id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.11629 | QPruner: Probabilistic Decision Quantization for Structured Pruning in
Large Language Models | [
"cs.LG"
] | The rise of large language models (LLMs) has significantly advanced various natural language processing (NLP) tasks. However, the resource demands of these models pose substantial challenges. Structured pruning is an effective approach to reducing model size, but it often results in significant accuracy degradation, ne... | {
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2412.11631 | A Mapper Algorithm with implicit intervals and its optimization | [
"cs.LG",
"stat.ML"
] | The Mapper algorithm is an essential tool for visualizing complex, high dimensional data in topology data analysis (TDA) and has been widely used in biomedical research. It outputs a combinatorial graph whose structure implies the shape of the data. However,the need for manual parameter tuning and fixed intervals, alon... | {
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2412.11632 | Multi-Scale Incremental Modeling for Enhanced Human Motion Prediction in
Human-Robot Collaboration | [
"cs.RO",
"cs.AI"
] | Accurate human motion prediction is crucial for safe human-robot collaboration but remains challenging due to the complexity of modeling intricate and variable human movements. This paper presents Parallel Multi-scale Incremental Prediction (PMS), a novel framework that explicitly models incremental motion across multi... | {
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2412.11634 | Predicting the Original Appearance of Damaged Historical Documents | [
"cs.CV"
] | Historical documents encompass a wealth of cultural treasures but suffer from severe damages including character missing, paper damage, and ink erosion over time. However, existing document processing methods primarily focus on binarization, enhancement, etc., neglecting the repair of these damages. To this end, we pre... | {
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2412.11637 | On Crowdsourcing Task Design for Discourse Relation Annotation | [
"cs.CL"
] | Interpreting implicit discourse relations involves complex reasoning, requiring the integration of semantic cues with background knowledge, as overt connectives like because or then are absent. These relations often allow multiple interpretations, best represented as distributions. In this study, we compare two establi... | {
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2412.11638 | IDProtector: An Adversarial Noise Encoder to Protect Against
ID-Preserving Image Generation | [
"cs.CV"
] | Recently, zero-shot methods like InstantID have revolutionized identity-preserving generation. Unlike multi-image finetuning approaches such as DreamBooth, these zero-shot methods leverage powerful facial encoders to extract identity information from a single portrait photo, enabling efficient identity-preserving gener... | {
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2412.11639 | High-speed and High-quality Vision Reconstruction of Spike Camera with
Spike Stability Theorem | [
"cs.CV",
"eess.IV"
] | Neuromorphic vision sensors, such as the dynamic vision sensor (DVS) and spike camera, have gained increasing attention in recent years. The spike camera can detect fine textures by mimicking the fovea in the human visual system, and output a high-frequency spike stream. Real-time high-quality vision reconstruction fro... | {
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2412.11642 | Introduction to AI Planning | [
"cs.AI"
] | These are notes for lectures presented at the University of Stuttgart that provide an introduction to key concepts and techniques in AI Planning. Artificial Intelligence Planning, also known as Automated Planning, emerged somewhere in 1966 from the need to give autonomy to a wheeled robot. Since then, it has evolved in... | {
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2412.11643 | A comprehensive GeoAI review: Progress, Challenges and Outlooks | [
"cs.AI",
"physics.geo-ph"
] | In recent years, Geospatial Artificial Intelligence (GeoAI) has gained traction in the most relevant research works and industrial applications, while also becoming involved in various fields of use. This paper offers a comprehensive review of GeoAI as a synergistic concept applying Artificial Intelligence (AI) methods... | {
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2412.11646 | BA-BFL: Barycentric Aggregation for Bayesian Federated Learning | [
"cs.LG",
"cs.IT",
"cs.NI",
"math.IT"
] | In this work, we study the problem of aggregation in the context of Bayesian Federated Learning (BFL). Using an information geometric perspective, we interpret the BFL aggregation step as finding the barycenter of the trained posteriors for a pre-specified divergence metric. We study the barycenter problem for the para... | {
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2412.11647 | Q-DISCO: Query-Centric Densest Subgraphs in Networks with Opinion
Information | [
"cs.SI",
"physics.soc-ph"
] | Given a network $G=(V,E)$, where each node $v$ is associated with a vector $\boldsymbol{p}_v \in \mathbb{R}^d$ representing its opinion about $d$ different topics, how can we uncover subsets of nodes that not only exhibit exceptionally high density but also possess positively aligned opinions on multiple topics? In thi... | {
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2412.11650 | Image Gradient-Aided Photometric Stereo Network | [
"cs.CV"
] | Photometric stereo (PS) endeavors to ascertain surface normals using shading clues from photometric images under various illuminations. Recent deep learning-based PS methods often overlook the complexity of object surfaces. These neural network models, which exclusively rely on photometric images for training, often pr... | {
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2412.11652 | SE-GCL: An Event-Based Simple and Effective Graph Contrastive Learning
for Text Representation | [
"cs.CL",
"cs.AI"
