id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.12733 | EventFull: Complete and Consistent Event Relation Annotation | [
"cs.CL"
] | Event relation detection is a fundamental NLP task, leveraged in many downstream applications, whose modeling requires datasets annotated with event relations of various types. However, systematic and complete annotation of these relations is costly and challenging, due to the quadratic number of event pairs that need ... | {
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2412.12734 | Gaussian Billboards: Expressive 2D Gaussian Splatting with Textures | [
"cs.CV",
"cs.GR"
] | Gaussian Splatting has recently emerged as the go-to representation for reconstructing and rendering 3D scenes. The transition from 3D to 2D Gaussian primitives has further improved multi-view consistency and surface reconstruction accuracy. In this work we highlight the similarity between 2D Gaussian Splatting (2DGS) ... | {
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2412.12735 | GIRAFFE: Design Choices for Extending the Context Length of Visual
Language Models | [
"cs.CV",
"cs.AI",
"cs.CL"
] | Visual Language Models (VLMs) demonstrate impressive capabilities in processing multimodal inputs, yet applications such as visual agents, which require handling multiple images and high-resolution videos, demand enhanced long-range modeling. Moreover, existing open-source VLMs lack systematic exploration into extendin... | {
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2412.12737 | PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything
Model | [
"cs.CV"
] | PolSAR data presents unique challenges due to its rich and complex characteristics. Existing data representations, such as complex-valued data, polarimetric features, and amplitude images, are widely used. However, these formats often face issues related to usability, interpretability, and data integrity. Most feature ... | {
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2412.12739 | Deep Learning for Resilient Adversarial Decision Fusion in Byzantine
Networks | [
"cs.LG",
"cs.CR",
"cs.MA",
"cs.SI"
] | This paper introduces a deep learning-based framework for resilient decision fusion in adversarial multi-sensor networks, providing a unified mathematical setup that encompasses diverse scenarios, including varying Byzantine node proportions, synchronized and unsynchronized attacks, unbalanced priors, adaptive strategi... | {
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2412.12740 | Open-World Panoptic Segmentation | [
"cs.CV",
"cs.RO"
] | Perception is a key building block of autonomously acting vision systems such as autonomous vehicles. It is crucial that these systems are able to understand their surroundings in order to operate safely and robustly. Additionally, autonomous systems deployed in unconstrained real-world scenarios must be able of dealin... | {
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2412.12742 | Subspace Implicit Neural Representations for Real-Time Cardiac Cine MR
Imaging | [
"eess.IV",
"cs.AI",
"cs.LG"
] | Conventional cardiac cine MRI methods rely on retrospective gating, which limits temporal resolution and the ability to capture continuous cardiac dynamics, particularly in patients with arrhythmias and beat-to-beat variations. To address these challenges, we propose a reconstruction framework based on subspace implici... | {
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2412.12743 | Training a Distributed Acoustic Sensing Traffic Monitoring Network With
Video Inputs | [
"physics.geo-ph",
"cs.CV",
"cs.LG",
"eess.SP",
"physics.optics"
] | Distributed Acoustic Sensing (DAS) has emerged as a promising tool for real-time traffic monitoring in densely populated areas. In this paper, we present a novel concept that integrates DAS data with co-located visual information. We use YOLO-derived vehicle location and classification from camera inputs as labeled dat... | {
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2412.12744 | Your Next State-of-the-Art Could Come from Another Domain: A
Cross-Domain Analysis of Hierarchical Text Classification | [
"cs.CL",
"cs.AI",
"cs.LG"
] | Text classification with hierarchical labels is a prevalent and challenging task in natural language processing. Examples include assigning ICD codes to patient records, tagging patents into IPC classes, assigning EUROVOC descriptors to European legal texts, and more. Despite its widespread applications, a comprehensiv... | {
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2412.12749 | Safe Trajectory Sets for Online Operation of Power Systems under
Uncertainty | [
"eess.SY",
"cs.SY"
] | Flexibility provision from active distribution grids requires efficient and robust methods of optimization and control suitable to online operation. In this paper we introduce conditions for the safe operation of feedback optimization based controllers. We use the feasible operating region of a controlled system as bou... | {
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2412.12754 | Token-Level Graphs for Short Text Classification | [
"cs.IR"
] | The classification of short texts is a common subtask in Information Retrieval (IR). Recent advances in graph machine learning have led to interest in graph-based approaches for low resource scenarios, showing promise in such settings. However, existing methods face limitations such as not accounting for different mean... | {
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2412.12755 | Progressive Monitoring of Generative Model Training Evolution | [
"cs.LG",
"cs.CV"
] | While deep generative models (DGMs) have gained popularity, their susceptibility to biases and other inefficiencies that lead to undesirable outcomes remains an issue. With their growing complexity, there is a critical need for early detection of issues to achieve desired results and optimize resources. Hence, we intro... | {
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2412.12759 | Versatile Ordering Network: An Attention-based Neural Network for
Ordering Across Scales and Quality Metrics | [
"cs.LG"
