id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.13475 | A Statistical and Multi-Perspective Revisiting of the Membership
Inference Attack in Large Language Models | [
"cs.CL",
"cs.AI"
] | The lack of data transparency in Large Language Models (LLMs) has highlighted the importance of Membership Inference Attack (MIA), which differentiates trained (member) and untrained (non-member) data. Though it shows success in previous studies, recent research reported a near-random performance in different settings,... | {
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2412.13477 | Generating Unseen Nonlinear Evolution in Sea Surface Temperature Using a
Deep Learning-Based Latent Space Data Assimilation Framework | [
"physics.ao-ph",
"cs.AI",
"cs.CV",
"cs.LG",
"physics.geo-ph"
] | Advances in data assimilation (DA) methods have greatly improved the accuracy of Earth system predictions. To fuse multi-source data and reconstruct the nonlinear evolution missing from observations, geoscientists are developing future-oriented DA methods. In this paper, we redesign a purely data-driven latent space DA... | {
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2412.13478 | Efficient Fine-Tuning of Single-Cell Foundation Models Enables Zero-Shot
Molecular Perturbation Prediction | [
"cs.LG",
"q-bio.QM"
] | Predicting transcriptional responses to novel drugs provides a unique opportunity to accelerate biomedical research and advance drug discovery efforts. However, the inherent complexity and high dimensionality of cellular responses, combined with the extremely limited available experimental data, makes the task challeng... | {
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2412.13479 | Real-time One-Step Diffusion-based Expressive Portrait Videos Generation | [
"cs.CV"
] | Latent diffusion models have made great strides in generating expressive portrait videos with accurate lip-sync and natural motion from a single reference image and audio input. However, these models are far from real-time, often requiring many sampling steps that take minutes to generate even one second of video-signi... | {
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2412.13484 | Curriculum Learning for Cross-Lingual Data-to-Text Generation With Noisy
Data | [
"cs.CL"
] | Curriculum learning has been used to improve the quality of text generation systems by ordering the training samples according to a particular schedule in various tasks. In the context of data-to-text generation (DTG), previous studies used various difficulty criteria to order the training samples for monolingual DTG. ... | {
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2412.13486 | T$^3$-S2S: Training-free Triplet Tuning for Sketch to Scene Generation | [
"cs.CV",
"cs.CL",
"cs.GR"
] | Scene generation is crucial to many computer graphics applications. Recent advances in generative AI have streamlined sketch-to-image workflows, easing the workload for artists and designers in creating scene concept art. However, these methods often struggle for complex scenes with multiple detailed objects, sometimes... | {
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2412.13488 | Refining Salience-Aware Sparse Fine-Tuning Strategies for Language
Models | [
"cs.CL",
"cs.AI"
] | Parameter-Efficient Fine-Tuning (PEFT) has gained prominence through low-rank adaptation methods like LoRA. In this paper, we focus on sparsity-based PEFT (SPEFT), which introduces trainable sparse adaptations to the weight matrices in the model, offering greater flexibility in selecting fine-tuned parameters compared ... | {
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2412.13489 | Analysis of Higher-Order Ising Hamiltonians | [
"cs.AI",
"cond-mat.stat-mech",
"physics.comp-ph",
"quant-ph"
] | It is challenging to scale Ising machines for industrial-level problems due to algorithm or hardware limitations. Although higher-order Ising models provide a more compact encoding, they are, however, hard to physically implement. This work proposes a theoretical framework of a higher-order Ising simulator, IsingSim. T... | {
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2412.13490 | Comparative Analysis of YOLOv9, YOLOv10 and RT-DETR for Real-Time Weed
Detection | [
"cs.CV"
] | This paper presents a comprehensive evaluation of state-of-the-art object detection models, including YOLOv9, YOLOv10, and RT-DETR, for the task of weed detection in smart-spraying applications focusing on three classes: Sugarbeet, Monocot, and Dicot. The performance of these models is compared based on mean Average Pr... | {
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2412.13492 | Efficient Language-instructed Skill Acquisition via Reward-Policy
Co-Evolution | [
"cs.RO",
"cs.LG"
] | The ability to autonomously explore and resolve tasks with minimal human guidance is crucial for the self-development of embodied intelligence. Although reinforcement learning methods can largely ease human effort, it's challenging to design reward functions for real-world tasks, especially for high-dimensional robotic... | {
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2412.13495 | Federated t-SNE and UMAP for Distributed Data Visualization | [
"cs.LG",
"cs.AI"
] | High-dimensional data visualization is crucial in the big data era and these techniques such as t-SNE and UMAP have been widely used in science and engineering. Big data, however, is often distributed across multiple data centers and subject to security and privacy concerns, which leads to difficulties for the standard... | {
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2412.13496 | QueryCDR: Query-Based Controllable Distortion Rectification Network for
Fisheye Images | [
"cs.CV"
] | Fisheye image rectification aims to correct distortions in images taken with fisheye cameras. Although current models show promising results on images with a similar degree of distortion as the training data, they will produce sub-optimal results when the degree of distortion changes and without retraining. The lack of... | {
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2412.13501 | GUI Agents: A Survey | [
"cs.AI",
"cs.HC"
] | Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomously interact with digital systems or software applications via GUIs, emulating human actions such as clicking, typing, and navigating visua... | {
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2412.13502 | Level-Set Parameters: Novel Representation for 3D Shape Analysis | [
"cs.CV"
] | 3D shape analysis has been largely focused on traditional 3D representations of point clouds and meshes, but the discrete nature of these data makes the analysis susceptible to variations in input resolutions. Recent development of neural fields brings in level-set parameters from signed distance functions as a novel, ... | {
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2412.13503 | VaeDiff-DocRE: End-to-end Data Augmentation Framework for Document-level
Relation Extraction | [
"cs.CL",
"cs.AI"
] | Document-level Relation Extraction (DocRE) aims to identify relationships between entity pairs within a document. However, most existing methods assume a uniform label distribution, resulting in suboptimal performance on real-world, imbalanced datasets. To tackle this challenge, we propose a novel data augmentation app... | {
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2412.13504 | Urban Air Temperature Prediction using Conditional Diffusion Models | [
"cs.CV",
"eess.IV"
] | Urbanization as a global trend has led to many environmental challenges, including the urban heat island (UHI) effect. The increase in temperature has a significant impact on the well-being of urban residents. Air temperature ($T_a$) at 2m above the surface is a key indicator of the UHI effect. How land use land cover ... | {
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2412.13507 | Novel AI Camera Camouflage: Face Cloaking Without Full Disguise | [
"cs.CV"
] | This study demonstrates a novel approach to facial camouflage that combines targeted cosmetic perturbations and alpha transparency layer manipulation to evade modern facial recognition systems. Unlike previous methods -- such as CV dazzle, adversarial patches, and theatrical disguises -- this work achieves effective ob... | {
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2412.13508 | Plug-and-Play Tri-Branch Invertible Block for Image Rescaling | [
"eess.IV",
"cs.CV"
] | High-resolution (HR) images are commonly downscaled to low-resolution (LR) to reduce bandwidth, followed by upscaling to restore their original details. Recent advancements in image rescaling algorithms have employed invertible neural networks (INNs) to create a unified framework for downscaling and upscaling, ensuring... | {
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2412.13510 | Dynamic Adapter with Semantics Disentangling for Cross-lingual
Cross-modal Retrieval | [
"cs.CV",
"cs.CL"
] | Existing cross-modal retrieval methods typically rely on large-scale vision-language pair data. This makes it challenging to efficiently develop a cross-modal retrieval model for under-resourced languages of interest. Therefore, Cross-lingual Cross-modal Retrieval (CCR), which aims to align vision and the low-resource ... | {
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2412.13511 | CEHA: A Dataset of Conflict Events in the Horn of Africa | [
"cs.CL"
] | Natural Language Processing (NLP) of news articles can play an important role in understanding the dynamics and causes of violent conflict. Despite the availability of datasets categorizing various conflict events, the existing labels often do not cover all of the fine-grained violent conflict event types relevant to a... | {
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2412.13514 | Tuning Music Education: AI-Powered Personalization in Learning Music | [
"cs.SD",
"cs.AI",
"eess.AS"
] | Recent AI-driven step-function advances in several longstanding problems in music technology are opening up new avenues to create the next generation of music education tools. Creating personalized, engaging, and effective learning experiences are continuously evolving challenges in music education. Here we present two... | {
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2412.13516 | Learning Causal Transition Matrix for Instance-dependent Label Noise | [
"cs.LG"
] | Noisy labels are both inevitable and problematic in machine learning methods, as they negatively impact models' generalization ability by causing overfitting. In the context of learning with noise, the transition matrix plays a crucial role in the design of statistically consistent algorithms. However, the transition m... | {
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2412.13519 | Open-Source Protein Language Models for Function Prediction and Protein
Design | [
"cs.LG",
"q-bio.BM"
] | Protein language models (PLMs) have shown promise in improving the understanding of protein sequences, contributing to advances in areas such as function prediction and protein engineering. However, training these models from scratch requires significant computational resources, limiting their accessibility. To address... | {
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2412.13520 | ROMAS: A Role-Based Multi-Agent System for Database monitoring and
Planning | [
"cs.AI",
"cs.DB",
"cs.MA"
] | In recent years, Large Language Models (LLMs) have demonstrated remarkable capabilities in data analytics when integrated with Multi-Agent Systems (MAS). However, these systems often struggle with complex tasks that involve diverse functional requirements and intricate data processing challenges, necessitating customiz... | {
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2412.13525 | Hybrid Data-Free Knowledge Distillation | [
"cs.CV"
] | Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generation-based methods train student networks by collecting massive real examples and generating synthetic ex... | {
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2412.13526 | Rethink the Evaluation Protocol of Model Merging on Classification Task | [
"cs.LG"
] | Model merging combines multiple fine-tuned models into a single one via parameter fusion, achieving improvements across many tasks. However, in the classification task, we find a misalignment issue between merging outputs and the fine-tuned classifier, which limits its effectiveness. In this paper, we demonstrate the f... | {