] | Text representation learning is significant as the cornerstone of natural language processing. In recent years, graph contrastive learning (GCL) has been widely used in text representation learning due to its ability to represent and capture complex text information in a self-supervised setting. However, current mainst... | {
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2412.11653 | Self-Adaptive Paraphrasing and Preference Learning for Improved Claim
Verifiability | [
"cs.CL"
] | In fact-checking, structure and phrasing of claims critically influence a model's ability to predict verdicts accurately. Social media content in particular rarely serves as optimal input for verification systems, which necessitates pre-processing to extract the claim from noisy context before fact checking. Prior work... | {
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2412.11654 | Smoothness Really Matters: A Simple Yet Effective Approach for
Unsupervised Graph Domain Adaptation | [
"cs.LG",
"cs.AI"
] | Unsupervised Graph Domain Adaptation (UGDA) seeks to bridge distribution shifts between domains by transferring knowledge from labeled source graphs to given unlabeled target graphs. Existing UGDA methods primarily focus on aligning features in the latent space learned by graph neural networks (GNNs) across domains, of... | {
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2412.11656 | Private Yet Social: How LLM Chatbots Support and Challenge Eating
Disorder Recovery | [
"cs.HC",
"cs.LG"
] | Eating disorders (ED) are complex mental health conditions that require long-term management and support. Recent advancements in large language model (LLM)-based chatbots offer the potential to assist individuals in receiving immediate support. Yet, concerns remain about their reliability and safety in sensitive contex... | {
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2412.11657 | CNNtention: Can CNNs do better with Attention? | [
"cs.CV",
"cs.LG"
] | Convolutional Neural Networks (CNNs) have been the standard for image classification tasks for a long time, but more recently attention-based mechanisms have gained traction. This project aims to compare traditional CNNs with attention-augmented CNNs across an image classification task. By evaluating and comparing thei... | {
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2412.11660 | Non-Convex Optimization in Federated Learning via Variance Reduction and
Adaptive Learning | [
"cs.LG"
] | This paper proposes a novel federated algorithm that leverages momentum-based variance reduction with adaptive learning to address non-convex settings across heterogeneous data. We intend to minimize communication and computation overhead, thereby fostering a sustainable federated learning system. We aim to overcome ch... | {
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2412.11661 | Rewriting Consistent Answers on Annotated Data | [
"cs.DB",
"cs.LO"
] | We embark on a study of the consistent answers of queries over databases annotated with values from a naturally ordered positive semiring. In this setting, the consistent answers of a query are defined as the minimum of the semiring values that the query takes over all repairs of an inconsistent database. The main focu... | {
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2412.11663 | LMM-Regularized CLIP Embeddings for Image Classification | [
"cs.CV",
"cs.MM"
] | In this paper we deal with image classification tasks using the powerful CLIP vision-language model. Our goal is to advance the classification performance using the CLIP's image encoder, by proposing a novel Large Multimodal Model (LMM) based regularization method. The proposed method uses an LMM to extract semantic de... | {
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2412.11664 | C3oT: Generating Shorter Chain-of-Thought without Compromising
Effectiveness | [
"cs.CL",
"cs.LG"
] | Generating Chain-of-Thought (CoT) before deriving the answer can effectively improve the reasoning capabilities of large language models (LLMs) and significantly improve the accuracy of the generated answer. However, in most cases, the length of the generated CoT is much longer than the desired final answer, which resu... | {
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2412.11666 | On the SDP Relaxation of Direct Torque Finite Control Set Model
Predictive Control | [
"math.OC",
"cs.SY",
"eess.SY"
] | This paper formulates a semidefinite programming relaxation for a long horizon direct-torque finite-control-set model predictive control problem. In parallel with this relaxation, a conventional branch-and-bound algorithm tailored for the original problem, but with an iteration limit to restrict its computational burde... | {
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2412.11668 | Online Writer Retrieval with Chinese Handwritten Phrases: A Synergistic
Temporal-Frequency Representation Learning Approach | [
"cs.CV"
] | Currently, the prevalence of online handwriting has spurred a critical need for effective retrieval systems to accurately search relevant handwriting instances from specific writers, known as online writer retrieval. Despite the growing demand, this field suffers from a scarcity of well-established methodologies and pu... | {
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2412.11669 | Soft and Constrained Hypertree Width | [
"cs.DB"
] | Hypertree decompositions provide a way to evaluate Conjunctive Queries (CQs) in polynomial time, where the exponent of this polynomial is determined by the width of the decomposition. In theory, the goal of efficient CQ evaluation therefore has to be a minimisation of the width. However, in practical settings, it turns... | {
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2412.11671 | BioBridge: Unified Bio-Embedding with Bridging Modality in Code-Switched
EMR | [
"cs.CL",
"cs.AI"
] | Pediatric Emergency Department (PED) overcrowding presents a significant global challenge, prompting the need for efficient solutions. This paper introduces the BioBridge framework, a novel approach that applies Natural Language Processing (NLP) to Electronic Medical Records (EMRs) in written free-text form to enhance ... | {
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2412.11672 | LLM-DaaS: LLM-driven Drone-as-a-Service Operations from Text User