] | Ordering has been extensively studied in many visualization applications, such as axis and matrix reordering, for the simple reason that the order will greatly impact the perceived pattern of data. Many quality metrics concerning data pattern, perception, and aesthetics are proposed, and respective optimization algorit... | {
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2412.12761 | Revealing the impact of synthetic native samples and multi-tasking
strategies in Hindi-English code-mixed humour and sarcasm detection | [
"cs.CL",
"cs.AI"
] | In this paper, we reported our experiments with various strategies to improve code-mixed humour and sarcasm detection. We did all of our experiments for Hindi-English code-mixed scenario, as we have the linguistic expertise for the same. We experimented with three approaches, namely (i) native sample mixing, (ii) multi... | {
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2412.12765 | Monocular Facial Appearance Capture in the Wild | [
"cs.CV",
"cs.GR"
] | We present a new method for reconstructing the appearance properties of human faces from a lightweight capture procedure in an unconstrained environment. Our method recovers the surface geometry, diffuse albedo, specular intensity and specular roughness from a monocular video containing a simple head rotation in-the-wi... | {
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2412.12766 | Towards a Training Free Approach for 3D Scene Editing | [
"cs.CV"
] | Text driven diffusion models have shown remarkable capabilities in editing images. However, when editing 3D scenes, existing works mostly rely on training a NeRF for 3D editing. Recent NeRF editing methods leverages edit operations by deploying 2D diffusion models and project these edits into 3D space. They require str... | {
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2412.12767 | A Survey of Calibration Process for Black-Box LLMs | [
"cs.AI",
"cs.CL"
] | Large Language Models (LLMs) demonstrate remarkable performance in semantic understanding and generation, yet accurately assessing their output reliability remains a significant challenge. While numerous studies have explored calibration techniques, they primarily focus on White-Box LLMs with accessible parameters. Bla... | {
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2412.12770 | A Survey on Sequential Recommendation | [
"cs.IR"
] | Different from most conventional recommendation problems, sequential recommendation focuses on learning users' preferences by exploiting the internal order and dependency among the interacted items, which has received significant attention from both researchers and practitioners. In recent years, we have witnessed grea... | {
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2412.12771 | Guided and Variance-Corrected Fusion with One-shot Style Alignment for
Large-Content Image Generation | [
"cs.CV",
"cs.AI"
] | Producing large images using small diffusion models is gaining increasing popularity, as the cost of training large models could be prohibitive. A common approach involves jointly generating a series of overlapped image patches and obtaining large images by merging adjacent patches. However, results from existing metho... | {
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2412.12772 | Optimize the Unseen -- Fast NeRF Cleanup with Free Space Prior | [
"cs.CV"
] | Neural Radiance Fields (NeRF) have advanced photorealistic novel view synthesis, but their reliance on photometric reconstruction introduces artifacts, commonly known as "floaters". These artifacts degrade novel view quality, especially in areas unseen by the training cameras. We present a fast, post-hoc NeRF cleanup m... | {
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2412.12774 | A Framework for Critical Evaluation of Text-to-Image Models: Integrating
Art Historical Analysis, Artistic Exploration, and Critical Prompt
Engineering | [
"cs.CV",
"cs.CY"
] | This paper proposes a novel interdisciplinary framework for the critical evaluation of text-to-image models, addressing the limitations of current technical metrics and bias studies. By integrating art historical analysis, artistic exploration, and critical prompt engineering, the framework offers a more nuanced unders... | {
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2412.12775 | RemoteRAG: A Privacy-Preserving LLM Cloud RAG Service | [
"cs.IR",
"cs.CR"
] | Retrieval-augmented generation (RAG) improves the service quality of large language models by retrieving relevant documents from credible literature and integrating them into the context of the user query. Recently, the rise of the cloud RAG service has made it possible for users to query relevant documents convenientl... | {
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2412.12776 | Physical simulation of Marsupial UAV-UGV Systems Connected by a Hanging
Tether using Gazebo | [
"cs.RO"
] | This paper presents a ROS 2-based simulator framework for tethered UAV-UGV marsupial systems in Gazebo. The framework models interactions among a UAV, a UGV, and a winch with dynamically adjustable length and slack of the tether. It supports both manual control and automated trajectory tracking, with the winch adjustin... | {
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2412.12778 | Rethinking Diffusion-Based Image Generators for Fundus Fluorescein
Angiography Synthesis on Limited Data | [
"cs.CV",
"cs.AI"
] | Fundus imaging is a critical tool in ophthalmology, with different imaging modalities offering unique advantages. For instance, fundus fluorescein angiography (FFA) can accurately identify eye diseases. However, traditional invasive FFA involves the injection of sodium fluorescein, which can cause discomfort and risks.... | {
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2412.12779 | A Two-Phase Flow Solver with Variable Liquid Compressibility and
Temperature Equation for Partitioned Simulation of Elastohydrodynamic
Lubrication | [
"cs.CE"
] | This paper presents a new solver developed in OpenFOAM for the modeling of lubricant in the narrow gap between two surfaces inducing hydrodynamic pressures up to few gigapascal. Cavitation is modeled using the homogeneous equilibrium model. The mechanical and thermodynamic constitutive behavior of the lubricant is accu... | {
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2412.12781 | Predicting change in time production -- A machine learning approach to