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2412.13529 | Quantum Machine Learning in Log-based Anomaly Detection: Challenges and
Opportunities | [
"cs.LG",
"quant-ph"
] | Log-based anomaly detection (LogAD) is the main component of Artificial Intelligence for IT Operations (AIOps), which can detect anomalous that occur during the system on-the-fly. Existing methods commonly extract log sequence features using classical machine learning techniques to identify whether a new sequence is an... | {
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2412.13533 | Language-guided Medical Image Segmentation with Target-informed
Multi-level Contrastive Alignments | [
"cs.CV"
] | Medical image segmentation is crucial in modern medical image analysis, which can aid into diagnosis of various disease conditions. Recently, language-guided segmentation methods have shown promising results in automating image segmentation where text reports are incorporated as guidance. These text reports, containing... | {
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2412.13534 | Information-Theoretic Generative Clustering of Documents | [
"cs.LG",
"cs.CL",
"cs.IR",
"cs.IT",
"math.IT"
] | We present {\em generative clustering} (GC) for clustering a set of documents, $\mathrm{X}$, by using texts $\mathrm{Y}$ generated by large language models (LLMs) instead of by clustering the original documents $\mathrm{X}$. Because LLMs provide probability distributions, the similarity between two documents can be rig... | {
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2412.13536 | MetaRuleGPT: Recursive Numerical Reasoning of Language Models Trained
with Simple Rules | [
"cs.CL"
] | Recent studies have highlighted the limitations of large language models in mathematical reasoning, particularly their inability to capture the underlying logic. Inspired by meta-learning, we propose that models should acquire not only task-specific knowledge but also transferable problem-solving skills. We introduce M... | {
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2412.13540 | Benchmarking and Improving Large Vision-Language Models for Fundamental
Visual Graph Understanding and Reasoning | [
"cs.CL",
"cs.CV"
] | Large Vision-Language Models (LVLMs) have demonstrated remarkable performance across diverse tasks. Despite great success, recent studies show that LVLMs encounter substantial limitations when engaging with visual graphs. To study the reason behind these limitations, we propose VGCure, a comprehensive benchmark coverin... | {
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2412.13541 | Spatio-Temporal Fuzzy-oriented Multi-Modal Meta-Learning for
Fine-grained Emotion Recognition | [
"cs.CV",
"cs.LG",
"cs.NE"
] | Fine-grained emotion recognition (FER) plays a vital role in various fields, such as disease diagnosis, personalized recommendations, and multimedia mining. However, existing FER methods face three key challenges in real-world applications: (i) they rely on large amounts of continuously annotated data to ensure accurac... | {
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2412.13542 | Multi-Granularity Open Intent Classification via Adaptive Granular-Ball
Decision Boundary | [
"cs.CL"
] | Open intent classification is critical for the development of dialogue systems, aiming to accurately classify known intents into their corresponding classes while identifying unknown intents. Prior boundary-based methods assumed known intents fit within compact spherical regions, focusing on coarse-grained representati... | {
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2412.13543 | Query-centric Audio-Visual Cognition Network for Moment Retrieval,
Segmentation and Step-Captioning | [
"cs.CV",
"cs.AI",
"cs.CL"
] | Video has emerged as a favored multimedia format on the internet. To better gain video contents, a new topic HIREST is presented, including video retrieval, moment retrieval, moment segmentation, and step-captioning. The pioneering work chooses the pre-trained CLIP-based model for video retrieval, and leverages it as a... | {
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2412.13544 | Bridging the User-side Knowledge Gap in Knowledge-aware Recommendations
with Large Language Models | [
"cs.IR",
"cs.AI"
] | In recent years, knowledge graphs have been integrated into recommender systems as item-side auxiliary information, enhancing recommendation accuracy. However, constructing and integrating structural user-side knowledge remains a significant challenge due to the improper granularity and inherent scarcity of user-side f... | {
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2412.13547 | Turbo-GS: Accelerating 3D Gaussian Fitting for High-Quality Radiance
Fields | [
"cs.CV"
] | Novel-view synthesis is an important problem in computer vision with applications in 3D reconstruction, mixed reality, and robotics. Recent methods like 3D Gaussian Splatting (3DGS) have become the preferred method for this task, providing high-quality novel views in real time. However, the training time of a 3DGS mode... | {
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2412.13548 | TelePreview: A User-Friendly Teleoperation System with Virtual Arm
Assistance for Enhanced Effectiveness | [
"cs.RO",
"cs.HC"
] | Teleoperation provides an effective way to collect robot data, which is crucial for learning from demonstrations. In this field, teleoperation faces several key challenges: user-friendliness for new users, safety assurance, and transferability across different platforms. While collecting real robot dexterous manipulati... | {
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2412.13549 | EscapeBench: Pushing Language Models to Think Outside the Box | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Language model agents excel in long-session planning and reasoning, but existing benchmarks primarily focus on goal-oriented tasks with explicit objectives, neglecting creative adaptation in unfamiliar environments. To address this, we introduce EscapeBench, a benchmark suite of room escape game environments designed t... | {
