id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.16592 | Leveraging Contrastive Learning for Semantic Segmentation with
Consistent Labels Across Varying Appearances | [
"cs.CV"
] | This paper introduces a novel synthetic dataset that captures urban scenes under a variety of weather conditions, providing pixel-perfect, ground-truth-aligned images to facilitate effective feature alignment across domains. Additionally, we propose a method for domain adaptation and generalization that takes advantage... | {
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2412.16594 | AIGCodeSet: A New Annotated Dataset for AI Generated Code Detection | [
"cs.SE",
"cs.AI"
] | With the rapid advancement of LLM models, they have become widely useful in various fields. While these AI systems can be used for code generation, significantly simplifying and accelerating the tasks of developers, their use for students to do assignments has raised ethical questions in the field of education. In this... | {
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2412.16599 | Do Multimodal Language Models Really Understand Direction? A Benchmark
for Compass Direction Reasoning | [
"cs.AI"
] | Direction reasoning is essential for intelligent systems to understand the real world. While existing work focuses primarily on spatial reasoning, compass direction reasoning remains underexplored. To address this, we propose the Compass Direction Reasoning (CDR) benchmark, designed to evaluate the direction reasoning ... | {
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2412.16602 | V"Mean"ba: Visual State Space Models only need 1 hidden dimension | [
"cs.CV",
"cs.AI"
] | Vision transformers dominate image processing tasks due to their superior performance. However, the quadratic complexity of self-attention limits the scalability of these systems and their deployment on resource-constrained devices. State Space Models (SSMs) have emerged as a solution by introducing a linear recurrence... | {
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2412.16604 | OmniSplat: Taming Feed-Forward 3D Gaussian Splatting for Omnidirectional
Images with Editable Capabilities | [
"cs.CV"
] | Feed-forward 3D Gaussian Splatting (3DGS) models have gained significant popularity due to their ability to generate scenes immediately without needing per-scene optimization. Although omnidirectional images are getting more popular since they reduce the computation for image stitching to composite a holistic scene, ex... | {
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2412.16609 | Concept Guided Co-saliency Objection Detection | [
"cs.CV"
] | The task of co-saliency object detection (Co-SOD) seeks to identify common, salient objects across a collection of images by examining shared visual features. However, traditional Co-SOD methods often encounter limitations when faced with diverse object variations (e.g., different postures) and irrelevant background el... | {
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2412.16611 | A Tutorial on Non-Terrestrial Networks: Towards Global and Ubiquitous 6G
Connectivity | [
"eess.SP",
"cs.IT",
"math.IT"
] | The International Mobile Telecommunications (IMT)-2030 framework recently adopted by the International Telecommunication Union Radiocommunication Sector (ITU-R) envisions 6G networks to deliver intelligent, seamless connectivity that supports reliable, sustainable, and resilient communications. Recent developments in t... | {
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2412.16614 | Automated Classification of Cybercrime Complaints using
Transformer-based Language Models for Hinglish Texts | [
"cs.CR",
"cs.AI",
"cs.LG"
] | The rise in cybercrime and the complexity of multilingual and code-mixed complaints present significant challenges for law enforcement and cybersecurity agencies. These organizations need automated, scalable methods to identify crime types, enabling efficient processing and prioritization of large complaint volumes. Ma... | {
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2412.16615 | Large Language Model Can Be a Foundation for Hidden Rationale-Based
Retrieval | [
"cs.IR",
"cs.CL",
"cs.LG"
] | Despite the recent advancement in Retrieval-Augmented Generation (RAG) systems, most retrieval methodologies are often developed for factual retrieval, which assumes query and positive documents are semantically similar. In this paper, we instead propose and study a more challenging type of retrieval task, called hidde... | {
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2412.16616 | Distributed Inference on Mobile Edge and Cloud: A Data-Cartography based
Clustering Approach | [
"cs.DC",
"cs.AI"
] | The large size of DNNs poses a significant challenge for deployment on devices with limited resources, such as mobile, edge, and IoT platforms. To address this issue, a distributed inference framework can be utilized. In this framework, a small-scale DNN (initial layers) is deployed on mobile devices, a larger version ... | {
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2412.16619 | Topology-Aware 3D Gaussian Splatting: Leveraging Persistent Homology for
Optimized Structural Integrity | [
"cs.CV",
"cs.LG",
"eess.IV",
"math.AT",
"math.GT"
] | Gaussian Splatting (GS) has emerged as a crucial technique for representing discrete volumetric radiance fields. It leverages unique parametrization to mitigate computational demands in scene optimization. This work introduces Topology-Aware 3D Gaussian Splatting (Topology-GS), which addresses two key limitations in cu... | {
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2412.16624 | Automated Bleeding Detection and Classification in Wireless Capsule
Endoscopy with YOLOv8-X | [
"cs.CV",
"cs.AI"
] | Gastrointestinal (GI) bleeding, a critical indicator of digestive system disorders, re quires efficient and accurate detection methods. This paper presents our solution to the Auto-WCEBleedGen Version V1 Challenge, where we achieved the consolation position. We developed a unified YOLOv8-X model for both detection and ... | {
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2412.16626 | Mamba-SEUNet: Mamba UNet for Monaural Speech Enhancement | [
"cs.SD",
"cs.AI",
"eess.AS"