Requests | [
"cs.AI",
"cs.HC"
] | We propose LLM-DaaS, a novel Drone-as-a-Service (DaaS) framework that leverages Large Language Models (LLMs) to transform free-text user requests into structured, actionable DaaS operation tasks. Our approach addresses the key challenge of interpreting and structuring natural language input to automate drone service op... | {
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2412.11673 | DINO-Foresight: Looking into the Future with DINO | [
"cs.CV"
] | Predicting future dynamics is crucial for applications like autonomous driving and robotics, where understanding the environment is key. Existing pixel-level methods are computationally expensive and often focus on irrelevant details. To address these challenges, we introduce DINO-Foresight, a novel framework that oper... | {
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2412.11674 | UA-PDFL: A Personalized Approach for Decentralized Federated Learning | [
"cs.LG",
"cs.AI"
] | Federated learning (FL) is a privacy preserving machine learning paradigm designed to collaboratively learn a global model without data leakage. Specifically, in a typical FL system, the central server solely functions as an coordinator to iteratively aggregate the collected local models trained by each client, potenti... | {
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2412.11678 | Loosely Synchronized Rule-Based Planning for Multi-Agent Path Finding
with Asynchronous Actions | [
"cs.MA",
"cs.AI"
] | Multi-Agent Path Finding (MAPF) seeks collision-free paths for multiple agents from their respective starting locations to their respective goal locations while minimizing path costs. Although many MAPF algorithms were developed and can handle up to thousands of agents, they usually rely on the assumption that each act... | {
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2412.11679 | Bias Vector: Mitigating Biases in Language Models with Task Arithmetic
Approach | [
"cs.CL",
"cs.AI"
] | The use of language models (LMs) has increased considerably in recent years, and the biases and stereotypes in training data that are reflected in the LM outputs are causing social problems. In this paper, inspired by the task arithmetic, we propose the ``Bias Vector'' method for the mitigation of these LM biases. The ... | {
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2412.11680 | EGP3D: Edge-guided Geometric Preserving 3D Point Cloud Super-resolution
for RGB-D camera | [
"cs.CV"
] | Point clouds or depth images captured by current RGB-D cameras often suffer from low resolution, rendering them insufficient for applications such as 3D reconstruction and robots. Existing point cloud super-resolution (PCSR) methods are either constrained by geometric artifacts or lack attention to edge details. To add... | {
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2412.11681 | Fast-staged CNN Model for Accurate pulmonary diseases and Lung cancer
detection | [
"eess.IV",
"cs.AI",
"cs.CV"
] | Pulmonary pathologies are a significant global health concern, often leading to fatal outcomes if not diagnosed and treated promptly. Chest radiography serves as a primary diagnostic tool, but the availability of experienced radiologists remains limited. Advances in Artificial Intelligence (AI) and machine learning, pa... | {
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2412.11682 | NEST: A Neuromodulated Small-world Hypergraph Trajectory Prediction
Model for Autonomous Driving | [
"cs.RO",
"cs.AI",
"cs.LG"
] | Accurate trajectory prediction is essential for the safety and efficiency of autonomous driving. Traditional models often struggle with real-time processing, capturing non-linearity and uncertainty in traffic environments, efficiency in dense traffic, and modeling temporal dynamics of interactions. We introduce NEST (N... | {
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2412.11683 | Multimodal LLM for Intelligent Transportation Systems | [
"cs.LG"
] | In the evolving landscape of transportation systems, integrating Large Language Models (LLMs) offers a promising frontier for advancing intelligent decision-making across various applications. This paper introduces a novel 3-dimensional framework that encapsulates the intersection of applications, machine learning meth... | {
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2412.11684 | Runtime Analysis for Multi-Objective Evolutionary Algorithms in
Unbounded Integer Spaces | [
"cs.NE"
] | Randomized search heuristics have been applied successfully to a plethora of problems. This success is complemented by a large body of theoretical results. Unfortunately, the vast majority of these results regard problems with binary or continuous decision variables -- the theoretical analysis of randomized search heur... | {
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2412.11685 | Ultra-High-Definition Dynamic Multi-Exposure Image Fusion via Infinite
Pixel Learning | [
"cs.CV"
] | With the continuous improvement of device imaging resolution, the popularity of Ultra-High-Definition (UHD) images is increasing. Unfortunately, existing methods for fusing multi-exposure images in dynamic scenes are designed for low-resolution images, which makes them inefficient for generating high-quality UHD images... | {
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2412.11687 | Dual Unscented Kalman Filter Architecture for Sensor Fusion in Water
Networks Leak Localization | [
"eess.SY",
"cs.LG",
"cs.SY",
"math.ST",
"stat.TH"
] | Leakage in water systems results in significant daily water losses, degrading service quality, increasing costs, and aggravating environmental problems. Most leak localization methods rely solely on pressure data, missing valuable information from other sensor types. This article proposes a hydraulic state estimation m... | {
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2412.11689 | Just a Simple Transformation is Enough for Data Protection in Vertical
Federated Learning | [
"cs.LG",
"cs.CR"
