... | {
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2412.09968 | GraSP: Simple yet Effective Graph Similarity Predictions | [
"cs.LG"
] | Graph similarity computation (GSC) is to calculate the similarity between one pair of graphs, which is a fundamental problem with fruitful applications in the graph community. In GSC, graph edit distance (GED) and maximum common subgraph (MCS) are two important similarity metrics, both of which are NP-hard to compute. ... | {
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2412.09972 | Efficient Large-Scale Traffic Forecasting with Transformers: A Spatial
Data Management Perspective | [
"cs.LG",
"cs.AI"
] | Road traffic forecasting is crucial in real-world intelligent transportation scenarios like traffic dispatching and path planning in city management and personal traveling. Spatio-temporal graph neural networks (STGNNs) stand out as the mainstream solution in this task. Nevertheless, the quadratic complexity of remarka... | {
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2412.09978 | Coordinated vehicle dispatching and charging scheduling for an electric
ride-hailing fleet under charging congestion and dynamic prices | [
"math.OC",
"cs.SY",
"eess.SY"
] | Effective utilization of charging station capacity plays an important role in enhancing the profitability of ride-hailing systems using electric vehicles. Existing studies assume constant energy prices and uncapacitated charging stations or do not explicitly consider vehicle queueing at charging stations, resulting in ... | {
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2412.09980 | Real-Time Fall Detection Using Smartphone Accelerometers and WiFi
Channel State Information | [
"cs.LG"
] | In recent years, as the population ages, falls have increasingly posed a significant threat to the health of the elderly. We propose a real-time fall detection system that integrates the inertial measurement unit (IMU) of a smartphone with optimized Wi-Fi channel state information (CSI) for secondary validation. Initia... | {
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2412.09981 | SUMI-IFL: An Information-Theoretic Framework for Image Forgery
Localization with Sufficiency and Minimality Constraints | [
"cs.CV",
"cs.AI"
] | Image forgery localization (IFL) is a crucial technique for preventing tampered image misuse and protecting social safety. However, due to the rapid development of image tampering technologies, extracting more comprehensive and accurate forgery clues remains an urgent challenge. To address these challenges, we introduc... | {
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2412.09982 | SplineGS: Robust Motion-Adaptive Spline for Real-Time Dynamic 3D
Gaussians from Monocular Video | [
"cs.CV"
] | Synthesizing novel views from in-the-wild monocular videos is challenging due to scene dynamics and the lack of multi-view cues. To address this, we propose SplineGS, a COLMAP-free dynamic 3D Gaussian Splatting (3DGS) framework for high-quality reconstruction and fast rendering from monocular videos. At its core is a n... | {
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2412.09983 | Static Pruning in Dense Retrieval using Matrix Decomposition | [
"cs.IR"
] | In the era of dense retrieval, document indexing and retrieval is largely based on encoding models that transform text documents into embeddings. The efficiency of retrieval is directly proportional to the number of documents and the size of the embeddings. Recent studies have shown that it is possible to reduce embedd... | {
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2412.09988 | AI and the Future of Digital Public Squares | [
"cs.CY",
"cs.AI"
] | Two substantial technological advances have reshaped the public square in recent decades: first with the advent of the internet and second with the recent introduction of large language models (LLMs). LLMs offer opportunities for a paradigm shift towards more decentralized, participatory online spaces that can be used ... | {
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2412.09989 | One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation
in Unknown Environments | [
"cs.RO",
"cs.AI",
"cs.LG",
"cs.SY",
"eess.SY"
] | As learning-based methods for legged robots rapidly grow in popularity, it is important that we can provide safety assurances efficiently across different controllers and environments. Existing works either rely on a priori knowledge of the environment and safety constraints to ensure system safety or provide assurance... | {
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2412.09990 | Small Language Model as Data Prospector for Large Language Model | [
"cs.CL",
"cs.AI"