time perception | [
"cs.HC",
"cs.AI",
"cs.LG"
] | Time perception research has advanced significantly over the years. However, some areas remain largely unexplored. This study addresses two such under-explored areas in timing research: (1) A quantitative analysis of time perception at an individual level, and (2) Time perception in an ecological setting. In this conte... | {
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2412.12782 | Bidirectional Logits Tree: Pursuing Granularity Reconcilement in
Fine-Grained Classification | [
"cs.CV"
] | This paper addresses the challenge of Granularity Competition in fine-grained classification tasks, which arises due to the semantic gap between multi-granularity labels. Existing approaches typically develop independent hierarchy-aware models based on shared features extracted from a common base encoder. However, beca... | {
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2412.12783 | Noise-based Local Learning using Stochastic Magnetic Tunnel Junctions | [
"cs.ET",
"cond-mat.mes-hall",
"cs.LG"
] | Brain-inspired learning in physical hardware has enormous potential to learn fast at minimal energy expenditure. One of the characteristics of biological learning systems is their ability to learn in the presence of various noise sources. Inspired by this observation, we introduce a novel noise-based learning approach ... | {
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2412.12785 | Activating Distributed Visual Region within LLMs for Efficient and
Effective Vision-Language Training and Inference | [
"cs.CV"
] | Large Vision-Language Models (LVLMs) typically learn visual capacity through visual instruction tuning, involving updates to both a projector and their LLM backbones. Drawing inspiration from the concept of visual region in the human brain, we investigate the existence of an analogous \textit{visual region} within LLMs... | {
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2412.12788 | RA-SGG: Retrieval-Augmented Scene Graph Generation Framework via
Multi-Prototype Learning | [
"cs.CV"
] | Scene Graph Generation (SGG) research has suffered from two fundamental challenges: the long-tailed predicate distribution and semantic ambiguity between predicates. These challenges lead to a bias towards head predicates in SGG models, favoring dominant general predicates while overlooking fine-grained predicates. In ... | {
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2412.12789 | 2D-AoI: Age-of-Information of Distributed Sensors for Spatio-Temporal
Processes | [
"cs.NI",
"cs.IT",
"cs.PF",
"math.IT"
] | The freshness of sensor data is critical for all types of cyber-physical systems. An established measure for quantifying data freshness is the Age-of-Information (AoI), which has been the subject of extensive research. Recently, there has been increased interest in multi-sensor systems: redundant sensors producing samp... | {
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2412.12790 | Structural Cellular Hash Chemistry | [
"q-bio.PE",
"cs.NE",
"nlin.AO"
] | Hash Chemistry, a minimalistic artificial chemistry model of open-ended evolution, has recently been extended to non-spatial and cellular versions. The non-spatial version successfully demonstrated continuous adaptation and unbounded growth of complexity of self-replicating entities, but it did not simulate multiscale ... | {
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2412.12791 | Implicit Location-Caption Alignment via Complementary Masking for
Weakly-Supervised Dense Video Captioning | [
"cs.CV",
"cs.AI",
"cs.MM"
] | Weakly-Supervised Dense Video Captioning (WSDVC) aims to localize and describe all events of interest in a video without requiring annotations of event boundaries. This setting poses a great challenge in accurately locating the temporal location of event, as the relevant supervision is unavailable. Existing methods rel... | {
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2412.12793 | CRoF: CLIP-based Robust Few-shot Learning on Noisy Labels | [
"cs.CV"
] | Noisy labels threaten the robustness of few-shot learning (FSL) due to the inexact features in a new domain. CLIP, a large-scale vision-language model, performs well in FSL on image-text embedding similarities, but it is susceptible to misclassification caused by noisy labels. How to enhance domain generalization of CL... | {
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2412.12797 | Is it the end of (generative) linguistics as we know it? | [
"cs.CL"
] | A significant debate has emerged in response to a paper written by Steven Piantadosi (Piantadosi, 2023) and uploaded to the LingBuzz platform, the open archive for generative linguistics. Piantadosi's dismissal of Chomsky's approach is ruthless, but generative linguists deserve it. In this paper, I will adopt three ide... | {
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2412.12798 | ZoRI: Towards Discriminative Zero-Shot Remote Sensing Instance
Segmentation | [
"cs.CV"
] | Instance segmentation algorithms in remote sensing are typically based on conventional methods, limiting their application to seen scenarios and closed-set predictions. In this work, we propose a novel task called zero-shot remote sensing instance segmentation, aimed at identifying aerial objects that are absent from t... | {
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2412.12799 | RCTrans: Radar-Camera Transformer via Radar Densifier and Sequential
Decoder for 3D Object Detection | [
"cs.CV",
"cs.AI"
] | In radar-camera 3D object detection, the radar point clouds are sparse and noisy, which causes difficulties in fusing camera and radar modalities. To solve this, we introduce a novel query-based detection method named Radar-Camera Transformer (RCTrans). Specifically, we first design a Radar Dense Encoder to enrich the ... | {
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2412.12800 | Breaking the Programming Language Barrier: Multilingual Prompting to
Empower Non-Native English Learners | [
"cs.CY",
"cs.AI",
"cs.HC"
