id stringlengths 9 16 | title stringlengths 4 278 | categories listlengths 1 13 | abstract stringlengths 3 4.08k | filtered_category_membership dict |
|---|---|---|---|---|
2412.14172 | Learning from Massive Human Videos for Universal Humanoid Pose Control | [
"cs.RO",
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] | Scalable learning of humanoid robots is crucial for their deployment in real-world applications. While traditional approaches primarily rely on reinforcement learning or teleoperation to achieve whole-body control, they are often limited by the diversity of simulated environments and the high costs of demonstration col... | {
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2412.14173 | AniDoc: Animation Creation Made Easier | [
"cs.CV"
] | The production of 2D animation follows an industry-standard workflow, encompassing four essential stages: character design, keyframe animation, in-betweening, and coloring. Our research focuses on reducing the labor costs in the above process by harnessing the potential of increasingly powerful generative AI. Using vid... | {
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2412.14175 | BiTSA: Leveraging Time Series Foundation Model for Building Energy
Analytics | [
"cs.CE",
"cs.CY",
"cs.HC"
] | Incorporating AI technologies into digital infrastructure offers transformative potential for energy management, particularly in enhancing energy efficiency and supporting net-zero objectives. However, the complexity of IoT-generated datasets often poses a significant challenge, hindering the translation of research in... | {
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2412.14179 | Benchmarking Harmonized Tariff Schedule Classification Models | [
"cs.SE",
"cs.AI"
] | The Harmonized Tariff System (HTS) classification industry, essential to e-commerce and international trade, currently lacks standardized benchmarks for evaluating the effectiveness of classification solutions. This study establishes and tests a benchmark framework for imports to the United States, inspired by the benc... | {
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2412.14185 | Fabric Sensing of Intrinsic Hand Muscle Activity | [
"cs.HC",
"cs.RO"
] | Wearable robotics have the capacity to assist stroke survivors in assisting and rehabilitating hand function. Many devices that use surface electromyographic (sEMG) for control rely on extrinsic muscle signals, since sEMG sensors are relatively easy to place on the forearm without interfering with hand activity. In thi... | {
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2412.14186 | Towards AI-$45^{\circ}$ Law: A Roadmap to Trustworthy AGI | [
"cs.CY",
"cs.AI",
"cs.CL",
"cs.LG"
] | Ensuring Artificial General Intelligence (AGI) reliably avoids harmful behaviors is a critical challenge, especially for systems with high autonomy or in safety-critical domains. Despite various safety assurance proposals and extreme risk warnings, comprehensive guidelines balancing AI safety and capability remain lack... | {
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2412.14187 | Detecting Dark Patterns in User Interfaces Using Logistic Regression and
Bag-of-Words Representation | [
"cs.HC",
"cs.LG"
] | Dark patterns in user interfaces represent deceptive design practices intended to manipulate users' behavior, often leading to unintended consequences such as coerced purchases, involuntary data disclosures, or user frustration. Detecting and mitigating these dark patterns is crucial for promoting transparency, trust, ... | {
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2412.14188 | CogSimulator: A Model for Simulating User Cognition & Behavior with
Minimal Data for Tailored Cognitive Enhancement | [
"cs.HC",
"cs.AI",
"q-bio.NC"
] | The interplay between cognition and gaming, notably through educational games enhancing cognitive skills, has garnered significant attention in recent years. This research introduces the CogSimulator, a novel algorithm for simulating user cognition in small-group settings with minimal data, as the educational game Word... | {
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2412.14190 | Lessons From an App Update at Replika AI: Identity Discontinuity in
Human-AI Relationships | [
"cs.HC",
"cs.AI",
"cs.CY"
] | Can consumers form especially deep emotional bonds with AI and be vested in AI identities over time? We leverage a natural app-update event at Replika AI, a popular US-based AI companion, to shed light on these questions. We find that, after the app removed its erotic role play (ERP) feature, preventing intimate intera... | {
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2412.14191 | Ontology-Aware RAG for Improved Question-Answering in Cybersecurity
Education | [
"cs.CY",
"cs.AI"
] | Integrating AI into education has the potential to transform the teaching of science and technology courses, particularly in the field of cybersecurity. AI-driven question-answering (QA) systems can actively manage uncertainty in cybersecurity problem-solving, offering interactive, inquiry-based learning experiences. L... | {
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2412.14193 | Whom do Explanations Serve? A Systematic Literature Survey of User
Characteristics in Explainable Recommender Systems Evaluation | [
"cs.HC",
"cs.AI",
"cs.IR"