] | In recent speech enhancement (SE) research, transformer and its variants have emerged as the predominant methodologies. However, the quadratic complexity of the self-attention mechanism imposes certain limitations on practical deployment. Mamba, as a novel state-space model (SSM), has gained widespread application in n... | {
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2412.16631 | Deep Learning for Spatio-Temporal Fusion in Land Surface Temperature
Estimation: A Comprehensive Survey, Experimental Analysis, and Future Trends | [
"cs.LG",
"cs.AI",
"cs.CV"
] | The rapid advancements in satellite remote sensing have enhanced the capability to monitor and analyze the Earth's surface. Among the many variables captured through satellite sensors, Land Surface Temperature (LST) plays a critical role in understanding key environmental processes. However, obtaining high-resolution L... | {
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2412.16632 | Vehicle Rebalancing Under Adherence Uncertainty | [
"eess.SY",
"cs.SY"
] | Ride hailing systems suffer from spatial-temporal supply demand imbalance due to drivers operating in independent, and uncoordinated manner. Several fleet rebalancing models have been proposed that can provide repositioning recommendations to idle standing drivers with the objective of maximizing service rate or minimi... | {
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2412.16633 | POEX: Understanding and Mitigating Policy Executable Jailbreak Attacks
against Embodied AI | [
"cs.RO",
"cs.AI",
"cs.CY"
] | Embodied AI systems are rapidly evolving due to the integration of LLMs as planning modules, which transform complex instructions into executable policies. However, LLMs are vulnerable to jailbreak attacks, which can generate malicious content. This paper investigates the feasibility and rationale behind applying tradi... | {
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2412.16635 | Task-Driven Co-Design of Mobile Manipulators | [
"cs.RO"
] | Recent interest in mobile manipulation has resulted in a wide range of new robot designs. A large family of these designs focuses on modular platforms that combine existing mobile bases with static manipulator arms. They combine these modules by mounting the arm in a tabletop configuration. However, the operating works... | {
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2412.16641 | A Systems Thinking Approach to Algorithmic Fairness | [
"cs.AI",
"cs.CY"
] | Systems thinking provides us with a way to model the algorithmic fairness problem by allowing us to encode prior knowledge and assumptions about where we believe bias might exist in the data generating process. We can then encode these beliefs as a series of causal graphs, enabling us to link AI/ML systems to politics ... | {
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2412.16642 | L3TC: Leveraging RWKV for Learned Lossless Low-Complexity Text
Compression | [
"cs.CL",
"cs.AI",
"cs.IT",
"cs.MM",
"math.IT"
] | Learning-based probabilistic models can be combined with an entropy coder for data compression. However, due to the high complexity of learning-based models, their practical application as text compressors has been largely overlooked. To address this issue, our work focuses on a low-complexity design while maintaining ... | {
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2412.16643 | TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented
Generation | [
"cs.AI"
] | Although the rise of large language models (LLMs) has introduced new opportunities for time series forecasting, existing LLM-based solutions require excessive training and exhibit limited transferability. In view of these challenges, we propose TimeRAG, a framework that incorporates Retrieval-Augmented Generation (RAG)... | {
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2412.16644 | An explainable operator approximation framework under the guideline of
Green's function | [
"physics.comp-ph",
"cs.LG"
] | Traditional numerical methods, such as the finite element method and finite volume method, adress partial differential equations (PDEs) by discretizing them into algebraic equations and solving these iteratively. However, this process is often computationally expensive and time-consuming. An alternative approach involv... | {
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2412.16645 | Complementary Advantages: Exploiting Cross-Field Frequency Correlation
for NIR-Assisted Image Denoising | [
"cs.CV"
] | Existing single-image denoising algorithms often struggle to restore details when dealing with complex noisy images. The introduction of near-infrared (NIR) images offers new possibilities for RGB image denoising. However, due to the inconsistency between NIR and RGB images, the existing works still struggle to balance... | {
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2412.16651 | PB-UAP: Hybrid Universal Adversarial Attack For Image Segmentation | [
"cs.CV",
"cs.AI"
] | With the rapid advancement of deep learning, the model robustness has become a significant research hotspot, \ie, adversarial attacks on deep neural networks. Existing works primarily focus on image classification tasks, aiming to alter the model's predicted labels. Due to the output complexity and deeper network archi... | {
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2412.16653 | Internalized Self-Correction for Large Language Models | [
"cs.AI"
] | In this article, we introduce 'Internalized Self-Correction' (InSeC) for large language models (LLMs). While many approaches exist for self-reflection at inference time, we propose a novel method that combines ideas from negative sampling, self-reflection during training, and inference time. InSeC allows LLMs to correc... | {
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2412.16654 | IV-tuning: Parameter-Efficient Transfer Learning for Infrared-Visible
Tasks | [
"cs.CV"
] | Infrared-visible (IR-VIS) tasks, such as semantic segmentation and object detection, greatly benefit from the advantage of combining infrared and visible modalities. To inherit the general representations of the Vision Foundation Models (VFMs), task-specific dual-branch networks are designed and fully fine-tuned on dow... | {