] | Vertical Federated Learning (VFL) aims to enable collaborative training of deep learning models while maintaining privacy protection. However, the VFL procedure still has components that are vulnerable to attacks by malicious parties. In our work, we consider feature reconstruction attacks, a common risk targeting inpu... | {
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2412.11691 | Multilingual and Explainable Text Detoxification with Parallel Corpora | [
"cs.CL",
"cs.AI"
] | Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant issue. One potential approach to address this challenge is automatic text detoxification, a text style ... | {
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2412.11694 | From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with
Multi-modalities | [
"cs.AI",
"cs.CL",
"cs.LG"
] | To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints of any specific non-linguistic modality, Omni-MLLMs map various non-linguistic modalities into the embedding space of LLMs and enable the int... | {
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2412.11695 | CiTrus: Squeezing Extra Performance out of Low-data Bio-signal Transfer
Learning | [
"cs.LG"
] | Transfer learning for bio-signals has recently become an important technique to improve prediction performance on downstream tasks with small bio-signal datasets. Recent works have shown that pre-training a neural network model on a large dataset (e.g. EEG) with a self-supervised task, replacing the self-supervised hea... | {
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2412.11698 | On Large Language Models in Mission-Critical IT Governance: Are We Ready
Yet? | [
"cs.CR",
"cs.AI",
"cs.ET",
"cs.SE"
] | Context. The security of critical infrastructure has been a pressing concern since the advent of computers and has become even more critical in today's era of cyber warfare. Protecting mission-critical systems (MCSs), essential for national security, requires swift and robust governance, yet recent events reveal the in... | {
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2412.11699 | CoinMath: Harnessing the Power of Coding Instruction for Math LLMs | [
"cs.CL"
] | Large Language Models (LLMs) have shown strong performance in solving mathematical problems, with code-based solutions proving particularly effective. However, the best practice to leverage coding instruction data to enhance mathematical reasoning remains underexplored. This study investigates three key questions: (1) ... | {
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2412.11702 | Flex-PE: Flexible and SIMD Multi-Precision Processing Element for AI
Workloads | [
"cs.AR",
"cs.CV",
"cs.DC",
"cs.ET",
"eess.IV"
] | The rapid adaptation of data driven AI models, such as deep learning inference, training, Vision Transformers (ViTs), and other HPC applications, drives a strong need for runtime precision configurable different non linear activation functions (AF) hardware support. Existing solutions support diverse precision or runti... | {
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2412.11704 | Vocabulary Expansion of Chat Models with Unlabeled Target Language Data | [
"cs.CL",
"cs.AI"
] | Chat models (i.e. language models trained to follow instructions through conversation with humans) outperform base models (i.e. trained solely on unlabeled data) in both conversation and general task-solving abilities. These models are generally English-centric and require further adaptation for languages that are unde... | {
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2412.11706 | AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric
Reduction and Restoration | [
"cs.CV"
] | Video Diffusion Transformers (DiTs) have demonstrated significant potential for generating high-fidelity videos but are computationally intensive. Existing acceleration methods include distillation, which requires costly retraining, and feature caching, which is highly sensitive to network architecture. Recent token re... | {
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2412.11707 | Context Filtering with Reward Modeling in Question Answering | [
"cs.CL"
] | Question Answering (QA) in NLP is the task of finding answers to a query within a relevant context retrieved by a retrieval system. Yet, the mix of relevant and irrelevant information in these contexts can hinder performance enhancements in QA tasks. To address this, we introduce a context filtering approach that remov... | {
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2412.11710 | Re-Attentional Controllable Video Diffusion Editing | [
"cs.CV",
"cs.AI"
] | Editing videos with textual guidance has garnered popularity due to its streamlined process which mandates users to solely edit the text prompt corresponding to the source video. Recent studies have explored and exploited large-scale text-to-image diffusion models for text-guided video editing, resulting in remarkable ... | {
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2412.11711 | MiMoTable: A Multi-scale Spreadsheet Benchmark with Meta Operations for
Table Reasoning | [
"cs.CL"
] | Extensive research has been conducted to explore the capability of Large Language Models (LLMs) for table reasoning and has significantly improved the performance on existing benchmarks. However, tables and user questions in real-world applications are more complex and diverse, presenting an unignorable gap compared to... | {
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2412.11713 | Seeker: Towards Exception Safety Code Generation with Intermediate
Language Agents Framework | [
"cs.CL",
"cs.SE"
] | In real world software development, improper or missing exception handling can severely impact the robustness and reliability of code. Exception handling mechanisms require developers to detect, capture, and manage exceptions according to high standards, but many developers struggle with these tasks, leading to fragile... | {
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2412.11715 | Discrepancy-Aware Attention Network for Enhanced Audio-Visual Zero-Shot
Learning | [
"cs.CV",
"cs.MM",
"cs.SD",
"eess.AS"