] | Adding explanations to recommender systems is said to have multiple benefits, such as increasing user trust or system transparency. Previous work from other application areas suggests that specific user characteristics impact the users' perception of the explanation. However, we rarely find this type of evaluation for ... | {
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2412.14194 | Detecting Cognitive Impairment and Psychological Well-being among Older
Adults Using Facial, Acoustic, Linguistic, and Cardiovascular Patterns
Derived from Remote Conversations | [
"cs.HC",
"cs.AI"
] | The aging society urgently requires scalable methods to monitor cognitive decline and identify social and psychological factors indicative of dementia risk in older adults. Our machine learning (ML) models captured facial, acoustic, linguistic, and cardiovascular features from 39 individuals with normal cognition or Mi... | {
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2412.14195 | IMPROVE: Impact of Mobile Phones on Remote Online Virtual Education | [
"cs.HC",
"cs.CV"
] | This work presents the IMPROVE dataset, designed to evaluate the effects of mobile phone usage on learners during online education. The dataset not only assesses academic performance and subjective learner feedback but also captures biometric, behavioral, and physiological signals, providing a comprehensive analysis of... | {
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2412.14197 | Advancing Vehicle Plate Recognition: Multitasking Visual Language Models
with VehiclePaliGemma | [
"cs.CV",
"cs.LG"
] | License plate recognition (LPR) involves automated systems that utilize cameras and computer vision to read vehicle license plates. Such plates collected through LPR can then be compared against databases to identify stolen vehicles, uninsured drivers, crime suspects, and more. The LPR system plays a significant role i... | {
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2412.14203 | BlenderLLM: Training Large Language Models for Computer-Aided Design
with Self-improvement | [
"cs.HC",
"cs.AI"
] | The application of Large Language Models (LLMs) in Computer-Aided Design (CAD) remains an underexplored area, despite their remarkable advancements in other domains. In this paper, we present BlenderLLM, a novel framework for training LLMs specifically for CAD tasks leveraging a self-improvement methodology. To support... | {
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2412.14205 | Large-scale Group Brainstorming using Conversational Swarm Intelligence
(CSI) versus Traditional Chat | [
"cs.HC",
"cs.AI",
"cs.SI"
] | Conversational Swarm Intelligence (CSI) is an AI-facilitated method for enabling real-time conversational deliberations and prioritizations among networked human groups of potentially unlimited size. Based on the biological principle of Swarm Intelligence and modelled on the decision-making dynamics of fish schools, CS... | {
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2412.14207 | A Comprehensive Review on Traffic Datasets and Simulators for Autonomous
Vehicles | [
"cs.RO"
] | Autonomous driving has rapidly developed and shown promising performance due to recent advances in hardware and deep learning techniques. High-quality datasets are fundamental for developing reliable autonomous driving algorithms. Previous dataset surveys either focused on a limited number or lacked detailed investigat... | {
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2412.14208 | Beacon: A Naturalistic Driving Dataset During Blackouts for Benchmarking
Traffic Reconstruction and Control | [
"cs.RO"
] | Extreme weather events and other vulnerabilities are causing blackouts with increasing frequency, disrupting traffic control systems and posing significant challenges to urban mobility. To address this growing concern, we introduce \model{}, a naturalistic driving dataset collected during blackouts at complex intersect... | {
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2412.14209 | Integrating Evidence into the Design of XAI and AI-based Decision
Support Systems: A Means-End Framework for End-users in Construction | [
"cs.HC",
"cs.AI"
] | A narrative review is used to develop a theoretical evidence-based means-end framework to build an epistemic foundation to uphold explainable artificial intelligence instruments so that the reliability of outcomes generated from decision support systems can be assured and better explained to end-users. The implications... | {
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2412.14210 | Mobilizing Waldo: Evaluating Multimodal AI for Public Mobilization | [
"cs.HC",
"cs.CY",
"cs.SI"
] | Advancements in multimodal Large Language Models (LLMs), such as OpenAI's GPT-4o, offer significant potential for mediating human interactions across various contexts. However, their use in areas such as persuasion, influence, and recruitment raises ethical and security concerns. To evaluate these models ethically in p... | {
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2412.14211 | Improving Generalization Performance of YOLOv8 for Camera Trap Object
Detection | [
"cs.CV",
"cs.LG"
] | Camera traps have become integral tools in wildlife conservation, providing non-intrusive means to monitor and study wildlife in their natural habitats. The utilization of object detection algorithms to automate species identification from Camera Trap images is of huge importance for research and conservation purposes.... | {