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2412.16656 | Generalizable Articulated Object Perception with Superpoints | [
"cs.CV",
"cs.AI"
] | Manipulating articulated objects with robotic arms is challenging due to the complex kinematic structure, which requires precise part segmentation for efficient manipulation. In this work, we introduce a novel superpoint-based perception method designed to improve part segmentation in 3D point clouds of articulated obj... | {
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2412.16662 | Adversarial Attack Against Images Classification based on Generative
Adversarial Networks | [
"cs.CV",
"cs.AI"
] | Adversarial attacks on image classification systems have always been an important problem in the field of machine learning, and generative adversarial networks (GANs), as popular models in the field of image generation, have been widely used in various novel scenarios due to their powerful generative capabilities. Howe... | {
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2412.16664 | Transformer-based toxin-protein interaction analysis prioritizes
airborne particulate matter components with potential adverse health effects | [
"cs.LG",
"q-bio.BM"
] | Air pollution, particularly airborne particulate matter (PM), poses a significant threat to public health globally. It is crucial to comprehend the association between PM-associated toxic components and their cellular targets in humans to understand the mechanisms by which air pollution impacts health and to establish ... | {
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2412.16669 | Label Privacy in Split Learning for Large Models with
Parameter-Efficient Training | [
"cs.LG",
"cs.CR"
] | As deep learning models become larger and more expensive, many practitioners turn to fine-tuning APIs. These web services allow fine-tuning a model between two parties: the client that provides the data, and the server that hosts the model. While convenient, these APIs raise a new concern: the data of the client is at ... | {
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2412.16670 | Two-in-One: Unified Multi-Person Interactive Motion Generation by Latent
Diffusion Transformer | [
"cs.CV",
"cs.GR"
] | Multi-person interactive motion generation, a critical yet under-explored domain in computer character animation, poses significant challenges such as intricate modeling of inter-human interactions beyond individual motions and generating two motions with huge differences from one text condition. Current research often... | {
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2412.16673 | On Enhancing Network Throughput using Reinforcement Learning in Sliced
Testbeds | [
"cs.AI"
] | Novel applications demand high throughput, low latency, and high reliability connectivity and still pose significant challenges to slicing orchestration architectures. The literature explores network slicing techniques that employ canonical methods, artificial intelligence, and combinatorial optimization to address err... | {
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2412.16674 | STAMPsy: Towards SpatioTemporal-Aware Mixed-Type Dialogues for
Psychological Counseling | [
"cs.AI"
] | Online psychological counseling dialogue systems are trending, offering a convenient and accessible alternative to traditional in-person therapy. However, existing psychological counseling dialogue systems mainly focus on basic empathetic dialogue or QA with minimal professional knowledge and without goal guidance. In ... | {
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2412.16677 | VAST 1.0: A Unified Framework for Controllable and Consistent Video
Generation | [
"cs.CV"
] | Generating high-quality videos from textual descriptions poses challenges in maintaining temporal coherence and control over subject motion. We propose VAST (Video As Storyboard from Text), a two-stage framework to address these challenges and enable high-quality video generation. In the first stage, StoryForge transfo... | {
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2412.16682 | The Task Shield: Enforcing Task Alignment to Defend Against Indirect
Prompt Injection in LLM Agents | [
"cs.CR",
"cs.AI",
"cs.CL",
"cs.LG"
] | Large Language Model (LLM) agents are increasingly being deployed as conversational assistants capable of performing complex real-world tasks through tool integration. This enhanced ability to interact with external systems and process various data sources, while powerful, introduces significant security vulnerabilitie... | {
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2412.16686 | NILE: Internal Consistency Alignment in Large Language Models | [
"cs.CL"
] | As a crucial step to enhance LLMs alignment with human intentions, Instruction Fine-Tuning (IFT) has a high demand on dataset quality. However, existing IFT datasets often contain knowledge that is inconsistent with LLMs' internal knowledge learned from the pre-training phase, which can greatly affect the efficacy of I... | {
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2412.16687 | Subgoal Discovery Using a Free Energy Paradigm and State Aggregations | [
"cs.LG",
"cs.AI"
] | Reinforcement learning (RL) plays a major role in solving complex sequential decision-making tasks. Hierarchical and goal-conditioned RL are promising methods for dealing with two major problems in RL, namely sample inefficiency and difficulties in reward shaping. These methods tackle the mentioned problems by decompos... | {
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2412.16689 | Formal Language Knowledge Corpus for Retrieval Augmented Generation | [
"cs.AI"
] | The integration of retrieval-augmented techniques with LLMs has shown promise in improving performance across various domains. However, their utility in tasks requiring advanced reasoning, such as generating and evaluating mathematical statements and proofs, remains underexplored. This study explores the use of Lean, a... | {
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2412.16691 | From Correlation to Causation: Understanding Climate Change through
Causal Analysis and LLM Interpretations | [
"cs.LG",
"cs.CY",
"stat.ME",
"stat.ML"