] | Audio-visual Zero-Shot Learning (ZSL) has attracted significant attention for its ability to identify unseen classes and perform well in video classification tasks. However, modal imbalance in (G)ZSL leads to over-reliance on the optimal modality, reducing discriminative capabilities for unseen classes. Some studies ha... | {
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2412.11716 | LLMs Can Simulate Standardized Patients via Agent Coevolution | [
"cs.CL",
"cs.AI",
"cs.HC",
"cs.MA"
] | Training medical personnel using standardized patients (SPs) remains a complex challenge, requiring extensive domain expertise and role-specific practice. Most research on Large Language Model (LLM)-based simulated patients focuses on improving data retrieval accuracy or adjusting prompts through human feedback. Howeve... | {
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2412.11717 | Learning UAV-based path planning for efficient localization of objects
using prior knowledge | [
"cs.RO"
] | UAV's are becoming popular for various object search applications in agriculture, however they usually use time-consuming row-by-row flight paths. This paper presents a deep-reinforcement-learning method for path planning to efficiently localize objects of interest using UAVs with a minimal flight-path length. The meth... | {
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2412.11729 | STAIR: Manipulating Collaborative and Multimodal Information for
E-Commerce Recommendation | [
"cs.IR"
] | While the mining of modalities is the focus of most multimodal recommendation methods, we believe that how to fully utilize both collaborative and multimodal information is pivotal in e-commerce scenarios where, as clarified in this work, the user behaviors are rarely determined entirely by multimodal features. In orde... | {
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2412.11732 | Findings of the WMT 2024 Shared Task on Discourse-Level Literary
Translation | [
"cs.CL"
] | Following last year, we have continued to host the WMT translation shared task this year, the second edition of the Discourse-Level Literary Translation. We focus on three language directions: Chinese-English, Chinese-German, and Chinese-Russian, with the latter two ones newly added. This year, we totally received 10 s... | {
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2412.11735 | Transferable Adversarial Face Attack with Text Controlled Attribute | [
"cs.CV",
"cs.AI"
] | Traditional adversarial attacks typically produce adversarial examples under norm-constrained conditions, whereas unrestricted adversarial examples are free-form with semantically meaningful perturbations. Current unrestricted adversarial impersonation attacks exhibit limited control over adversarial face attributes an... | {
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2412.11736 | Personalized LLM for Generating Customized Responses to the Same Query
from Different Users | [
"cs.CL"
] | Existing work on large language model (LLM) personalization assigned different responding roles to LLM, but overlooked the diversity of questioners. In this work, we propose a new form of questioner-aware LLM personalization, generating different responses even for the same query from different questioners. We design a... | {
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2412.11737 | Efficiently Achieving Secure Model Training and Secure Aggregation to
Ensure Bidirectional Privacy-Preservation in Federated Learning | [
"cs.LG",
"cs.CR"
] | Bidirectional privacy-preservation federated learning is crucial as both local gradients and the global model may leak privacy. However, only a few works attempt to achieve it, and they often face challenges such as excessive communication and computational overheads, or significant degradation of model accuracy, which... | {
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2412.11739 | Asymmetric Learning for Spectral Graph Neural Networks | [
"cs.LG"
] | Optimizing spectral graph neural networks (GNNs) remains a critical challenge in the field, yet the underlying processes are not well understood. In this paper, we investigate the inherent differences between graph convolution parameters and feature transformation parameters in spectral GNNs and their impact on the opt... | {
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2412.11741 | CSR:Achieving 1 Bit Key-Value Cache via Sparse Representation | [
"cs.CL"
] | The emergence of long-context text applications utilizing large language models (LLMs) has presented significant scalability challenges, particularly in memory footprint. The linear growth of the Key-Value (KV) cache responsible for storing attention keys and values to minimize redundant computations can lead to substa... | {
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2412.11743 | Generalized Bayesian deep reinforcement learning | [
"stat.ML",
"cs.LG",
"stat.ME"
] | Bayesian reinforcement learning (BRL) is a method that merges principles from Bayesian statistics and reinforcement learning to make optimal decisions in uncertain environments. Similar to other model-based RL approaches, it involves two key components: (1) Inferring the posterior distribution of the data generating pr... | {
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2412.11744 | Conditional Diffusion Models Based Conditional Independence Testing | [
"stat.ML",
"cs.LG"
] | Conditional independence (CI) testing is a fundamental task in modern statistics and machine learning. The conditional randomization test (CRT) was recently introduced to test whether two random variables, $X$ and $Y$, are conditionally independent given a potentially high-dimensional set of random variables, $Z$. The ... | {
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2412.11745 | Beyond Dataset Creation: Critical View of Annotation Variation and Bias
Probing of a Dataset for Online Radical Content Detection | [
"cs.CL"
] | The proliferation of radical content on online platforms poses significant risks, including inciting violence and spreading extremist ideologies. Despite ongoing research, existing datasets and models often fail to address the complexities of multilingual and diverse data. To bridge this gap, we introduce a publicly av... | {