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2412.14212 | Tree-of-Code: A Hybrid Approach for Robust Complex Task Planning and
Execution | [
"cs.SE",
"cs.AI"
] | The exceptional capabilities of large language models (LLMs) have substantially accelerated the rapid rise and widespread adoption of agents. Recent studies have demonstrated that generating Python code to consolidate LLM-based agents' actions into a unified action space (CodeAct) is a promising approach for developing... | {
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2412.14214 | GraphicsDreamer: Image to 3D Generation with Physical Consistency | [
"cs.GR",
"cs.AI",
"cs.CV"
] | Recently, the surge of efficient and automated 3D AI-generated content (AIGC) methods has increasingly illuminated the path of transforming human imagination into complex 3D structures. However, the automated generation of 3D content is still significantly lags in industrial application. This gap exists because 3D mode... | {
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2412.14215 | Generative AI Toolkit -- a framework for increasing the quality of
LLM-based applications over their whole life cycle | [
"cs.SE",
"cs.AI"
] | As LLM-based applications reach millions of customers, ensuring their scalability and continuous quality improvement is critical for success. However, the current workflows for developing, maintaining, and operating (DevOps) these applications are predominantly manual, slow, and based on trial-and-error. With this pape... | {
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2412.14218 | Heterogeneous Multi-Agent Reinforcement Learning for Distributed Channel
Access in WLANs | [
"cs.LG",
"cs.AI",
"cs.NI"
] | This paper investigates the use of multi-agent reinforcement learning (MARL) to address distributed channel access in wireless local area networks. In particular, we consider the challenging yet more practical case where the agents heterogeneously adopt value-based or policy-based reinforcement learning algorithms to t... | {
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2412.14219 | A Survey on Inference Optimization Techniques for Mixture of Experts
Models | [
"cs.LG",
"cs.AI",
"cs.DC"
] | The emergence of large-scale Mixture of Experts (MoE) models represents a significant advancement in artificial intelligence, offering enhanced model capacity and computational efficiency through conditional computation. However, deploying and running inference on these models presents significant challenges in computa... | {
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2412.14220 | Distilled Pooling Transformer Encoder for Efficient Realistic Image
Dehazing | [
"cs.CV"
] | This paper proposes a lightweight neural network designed for realistic image dehazing, utilizing a Distilled Pooling Transformer Encoder, named DPTE-Net. Recently, while vision transformers (ViTs) have achieved great success in various vision tasks, their self-attention (SA) module's complexity scales quadratically wi... | {
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2412.14222 | A Survey on Large Language Model-based Agents for Statistics and Data
Science | [
"cs.AI",
"cs.CL",
"cs.LG",
"stat.OT"
] | In recent years, data science agents powered by Large Language Models (LLMs), known as "data agents," have shown significant potential to transform the traditional data analysis paradigm. This survey provides an overview of the evolution, capabilities, and applications of LLM-based data agents, highlighting their role ... | {
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2412.14223 | Towards Precise Prediction Uncertainty in GNNs: Refining GNNs with
Topology-grouping Strategy | [
"cs.LG"
] | Recent advancements in graph neural networks (GNNs) have highlighted the critical need of calibrating model predictions, with neighborhood prediction similarity recognized as a pivotal component. Existing studies suggest that nodes with analogous neighborhood prediction similarity often exhibit similar calibration char... | {
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2412.14226 | FedSTaS: Client Stratification and Client Level Sampling for Efficient
Federated Learning | [
"cs.LG",
"stat.ML"
] | Federated learning (FL) is a machine learning methodology that involves the collaborative training of a global model across multiple decentralized clients in a privacy-preserving way. Several FL methods are introduced to tackle communication inefficiencies but do not address how to sample participating clients in each ... | {
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2412.14229 | Transversal PACS Browser API: Addressing Interoperability Challenges in
Medical Imaging Systems | [
"cs.HC",
"cs.CE",
"cs.CV",
"cs.IR"
] | Advances in imaging technologies have revolutionised the medical imaging and healthcare sectors, leading to the widespread adoption of PACS for the storage, retrieval, and communication of medical images. Although these systems have improved operational efficiency, significant challenges remain in effectively retrievin... | {
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2412.14231 | ViTmiX: Vision Transformer Explainability Augmented by Mixed
Visualization Methods | [
"cs.CV"