] | This research presents a three-step causal inference framework that integrates correlation analysis, machine learning-based causality discovery, and LLM-driven interpretations to identify socioeconomic factors influencing carbon emissions and contributing to climate change. The approach begins with identifying correlat... | {
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2412.16694 | DragonVerseQA: Open-Domain Long-Form Context-Aware Question-Answering | [
"cs.CL",
"cs.IR"
] | This paper proposes a novel approach to develop an open-domain and long-form Over-The-Top (OTT) Question-Answering (QA) dataset, DragonVerseQA, specifically oriented to the fantasy universe of "House of the Dragon" and "Game Of Thrones" TV series. Most existing QA datasets focus on short, fact-based answers sourced alm... | {
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2412.16698 | Interact with me: Joint Egocentric Forecasting of Intent to Interact,
Attitude and Social Actions | [
"cs.CV",
"cs.HC"
] | For efficient human-agent interaction, an agent should proactively recognize their target user and prepare for upcoming interactions. We formulate this challenging problem as the novel task of jointly forecasting a person's intent to interact with the agent, their attitude towards the agent and the action they will per... | {
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2412.16699 | FAP-CD: Fairness-Driven Age-Friendly Community Planning via Conditional
Diffusion Generation | [
"cs.AI"
] | As global populations age rapidly, incorporating age-specific considerations into urban planning has become essential to addressing the urgent demand for age-friendly built environments and ensuring sustainable urban development. However, current practices often overlook these considerations, resulting in inadequate an... | {
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2412.16700 | TCAQ-DM: Timestep-Channel Adaptive Quantization for Diffusion Models | [
"cs.CV"
] | Diffusion models have achieved remarkable success in the image and video generation tasks. Nevertheless, they often require a large amount of memory and time overhead during inference, due to the complex network architecture and considerable number of timesteps for iterative diffusion. Recently, the post-training quant... | {
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2412.16701 | AlzheimerRAG: Multimodal Retrieval Augmented Generation for PubMed
articles | [
"cs.IR",
"cs.CL"
] | Recent advancements in generative AI have flourished the development of highly adept Large Language Models (LLMs) that integrate diverse data types to empower decision-making. Among these, Multimodal Retrieval-Augmented Generation (RAG) applications are promising for their capability to combine the strengths of informa... | {
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2412.16708 | Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under
Adversarial Poisoning Attacks | [
"cs.IR"
] | Retrieval-Augmented Generation (RAG) systems have emerged as a promising solution to mitigate LLM hallucinations and enhance their performance in knowledge-intensive domains. However, these systems are vulnerable to adversarial poisoning attacks, where malicious passages injected into retrieval databases can mislead th... | {
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2412.16711 | From Pixels to Gigapixels: Bridging Local Inductive Bias and Long-Range
Dependencies with Pixel-Mamba | [
"cs.CV"
] | Histopathology plays a critical role in medical diagnostics, with whole slide images (WSIs) offering valuable insights that directly influence clinical decision-making. However, the large size and complexity of WSIs may pose significant challenges for deep learning models, in both computational efficiency and effective... | {
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2412.16713 | A Unifying Family of Data-Adaptive Partitioning Algorithms | [
"math.NA",
"cs.LG",
"cs.NA"
] | Clustering algorithms remain valuable tools for grouping and summarizing the most important aspects of data. Example areas where this is the case include image segmentation, dimension reduction, signals analysis, model order reduction, numerical analysis, and others. As a consequence, many clustering approaches have be... | {
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2412.16715 | From Histopathology Images to Cell Clouds: Learning Slide
Representations with Hierarchical Cell Transformer | [
"cs.CV",
"cs.AI"
] | It is clinically crucial and potentially very beneficial to be able to analyze and model directly the spatial distributions of cells in histopathology whole slide images (WSI). However, most existing WSI datasets lack cell-level annotations, owing to the extremely high cost over giga-pixel images. Thus, it remains an o... | {
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2412.16717 | GANFusion: Feed-Forward Text-to-3D with Diffusion in GAN Space | [
"cs.CV",
"cs.LG"
] | We train a feed-forward text-to-3D diffusion generator for human characters using only single-view 2D data for supervision. Existing 3D generative models cannot yet match the fidelity of image or video generative models. State-of-the-art 3D generators are either trained with explicit 3D supervision and are thus limited... | {
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2412.16719 | Lillama: Large Language Models Compression via Low-Rank Feature
Distillation | [
"cs.LG",
"cs.AI"
] | Current LLM structured pruning methods typically involve two steps: (1) compression with calibration data and (2) costly continued pretraining on billions of tokens to recover lost performance. This second step is necessary as the first significantly impacts model accuracy. Prior research suggests pretrained Transforme... | {
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2412.16720 | OpenAI o1 System Card | [
"cs.AI"
] | The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the safety and robustness of our models. In particular, our models can reason about our safety policies in context when responding to potential... | {
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2412.16723 | Divide and Conquer: Grounding a Bleeding Areas in Gastrointestinal Image
with Two-Stage Model | [
"cs.CV"