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2412.11747 | Beyond Graph Convolution: Multimodal Recommendation with Topology-aware
MLPs | [
"cs.IR"
] | Given the large volume of side information from different modalities, multimodal recommender systems have become increasingly vital, as they exploit richer semantic information beyond user-item interactions. Recent works highlight that leveraging Graph Convolutional Networks (GCNs) to explicitly model multimodal item-i... | {
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2412.11750 | Common Ground, Diverse Roots: The Difficulty of Classifying Common
Examples in Spanish Varieties | [
"cs.CL"
] | Variations in languages across geographic regions or cultures are crucial to address to avoid biases in NLP systems designed for culturally sensitive tasks, such as hate speech detection or dialog with conversational agents. In languages such as Spanish, where varieties can significantly overlap, many examples can be v... | {
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2412.11752 | Deformable Radial Kernel Splatting | [
"cs.CV",
"cs.GR"
] | Recently, Gaussian splatting has emerged as a robust technique for representing 3D scenes, enabling real-time rasterization and high-fidelity rendering. However, Gaussians' inherent radial symmetry and smoothness constraints limit their ability to represent complex shapes, often requiring thousands of primitives to app... | {
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2412.11753 | DriveGazen: Event-Based Driving Status Recognition using Conventional
Camera | [
"cs.CV",
"cs.AI"
] | We introduce a wearable driving status recognition device and our open-source dataset, along with a new real-time method robust to changes in lighting conditions for identifying driving status from eye observations of drivers. The core of our method is generating event frames from conventional intensity frames, and the... | {
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2412.11755 | Generative Inbetweening through Frame-wise Conditions-Driven Video
Generation | [
"cs.CV"
] | Generative inbetweening aims to generate intermediate frame sequences by utilizing two key frames as input. Although remarkable progress has been made in video generation models, generative inbetweening still faces challenges in maintaining temporal stability due to the ambiguous interpolation path between two key fram... | {
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2412.11757 | SCITAT: A Question Answering Benchmark for Scientific Tables and Text
Covering Diverse Reasoning Types | [
"cs.CL"
] | Scientific question answering (SQA) is an important task aimed at answering questions based on papers. However, current SQA datasets have limited reasoning types and neglect the relevance between tables and text, creating a significant gap with real scenarios. To address these challenges, we propose a QA benchmark for ... | {
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2412.11758 | Establishing a Foundation for Tetun Text Ad-Hoc Retrieval: Indexing,
Stemming, Retrieval, and Ranking | [
"cs.IR"
] | Searching for information on the internet and digital platforms to satisfy an information need requires effective retrieval solutions. However, such solutions are not yet available for Tetun, making it challenging to find relevant documents for text-based search queries in this language. To address these challenges, th... | {
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2412.11760 | Efficient LiDAR Bundle Adjustment for Multi-Scan Alignment Utilizing
Continuous-Time Trajectories | [
"cs.RO"
] | Constructing precise global maps is a key task in robotics and is required for localization, surveying, monitoring, or constructing digital twins. To build accurate maps, data from mobile 3D LiDAR sensors is often used. Mapping requires correctly aligning the individual point clouds to each other to obtain a globally c... | {
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2412.11761 | Harnessing Language for Coordination: A Framework and Benchmark for
LLM-Driven Multi-Agent Control | [
"cs.AI"
] | Large Language Models (LLMs) have demonstrated remarkable performance across various tasks. A promising but largely under-explored area is their potential to facilitate human coordination with many agents. Such capabilities would be useful in domains including disaster response, urban planning, and real-time strategy s... | {
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2412.11762 | GS-ProCams: Gaussian Splatting-based Projector-Camera Systems | [
"cs.CV",
"cs.GR",
"cs.MM"
] | We present GS-ProCams, the first Gaussian Splatting-based framework for projector-camera systems (ProCams). GS-ProCams significantly enhances the efficiency of projection mapping (PM) that requires establishing geometric and radiometric mappings between the projector and the camera. Previous CNN-based ProCams are const... | {
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2412.11763 | QUENCH: Measuring the gap between Indic and Non-Indic Contextual General
Reasoning in LLMs | [
"cs.CL"
] | The rise of large language models (LLMs) has created a need for advanced benchmarking systems beyond traditional setups. To this end, we introduce QUENCH, a novel text-based English Quizzing Benchmark manually curated and transcribed from YouTube quiz videos. QUENCH possesses masked entities and rationales for the LLMs... | {
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2412.11764 | What Matters in Learning A Zero-Shot Sim-to-Real RL Policy for Quadrotor
Control? A Comprehensive Study | [
"cs.RO",
"cs.LG"
] | Executing precise and agile flight maneuvers is critical for quadrotors in various applications. Traditional quadrotor control approaches are limited by their reliance on flat trajectories or time-consuming optimization, which restricts their flexibility. Recently, RL-based policy has emerged as a promising alternative... | {
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2412.11766 | Interplay of epidemic spreading and vaccine uptake under complex social
contagion | [
"physics.soc-ph",
"cs.SI"