] | Recent advancements in Vision Transformers (ViT) have demonstrated exceptional results in various visual recognition tasks, owing to their ability to capture long-range dependencies in images through self-attention mechanisms. However, the complex nature of ViT models requires robust explainability methods to unveil th... | {
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2412.14233 | Descriptive Caption Enhancement with Visual Specialists for Multimodal
Perception | [
"cs.CV"
] | Training Large Multimodality Models (LMMs) relies on descriptive image caption that connects image and language. Existing methods either distill the caption from the LMM models or construct the captions from the internet images or by human. We propose to leverage off-the-shelf visual specialists, which were trained fro... | {
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2412.14234 | Syzygy: Dual Code-Test C to (safe) Rust Translation using LLMs and
Dynamic Analysis | [
"cs.SE",
"cs.AI",
"cs.LG",
"cs.PL"
] | Despite extensive usage in high-performance, low-level systems programming applications, C is susceptible to vulnerabilities due to manual memory management and unsafe pointer operations. Rust, a modern systems programming language, offers a compelling alternative. Its unique ownership model and type system ensure memo... | {
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2412.14272 | Split Learning in Computer Vision for Semantic Segmentation Delay
Minimization | [
"cs.CV",
"cs.AI",
"cs.DC",
"cs.IT",
"cs.LG",
"math.IT"
] | In this paper, we propose a novel approach to minimize the inference delay in semantic segmentation using split learning (SL), tailored to the needs of real-time computer vision (CV) applications for resource-constrained devices. Semantic segmentation is essential for applications such as autonomous vehicles and smart ... | {
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2412.14273 | Approximation Schemes for Age of Information Minimization in UAV Grid
Patrols | [
"cs.IT",
"math.IT",
"math.OC"
] | Motivated by the critical need for unmanned aerial vehicles (UAVs) to patrol grid systems in hazardous and dynamically changing environments, this study addresses a routing problem aimed at minimizing the time-average Age of Information (AoI) for edges in general graphs. We establish a lower bound for all feasible patr... | {
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2412.14276 | Fake News Detection: Comparative Evaluation of BERT-like Models and
Large Language Models with Generative AI-Annotated Data | [
"cs.CL",
"cs.AI"
] | Fake news poses a significant threat to public opinion and social stability in modern society. This study presents a comparative evaluation of BERT-like encoder-only models and autoregressive decoder-only large language models (LLMs) for fake news detection. We introduce a dataset of news articles labeled with GPT-4 as... | {
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2412.14283 | PixelMan: Consistent Object Editing with Diffusion Models via Pixel
Manipulation and Generation | [
"cs.CV",
"cs.AI",
"cs.GR"
] | Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving the consistency of objects and background without changing their texture and attributes. Current inference-time methods often rely on DDIM i... | {
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2412.14291 | Projected gradient methods for nonconvex and stochastic optimization:
new complexities and auto-conditioned stepsizes | [
"math.OC",
"cs.LG",
"stat.ML"
] | We present a novel class of projected gradient (PG) methods for minimizing a smooth but not necessarily convex function over a convex compact set. We first provide a novel analysis of the "vanilla" PG method, achieving the best-known iteration complexity for finding an approximate stationary point of the problem. We th... | {
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2412.14294 | TRecViT: A Recurrent Video Transformer | [
"cs.CV",
"cs.LG"
] | We propose a novel block for video modelling. It relies on a time-space-channel factorisation with dedicated blocks for each dimension: gated linear recurrent units (LRUs) perform information mixing over time, self-attention layers perform mixing over space, and MLPs over channels. The resulting architecture TRecViT pe... | {
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2412.14295 | Temporally Consistent Object-Centric Learning by Contrasting Slots | [
"cs.CV",
"cs.AI",
"cs.LG",
"cs.RO"
] | Unsupervised object-centric learning from videos is a promising approach to extract structured representations from large, unlabeled collections of videos. To support downstream tasks like autonomous control, these representations must be both compositional and temporally consistent. Existing approaches based on recurr... | {
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2412.14297 | Distributionally Robust Policy Learning under Concept Drifts | [
"cs.LG",
"stat.ML"
] | Distributionally robust policy learning aims to find a policy that performs well under the worst-case distributional shift, and yet most existing methods for robust policy learning consider the worst-case joint distribution of the covariate and the outcome. The joint-modeling strategy can be unnecessarily conservative ... | {
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2412.14299 | The Multiplex Classification Framework: optimizing multi-label
classifiers through problem transformation, ontology engineering, and model