] | Accurate detection and segmentation of gastrointestinal bleeding are critical for diagnosing diseases such as peptic ulcers and colorectal cancer. This study proposes a two-stage framework that decouples classification and grounding to address the inherent challenges posed by traditional Multi-Task Learning models, whi... | {
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2412.16724 | Coupling Neural Networks and Physics Equations For Li-Ion Battery
State-of-Charge Prediction | [
"cs.LG",
"cs.AI"
] | Estimating the evolution of the battery's State of Charge (SoC) in response to its usage is critical for implementing effective power management policies and for ultimately improving the system's lifetime. Most existing estimation methods are either physics-based digital twins of the battery or data-driven models such ... | {
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2412.16725 | Argumentation Computation with Large Language Models : A Benchmark Study | [
"cs.AI"
] | In recent years, large language models (LLMs) have made significant advancements in neuro-symbolic computing. However, the combination of LLM with argumentation computation remains an underexplored domain, despite its considerable potential for real-world applications requiring defeasible reasoning. In this paper, we a... | {
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2412.16728 | Reasoning about Actual Causes in Nondeterministic Domains -- Extended
Version | [
"cs.AI"
] | Reasoning about the causes behind observations is crucial to the formalization of rationality. While extensive research has been conducted on root cause analysis, most studies have predominantly focused on deterministic settings. In this paper, we investigate causation in more realistic nondeterministic domains, where ... | {
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2412.16737 | LUCES-MV: A Multi-View Dataset for Near-Field Point Light Source
Photometric Stereo | [
"cs.CV"
] | The biggest improvements in Photometric Stereo (PS) field has recently come from adoption of differentiable volumetric rendering techniques such as NeRF or Neural SDF achieving impressive reconstruction error of 0.2mm on DiLiGenT-MV benchmark. However, while there are sizeable datasets for environment lit objects such ... | {
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2412.16738 | KKANs: Kurkova-Kolmogorov-Arnold Networks and Their Learning Dynamics | [
"cs.LG",
"cs.NA",
"math.NA",
"stat.ML"
] | Inspired by the Kolmogorov-Arnold representation theorem and Kurkova's principle of using approximate representations, we propose the Kurkova-Kolmogorov-Arnold Network (KKAN), a new two-block architecture that combines robust multi-layer perceptron (MLP) based inner functions with flexible linear combinations of basis ... | {
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2412.16739 | UNEM: UNrolled Generalized EM for Transductive Few-Shot Learning | [
"cs.CV"
] | Transductive few-shot learning has recently triggered wide attention in computer vision. Yet, current methods introduce key hyper-parameters, which control the prediction statistics of the test batches, such as the level of class balance, affecting performances significantly. Such hyper-parameters are empirically grid-... | {
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2412.16742 | EasyVis2: A Real Time Multi-view 3D Visualization for Laparoscopic
Surgery Training Enhanced by a Deep Neural Network YOLOv8-Pose | [
"cs.CV"
] | EasyVis2 is a system designed for hands-free, real-time 3D visualization during laparoscopic surgery. It incorporates a surgical trocar equipped with a set of micro-cameras, which are inserted into the body cavity to provide an expanded field of view and a 3D perspective of the surgical procedure. A sophisticated deep ... | {
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2412.16745 | ViM-Disparity: Bridging the Gap of Speed, Accuracy and Memory for
Disparity Map Generation | [
"cs.CV"
] | In this work we propose a Visual Mamba (ViM) based architecture, to dissolve the existing trade-off for real-time and accurate model with low computation overhead for disparity map generation (DMG). Moreover, we proposed a performance measure that can jointly evaluate the inference speed, computation overhead and the a... | {
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2412.16746 | Unpacking Political Bias in Large Language Models: Insights Across Topic
Polarization | [
"cs.CY",
"cs.AI"
] | Large Language Models (LLMs) have been widely used to generate responses on social topics due to their world knowledge and generative capabilities. Beyond reasoning and generation performance, political bias is an essential issue that warrants attention. Political bias, as a universal phenomenon in human society, may b... | {
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2412.16747 | Space-Air-Ground Integrated Networks: Their Channel Model and
Performance Analysis | [
"cs.IT",
"eess.SP",
"math.IT"
] | Given their extensive geographic coverage, low Earth orbit (LEO) satellites are envisioned to find their way into next-generation (6G) wireless communications. This paper explores space-air-ground integrated networks (SAGINs) leveraging LEOs to support terrestrial and non-terrestrial users. We first propose a practical... | {
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2412.16748 | Solving Inverse Problems via Diffusion Optimal Control | [
"cs.LG"
] | Existing approaches to diffusion-based inverse problem solvers frame the signal recovery task as a probabilistic sampling episode, where the solution is drawn from the desired posterior distribution. This framework suffers from several critical drawbacks, including the intractability of the conditional likelihood funct... | {
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2412.16750 | Gradient-based Trajectory Optimization with Parallelized Differentiable
Traffic Simulation | [
"cs.RO",
"cs.DC",
"cs.LG"
] | We present a parallelized differentiable traffic simulator based on the Intelligent Driver Model (IDM), a car-following framework that incorporates driver behavior as key variables. Our vehicle simulator efficiently models vehicle motion, generating trajectories that can be supervised to fit real-world data. By leverag... | {