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2412.13550 | Multi-view Granular-ball Contrastive Clustering | [
"cs.LG"
] | Previous multi-view contrastive learning methods typically operate at two scales: instance-level and cluster-level. Instance-level approaches construct positive and negative pairs based on sample correspondences, aiming to bring positive pairs closer and push negative pairs further apart in the latent space. Cluster-le... | {
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2412.13552 | DragScene: Interactive 3D Scene Editing with Single-view Drag
Instructions | [
"cs.CV",
"cs.GR"
] | 3D editing has shown remarkable capability in editing scenes based on various instructions. However, existing methods struggle with achieving intuitive, localized editing, such as selectively making flowers blossom. Drag-style editing has shown exceptional capability to edit images with direct manipulation instead of a... | {
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2412.13553 | Combining Aggregated Attention and Transformer Architecture for Accurate
and Efficient Performance of Spiking Neural Networks | [
"cs.NE"
] | Spiking Neural Networks have attracted significant attention in recent years due to their distinctive low-power characteristics. Meanwhile, Transformer models, known for their powerful self-attention mechanisms and parallel processing capabilities, have demonstrated exceptional performance across various domains, inclu... | {
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2412.13558 | Read Like a Radiologist: Efficient Vision-Language Model for 3D Medical
Imaging Interpretation | [
"eess.IV",
"cs.CL",
"cs.CV",
"cs.LG"
] | Recent medical vision-language models (VLMs) have shown promise in 2D medical image interpretation. However extending them to 3D medical imaging has been challenging due to computational complexities and data scarcity. Although a few recent VLMs specified for 3D medical imaging have emerged, all are limited to learning... | {
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2412.13559 | Indirect Query Bayesian Optimization with Integrated Feedback | [
"cs.LG"
] | We develop the framework of Indirect Query Bayesian Optimization (IQBO), a new class of Bayesian optimization problems where the integrated feedback is given via a conditional expectation of the unknown function $f$ to be optimized. The underlying conditional distribution can be unknown and learned from data. The goal ... | {
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2412.13564 | The networked input-output economic problem | [
"eess.SY",
"cs.SY",
"math.OC"
] | In this paper, we formulate an input-output economic model with multiple interactive economic systems. The model captures the multi-dimensional nature of the economic sectors or industries in each economic system, the interdependencies among industries within an economic system and across different economic systems, an... | {
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2412.13565 | CA-Edit: Causality-Aware Condition Adapter for High-Fidelity Local
Facial Attribute Editing | [
"cs.CV",
"cs.AI"
] | For efficient and high-fidelity local facial attribute editing, most existing editing methods either require additional fine-tuning for different editing effects or tend to affect beyond the editing regions. Alternatively, inpainting methods can edit the target image region while preserving external areas. However, cur... | {
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2412.13569 | Multi-View Pedestrian Occupancy Prediction with a Novel Synthetic
Dataset | [
"cs.CV"
] | We address an advanced challenge of predicting pedestrian occupancy as an extension of multi-view pedestrian detection in urban traffic. To support this, we have created a new synthetic dataset called MVP-Occ, designed for dense pedestrian scenarios in large-scale scenes. Our dataset provides detailed representations o... | {
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2412.13571 | PowerMLP: An Efficient Version of KAN | [
"cs.LG",
"cs.NA",
"math.NA"
] | The Kolmogorov-Arnold Network (KAN) is a new network architecture known for its high accuracy in several tasks such as function fitting and PDE solving. The superior expressive capability of KAN arises from the Kolmogorov-Arnold representation theorem and learnable spline functions. However, the computation of spline f... | {
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2412.13573 | Seeking Consistent Flat Minima for Better Domain Generalization via
Refining Loss Landscapes | [
"cs.CV",
"cs.AI"
] | Domain generalization aims to learn a model from multiple training domains and generalize it to unseen test domains. Recent theory has shown that seeking the deep models, whose parameters lie in the flat minima of the loss landscape, can significantly reduce the out-of-domain generalization error. However, existing met... | {
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2412.13575 | Generating Long-form Story Using Dynamic Hierarchical Outlining with
Memory-Enhancement | [
"cs.CL"
] | Long-form story generation task aims to produce coherent and sufficiently lengthy text, essential for applications such as novel writingand interactive storytelling. However, existing methods, including LLMs, rely on rigid outlines or lack macro-level planning, making it difficult to achieve both contextual consistency... | {
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2412.13577 | Bridge then Begin Anew: Generating Target-relevant Intermediate Model
for Source-free Visual Emotion Adaptation | [
"cs.CV",
"cs.AI"
] | Visual emotion recognition (VER), which aims at understanding humans' emotional reactions toward different visual stimuli, has attracted increasing attention. Given the subjective and ambiguous characteristics of emotion, annotating a reliable large-scale dataset is hard. For reducing reliance on data labeling, domain ... | {
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2412.13578 | Socio-Culturally Aware Evaluation Framework for LLM-Based Content
Moderation | [
"cs.CL",
"cs.AI"