] | Non-native English speakers (NNES) face multiple barriers to learning programming. These barriers can be obvious, such as the fact that programming language syntax and instruction are often in English, or more subtle, such as being afraid to ask for help in a classroom full of native English speakers. However, these ba... | {
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2412.12801 | Multi-View Incremental Learning with Structured Hebbian Plasticity for
Enhanced Fusion Efficiency | [
"cs.CV",
"cs.LG"
] | The rapid evolution of multimedia technology has revolutionized human perception, paving the way for multi-view learning. However, traditional multi-view learning approaches are tailored for scenarios with fixed data views, falling short of emulating the intricate cognitive procedures of the human brain processing sign... | {
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2412.12806 | Cross-Dialect Information Retrieval: Information Access in Low-Resource
and High-Variance Languages | [
"cs.CL",
"cs.IR"
] | A large amount of local and culture-specific knowledge (e.g., people, traditions, food) can only be found in documents written in dialects. While there has been extensive research conducted on cross-lingual information retrieval (CLIR), the field of cross-dialect retrieval (CDIR) has received limited attention. Dialect... | {
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2412.12807 | Ask for More Than Bayes Optimal: A Theory of Indecisions for
Classification | [
"math.ST",
"cs.LG",
"stat.ME",
"stat.ML",
"stat.TH"
] | Selective classification frameworks are useful tools for automated decision making in highly risky scenarios, since they allow for a classifier to only make highly confident decisions, while abstaining from making a decision when it is not confident enough to do so, which is otherwise known as an indecision. For a give... | {
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2412.12808 | Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning | [
"cs.CL",
"cs.AI"
] | This paper focuses on sarcasm detection, which aims to identify whether given statements convey criticism, mockery, or other negative sentiment opposite to the literal meaning. To detect sarcasm, humans often require a comprehensive understanding of the semantics in the statement and even resort to external commonsense... | {
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2412.12821 | ComprehendEdit: A Comprehensive Dataset and Evaluation Framework for
Multimodal Knowledge Editing | [
"cs.CV"
] | Large multimodal language models (MLLMs) have revolutionized natural language processing and visual understanding, but often contain outdated or inaccurate information. Current multimodal knowledge editing evaluations are limited in scope and potentially biased, focusing on narrow tasks and failing to assess the impact... | {
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2412.12825 | Enhancing Exploration Efficiency using Uncertainty-Aware Information
Prediction | [
"cs.RO"
] | Autonomous exploration is a crucial aspect of robotics, enabling robots to explore unknown environments and generate maps without prior knowledge. This paper proposes a method to enhance exploration efficiency by integrating neural network-based occupancy grid map prediction with uncertainty-aware Bayesian neural netwo... | {
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2412.12827 | TabSniper: Towards Accurate Table Detection & Structure Recognition for
Bank Statements | [
"cs.CV"
] | Extraction of transaction information from bank statements is required to assess one's financial well-being for credit rating and underwriting decisions. Unlike other financial documents such as tax forms or financial statements, extracting the transaction descriptions from bank statements can provide a comprehensive a... | {
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2412.12829 | 2by2: Weakly-Supervised Learning for Global Action Segmentation | [
"cs.CV"
] | This paper presents a simple yet effective approach for the poorly investigated task of global action segmentation, aiming at grouping frames capturing the same action across videos of different activities. Unlike the case of videos depicting all the same activity, the temporal order of actions is not roughly shared am... | {
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2412.12830 | Differential Alignment for Domain Adaptive Object Detection | [
"cs.CV"
] | Domain adaptive object detection (DAOD) aims to generalize an object detector trained on labeled source-domain data to a target domain without annotations, the core principle of which is \emph{source-target feature alignment}. Typically, existing approaches employ adversarial learning to align the distributions of the ... | {
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2412.12832 | DSGram: Dynamic Weighting Sub-Metrics for Grammatical Error Correction
in the Era of Large Language Models | [
"cs.CL",
"cs.AI"
] | Evaluating the performance of Grammatical Error Correction (GEC) models has become increasingly challenging, as large language model (LLM)-based GEC systems often produce corrections that diverge from provided gold references. This discrepancy undermines the reliability of traditional reference-based evaluation metrics... | {
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2412.12833 | FocusChat: Text-guided Long Video Understanding via Spatiotemporal
Information Filtering | [
"cs.CV"
] | Recently, multi-modal large language models have made significant progress. However, visual information lacking of guidance from the user's intention may lead to redundant computation and involve unnecessary visual noise, especially in long, untrimmed videos. To address this issue, we propose FocusChat, a text-guided m... | {
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2412.12834 | Comparative Analysis of Zero-Shot Capability of Time-Series Foundation
Models in Short-Term Load Prediction | [
"eess.SY",
"cs.SY"
] | Short-term load prediction (STLP) is critical for modern power distribution system operations, particularly as demand and generation uncertainties grow with the integration of low-carbon technologies, such as electric vehicles and photovoltaics. In this study, we evaluate the zero-shot prediction capabilities of five T... | {