] | The quality of instruction data directly affects the performance of fine-tuned Large Language Models (LLMs). Previously, \cite{li2023one} proposed \texttt{NUGGETS}, which identifies and selects high-quality quality data from a large dataset by identifying those individual instruction examples that can significantly imp... | {
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2412.09991 | Visual Object Tracking across Diverse Data Modalities: A Review | [
"cs.CV",
"cs.AI"
] | Visual Object Tracking (VOT) is an attractive and significant research area in computer vision, which aims to recognize and track specific targets in video sequences where the target objects are arbitrary and class-agnostic. The VOT technology could be applied in various scenarios, processing data of diverse modalities... | {
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2412.09993 | A Comparative Study of LLMs, NMT Models, and Their Combination in
Persian-English Idiom Translation | [
"cs.CL"
] | Large language models (LLMs) have shown superior capabilities in translating figurative language compared to neural machine translation (NMT) systems. However, the impact of different prompting methods and LLM-NMT combinations on idiom translation has yet to be thoroughly investigated. This paper introduces two paralle... | {
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2412.09995 | Virtualization & Microservice Architecture for Software-Defined
Vehicles: An Evaluation and Exploration | [
"cs.RO"
] | The emergence of Software-Defined Vehicles (SDVs) signifies a shift from a distributed network of electronic control units (ECUs) to a centralized computing architecture within the vehicle's electrical and electronic systems. This transition addresses the growing complexity and demand for enhanced functionality in trad... | {
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2412.09997 | GT23D-Bench: A Comprehensive General Text-to-3D Generation Benchmark | [
"cs.CV"
] | Recent advances in General Text-to-3D (GT23D) have been significant. However, the lack of a benchmark has hindered systematic evaluation and progress due to issues in datasets and metrics: 1) The largest 3D dataset Objaverse suffers from omitted annotations, disorganization, and low-quality. 2) Existing metrics only ev... | {
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2412.09998 | Cycle-Consistent Bridge Diffusion Model for Accelerated MRI
Reconstruction | [
"eess.IV",
"cs.AI",
"cs.CV"
] | Accelerated MRI reconstruction techniques aim to reduce examination time while maintaining high image fidelity, which is highly desirable in clinical settings for improving patient comfort and hospital efficiency. Existing deep learning methods typically reconstruct images from under-sampled data with traditional recon... | {
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2412.10002 | NowYouSee Me: Context-Aware Automatic Audio Description | [
"cs.CV"
] | Audio Description (AD) plays a pivotal role as an application system aimed at guaranteeing accessibility in multimedia content, which provides additional narrations at suitable intervals to describe visual elements, catering specifically to the needs of visually impaired audiences. In this paper, we introduce $\mathrm{... | {
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2412.10004 | NeRF-Texture: Synthesizing Neural Radiance Field Textures | [
"cs.CV",
"cs.GR"
] | Texture synthesis is a fundamental problem in computer graphics that would benefit various applications. Existing methods are effective in handling 2D image textures. In contrast, many real-world textures contain meso-structure in the 3D geometry space, such as grass, leaves, and fabrics, which cannot be effectively mo... | {
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2412.10005 | Matrix Completion via Residual Spectral Matching | [
"stat.ML",
"cs.LG",
"stat.ME"
] | Noisy matrix completion has attracted significant attention due to its applications in recommendation systems, signal processing and image restoration. Most existing works rely on (weighted) least squares methods under various low-rank constraints. However, minimizing the sum of squared residuals is not always efficien... | {
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2412.10006 | The role of inhibitory control in garden-path sentence processing: A
Chinese-English bilingual perspective | [
"cs.CL"
] | In reading garden-path sentences, people must resolve competing interpretations, though initial misinterpretations can linger despite reanalysis. This study examines the role of inhibitory control (IC) in managing these misinterpretations among Chinese-English bilinguals. Using self-paced reading tasks, we investigated... | {
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2412.10008 | Automated Collection of Evaluation Dataset for Semantic Search in
Low-Resource Domain Language | [
"cs.CL"