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2412.16751 | The Master Key Filters Hypothesis: Deep Filters Are General | [
"cs.CV",
"cs.AI"
] | This paper challenges the prevailing view that convolutional neural network (CNN) filters become increasingly specialized in deeper layers. Motivated by recent observations of clusterable repeating patterns in depthwise separable CNNs (DS-CNNs) trained on ImageNet, we extend this investigation across various domains an... | {
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2412.16755 | A Novel Approach to Tomato Harvesting Using a Hybrid Gripper with
Semantic Segmentation and Keypoint Detection | [
"cs.RO"
] | Current agriculture and farming industries are able to reap advancements in robotics and automation technology to harvest fruits and vegetables using robots with adaptive grasping forces based on the compliance or softness of the fruit or vegetable. A successful operation depends on using a gripper that can adapt to th... | {
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2412.16757 | Leveraging Highly Approximated Multipliers in DNN Inference | [
"cs.AR",
"cs.LG"
] | In this work, we present a control variate approximation technique that enables the exploitation of highly approximate multipliers in Deep Neural Network (DNN) accelerators. Our approach does not require retraining and significantly decreases the induced error due to approximate multiplications, improving the overall i... | {
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2412.16758 | Evaluation of radiomic feature harmonization techniques for benign and
malignant pulmonary nodules | [
"physics.med-ph",
"cs.CV"
] | BACKGROUND: Radiomics provides quantitative features of pulmonary nodules (PNs) which could aid lung cancer diagnosis, but medical image acquisition variability is an obstacle to clinical application. Acquisition effects may differ between radiomic features from benign vs. malignant PNs. PURPOSE: We evaluated how to ac... | {
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2412.16761 | Non-Asymptotic Error Analysis of Subspace Identification for
Deterministic Systems | [
"eess.SY",
"cs.SY"
] | This paper is concerned with the perturbation error analysis of the widely-used Subspace Identification Methods (SIM) for n-dimensional discrete-time Multiple-Input Multiple-Output (MIMO) Linear Time-Invariant (LTI) systems with m outputs, based on finite input/output sample data. Using a single input/output trajectory... | {
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2412.16762 | A Method for the Runtime Validation of AI-based Environment Perception
in Automated Driving System | [
"cs.RO",
"cs.AI",
"cs.SE"
] | Environment perception is a fundamental part of the dynamic driving task executed by Autonomous Driving Systems (ADS). Artificial Intelligence (AI)-based approaches have prevailed over classical techniques for realizing the environment perception. Current safety-relevant standards for automotive systems, International ... | {
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2412.16763 | Paraformer: Parameterization of Sub-grid Scale Processes Using
Transformers | [
"cs.LG",
"physics.ao-ph"
] | One of the major sources of uncertainty in the current generation of Global Climate Models (GCMs) is the representation of sub-grid scale physical processes. Over the years, a series of deep-learning-based parameterization schemes have been developed and tested on both idealized and real-geography GCMs. However, datase... | {
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2412.16764 | Towards Selection and Transition Between Behavior-Based Neural Networks
for Automated Driving | [
"cs.RO",
"cs.AI"
] | Autonomous driving technology is progressing rapidly, largely due to complex End To End systems based on deep neural networks. While these systems are effective, their complexity can make it difficult to understand their behavior, raising safety concerns. This paper presents a new solution a Behavior Selector that uses... | {
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2412.16765 | Optimization Insights into Deep Diagonal Linear Networks | [
"cs.LG",
"math.OC",
"stat.ML"
] | Overparameterized models trained with (stochastic) gradient descent are ubiquitous in modern machine learning. These large models achieve unprecedented performance on test data, but their theoretical understanding is still limited. In this paper, we take a step towards filling this gap by adopting an optimization persp... | {
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2412.16766 | Apples to Apples: Establishing Comparability in Knowledge Generation
Tasks Involving Users | [
"cs.HC",
"cs.AI",
"cs.DB"
] | Knowledge graph construction (KGC) from (semi-)structured data is challenging, and facilitating user involvement is an issue frequently brought up within this community. We cannot deny the progress we have made with respect to (declarative) knowledge generation languages and tools to help build such mappings. However, ... | {
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2412.16768 | A Comparative Study on Machine Learning Models to Classify Diseases
Based on Patient Behaviour and Habits | [
"cs.LG",
"cs.AI"
] | In recent years, ML algorithms have been shown to be useful for predicting diseases based on health data and posed a potential application area for these algorithms such as modeling of diseases. The majority of these applications employ supervised rather than unsupervised ML algorithms. In addition, each year, the amou... | {
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2412.16769 | Does calibration mean what they say it means; or, the reference class
problem rises again | [
"cs.LG"
] | Discussions of statistical criteria for fairness commonly convey the normative significance of calibration within groups by invoking what risk scores "mean." On the Same Meaning picture, group-calibrated scores "mean the same thing" (on average) across individuals from different groups and accordingly, guard against di... | {
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2412.16771 | SilVar: Speech Driven Multimodal Model for Reasoning Visual Question