] | Modeling human behavior is essential to accurately predict epidemic spread, with behaviors like vaccine hesitancy complicating control efforts. While epidemic spread is often treated as a simple contagion, vaccine uptake may follow complex contagion dynamics, where individuals' decisions depend on multiple social conta... | {
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2412.11767 | IDEA-Bench: How Far are Generative Models from Professional Designing? | [
"cs.CV"
] | Real-world design tasks - such as picture book creation, film storyboard development using character sets, photo retouching, visual effects, and font transfer - are highly diverse and complex, requiring deep interpretation and extraction of various elements from instructions, descriptions, and reference images. The res... | {
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2412.11768 | No More Adam: Learning Rate Scaling at Initialization is All You Need | [
"cs.LG",
"cs.AI"
] | In this work, we question the necessity of adaptive gradient methods for training deep neural networks. SGD-SaI is a simple yet effective enhancement to stochastic gradient descent with momentum (SGDM). SGD-SaI performs learning rate Scaling at Initialization (SaI) to distinct parameter groups, guided by their respecti... | {
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2412.11769 | Does it Chug? Towards a Data-Driven Understanding of Guitar Tone
Description | [
"cs.SD",
"cs.AI",
"eess.AS"
] | Natural language is commonly used to describe instrument timbre, such as a "warm" or "heavy" sound. As these descriptors are based on human perception, there can be disagreement over which acoustic features correspond to a given adjective. In this work, we pursue a data-driven approach to further our understanding of s... | {
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2412.11771 | Point Cloud-Assisted Neural Image Compression | [
"eess.IV",
"cs.CV"
] | High-efficient image compression is a critical requirement. In several scenarios where multiple modalities of data are captured by different sensors, the auxiliary information from other modalities are not fully leveraged by existing image-only codecs, leading to suboptimal compression efficiency. In this paper, we inc... | {
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2412.11777 | Fast and Slow Gradient Approximation for Binary Neural Network
Optimization | [
"cs.LG"
] | Binary Neural Networks (BNNs) have garnered significant attention due to their immense potential for deployment on edge devices. However, the non-differentiability of the quantization function poses a challenge for the optimization of BNNs, as its derivative cannot be backpropagated. To address this issue, hypernetwork... | {
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2412.11779 | Impact of Face Alignment on Face Image Quality | [
"cs.CV"
] | Face alignment is a crucial step in preparing face images for feature extraction in facial analysis tasks. For applications such as face recognition, facial expression recognition, and facial attribute classification, alignment is widely utilized during both training and inference to standardize the positions of key la... | {
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2412.11785 | InterDyn: Controllable Interactive Dynamics with Video Diffusion Models | [
"cs.CV"
] | Predicting the dynamics of interacting objects is essential for both humans and intelligent systems. However, existing approaches are limited to simplified, toy settings and lack generalizability to complex, real-world environments. Recent advances in generative models have enabled the prediction of state transitions b... | {
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2412.11787 | A Method for Detecting Legal Article Competition for Korean Criminal Law
Using a Case-augmented Mention Graph | [
"cs.CL",
"cs.AI",
"cs.IR",
"cs.LG"
] | As social systems become increasingly complex, legal articles are also growing more intricate, making it progressively harder for humans to identify any potential competitions among them, particularly when drafting new laws or applying existing laws. Despite this challenge, no method for detecting such competitions has... | {
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2412.11788 | Neural Collapse Inspired Knowledge Distillation | [
"cs.CV"
] | Existing knowledge distillation (KD) methods have demonstrated their ability in achieving student network performance on par with their teachers. However, the knowledge gap between the teacher and student remains significant and may hinder the effectiveness of the distillation process. In this work, we introduce the st... | {
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2412.11795 | ProsodyFM: Unsupervised Phrasing and Intonation Control for Intelligible
Speech Synthesis | [
"cs.CL",
"cs.SD",
"eess.AS"
] | Prosody contains rich information beyond the literal meaning of words, which is crucial for the intelligibility of speech. Current models still fall short in phrasing and intonation; they not only miss or misplace breaks when synthesizing long sentences with complex structures but also produce unnatural intonation. We ... | {
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2412.11799 | Adaptive Manipulation for Coalitions in Knockout Tournaments | [
"cs.DS",
"cs.GT",
"cs.MA"
] | Knockout tournaments, also known as single-elimination or cup tournaments, are a popular form of sports competitions. In the standard probabilistic setting, for each pairing of players, one of the players wins the game with a certain (a priori known) probability. Due to their competitive nature, tournaments are prone t... | {
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2412.11800 | Scalable Temporal Anomaly Causality Discovery in Large Systems:
Achieving Computational Efficiency with Binary Anomaly Flag Data | [
"cs.LG",
"stat.ML"
] | Extracting anomaly causality facilitates diagnostics once monitoring systems detect system faults. Identifying anomaly causes in large systems involves investigating a more extensive set of monitoring variables across multiple subsystems. However, learning causal graphs comes with a significant computational burden tha... | {