] | Domain-specific languages that use a lot of specific terminology often fall into the category of low-resource languages. Collecting test datasets in a narrow domain is time-consuming and requires skilled human resources with domain knowledge and training for the annotation task. This study addresses the challenge of au... | {
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2412.10009 | Class flipping for uplift modeling and Heterogeneous Treatment Effect
estimation on imbalanced RCT data | [
"cs.LG",
"stat.ML"
] | Uplift modeling and Heterogeneous Treatment Effect (HTE) estimation aim at predicting the causal effect of an action, such as a medical treatment or a marketing campaign on a specific individual. In this paper, we focus on data from Randomized Controlled Experiments which guarantee causal interpretation of the outcomes... | {
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2412.10011 | Enhanced Speech Emotion Recognition with Efficient Channel Attention
Guided Deep CNN-BiLSTM Framework | [
"cs.SD",
"cs.AI",
"cs.LG",
"eess.AS"
] | Speech emotion recognition (SER) is crucial for enhancing affective computing and enriching the domain of human-computer interaction. However, the main challenge in SER lies in selecting relevant feature representations from speech signals with lower computational costs. In this paper, we propose a lightweight SER arch... | {
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2412.10028 | Mr. DETR: Instructive Multi-Route Training for Detection Transformers | [
"cs.CV"
] | Existing methods enhance the training of detection transformers by incorporating an auxiliary one-to-many assignment. In this work, we treat the model as a multi-task framework, simultaneously performing one-to-one and one-to-many predictions. We investigate the roles of each component in the transformer decoder across... | {
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2412.10029 | Enhancing Fine-Grained Vision-Language Pretraining with Negative
Augmented Samples | [
"cs.CV"
] | Existing Vision-Language Pretraining (VLP) methods have achieved remarkable improvements across a variety of vision-language tasks, confirming their effectiveness in capturing coarse-grained semantic correlations. However, their capability for fine-grained understanding, which is critical for many nuanced vision-langua... | {
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2412.10031 | FM2S: Self-Supervised Fluorescence Microscopy Denoising With Single
Noisy Image | [
"eess.IV",
"cs.CV"
] | Fluorescence microscopy has significantly advanced biological research by visualizing detailed cellular structures and biological processes. However, such image denoising task often faces challenges due to difficulty in precisely modeling the inherent noise and acquiring clean images for training, which constrains most... | {
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2412.10032 | Object-Focused Data Selection for Dense Prediction Tasks | [
"cs.CV"
] | Dense prediction tasks such as object detection and segmentation require high-quality labels at pixel level, which are costly to obtain. Recent advances in foundation models have enabled the generation of autolabels, which we find to be competitive but not yet sufficient to fully replace human annotations, especially f... | {
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2412.10033 | Timealign: A multi-modal object detection method for time misalignment
fusing in autonomous driving | [
"cs.CV"
] | The multi-modal perception methods are thriving in the autonomous driving field due to their better usage of complementary data from different sensors. Such methods depend on calibration and synchronization between sensors to get accurate environmental information. There have already been studies about space-alignment ... | {
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2412.10040 | RemDet: Rethinking Efficient Model Design for UAV Object Detection | [
"cs.CV"
] | Object detection in Unmanned Aerial Vehicle (UAV) images has emerged as a focal area of research, which presents two significant challenges: i) objects are typically small and dense within vast images; ii) computational resource constraints render most models unsuitable for real-time deployment. Current real-time objec... | {
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2412.10047 | Large Action Models: From Inception to Implementation | [
"cs.AI"
] | As AI continues to advance, there is a growing demand for systems that go beyond language-based assistance and move toward intelligent agents capable of performing real-world actions. This evolution requires the transition from traditional Large Language Models (LLMs), which excel at generating textual responses, to La... | {
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2412.10048 | BatDeck -- Ultra Low-power Ultrasonic Ego-velocity Estimation and