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2412.12836 | A Survey on Recommendation Unlearning: Fundamentals, Taxonomy,
Evaluation, and Open Questions | [
"cs.IR",
"cs.AI"
] | Recommender systems have become increasingly influential in shaping user behavior and decision-making, highlighting their growing impact in various domains. Meanwhile, the widespread adoption of machine learning models in recommender systems has raised significant concerns regarding user privacy and security. As compli... | {
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2412.12837 | Scrutinizing the Vulnerability of Decentralized Learning to Membership
Inference Attacks | [
"cs.LG",
"cs.DC"
] | The primary promise of decentralized learning is to allow users to engage in the training of machine learning models in a collaborative manner while keeping their data on their premises and without relying on any central entity. However, this paradigm necessitates the exchange of model parameters or gradients between p... | {
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2412.12839 | From An LLM Swarm To A PDDL-Empowered HIVE: Planning Self-Executed
Instructions In A Multi-Modal Jungle | [
"cs.AI"
] | In response to the call for agent-based solutions that leverage the ever-increasing capabilities of the deep models' ecosystem, we introduce Hive -- a comprehensive solution for selecting appropriate models and subsequently planning a set of atomic actions to satisfy the end-users' instructions. Hive operates over sets... | {
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2412.12841 | Benchmarking and Understanding Compositional Relational Reasoning of
LLMs | [
"cs.CL",
"cs.LG"
] | Compositional relational reasoning (CRR) is a hallmark of human intelligence, but we lack a clear understanding of whether and how existing transformer large language models (LLMs) can solve CRR tasks. To enable systematic exploration of the CRR capability of LLMs, we first propose a new synthetic benchmark called Gene... | {
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2412.12843 | Efficient Event-based Semantic Segmentation with Spike-driven
Lightweight Transformer-based Networks | [
"cs.CV",
"cs.AI"
] | Event-based semantic segmentation has great potential in autonomous driving and robotics due to the advantages of event cameras, such as high dynamic range, low latency, and low power cost. Unfortunately, current artificial neural network (ANN)-based segmentation methods suffer from high computational demands, the requ... | {
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2412.12844 | Concurrent vertical and horizontal federated learning with fuzzy
cognitive maps | [
"cs.LG"
] | Data privacy is a major concern in industries such as healthcare or finance. The requirement to safeguard privacy is essential to prevent data breaches and misuse, which can have severe consequences for individuals and organisations. Federated learning is a distributed machine learning approach where multiple participa... | {
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2412.12845 | Efficient damage simulations under material uncertainties in a
weakly-intrusive implementation | [
"cs.CE"
] | Uncertainty quantification is not yet widely adapted in the design process of engineering components despite its importance for achieving sustainable and resource-efficient structures. This is mainly due to two reasons: 1) Tracing the effect of uncertainty in engineering simulations is a computationally challenging tas... | {
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2412.12848 | ClarityEthic: Explainable Moral Judgment Utilizing Contrastive Ethical
Insights from Large Language Models | [
"cs.CY",
"cs.AI",
"cs.SI"
] | With the rise and widespread use of Large Language Models (LLMs), ensuring their safety is crucial to prevent harm to humans and promote ethical behaviors. However, directly assessing value valence (i.e., support or oppose) by leveraging large-scale data training is untrustworthy and inexplainable. We assume that emula... | {
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2412.12849 | HyperGS: Hyperspectral 3D Gaussian Splatting | [
"cs.CV"
] | We introduce HyperGS, a novel framework for Hyperspectral Novel View Synthesis (HNVS), based on a new latent 3D Gaussian Splatting (3DGS) technique. Our approach enables simultaneous spatial and spectral renderings by encoding material properties from multi-view 3D hyperspectral datasets. HyperGS reconstructs high-fide... | {
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2412.12850 | Boosting Fine-Grained Visual Anomaly Detection with
Coarse-Knowledge-Aware Adversarial Learning | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Many unsupervised visual anomaly detection methods train an auto-encoder to reconstruct normal samples and then leverage the reconstruction error map to detect and localize the anomalies. However, due to the powerful modeling and generalization ability of neural networks, some anomalies can also be well reconstructed, ... | {
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2412.12852 | Selective Shot Learning for Code Explanation | [
"cs.SE",
"cs.CL",
"cs.IR"
] | Code explanation plays a crucial role in the software engineering domain, aiding developers in grasping code functionality efficiently. Recent work shows that the performance of LLMs for code explanation improves in a few-shot setting, especially when the few-shot examples are selected intelligently. State-of-the-art a... | {
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2412.12853 | Automatic Left Ventricular Cavity Segmentation via Deep Spatial
Sequential Network in 4D Computed Tomography Studies | [
"eess.IV",
"cs.CV"
] | Automated segmentation of left ventricular cavity (LVC) in temporal cardiac image sequences (multiple time points) is a fundamental requirement for quantitative analysis of its structural and functional changes. Deep learning based methods for the segmentation of LVC are the state of the art; however, these methods are... | {
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2412.12856 | Diffusion backbone of temporal higher-order networks | [
"physics.soc-ph",
"cs.SI"