ensembling | [
"cs.LG"
] | Classification is a fundamental task in machine learning. While conventional methods-such as binary, multiclass, and multi-label classification-are effective for simpler problems, they may not adequately address the complexities of some real-world scenarios. This paper introduces the Multiplex Classification Framework,... | {
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2412.14301 | What Has Been Overlooked in Contrastive Source-Free Domain Adaptation:
Leveraging Source-Informed Latent Augmentation within Neighborhood Context | [
"cs.CV",
"cs.LG"
] | Source-free domain adaptation (SFDA) involves adapting a model originally trained using a labeled dataset ({\em source domain}) to perform effectively on an unlabeled dataset ({\em target domain}) without relying on any source data during adaptation. This adaptation is especially crucial when significant disparities in... | {
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2412.14302 | SAFERec: Self-Attention and Frequency Enriched Model for Next Basket
Recommendation | [
"cs.IR",
"cs.AI"
] | Transformer-based approaches such as BERT4Rec and SASRec demonstrate strong performance in Next Item Recommendation (NIR) tasks. However, applying these architectures to Next-Basket Recommendation (NBR) tasks, which often involve highly repetitive interactions, is challenging due to the vast number of possible item com... | {
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2412.14304 | Multi-OphthaLingua: A Multilingual Benchmark for Assessing and Debiasing
LLM Ophthalmological QA in LMICs | [
"cs.CL",
"cs.AI"
] | Current ophthalmology clinical workflows are plagued by over-referrals, long waits, and complex and heterogeneous medical records. Large language models (LLMs) present a promising solution to automate various procedures such as triaging, preliminary tests like visual acuity assessment, and report summaries. However, LL... | {
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2412.14306 | Closing the Gap: A User Study on the Real-world Usefulness of AI-powered
Vulnerability Detection & Repair in the IDE | [
"cs.SE",
"cs.CR",
"cs.LG"
] | This paper presents the first empirical study of a vulnerability detection and fix tool with professional software developers on real projects that they own. We implemented DeepVulGuard, an IDE-integrated tool based on state-of-the-art detection and fix models, and show that it has promising performance on benchmarks o... | {
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2412.14307 | Race Discrimination in Internet Advertising: Evidence From a Field
Experiment | [
"cs.CY",
"cs.HC",
"cs.SI",
"econ.GN",
"q-fin.EC"
] | We present the results of an experiment documenting racial bias on Meta's Advertising Platform in Brazil and the United States. We find that darker skin complexions are penalized, leading to real economic consequences. For every \$1,000 an advertiser spends on ads with models with light-skin complexions, that advertise... | {
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2412.14308 | Reinforcement Learning from Automatic Feedback for High-Quality Unit
Test Generation | [
"cs.SE",
"cs.LG"
] | Software testing is a crucial but time-consuming aspect of software development, and recently, Large Language Models (LLMs) have gained popularity for automated test case generation. However, because LLMs are trained on vast amounts of open-source code, they often generate test cases that do not adhere to best practice... | {
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2412.14309 | Consistency Matters: Defining Demonstration Data Quality Metrics in
Robot Learning from Demonstration | [
"cs.RO",
"cs.HC"
] | Learning from Demonstration (LfD) empowers robots to acquire new skills through human demonstrations, making it feasible for everyday users to teach robots. However, the success of learning and generalization heavily depends on the quality of these demonstrations. Consistency is often used to indicate quality in LfD, y... | {
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2412.14312 | Stealing That Free Lunch: Exposing the Limits of Dyna-Style
Reinforcement Learning | [
"cs.LG"
] | Dyna-style off-policy model-based reinforcement learning (DMBRL) algorithms are a family of techniques for generating synthetic state transition data and thereby enhancing the sample efficiency of off-policy RL algorithms. This paper identifies and investigates a surprising performance gap observed when applying DMBRL ... | {
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2412.14315 | On the Robustness of Spectral Algorithms for Semirandom Stochastic Block
Models | [
"stat.ML",
"cs.DS",
"cs.LG",
"cs.SI"
] | In a graph bisection problem, we are given a graph $G$ with two equally-sized unlabeled communities, and the goal is to recover the vertices in these communities. A popular heuristic, known as spectral clustering, is to output an estimated community assignment based on the eigenvector corresponding to the second smalle... | {
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2412.14323 | The Role of Handling Attributive Nouns in Improving Chinese-To-English
Machine Translation | [
"cs.CL",
"cs.AI"