] | With the growth of social media and large language models, content moderation has become crucial. Many existing datasets lack adequate representation of different groups, resulting in unreliable assessments. To tackle this, we propose a socio-culturally aware evaluation framework for LLM-driven content moderation and i... | {
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2412.13582 | EvoWiki: Evaluating LLMs on Evolving Knowledge | [
"cs.CL"
] | Knowledge utilization is a critical aspect of LLMs, and understanding how they adapt to evolving knowledge is essential for their effective deployment. However, existing benchmarks are predominantly static, failing to capture the evolving nature of LLMs and knowledge, leading to inaccuracies and vulnerabilities such as... | {
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2412.13589 | SemiDFL: A Semi-Supervised Paradigm for Decentralized Federated Learning | [
"cs.LG",
"cs.AI",
"cs.DC"
] | Decentralized federated learning (DFL) realizes cooperative model training among connected clients without relying on a central server, thereby mitigating communication bottlenecks and eliminating the single-point failure issue present in centralized federated learning (CFL). Most existing work on DFL focuses on superv... | {
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2412.13592 | PASCO (PArallel Structured COarsening): an overlay to speed up graph
clustering algorithms | [
"cs.LG",
"stat.ML"
] | Clustering the nodes of a graph is a cornerstone of graph analysis and has been extensively studied. However, some popular methods are not suitable for very large graphs: e.g., spectral clustering requires the computation of the spectral decomposition of the Laplacian matrix, which is not applicable for large graphs wi... | {
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2412.13594 | Generalizable Sensor-Based Activity Recognition via Categorical Concept
Invariant Learning | [
"cs.CV",
"cs.AI"
] | Human Activity Recognition (HAR) aims to recognize activities by training models on massive sensor data. In real-world deployment, a crucial aspect of HAR that has been largely overlooked is that the test sets may have different distributions from training sets due to inter-subject variability including age, gender, be... | {
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2412.13599 | Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary
Learning Framework for Abnormality Detection and Report Generation | [
"cs.CV",
"cs.CL"
] | Anatomical abnormality detection and report generation of chest X-ray (CXR) are two essential tasks in clinical practice. The former aims at localizing and characterizing cardiopulmonary radiological findings in CXRs, while the latter summarizes the findings in a detailed report for further diagnosis and treatment. Exi... | {
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2412.13601 | Hybrid CNN-LSTM based Indoor Pedestrian Localization with CSI
Fingerprint Maps | [
"cs.CV",
"cs.AI"
] | The paper presents a novel Wi-Fi fingerprinting system that uses Channel State Information (CSI) data for fine-grained pedestrian localization. The proposed system exploits the frequency diversity and spatial diversity of the features extracted from CSI data to generate a 2D+channel image termed as a CSI Fingerprint Ma... | {
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2412.13602 | Beyond Outcomes: Transparent Assessment of LLM Reasoning in Games | [
"cs.CL"
] | Large Language Models (LLMs) are increasingly deployed in real-world applications that demand complex reasoning. To track progress, robust benchmarks are required to evaluate their capabilities beyond superficial pattern recognition. However, current LLM reasoning benchmarks often face challenges such as insufficient i... | {
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2412.13606 | Exploiting Symmetries in MUS Computation (Extended version) | [
"cs.AI"
] | In eXplainable Constraint Solving (XCS), it is common to extract a Minimal Unsatisfiable Subset (MUS) from a set of unsatisfiable constraints. This helps explain to a user why a constraint specification does not admit a solution. Finding MUSes can be computationally expensive for highly symmetric problems, as many comb... | {
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2412.13607 | PreMixer: MLP-Based Pre-training Enhanced MLP-Mixers for Large-scale
Traffic Forecasting | [
"cs.LG",
"cs.ET"
] | In urban computing, precise and swift forecasting of multivariate time series data from traffic networks is crucial. This data incorporates additional spatial contexts such as sensor placements and road network layouts, and exhibits complex temporal patterns that amplify challenges for predictive learning in traffic ma... | {
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2412.13609 | Sign-IDD: Iconicity Disentangled Diffusion for Sign Language Production | [
"cs.CV",
"cs.MM"
] | Sign Language Production (SLP) aims to generate semantically consistent sign videos from textual statements, where the conversion from textual glosses to sign poses (G2P) is a crucial step. Existing G2P methods typically treat sign poses as discrete three-dimensional coordinates and directly fit them, which overlooks t... | {
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2412.13610 | Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking
Calculation | [
"cs.NE",
"cs.AI",
"cs.CV"
] | Spiking Neural Network (SNN), as a brain-inspired and energy-efficient network, is currently facing the pivotal challenge of exploring a suitable and efficient learning framework. The predominant training methodologies, namely Spatial-Temporal Back-propagation (STBP) and ANN-SNN Conversion, are encumbered by substantia... | {
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2412.13611 | Robust Tracking via Mamba-based Context-aware Token Learning | [
"cs.CV"
] | How to make a good trade-off between performance and computational cost is crucial for a tracker. However, current famous methods typically focus on complicated and time-consuming learning that combining temporal and appearance information by input more and more images (or features). Consequently, these methods not onl... | {