] | Temporal higher-order networks, where each hyperlink involving a group of nodes are activated or deactivated over time, are recently used to represent complex systems such as social contacts, interactions or collaborations that occur at specific times. Such networks are substrates for social contagion processes like th... | {
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2412.12858 | Efficient Speech Command Recognition Leveraging Spiking Neural Network
and Curriculum Learning-based Knowledge Distillation | [
"cs.LG",
"cs.AI",
"cs.HC"
] | The intrinsic dynamics and event-driven nature of spiking neural networks (SNNs) make them excel in processing temporal information by naturally utilizing embedded time sequences as time steps. Recent studies adopting this approach have demonstrated SNNs' effectiveness in speech command recognition, achieving high perf... | {
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2412.12859 | Bayesian Persuasion with Externalities: Exploiting Agent Types | [
"cs.AI",
"cs.GT"
] | We study a Bayesian persuasion problem with externalities. In this model, a principal sends signals to inform multiple agents about the state of the world. Simultaneously, due to the existence of externalities in the agents' utilities, the principal also acts as a correlation device to correlate the agents' actions. We... | {
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2412.12861 | Dyn-HaMR: Recovering 4D Interacting Hand Motion from a Dynamic Camera | [
"cs.CV"
] | We propose Dyn-HaMR, to the best of our knowledge, the first approach to reconstruct 4D global hand motion from monocular videos recorded by dynamic cameras in the wild. Reconstructing accurate 3D hand meshes from monocular videos is a crucial task for understanding human behaviour, with significant applications in aug... | {
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2412.12863 | DISC: Plug-and-Play Decoding Intervention with Similarity of Characters
for Chinese Spelling Check | [
"cs.CL",
"cs.AI"
] | One key characteristic of the Chinese spelling check (CSC) task is that incorrect characters are usually similar to the correct ones in either phonetics or glyph. To accommodate this, previous works usually leverage confusion sets, which suffer from two problems, i.e., difficulty in determining which character pairs to... | {
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2412.12864 | Geodesic Flow Kernels for Semi-Supervised Learning on Mixed-Variable
Tabular Dataset | [
"cs.LG"
] | Tabular data poses unique challenges due to its heterogeneous nature, combining both continuous and categorical variables. Existing approaches often struggle to effectively capture the underlying structure and relationships within such data. We propose GFTab (Geodesic Flow Kernels for Semi- Supervised Learning on Mixed... | {
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2412.12865 | Preference-Oriented Supervised Fine-Tuning: Favoring Target Model Over
Aligned Large Language Models | [
"cs.CL"
] | Alignment, endowing a pre-trained Large language model (LLM) with the ability to follow instructions, is crucial for its real-world applications. Conventional supervised fine-tuning (SFT) methods formalize it as causal language modeling typically with a cross-entropy objective, requiring a large amount of high-quality ... | {
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2412.12870 | Towards Physically Interpretable World Models: Meaningful Weakly
Supervised Representations for Visual Trajectory Prediction | [
"cs.LG"
] | Deep learning models are increasingly employed for perception, prediction, and control in complex systems. Embedding physical knowledge into these models is crucial for achieving realistic and consistent outputs, a challenge often addressed by physics-informed machine learning. However, integrating physical knowledge w... | {
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2412.12877 | MIVE: New Design and Benchmark for Multi-Instance Video Editing | [
"cs.CV"
] | Recent AI-based video editing has enabled users to edit videos through simple text prompts, significantly simplifying the editing process. However, recent zero-shot video editing techniques primarily focus on global or single-object edits, which can lead to unintended changes in other parts of the video. When multiple ... | {
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2412.12880 | Towards Effective Graph Rationalization via Boosting Environment
Diversity | [
"cs.LG"
] | Graph Neural Networks (GNNs) perform effectively when training and testing graphs are drawn from the same distribution, but struggle to generalize well in the face of distribution shifts. To address this issue, existing mainstreaming graph rationalization methods first identify rationale and environment subgraphs from ... | {
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2412.12881 | RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented
Verification and Refinement | [
"cs.CL",
"cs.AI"
] | Existing large language models (LLMs) show exceptional problem-solving capabilities but might struggle with complex reasoning tasks. Despite the successes of chain-of-thought and tree-based search methods, they mainly depend on the internal knowledge of LLMs to search over intermediate reasoning steps, limited to deali... | {
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2412.12883 | A Comparative Study of Pruning Methods in Transformer-based Time Series
Forecasting | [
"cs.LG",
"cs.AI"
] | The current landscape in time-series forecasting is dominated by Transformer-based models. Their high parameter count and corresponding demand in computational resources pose a challenge to real-world deployment, especially for commercial and scientific applications with low-power embedded devices. Pruning is an establ... | {
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2412.12886 | TimeCHEAT: A Channel Harmony Strategy for Irregularly Sampled
Multivariate Time Series Analysis | [
"cs.LG"
] | Irregularly sampled multivariate time series (ISMTS) are prevalent in reality. Due to their non-uniform intervals between successive observations and varying sampling rates among series, the channel-independent (CI) strategy, which has been demonstrated more desirable for complete multivariate time series forecasting i... | {