] | Translating between languages with drastically different grammatical conventions poses challenges, not just for human interpreters but also for machine translation systems. In this work, we specifically target the translation challenges posed by attributive nouns in Chinese, which frequently cause ambiguities in Englis... | {
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2412.14326 | Covariances for Free: Exploiting Mean Distributions for Federated
Learning with Pre-Trained Models | [
"cs.LG",
"cs.CV"
] | Using pre-trained models has been found to reduce the effect of data heterogeneity and speed up federated learning algorithms. Recent works have investigated the use of first-order statistics and second-order statistics to aggregate local client data distributions at the server and achieve very high performance without... | {
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2412.14327 | Personalized Generative Low-light Image Denoising and Enhancement | [
"cs.CV"
] | While smartphone cameras today can produce astonishingly good photos, their performance in low light is still not completely satisfactory because of the fundamental limits in photon shot noise and sensor read noise. Generative image restoration methods have demonstrated promising results compared to traditional methods... | {
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2412.14328 | Semantic Role Labeling of NomBank Partitives | [
"cs.CL",
"cs.AI"
] | This article is about Semantic Role Labeling for English partitive nouns (5%/REL of the price/ARG1; The price/ARG1 rose 5 percent/REL) in the NomBank annotated corpus. Several systems are described using traditional and transformer-based machine learning, as well as ensembling. Our highest scoring system achieves an F1... | {
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2412.14329 | Embedding Cultural Diversity in Prototype-based Recommender Systems | [
"cs.IR",
"cs.AI",
"cs.CY"
] | Popularity bias in recommender systems can increase cultural overrepresentation by favoring norms from dominant cultures and marginalizing underrepresented groups. This issue is critical for platforms offering cultural products, as they influence consumption patterns and human perceptions. In this work, we address popu... | {
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2412.14333 | Joint Co-Speech Gesture and Expressive Talking Face Generation using
Diffusion with Adapters | [
"cs.CV"
] | Recent advances in co-speech gesture and talking head generation have been impressive, yet most methods focus on only one of the two tasks. Those that attempt to generate both often rely on separate models or network modules, increasing training complexity and ignoring the inherent relationship between face and body mo... | {
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2412.14340 | A Unifying Information-theoretic Perspective on Evaluating Generative
Models | [
"cs.LG",
"cs.AI",
"cs.CV"
] | Considering the difficulty of interpreting generative model output, there is significant current research focused on determining meaningful evaluation metrics. Several recent approaches utilize "precision" and "recall," borrowed from the classification domain, to individually quantify the output fidelity (realism) and ... | {
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2412.14350 | Gaussian-convolution-invariant shell approximation to
spherically-symmetric functions | [
"math.NA",
"cs.CE",
"cs.NA",
"math-ph",
"math.MP",
"q-bio.BM"
] | We develop a class of functions Omega_N(x; mu, nu) in N-dimensional space concentrated around a spherical shell of the radius mu and such that, being convoluted with an isotropic Gaussian function, these functions do not change their expression but only a value of its 'width' parameter, nu. Isotropic Gaussian functions... | {
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2412.14351 | Is Peer-Reviewing Worth the Effort? | [
"cs.CL",
"cs.AI"
] | How effective is peer-reviewing in identifying important papers? We treat this question as a forecasting task. Can we predict which papers will be highly cited in the future based on venue and "early returns" (citations soon after publication)? We show early returns are more predictive than venue. Finally, we end with ... | {
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2412.14352 | A Survey on LLM Inference-Time Self-Improvement | [
"cs.CL"
] | Techniques that enhance inference through increased computation at test-time have recently gained attention. In this survey, we investigate the current state of LLM Inference-Time Self-Improvement from three different perspectives: Independent Self-improvement, focusing on enhancements via decoding or sampling methods;... | {
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2412.14354 | State Space Models are Strong Text Rerankers | [
"cs.CL",
"cs.IR"
] | Transformers dominate NLP and IR; but their inference inefficiencies and challenges in extrapolating to longer contexts have sparked interest in alternative model architectures. Among these, state space models (SSMs) like Mamba offer promising advantages, particularly $O(1)$ time complexity in inference. Despite their ... | {
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2412.14355 | Enabling Realtime Reinforcement Learning at Scale with Staggered
Asynchronous Inference | [
"cs.LG",
"cs.AI"