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2412.13612 | Are LLMs Good Literature Review Writers? Evaluating the Literature
Review Writing Ability of Large Language Models | [
"cs.CL",
"cs.AI"
] | The literature review is a crucial form of academic writing that involves complex processes of literature collection, organization, and summarization. The emergence of large language models (LLMs) has introduced promising tools to automate these processes. However, their actual capabilities in writing comprehensive lit... | {
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2412.13613 | Some New Non-binary Quantum Codes from One-generator Quasi-cyclic Codes | [
"cs.IT",
"math.IT"
] | This article studies one-generator and two-generator quasi-cyclic codes over finite fields. We present two versions of necessary and sufficient conditions for the symplectic selforthogonality of one-generator quasi-cyclic codes, using both matrix and polynomial approaches. We provide two versions of necessary and suffi... | {
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2412.13614 | Reverse Region-to-Entity Annotation for Pixel-Level Visual Entity
Linking | [
"cs.CV",
"cs.AI",
"cs.CL",
"cs.IR",
"cs.MM"
] | Visual Entity Linking (VEL) is a crucial task for achieving fine-grained visual understanding, matching objects within images (visual mentions) to entities in a knowledge base. Previous VEL tasks rely on textual inputs, but writing queries for complex scenes can be challenging. Visual inputs like clicks or bounding box... | {
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2412.13615 | MambaLCT: Boosting Tracking via Long-term Context State Space Model | [
"cs.CV"
] | Effectively constructing context information with long-term dependencies from video sequences is crucial for object tracking. However, the context length constructed by existing work is limited, only considering object information from adjacent frames or video clips, leading to insufficient utilization of contextual in... | {
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2412.13616 | Quantum Codes from Group Ring Codes | [
"cs.IT",
"math.IT"
] | This article examines group ring codes over finite fields and finite groups. We also present a section on two-dimensional cyclic codes in the quotient ring $\mathbb{F}_q[x, y] / \langle x^{l} - 1, y^{m} - 1 \rangle$. These two-dimensional cyclic codes can be analyzed using the group ring $\mathbb{F}_q(C_{l} \times C_{m... | {
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2412.13618 | NPC: Neural Predictive Control for Fuel-Efficient Autonomous Trucks | [
"cs.RO",
"cs.AI"
] | Fuel efficiency is a crucial aspect of long-distance cargo transportation by oil-powered trucks that economize on costs and decrease carbon emissions. Current predictive control methods depend on an accurate model of vehicle dynamics and engine, including weight, drag coefficient, and the Brake-specific Fuel Consumptio... | {
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2412.13621 | Learning Quadrupedal Robot Locomotion for Narrow Pipe Inspection | [
"cs.RO"
] | Various pipes are extensively used in both industrial settings and daily life, but the pipe inspection especially those with narrow sizes are still very challenging with tremendous time and manufacturing consumed. Quadrupedal robots, inspired from patrol dogs, can be a substitution of traditional solutions but always s... | {
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2412.13623 | Unifying Attribution-Based Explanations Using Functional Decomposition | [
"cs.LG",
"cs.AI"
] | The black box problem in machine learning has led to the introduction of an ever-increasing set of explanation methods for complex models. These explanations have different properties, which in turn has led to the problem of method selection: which explanation method is most suitable for a given use case? In this work,... | {
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2412.13626 | LIFT: Improving Long Context Understanding Through Long Input
Fine-Tuning | [
"cs.CL",
"cs.AI"
] | Long context understanding remains challenging for large language models due to their limited context windows. This paper introduces Long Input Fine-Tuning (LIFT) for long context modeling, a novel framework that enhances LLM performance on long-context tasks by adapting model parameters to the context at test time. LI... | {
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2412.13627 | TAUDiff: Improving statistical downscaling for extreme weather events
using generative diffusion models | [
"cs.LG"
] | Deterministic regression-based downscaling models for climate variables often suffer from spectral bias, which can be mitigated by generative models like diffusion models. To enable efficient and reliable simulation of extreme weather events, it is crucial to achieve rapid turnaround, dynamical consistency, and accurat... | {
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2412.13630 | Policy Decorator: Model-Agnostic Online Refinement for Large Policy
Model | [
"cs.RO",
"cs.AI",
"cs.LG"
] | Recent advancements in robot learning have used imitation learning with large models and extensive demonstrations to develop effective policies. However, these models are often limited by the quantity, quality, and diversity of demonstrations. This paper explores improving offline-trained imitation learning models thro... | {
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2412.13631 | Mind Your Theory: Theory of Mind Goes Deeper Than Reasoning | [
"cs.AI",
"cs.CL"
] | Theory of Mind (ToM) capabilities in LLMs have recently become a central object of investigation. Cognitive science distinguishes between two steps required for ToM tasks: 1) determine whether to invoke ToM, which includes the appropriate Depth of Mentalizing (DoM), or level of recursion required to complete a task; an... | {
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2412.13632 | An Extension-Based Argument-Ranking Semantics: Social Rankings in
Abstract Argumentation Long Version | [
"cs.AI"