Obstacle Avoidance on Nano-drones | [
"cs.RO"
] | Nano-drones, with their small, lightweight design, are ideal for confined-space rescue missions and inherently safe for human interaction. However, their limited payload restricts the critical sensing needed for ego-velocity estimation and obstacle detection to single-bean laser-based time-of-flight (ToF) and low-resol... | {
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2412.10049 | SuperMark: Robust and Training-free Image Watermarking via
Diffusion-based Super-Resolution | [
"cs.CV"
] | In today's digital landscape, the blending of AI-generated and authentic content has underscored the need for copyright protection and content authentication. Watermarking has become a vital tool to address these challenges, safeguarding both generated and real content. Effective watermarking methods must withstand var... | {
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2412.10050 | ManipGPT: Is Affordance Segmentation by Large Vision Models Enough for
Articulated Object Manipulation? | [
"cs.RO",
"cs.CV"
] | Visual actionable affordance has emerged as a transformative approach in robotics, focusing on perceiving interaction areas prior to manipulation. Traditional methods rely on pixel sampling to identify successful interaction samples or processing pointclouds for affordance mapping. However, these approaches are computa... | {
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2412.10051 | TSGaussian: Semantic and Depth-Guided Target-Specific Gaussian Splatting
from Sparse Views | [
"cs.CV",
"cs.AI"
] | Recent advances in Gaussian Splatting have significantly advanced the field, achieving both panoptic and interactive segmentation of 3D scenes. However, existing methodologies often overlook the critical need for reconstructing specified targets with complex structures from sparse views. To address this issue, we intro... | {
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2412.10054 | Unsupervised Named Entity Disambiguation for Low Resource Domains | [
"cs.CL"
] | In the ever-evolving landscape of natural language processing and information retrieval, the need for robust and domain-specific entity linking algorithms has become increasingly apparent. It is crucial in a considerable number of fields such as humanities, technical writing and biomedical sciences to enrich texts with... | {
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2412.10056 | GAOKAO-Eval: Does high scores truly reflect strong capabilities in LLMs? | [
"cs.CL",
"cs.AI"
] | Large Language Models (LLMs) are commonly evaluated using human-crafted benchmarks, under the premise that higher scores implicitly reflect stronger human-like performance. However, there is growing concern that LLMs may ``game" these benchmarks due to data leakage, achieving high scores while struggling with tasks sim... | {
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2412.10059 | Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric
Quantization and Energy-Saving Bit-Slice Sparsity | [
"cs.AR",
"cs.AI"
] | Low bit-precisions and their bit-slice sparsity have recently been studied to accelerate general matrix-multiplications (GEMM) during large-scale deep neural network (DNN) inferences. While the conventional symmetric quantization facilitates low-resolution processing with bit-slice sparsity for both weight and activati... | {
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2412.10061 | Quaffure: Real-Time Quasi-Static Neural Hair Simulation | [
"cs.CV",
"cs.GR"
] | Realistic hair motion is crucial for high-quality avatars, but it is often limited by the computational resources available for real-time applications. To address this challenge, we propose a novel neural approach to predict physically plausible hair deformations that generalizes to various body poses, shapes, and hair... | {
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2412.10064 | Text2Cypher: Bridging Natural Language and Graph Databases | [
"cs.LG"
] | Knowledge graphs use nodes, relationships, and properties to represent arbitrarily complex data. When stored in a graph database, the Cypher query language enables efficient modeling and querying of knowledge graphs. However, using Cypher requires specialized knowledge, which can present a challenge for non-expert user... | {
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2412.10078 | Toy-GS: Assembling Local Gaussians for Precisely Rendering Large-Scale
Free Camera Trajectories | [
"cs.CV"
] | Currently, 3D rendering for large-scale free camera trajectories, namely, arbitrary input camera trajectories, poses significant challenges: 1) The distribution and observation angles of the cameras are irregular, and various types of scenes are included in the free trajectories; 2) Processing the entire point cloud an... | {