Answering and Object Localization | [
"cs.CV"
] | Visual Language Models have demonstrated remarkable capabilities across tasks, including visual question answering and image captioning. However, most models rely on text-based instructions, limiting their effectiveness in human-machine interactions. Moreover, the quality of language models depends on reasoning and pro... | {
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2412.16772 | Assessing Social Alignment: Do Personality-Prompted Large Language
Models Behave Like Humans? | [
"cs.CY",
"cs.AI",
"cs.LG"
] | The ongoing revolution in language modelling has led to various novel applications, some of which rely on the emerging "social abilities" of large language models (LLMs). Already, many turn to the new "cyber friends" for advice during pivotal moments of their lives and trust them with their deepest secrets, implying th... | {
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2412.16773 | Fast Multi-Group Gaussian Process Factor Models | [
"stat.ML",
"cs.LG",
"eess.SP",
"q-bio.NC"
] | Gaussian processes are now commonly used in dimensionality reduction approaches tailored to neuroscience, especially to describe changes in high-dimensional neural activity over time. As recording capabilities expand to include neuronal populations across multiple brain areas, cortical layers, and cell types, interest ... | {
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2412.16776 | DMesh++: An Efficient Differentiable Mesh for Complex Shapes | [
"cs.CV",
"cs.GR",
"cs.LG"
] | Recent probabilistic methods for 3D triangular meshes capture diverse shapes by differentiable mesh connectivity, but face high computational costs with increased shape details. We introduce a new differentiable mesh processing method in 2D and 3D that addresses this challenge and efficiently handles meshes with intric... | {
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2412.16777 | HyperCLIP: Adapting Vision-Language models with Hypernetworks | [
"cs.CV",
"cs.LG"
] | Self-supervised vision-language models trained with contrastive objectives form the basis of current state-of-the-art methods in AI vision tasks. The success of these models is a direct consequence of the huge web-scale datasets used to train them, but they require correspondingly large vision components to properly le... | {
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2412.16778 | RoomPainter: View-Integrated Diffusion for Consistent Indoor Scene
Texturing | [
"cs.CV"
] | Indoor scene texture synthesis has garnered significant interest due to its important potential applications in virtual reality, digital media, and creative arts. Existing diffusion model-based researches either rely on per-view inpainting techniques, which are plagued by severe cross-view inconsistencies and conspicuo... | {
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2412.16779 | Fed-ZOE: Communication-Efficient Over-the-Air Federated Learning via
Zeroth-Order Estimation | [
"cs.LG",
"eess.SP"
] | As 6G and beyond networks grow increasingly complex and interconnected, federated learning (FL) emerges as an indispensable paradigm for securely and efficiently leveraging decentralized edge data for AI. By virtue of the superposition property of communication signals, over-the-air FL (OtA-FL) achieves constant commun... | {
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2412.16780 | Forget Vectors at Play: Universal Input Perturbations Driving Machine
Unlearning in Image Classification | [
"cs.LG",
"cs.CV"
] | Machine unlearning (MU), which seeks to erase the influence of specific unwanted data from already-trained models, is becoming increasingly vital in model editing, particularly to comply with evolving data regulations like the ``right to be forgotten''. Conventional approaches are predominantly model-based, typically r... | {
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2412.16783 | SubData: A Python Library to Collect and Combine Datasets for Evaluating
LLM Alignment on Downstream Tasks | [
"cs.CL"
] | With the release of ever more capable large language models (LLMs), researchers in NLP and related disciplines have started to explore the usability of LLMs for a wide variety of different annotation tasks. Very recently, a lot of this attention has shifted to tasks that are subjective in nature. Given that the latest ... | {
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2412.16787 | Symplectic Neural Flows for Modeling and Discovery | [
"cs.LG",
"physics.comp-ph",
"physics.flu-dyn"
] | Hamilton's equations are fundamental for modeling complex physical systems, where preserving key properties such as energy and momentum is crucial for reliable long-term simulations. Geometric integrators are widely used for this purpose, but neural network-based methods that incorporate these principles remain underex... | {
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2412.16788 | DCOR: Anomaly Detection in Attributed Networks via Dual Contrastive
Learning Reconstruction | [
"cs.AI"
] | Anomaly detection using a network-based approach is one of the most efficient ways to identify abnormal events such as fraud, security breaches, and system faults in a variety of applied domains. While most of the earlier works address the complex nature of graph-structured data and predefined anomalies, the impact of ... | {
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2412.16791 | Enhancing web traffic attacks identification through ensemble methods
and feature selection | [
"cs.CR",
"cs.AI",
"cs.LG"
] | Websites, as essential digital assets, are highly vulnerable to cyberattacks because of their high traffic volume and the significant impact of breaches. This study aims to enhance the identification of web traffic attacks by leveraging machine learning techniques. A methodology was proposed to extract relevant feature... | {
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2412.16794 | Gradient-Based Non-Linear Inverse Learning | [
"stat.ML",
"cs.LG"
] | We study statistical inverse learning in the context of nonlinear inverse problems under random design. Specifically, we address a class of nonlinear problems by employing gradient descent (GD) and stochastic gradient descent (SGD) with mini-batching, both using constant step sizes. Our analysis derives convergence rat... | {