] | Realtime environments change even as agents perform action inference and learning, thus requiring high interaction frequencies to effectively minimize regret. However, recent advances in machine learning involve larger neural networks with longer inference times, raising questions about their applicability in realtime ... | {
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2412.14359 | Dynamic semantic VSLAM with known and unknown objects | [
"cs.CV"
] | Traditional Visual Simultaneous Localization and Mapping (VSLAM) systems assume a static environment, which makes them ineffective in highly dynamic settings. To overcome this, many approaches integrate semantic information from deep learning models to identify dynamic regions within images. However, these methods face... | {
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2412.14363 | ResQ: Mixed-Precision Quantization of Large Language Models with
Low-Rank Residuals | [
"cs.LG",
"cs.CL"
] | Post-training quantization (PTQ) of large language models (LLMs) holds the promise in reducing the prohibitive computational cost at inference time. Quantization of all weight, activation and key-value (KV) cache tensors to 4-bit without significantly degrading generalizability is challenging, due to the high quantizat... | {
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2412.14366 | Surrealistic-like Image Generation with Vision-Language Models | [
"cs.CV",
"cs.AI"
] | Recent advances in generative AI make it convenient to create different types of content, including text, images, and code. In this paper, we explore the generation of images in the style of paintings in the surrealism movement using vision-language generative models, including DALL-E, Deep Dream Generator, and DreamSt... | {
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2412.14367 | Implementing TD3 to train a Neural Network to fly a Quadcopter through
an FPV Gate | [
"cs.RO",
"cs.LG"
] | Deep Reinforcement learning has shown to be a powerful tool for developing policies in environments where an optimal solution is unclear. In this paper, we attempt to apply Twin Delayed Deep Deterministic Policy Gradients to train a neural network to act as a velocity controller for a quadcopter. The quadcopter's objec... | {
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2412.14368 | Memorization Over Reasoning? Exposing and Mitigating Verbatim
Memorization in Large Language Models' Character Understanding Evaluation | [
"cs.CL"
] | Recently, Large Language Models (LLMs) have shown impressive performance in character understanding tasks, such as analyzing the roles, personalities, and relationships of fictional characters. However, the extensive pre-training corpora used by LLMs raise concerns that they may rely on memorizing popular fictional wor... | {
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2412.14371 | SEREP: Semantic Facial Expression Representation for Robust In-the-Wild
Capture and Retargeting | [
"cs.CV",
"cs.GR",
"cs.LG"
] | Monocular facial performance capture in-the-wild is challenging due to varied capture conditions, face shapes, and expressions. Most current methods rely on linear 3D Morphable Models, which represent facial expressions independently of identity at the vertex displacement level. We propose SEREP (Semantic Expression Re... | {
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2412.14372 | Python Agent in Ludii | [
"cs.AI"
] | Ludii is a Java general game system with a considerable number of board games, with an API for developing new agents and a game description language to create new games. To improve versatility and ease development, we provide Python interfaces for agent programming. This allows the use of Python modules to implement ge... | {
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2412.14373 | ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram
Language Modeling | [
"cs.CL",
"eess.SP"
] | Large Language Models (LLMs) have shown remarkable adaptability across domains beyond text, specifically electrocardiograms (ECGs). More specifically, there is a growing body of work exploring the task of generating text from a multi-channeled ECG and corresponding textual prompt. Current approaches typically involve p... | {
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2412.14374 | Scaling Deep Learning Training with MPMD Pipeline Parallelism | [
"cs.DC",
"cs.LG",
"cs.PL"
] | We present JaxPP, a system for efficiently scaling the training of large deep learning models with flexible pipeline parallelism. We introduce a seamless programming model that allows implementing user-defined pipeline schedules for gradient accumulation. JaxPP automatically distributes tasks, corresponding to pipeline... | {
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2412.14375 | Network Modelling in Analysing Cyber-related Graphs | [
"cs.SI"
] | In order to improve the resilience of computer infrastructure against cyber attacks and finding ways to mitigate their impact we need to understand their structure and dynamics. Here we propose a novel network-based influence spreading model to investigate event trajectories or paths in various types of attack and caus... | {
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2412.14379 | HA-RDet: Hybrid Anchor Rotation Detector for Oriented Object Detection | [
"cs.CV"
] | Oriented object detection in aerial images poses a significant challenge due to their varying sizes and orientations. Current state-of-the-art detectors typically rely on either two-stage or one-stage approaches, often employing Anchor-based strategies, which can result in computationally expensive operations due to th... | {