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2412.10079 | Lost in the Middle, and In-Between: Enhancing Language Models' Ability
to Reason Over Long Contexts in Multi-Hop QA | [
"cs.CL"
] | Previous work finds that recent long-context language models fail to make equal use of information in the middle of their inputs, preferring pieces of information located at the tail ends which creates an undue bias in situations where we would like models to be equally capable of using different parts of the input. Th... | {
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2412.10083 | Heterogeneous Multi-Robot Graph Coverage with Proximity and Movement
Constraints | [
"cs.MA",
"cs.RO"
] | Multi-Robot Coverage problems have been extensively studied in robotics, planning and multi-agent systems. In this work, we consider the coverage problem when there are constraints on the proximity (e.g., maximum distance between the agents, or a blue agent must be adjacent to a red agent) and the movement (e.g., terra... | {
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2412.10084 | ProbeSDF: Light Field Probes for Neural Surface Reconstruction | [
"cs.CV"
] | SDF-based differential rendering frameworks have achieved state-of-the-art multiview 3D shape reconstruction. In this work, we re-examine this family of approaches by minimally reformulating its core appearance model in a way that simultaneously yields faster computation and increased performance. To this goal, we exhi... | {
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2412.10087 | Consensus-Based Dynamic Task Allocation for Multi-Robot System
Considering Payloads Consumption | [
"cs.RO"
] | This paper presents a consensus-based payload algorithm (CBPA) to deal with the condition of robots' capability decrease for multi-robot task allocation. During the execution of complex tasks, robots' capabilities could decrease with the consumption of payloads, which causes a problem that the robot coalition would not... | {
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2412.10088 | Model Order Reduction of Large-Scale Wind Farms: A Data-Driven Approach | [
"eess.SY",
"cs.SY"
] | This paper proposes a data-driven algorithm for model order reduction (MOR) of large-scale wind farms and studies the effects that the obtained reduced-order model (ROM) has when this is integrated into the power grid. With respect to standard MOR methods, the proposed algorithm has the advantages of having low computa... | {
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2412.10089 | Guidance Not Obstruction: A Conjugate Consistent Enhanced Strategy for
Domain Generalization | [
"cs.CV"
] | Domain generalization addresses domain shift in real-world applications. Most approaches adopt a domain angle, seeking invariant representation across domains by aligning their marginal distributions, irrespective of individual classes, naturally leading to insufficient exploration of discriminative information. Switch... | {
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2412.10091 | Data Pruning Can Do More: A Comprehensive Data Pruning Approach for
Object Re-identification | [
"cs.CV",
"cs.AI"
] | Previous studies have demonstrated that not each sample in a dataset is of equal importance during training. Data pruning aims to remove less important or informative samples while still achieving comparable results as training on the original (untruncated) dataset, thereby reducing storage and training costs. However,... | {
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2412.10092 | A Survey on Knowledge Graph Structure and Knowledge Graph Embeddings | [
"cs.LG"
] | Knowledge Graphs (KGs) and their machine learning counterpart, Knowledge Graph Embedding Models (KGEMs), have seen ever-increasing use in a wide variety of academic and applied settings. In particular, KGEMs are typically applied to KGs to solve the link prediction task; i.e. to predict new facts in the domain of a KG ... | {
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2412.10093 | AI in the Cosmos | [
"astro-ph.HE",
"astro-ph.GA",
"astro-ph.IM",
"cs.AI"
] | Artificial intelligence (AI) is revolutionizing research by enabling the efficient analysis of large datasets and the discovery of hidden patterns. In astrophysics, AI has become essential, transforming the classification of celestial sources, data modeling, and the interpretation of observations. In this review, I hig... | {
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2412.10095 | HiTZ at VarDial 2025 NorSID: Overcoming Data Scarcity with Language
Transfer and Automatic Data Annotation | [
"cs.CL",
"cs.AI",
"cs.LG"
] | In this paper we present our submission for the NorSID Shared Task as part of the 2025 VarDial Workshop (Scherrer et al., 2025), consisting of three tasks: Intent Detection, Slot Filling and Dialect Identification, evaluated using data in different dialects of the Norwegian language. For Intent Detection and Slot Filli... | {