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2412.12887 | Learning Coarse-to-Fine Pruning of Graph Convolutional Networks for
Skeleton-based Recognition | [
"cs.CV"
] | Magnitude Pruning is a staple lightweight network design method which seeks to remove connections with the smallest magnitude. This process is either achieved in a structured or unstructured manner. While structured pruning allows reaching high efficiency, unstructured one is more flexible and leads to better accuracy,... | {
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2412.12888 | ArtAug: Enhancing Text-to-Image Generation through
Synthesis-Understanding Interaction | [
"cs.CV",
"cs.AI"
] | The emergence of diffusion models has significantly advanced image synthesis. The recent studies of model interaction and self-corrective reasoning approach in large language models offer new insights for enhancing text-to-image models. Inspired by these studies, we propose a novel method called ArtAug for enhancing te... | {
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2412.12890 | Suppressing Uncertainty in Gaze Estimation | [
"cs.CV",
"cs.LG"
] | Uncertainty in gaze estimation manifests in two aspects: 1) low-quality images caused by occlusion, blurriness, inconsistent eye movements, or even non-face images; 2) incorrect labels resulting from the misalignment between the labeled and actual gaze points during the annotation process. Allowing these uncertainties ... | {
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2412.12892 | SAUGE: Taming SAM for Uncertainty-Aligned Multi-Granularity Edge
Detection | [
"cs.CV",
"cs.AI"
] | Edge labels are typically at various granularity levels owing to the varying preferences of annotators, thus handling the subjectivity of per-pixel labels has been a focal point for edge detection. Previous methods often employ a simple voting strategy to diminish such label uncertainty or impose a strong assumption of... | {
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2412.12893 | Question: How do Large Language Models perform on the Question Answering
tasks? Answer: | [
"cs.CL"
] | Large Language Models (LLMs) have been showing promising results for various NLP-tasks without the explicit need to be trained for these tasks by using few-shot or zero-shot prompting techniques. A common NLP-task is question-answering (QA). In this study, we propose a comprehensive performance comparison between small... | {
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2412.12894 | Design of Restricted Normalizing Flow towards Arbitrary Stochastic
Policy with Computational Efficiency | [
"cs.RO",
"cs.LG"
] | This paper proposes a new design method for a stochastic control policy using a normalizing flow (NF). In reinforcement learning (RL), the policy is usually modeled as a distribution model with trainable parameters. When this parameterization has less expressiveness, it would fail to acquiring the optimal policy. A mix... | {
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2412.12898 | An Agentic Approach to Automatic Creation of P&ID Diagrams from Natural
Language Descriptions | [
"cs.LG",
"cs.CE",
"cs.CL",
"cs.MA"
] | The Piping and Instrumentation Diagrams (P&IDs) are foundational to the design, construction, and operation of workflows in the engineering and process industries. However, their manual creation is often labor-intensive, error-prone, and lacks robust mechanisms for error detection and correction. While recent advanceme... | {
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2412.12900 | Shift-invariant spaces, bandlimited spaces and reproducing kernel spaces
with shift-invariant kernels on undirected finite graphs | [
"eess.SP",
"cs.IT",
"math.IT"
] | In this paper, we introduce the concept of graph shift-invariant space (GSIS) on an undirected finite graph, which is the linear space of graph signals being invariant under graph shifts, and we study its bandlimiting, kernel reproducing and sampling properties. Graph bandlimited spaces have been widely applied where... | {
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2412.12902 | DoPTA: Improving Document Layout Analysis using Patch-Text Alignment | [
"cs.CV"
] | The advent of multimodal learning has brought a significant improvement in document AI. Documents are now treated as multimodal entities, incorporating both textual and visual information for downstream analysis. However, works in this space are often focused on the textual aspect, using the visual space as auxiliary i... | {
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2412.12906 | CATSplat: Context-Aware Transformer with Spatial Guidance for
Generalizable 3D Gaussian Splatting from A Single-View Image | [
"cs.CV"
] | Recently, generalizable feed-forward methods based on 3D Gaussian Splatting have gained significant attention for their potential to reconstruct 3D scenes using finite resources. These approaches create a 3D radiance field, parameterized by per-pixel 3D Gaussian primitives, from just a few images in a single forward pa... | {
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2412.12909 | PT: A Plain Transformer is Good Hospital Readmission Predictor | [
"cs.LG"
] | Hospital readmission prediction is critical for clinical decision support, aiming to identify patients at risk of returning within 30 days post-discharge. High readmission rates often indicate inadequate treatment or post-discharge care, making effective prediction models essential for optimizing resources and improvin... | {
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2412.12910 | Sequential Harmful Shift Detection Without Labels | [
"stat.ML",
"cs.LG"
] | We introduce a novel approach for detecting distribution shifts that negatively impact the performance of machine learning models in continuous production environments, which requires no access to ground truth data labels. It builds upon the work of Podkopaev and Ramdas [2022], who address scenarios where labels are av... | {
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2412.12912 | Unsupervised Region-Based Image Editing of Denoising Diffusion Models | [
"cs.CV",
"cs.AI"