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2412.11802 | AMI-Net: Adaptive Mask Inpainting Network for Industrial Anomaly
Detection and Localization | [
"cs.CV",
"cs.AI"
] | Unsupervised visual anomaly detection is crucial for enhancing industrial production quality and efficiency. Among unsupervised methods, reconstruction approaches are popular due to their simplicity and effectiveness. The key aspect of reconstruction methods lies in the restoration of anomalous regions, which current m... | {
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2412.11803 | UAlign: Leveraging Uncertainty Estimations for Factuality Alignment on
Large Language Models | [
"cs.CL"
] | Despite demonstrating impressive capabilities, Large Language Models (LLMs) still often struggle to accurately express the factual knowledge they possess, especially in cases where the LLMs' knowledge boundaries are ambiguous. To improve LLMs' factual expressions, we propose the UAlign framework, which leverages Uncert... | {
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2412.11804 | A Long-Duration Autonomy Approach to Connected and Automated Vehicles | [
"eess.SY",
"cs.RO",
"cs.SY"
] | In this article, we present a long-duration autonomy approach for the control of connected and automated vehicles (CAVs) operating in a transportation network. In particular, we focus on the performance of CAVs at traffic bottlenecks, including roundabouts, merging roadways, and intersections. We take a principled appr... | {
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2412.11807 | PhysAug: A Physical-guided and Frequency-based Data Augmentation for
Single-Domain Generalized Object Detection | [
"cs.CV",
"cs.AI"
] | Single-Domain Generalized Object Detection~(S-DGOD) aims to train on a single source domain for robust performance across a variety of unseen target domains by taking advantage of an object detector. Existing S-DGOD approaches often rely on data augmentation strategies, including a composition of visual transformations... | {
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} |
2412.11810 | Optimal Gradient Checkpointing for Sparse and Recurrent Architectures
using Off-Chip Memory | [
"cs.NE",
"cs.AR",
"cs.LG"
] | Recurrent neural networks (RNNs) are valued for their computational efficiency and reduced memory requirements on tasks involving long sequence lengths but require high memory-processor bandwidth to train. Checkpointing techniques can reduce the memory requirements by only storing a subset of intermediate states, the c... | {
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} |
2412.11812 | CLDA-YOLO: Visual Contrastive Learning Based Domain Adaptive YOLO
Detector | [
"cs.CV"
] | Unsupervised domain adaptive (UDA) algorithms can markedly enhance the performance of object detectors under conditions of domain shifts, thereby reducing the necessity for extensive labeling and retraining. Current domain adaptive object detection algorithms primarily cater to two-stage detectors, which tend to offer ... | {
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} |
2412.11813 | Designing Semi-Structured Pruning of Graph Convolutional Networks for
Skeleton-based Recognition | [
"cs.CV"
] | Deep neural networks (DNNs) are nowadays witnessing a major success in solving many pattern recognition tasks including skeleton-based classification. The deployment of DNNs on edge-devices, endowed with limited time and memory resources, requires designing lightweight and efficient variants of these networks. Pruning ... | {
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} |
2412.11814 | EventSum: A Large-Scale Event-Centric Summarization Dataset for Chinese
Multi-News Documents | [
"cs.CL"
] | In real life, many dynamic events, such as major disasters and large-scale sports events, evolve continuously over time. Obtaining an overview of these events can help people quickly understand the situation and respond more effectively. This is challenging because the key information of the event is often scattered ac... | {
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2412.11815 | ColorFlow: Retrieval-Augmented Image Sequence Colorization | [
"cs.CV"
] | Automatic black-and-white image sequence colorization while preserving character and object identity (ID) is a complex task with significant market demand, such as in cartoon or comic series colorization. Despite advancements in visual colorization using large-scale generative models like diffusion models, challenges w... | {
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} |
2412.11818 | Leveraging User-Generated Metadata of Online Videos for Cover Song
Identification | [
"cs.MM",
"cs.IR"
] | YouTube is a rich source of cover songs. Since the platform itself is organized in terms of videos rather than songs, the retrieval of covers is not trivial. The field of cover song identification addresses this problem and provides approaches that usually rely on audio content. However, including the user-generated vi... | {
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} |
2412.11819 | HiGDA: Hierarchical Graph of Nodes to Learn Local-to-Global Topology for
Semi-Supervised Domain Adaptation | [
"cs.CV"
] | The enhanced representational power and broad applicability of deep learning models have attracted significant interest from the research community in recent years. However, these models often struggle to perform effectively under domain shift conditions, where the training data (the source domain) is related to but ex... | {
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} |
2412.11820 | Spatiotemporal Blind-Spot Network with Calibrated Flow Alignment for
Self-Supervised Video Denoising | [
"cs.CV"
] | Self-supervised video denoising aims to remove noise from videos without relying on ground truth data, leveraging the video itself to recover clean frames. Existing methods often rely on simplistic feature stacking or apply optical flow without thorough analysis. This results in suboptimal utilization of both inter-fra... | {
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} |
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