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2412.10096 | Reward Machine Inference for Robotic Manipulation | [
"cs.RO",
"cs.LG"
] | Learning from Demonstrations (LfD) and Reinforcement Learning (RL) have enabled robot agents to accomplish complex tasks. Reward Machines (RMs) enhance RL's capability to train policies over extended time horizons by structuring high-level task information. In this work, we introduce a novel LfD approach for learning R... | {
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2412.10102 | Indirect Adaptive Control Using a Static Update Law | [
"math.OC",
"cs.SY",
"eess.SY"
] | The update law in the indirect adaptive control scheme can be extended to include feedthrough of an error term. This reduces undesired oscillations of the calculated weights. When the {\sigma}-modification is used for achieving robustness against unstructured uncertainties, the gain of the feedthrough in the update law... | {
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2412.10103 | AMuSeD: An Attentive Deep Neural Network for Multimodal Sarcasm
Detection Incorporating Bi-modal Data Augmentation | [
"cs.CL"
] | Detecting sarcasm effectively requires a nuanced understanding of context, including vocal tones and facial expressions. The progression towards multimodal computational methods in sarcasm detection, however, faces challenges due to the scarcity of data. To address this, we present AMuSeD (Attentive deep neural network... | {
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2412.10104 | RETQA: A Large-Scale Open-Domain Tabular Question Answering Dataset for
Real Estate Sector | [
"cs.CL",
"cs.AI"
] | The real estate market relies heavily on structured data, such as property details, market trends, and price fluctuations. However, the lack of specialized Tabular Question Answering datasets in this domain limits the development of automated question-answering systems. To fill this gap, we introduce RETQA, the first l... | {
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2412.10105 | MALAMUTE: A Multilingual, Highly-granular, Template-free,
Education-based Probing Dataset | [
"cs.CL"
] | Language models (LMs) have excelled in various broad domains. However, to ensure their safe and effective integration into real-world educational settings, they must demonstrate proficiency in specific, granular areas of knowledge. Existing cloze-style benchmarks, commonly used to evaluate LMs' knowledge, have three ma... | {
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2412.10106 | A Cascaded Dilated Convolution Approach for Mpox Lesion Classification | [
"eess.IV",
"cs.AI",
"cs.CV"
] | The global outbreak of the Mpox virus, classified as a Public Health Emergency of International Concern (PHEIC) by the World Health Organization, presents significant diagnostic challenges due to its visual similarity to other skin lesion diseases. Traditional diagnostic methods for Mpox, which rely on clinical symptom... | {
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2412.10107 | NetOrchLLM: Mastering Wireless Network Orchestration with Large Language
Models | [
"cs.NI",
"cs.AI",
"cs.ET",
"cs.LG"
] | The transition to 6G networks promises unprecedented advancements in wireless communication, with increased data rates, ultra-low latency, and enhanced capacity. However, the complexity of managing and optimizing these next-generation networks presents significant challenges. The advent of large language models (LLMs) ... | {
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2412.10110 | Label-template based Few-Shot Text Classification with Contrastive
Learning | [
"cs.CL",
"cs.AI"
] | As an algorithmic framework for learning to learn, meta-learning provides a promising solution for few-shot text classification. However, most existing research fail to give enough attention to class labels. Traditional basic framework building meta-learner based on prototype networks heavily relies on inter-class vari... | {
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"cs.NE": 0,
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"cs.SY": 0
} |
2412.10115 | Filter or Compensate: Towards Invariant Representation from Distribution
Shift for Anomaly Detection | [
"cs.CV"
] | Recent Anomaly Detection (AD) methods have achieved great success with In-Distribution (ID) data. However, real-world data often exhibits distribution shift, causing huge performance decay on traditional AD methods. From this perspective, few previous work has explored AD with distribution shift, and the distribution-i... | {
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} |
2412.10116 | HS-FPN: High Frequency and Spatial Perception FPN for Tiny Object