] | In this paper, we introduce a new family of argument-ranking semantics which can be seen as a refinement of the classification of arguments into skeptically accepted, credulously accepted and rejected. To this end we use so-called social ranking functions which have been developed recently to rank individuals based on ... | {
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2412.13635 | Self-control: A Better Conditional Mechanism for Masked Autoregressive
Model | [
"cs.CV"
] | Autoregressive conditional image generation algorithms are capable of generating photorealistic images that are consistent with given textual or image conditions, and have great potential for a wide range of applications. Nevertheless, the majority of popular autoregressive image generation methods rely heavily on vect... | {
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2412.13636 | Consistency of Compositional Generalization across Multiple Levels | [
"cs.CV",
"cs.AI"
] | Compositional generalization is the capability of a model to understand novel compositions composed of seen concepts. There are multiple levels of novel compositions including phrase-phrase level, phrase-word level, and word-word level. Existing methods achieve promising compositional generalization, but the consistenc... | {
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2412.13638 | A Constraint Embedding Approach for Dynamics Modeling of Parallel
Kinematic Manipulators with Hybrid Limbs | [
"cs.RO",
"math.DS",
"math.GR",
"physics.app-ph"
] | Parallel kinematic manipulators (PKM) are characterized by closed kinematic loops, due to the parallel arrangement of limbs but also due to the existence of kinematic loops within the limbs. Moreover, many PKM are built with limbs constructed by serially combining kinematic loops. Such limbs are called hybrid, which fo... | {
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2412.13639 | 4D Radar-Inertial Odometry based on Gaussian Modeling and
Multi-Hypothesis Scan Matching | [
"cs.RO"
] | 4D millimeter-wave (mmWave) radars are sensors that provide robustness against adverse weather conditions (rain, snow, fog, etc.), and as such they are increasingly being used for odometry and SLAM applications. However, the noisy and sparse nature of the returned scan data proves to be a challenging obstacle for exist... | {
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2412.13641 | Learning to Control an Android Robot Head for Facial Animation | [
"cs.RO"
] | The ability to display rich facial expressions is crucial for human-like robotic heads. While manually defining such expressions is intricate, there already exist approaches to automatically learn them. In this work one such approach is applied to evaluate and control a robot head different from the one in the original... | {
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2412.13645 | On the Role of Model Prior in Real-World Inductive Reasoning | [
"cs.AI",
"cs.CL"
] | Large Language Models (LLMs) show impressive inductive reasoning capabilities, enabling them to generate hypotheses that could generalize effectively to new instances when guided by in-context demonstrations. However, in real-world applications, LLMs' hypothesis generation is not solely determined by these demonstratio... | {
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2412.13647 | G-VEval: A Versatile Metric for Evaluating Image and Video Captions
Using GPT-4o | [
"cs.CV",
"cs.AI",
"cs.CL"
] | Evaluation metric of visual captioning is important yet not thoroughly explored. Traditional metrics like BLEU, METEOR, CIDEr, and ROUGE often miss semantic depth, while trained metrics such as CLIP-Score, PAC-S, and Polos are limited in zero-shot scenarios. Advanced Language Model-based metrics also struggle with alig... | {
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2412.13649 | SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation | [
"cs.CL"
] | Key-Value (KV) cache has become a bottleneck of LLMs for long-context generation. Despite the numerous efforts in this area, the optimization for the decoding phase is generally ignored. However, we believe such optimization is crucial, especially for long-output generation tasks based on the following two observations... | {
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2412.13652 | RelationField: Relate Anything in Radiance Fields | [
"cs.CV"
] | Neural radiance fields are an emerging 3D scene representation and recently even been extended to learn features for scene understanding by distilling open-vocabulary features from vision-language models. However, current method primarily focus on object-centric representations, supporting object segmentation or detect... | {
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2412.13654 | GAGS: Granularity-Aware Feature Distillation for Language Gaussian
Splatting | [
"cs.CV"
] | 3D open-vocabulary scene understanding, which accurately perceives complex semantic properties of objects in space, has gained significant attention in recent years. In this paper, we propose GAGS, a framework that distills 2D CLIP features into 3D Gaussian splatting, enabling open-vocabulary queries for renderings on ... | {
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2412.13655 | VIIS: Visible and Infrared Information Synthesis for Severe Low-light
Image Enhancement | [
"cs.CV"
] | Images captured in severe low-light circumstances often suffer from significant information absence. Existing singular modality image enhancement methods struggle to restore image regions lacking valid information. By leveraging light-impervious infrared images, visible and infrared image fusion methods have the potent... | {
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2412.13656 | GLCF: A Global-Local Multimodal Coherence Analysis Framework for Talking
Face Generation Detection | [
"cs.CV"
] | Talking face generation (TFG) allows for producing lifelike talking videos of any character using only facial images and accompanying text. Abuse of this technology could pose significant risks to society, creating the urgent need for research into corresponding detection methods. However, research in this field has be... | {
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2412.13660 | PsyDT: Using LLMs to Construct the Digital Twin of Psychological