] | Although diffusion models have achieved remarkable success in the field of image generation, their latent space remains under-explored. Current methods for identifying semantics within latent space often rely on external supervision, such as textual information and segmentation masks. In this paper, we propose a method... | {
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2412.12916 | Graph Spring Neural ODEs for Link Sign Prediction | [
"cs.LG",
"cs.CY"
] | Signed graphs allow for encoding positive and negative relations between nodes and are used to model various online activities. Node representation learning for signed graphs is a well-studied task with important applications such as sign prediction. While the size of datasets is ever-increasing, recent methods often s... | {
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2412.12918 | BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided
Direction Lines and Subspace Embeddings | [
"stat.ML",
"cs.LG"
] | When it comes to expensive black-box optimization problems, Bayesian Optimization (BO) is a well-known and powerful solution. Many real-world applications involve a large number of dimensions, hence scaling BO to high dimension is of much interest. However, state-of-the-art high-dimensional BO methods still suffer from... | {
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2412.12919 | 4DRGS: 4D Radiative Gaussian Splatting for Efficient 3D Vessel
Reconstruction from Sparse-View Dynamic DSA Images | [
"eess.IV",
"cs.CV"
] | Reconstructing 3D vessel structures from sparse-view dynamic digital subtraction angiography (DSA) images enables accurate medical assessment while reducing radiation exposure. Existing methods often produce suboptimal results or require excessive computation time. In this work, we propose 4D radiative Gaussian splatti... | {
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} |
2412.12926 | Prediction-Based Control Barrier Functions for Input-Constrained Safety
Critical Systems | [
"eess.SY",
"cs.SY"
] | Control barrier functions (CBFs) have emerged as a popular topic in safety critical control due to their ability to provide formal safety guarantees for dynamical systems. Despite their powerful capabilities, the determination of feasible CBFs for input-constrained systems is still a formidable task and a challenging r... | {
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} |
2412.12928 | Truthful Text Sanitization Guided by Inference Attacks | [
"cs.CL"
] | The purpose of text sanitization is to rewrite those text spans in a document that may directly or indirectly identify an individual, to ensure they no longer disclose personal information. Text sanitization must strike a balance between preventing the leakage of personal information (privacy protection) while also ret... | {
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} |
2412.12929 | Spectra of Cardinality Queries over Description Logic Knowledge Bases | [
"cs.AI",
"cs.CC",
"cs.LO"
] | Recent works have explored the use of counting queries coupled with Description Logic ontologies. The answer to such a query in a model of a knowledge base is either an integer or $\infty$, and its spectrum is the set of its answers over all models. While it is unclear how to compute and manipulate such a set in genera... | {
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} |
2412.12931 | Multi-Subspace Matrix Recovery from Permuted Data | [
"cs.LG",
"stat.ML"
] | This paper aims to recover a multi-subspace matrix from permuted data: given a matrix, in which the columns are drawn from a union of low-dimensional subspaces and some columns are corrupted by permutations on their entries, recover the original matrix. The task has numerous practical applications such as data cleaning... | {
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} |
2412.12932 | CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large
Vision-Language Models | [
"cs.CV",
"cs.AI"
] | Large Vision-Language Models (LVLMs) have recently demonstrated amazing success in multi-modal tasks, including advancements in Multi-modal Chain-of-Thought (MCoT) reasoning. Despite these successes, current benchmarks still follow a traditional paradigm with multi-modal input and text-modal output, which leads to sign... | {
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} |
2412.12933 | Two Layer Walk: A Community-Aware Graph Embedding | [
"cs.SI",
"cs.AI"
] | Community structures are critical for understanding the mesoscopic organization of networks, bridging local and global patterns. While methods such as DeepWalk and node2vec capture local positional information through random walks, they fail to preserve community structures. Other approaches like modularized nonnegativ... | {
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} |
2412.12936 | A simple DNN regression for the chemical composition in essential oil | [
"cs.LG"
] | Although experimental design and methodological surveys for mono-molecular activity/property has been extensively investigated, those for chemical composition have received little attention, with the exception of a few prior studies. In this study, we configured three simple DNN regressors to predict essential oil prop... | {
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} |
2412.12938 | A Conceptual Model of Intelligent Multimedia Data Rendered using Flying
Light Specks | [
"cs.DB",
"cs.ET",
"cs.MM"
] | A Flying Light Speck, FLS, is a miniature sized drone configured with light sources to illuminate 3D multimedia objects in a fixed volume, an FLS display. A swarm of FLSs may provide haptic interactions by exerting force back at a user's touch. This paper presents a conceptual model for the multimedia data to enable co... | {
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} |
2412.12940 | Improving Fine-grained Visual Understanding in VLMs through Text-Only
Training | [
"cs.CL"
] | Visual-Language Models (VLMs) have become a powerful tool for bridging the gap between visual and linguistic understanding. However, the conventional learning approaches for VLMs often suffer from limitations, such as the high resource requirements of collecting and training image-text paired data. Recent research has ... | {
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} |
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