Detection | [
"cs.CV"
] | The introduction of Feature Pyramid Network (FPN) has significantly improved object detection performance. However, substantial challenges remain in detecting tiny objects, as their features occupy only a very small proportion of the feature maps. Although FPN integrates multi-scale features, it does not directly enhan... | {
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"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
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"cs.SY": 0
} |
2412.10117 | CosyVoice 2: Scalable Streaming Speech Synthesis with Large Language
Models | [
"cs.SD",
"cs.AI",
"cs.LG",
"eess.AS"
] | In our previous work, we introduced CosyVoice, a multilingual speech synthesis model based on supervised discrete speech tokens. By employing progressive semantic decoding with two popular generative models, language models (LMs) and Flow Matching, CosyVoice demonstrated high prosody naturalness, content consistency, a... | {
"Other": 0,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 1,
"cs.SI": 0,
"cs.SY": 0
} |
2412.10119 | AMUSE: Adaptive Model Updating using a Simulated Environment | [
"cs.LG",
"stat.ME",
"stat.ML"
] | Prediction models frequently face the challenge of concept drift, in which the underlying data distribution changes over time, weakening performance. Examples can include models which predict loan default, or those used in healthcare contexts. Typical management strategies involve regular model updates or updates trigg... | {
"Other": 0,
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"cs.CR": 0,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.10121 | Familiarity: Better Evaluation of Zero-Shot Named Entity Recognition by
Quantifying Label Shifts in Synthetic Training Data | [
"cs.CL"
] | Zero-shot named entity recognition (NER) is the task of detecting named entities of specific types (such as 'Person' or 'Medicine') without any training examples. Current research increasingly relies on large synthetic datasets, automatically generated to cover tens of thousands of distinct entity types, to train zero-... | {
"Other": 0,
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"cs.CL": 1,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.10122 | The Art of Deception: Color Visual Illusions and Diffusion Models | [
"cs.CV"
] | Visual illusions in humans arise when interpreting out-of-distribution stimuli: if the observer is adapted to certain statistics, perception of outliers deviates from reality. Recent studies have shown that artificial neural networks (ANNs) can also be deceived by visual illusions. This revelation raises profound quest... | {
"Other": 0,
"cs.AI": 0,
"cs.CE": 0,
"cs.CL": 0,
"cs.CR": 0,
"cs.CV": 1,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.10128 | Feature Selection for Latent Factor Models | [
"cs.LG",
"stat.AP"
] | Feature selection is crucial for pinpointing relevant features in high-dimensional datasets, mitigating the 'curse of dimensionality,' and enhancing machine learning performance. Traditional feature selection methods for classification use data from all classes to select features for each class. This paper explores fea... | {
"Other": 0,
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"cs.CY": 0,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
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"cs.SY": 0
} |
2412.10130 | Optimal Bounds for Private Minimum Spanning Trees via Input Perturbation | [
"cs.DS",
"cs.CR",
"cs.LG"
] | We study the problem of privately releasing an approximate minimum spanning tree (MST). Given a graph $G = (V, E, \vec{W})$ where $V$ is a set of $n$ vertices, $E$ is a set of $m$ undirected edges, and $ \vec{W} \in \mathbb{R}^{|E|} $ is an edge-weight vector, our goal is to publish an approximate MST under edge-weight... | {
"Other": 1,
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"cs.CR": 1,
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"cs.IR": 0,
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"cs.LG": 1,
"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
2412.10133 | You Name It, I Run It: An LLM Agent to Execute Tests of Arbitrary
Projects | [
"cs.SE",
"cs.AI"
] | The ability to execute the test suite of a project is essential in many scenarios, e.g., to assess code quality and code coverage, to validate code changes made by developers or automated tools, and to ensure compatibility with dependencies. Despite its importance, executing the test suite of a project can be challengi... | {
"Other": 1,
"cs.AI": 1,
"cs.CE": 0,
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"cs.CR": 0,
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"cs.MA": 0,
"cs.NE": 0,
"cs.RO": 0,
"cs.SD": 0,
"cs.SI": 0,
"cs.SY": 0
} |
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