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2412.16797 | Fixed-Time Input-to-State Stability for Singularly Perturbed Systems via
Composite Lyapunov Functions | [
"eess.SY",
"cs.SY"
] | We study singularly perturbed systems that exhibit input-to-state stability (ISS) with fixed-time properties in the presence of bounded disturbances. In these systems, solutions converge to the origin within a time frame independent of initial conditions when undisturbed, and to a vicinity of the origin when subjected ... | {
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2412.16802 | Balls-and-Bins Sampling for DP-SGD | [
"cs.LG",
"cs.CR",
"cs.DS",
"stat.ML"
] | We introduce the Balls-and-Bins sampling for differentially private (DP) optimization methods such as DP-SGD. While it has been common practice to use some form of shuffling in DP-SGD implementations, privacy accounting algorithms have typically assumed that Poisson subsampling is used instead. Recent work by Chua et a... | {
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2412.16803 | Modeling the Dynamics of Sub-Millisecond Electroadhesive Engagement and
Release Times | [
"cs.RO",
"cs.HC",
"physics.app-ph"
] | Electroadhesion is an electrically controllable switchable adhesive commonly used in soft robots and haptic user interfaces. It can form strong bonds to a wide variety of surfaces at low power consumption. However, electroadhesive clutches in the literature engage to and release from substrates several orders of magnit... | {
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2412.16805 | NMPC and Deep Learning-Based Vibration Control of Satellite Beam Antenna
Dynamics Using PZT Actuators and Sensors | [
"eess.SY",
"cs.SY"
] | This paper presents a novel approach for vibration control of satellite-based flexible beam-type antennas using Nonlinear Model Predictive Control (NMPC) and Deep Learning techniques. The developed control system leverages piezoelectric (PZT) actuators and sensors to manage the coupled attitude and structural dynamics ... | {
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2412.16806 | Quantum-Like Contextuality in Large Language Models | [
"cs.CL",
"quant-ph"
] | Contextuality is a distinguishing feature of quantum mechanics and there is growing evidence that it is a necessary condition for quantum advantage. In order to make use of it, researchers have been asking whether similar phenomena arise in other domains. The answer has been yes, e.g. in behavioural sciences. However, ... | {
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} |
2412.16807 | IMVB7t: A Multi-Modal Model for Food Preferences based on Artificially
Produced Traits | [
"cs.CV"
] | Human behavior and interactions are profoundly influenced by visual stimuli present in their surroundings. This influence extends to various aspects of life, notably food consumption and selection. In our study, we employed various models to extract different attributes from the environmental images. Specifically, we i... | {
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} |
2412.16809 | GeoTexDensifier: Geometry-Texture-Aware Densification for High-Quality
Photorealistic 3D Gaussian Splatting | [
"cs.CV"
] | 3D Gaussian Splatting (3DGS) has recently attracted wide attentions in various areas such as 3D navigation, Virtual Reality (VR) and 3D simulation, due to its photorealistic and efficient rendering performance. High-quality reconstrution of 3DGS relies on sufficient splats and a reasonable distribution of these splats ... | {
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} |
2412.16814 | An Exploration of Pattern Mining with ChatGPT | [
"cs.AI"
] | This paper takes an exploratory approach to examine the use of ChatGPT for pattern mining. It proposes an eight-step collaborative process that combines human insight with AI capabilities to extract patterns from known uses. The paper offers a practical demonstration of this process by creating a pattern language for i... | {
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} |
2412.16818 | Unsupervised Discovery of Formulas for Mathematical Constants | [
"cs.AI",
"cs.LG",
"math.NT"
] | Ongoing efforts that span over decades show a rise of AI methods for accelerating scientific discovery, yet accelerating discovery in mathematics remains a persistent challenge for AI. Specifically, AI methods were not effective in creation of formulas for mathematical constants because each such formula must be correc... | {
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} |
2412.16819 | Bi-Sparse Unsupervised Feature Selection | [
"math.OC",
"cs.LG"
] | To efficiently deal with high-dimensional datasets in many areas, unsupervised feature selection (UFS) has become a rising technique for dimension reduction. Even though there are many UFS methods, most of them only consider the global structure of datasets by embedding a single sparse regularization or constraint. In ... | {
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} |
2412.16822 | Layer- and Timestep-Adaptive Differentiable Token Compression Ratios for
Efficient Diffusion Transformers | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Diffusion Transformers (DiTs) have achieved state-of-the-art (SOTA) image generation quality but suffer from high latency and memory inefficiency, making them difficult to deploy on resource-constrained devices. One key efficiency bottleneck is that existing DiTs apply equal computation across all regions of an image. ... | {
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} |
2412.16827 | Optimal Error Analysis of Channel Estimation for IRS-assisted MIMO
Systems | [
"cs.IT",
"eess.SP",
"math.IT"
] | As intelligent reflecting surface (IRS) has emerged as a new and promising technology capable of configuring the wireless environment favorably, channel estimation for IRS-assisted multiple-input multiple-output (MIMO) systems has garnered extensive attention in recent years. While various algorithms have been proposed... | {
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} |
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