Counselor with Personalized Counseling Style for Psychological Counseling | [
"cs.CL"
] | Currently, large language models (LLMs) have made significant progress in the field of psychological counseling. However, existing mental health LLMs overlook a critical issue where they do not consider the fact that different psychological counselors exhibit different personal styles, including linguistic style and th... | {
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2412.13662 | When Should We Prefer State-to-Visual DAgger Over Visual Reinforcement
Learning? | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.RO"
] | Learning policies from high-dimensional visual inputs, such as pixels and point clouds, is crucial in various applications. Visual reinforcement learning is a promising approach that directly trains policies from visual observations, although it faces challenges in sample efficiency and computational costs. This study ... | {
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2412.13663 | Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for
Fast, Memory Efficient, and Long Context Finetuning and Inference | [
"cs.CL",
"cs.AI"
] | Encoder-only transformer models such as BERT offer a great performance-size tradeoff for retrieval and classification tasks with respect to larger decoder-only models. Despite being the workhorse of numerous production pipelines, there have been limited Pareto improvements to BERT since its release. In this paper, we i... | {
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} |
2412.13664 | A Skeleton-Based Topological Planner for Exploration in Complex Unknown
Environments | [
"cs.RO"
] | The capability of autonomous exploration in complex, unknown environments is important in many robotic applications. While recent research on autonomous exploration have achieved much progress, there are still limitations, e.g., existing methods relying on greedy heuristics or optimal path planning are often hindered b... | {
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} |
2412.13665 | Time-Reversible Bridges of Data with Machine Learning | [
"stat.ML",
"cs.LG"
] | The analysis of dynamical systems is a fundamental tool in the natural sciences and engineering. It is used to understand the evolution of systems as large as entire galaxies and as small as individual molecules. With predefined conditions on the evolution of dy-namical systems, the underlying differential equations ha... | {
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} |
2412.13666 | Evaluation of LLM Vulnerabilities to Being Misused for Personalized
Disinformation Generation | [
"cs.CL",
"cs.AI",
"cs.CY"
] | The capabilities of recent large language models (LLMs) to generate high-quality content indistinguishable by humans from human-written texts rises many concerns regarding their misuse. Previous research has shown that LLMs can be effectively misused for generating disinformation news articles following predefined narr... | {
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} |
2412.13667 | Exploring Multi-Modal Integration with Tool-Augmented LLM Agents for
Precise Causal Discovery | [
"cs.LG",
"cs.AI",
"stat.ME"
] | Causal inference is an imperative foundation for decision-making across domains, such as smart health, AI for drug discovery and AIOps. Traditional statistical causal discovery methods, while well-established, predominantly rely on observational data and often overlook the semantic cues inherent in cause-and-effect rel... | {
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} |
2412.13668 | Emotional Sequential Influence Modeling on False Information | [
"cs.SI"
] | The extensive dissemination of false information in social networks affects netizens social lives, morals, and behaviours. When a neighbour expresses strong emotions (e.g., fear, anger, excitement) based on a false statement, these emotions can be transmitted to others, especially through interactions on social media. ... | {
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} |
2412.13670 | AntiLeak-Bench: Preventing Data Contamination by Automatically
Constructing Benchmarks with Updated Real-World Knowledge | [
"cs.CL",
"cs.LG"
] | Data contamination hinders fair LLM evaluation by introducing test data into newer models' training sets. Existing studies solve this challenge by updating benchmarks with newly collected data. However, they fail to guarantee contamination-free evaluation as the newly collected data may contain pre-existing knowledge, ... | {
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} |
2412.13678 | Clio: Privacy-Preserving Insights into Real-World AI Use | [
"cs.CY",
"cs.AI",
"cs.CL",
"cs.CR",
"cs.LG"
] | How are AI assistants being used in the real world? While model providers in theory have a window into this impact via their users' data, both privacy concerns and practical challenges have made analyzing this data difficult. To address these issues, we present Clio (Claude insights and observations), a privacy-preserv... | {
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} |
2412.13679 | On Enhancing Root Cause Analysis with SQL Summaries for Failures in
Database Workload Replays at SAP HANA | [
"cs.LG",
"cs.DB"
] | Capturing the workload of a database and replaying this workload for a new version of the database can be an effective approach for regression testing. However, false positive errors caused by many factors such as data privacy limitations, time dependency or non-determinism in multi-threaded environment can negatively ... | {
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} |
2412.13681 | Dynamics of Parallel Manipulators with Hybrid Complex Limbs -- Modular
Modeling and Parallel Computing | [
"cs.RO"
] | Parallel manipulators, also called parallel kinematics machines (PKM), enable robotic solutions for highly dynamic handling and machining applications. The safe and accurate design and control necessitates high-fidelity dynamics models. Such modeling approaches have already been presented for PKM with simple limbs (i.e... | {
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} |
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