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2412.14382 | Balans: Multi-Armed Bandits-based Adaptive Large Neighborhood Search for
Mixed-Integer Programming Problem | [
"cs.AI",
"cs.LG",
"math.OC"
] | Mixed-Integer Programming (MIP) is a powerful paradigm for modeling and solving various important combinatorial optimization problems. Recently, learning-based approaches have shown potential to speed up MIP solving via offline training that then guides important design decisions during search. However, a significant d... | {
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2412.14384 | I0T: Embedding Standardization Method Towards Zero Modality Gap | [
"cs.LG",
"cs.AI",
"cs.CV"
] | Contrastive Language-Image Pretraining (CLIP) enables zero-shot inference in downstream tasks such as image-text retrieval and classification. However, recent works extending CLIP suffer from the issue of modality gap, which arises when the image and text embeddings are projected to disparate manifolds, deviating from ... | {
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2412.14387 | Clinical Trials Ontology Engineering with Large Language Models | [
"cs.AI"
] | Managing clinical trial information is currently a significant challenge for the medical industry, as traditional methods are both time-consuming and costly. This paper proposes a simple yet effective methodology to extract and integrate clinical trial data in a cost-effective and time-efficient manner. Allowing the me... | {
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2412.14392 | Nemesis: Noise-randomized Encryption with Modular Efficiency and Secure
Integration in Machine Learning Systems | [
"cs.CR",
"cs.LG"
] | Machine learning (ML) systems that guarantee security and privacy often rely on Fully Homomorphic Encryption (FHE) as a cornerstone technique, enabling computations on encrypted data without exposing sensitive information. However, a critical limitation of FHE is its computational inefficiency, making it impractical fo... | {
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2412.14396 | Fingerprinting Codes Meet Geometry: Improved Lower Bounds for Private
Query Release and Adaptive Data Analysis | [
"cs.DS",
"cs.CR",
"cs.LG"
] | Fingerprinting codes are a crucial tool for proving lower bounds in differential privacy. They have been used to prove tight lower bounds for several fundamental questions, especially in the ``low accuracy'' regime. Unlike reconstruction/discrepancy approaches however, they are more suited for query sets that arise nat... | {
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2412.14401 | The One RING: a Robotic Indoor Navigation Generalist | [
"cs.RO",
"cs.CV"
] | Modern robots vary significantly in shape, size, and sensor configurations used to perceive and interact with their environments. However, most navigation policies are embodiment-specific; a policy learned using one robot's configuration does not typically gracefully generalize to another. Even small changes in the bod... | {
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2412.14403 | Short-term wind forecasting via surface pressure measurements:
stochastic modeling and sensor placement | [
"physics.flu-dyn",
"cs.SY",
"eess.SY",
"math.DS",
"physics.ao-ph"
] | We propose a short-term wind forecasting framework for predicting real-time variations in atmospheric turbulence based on nacelle-mounted anemometer and ground-level air-pressure measurements. Our approach combines linear stochastic estimation and Kalman filtering algorithms to assimilate and process real-time field me... | {
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2412.14404 | Enhancing Fingerprint Recognition Systems: Comparative Analysis of
Biometric Authentication Algorithms and Techniques for Improved Accuracy and
Reliability | [
"cs.CV"
] | Fingerprint recognition systems stand as pillars in the realm of biometric authentication, providing indispensable security measures across various domains. This study investigates integrating Convolutional Neural Networks (CNNs) with Gabor filters to improve fingerprint recognition accuracy and robustness. Leveraging ... | {
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2412.14405 | ChainRank-DPO: Chain Rank Direct Preference Optimization for LLM Rankers | [
"cs.IR"
] | Large language models (LLMs) have demonstrated remarkable effectiveness in text reranking through works like RankGPT, leveraging their human-like reasoning about relevance. However, supervised fine-tuning for ranking often diminishes these models' general-purpose capabilities, including the crucial reasoning abilities ... | {
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2412.14409 | Multi-task Representation Learning for Mixed Integer Linear Programming | [
"cs.AI",
"cs.LG",
"math.OC"
] | Mixed Integer Linear Programs (MILPs) are highly flexible and powerful tools for modeling and solving complex real-world combinatorial optimization problems. Recently, machine learning (ML)-guided approaches have demonstrated significant potential in improving MILP-solving efficiency. However, these methods typically r... | {
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2412.14414 | In-Group Love, Out-Group Hate: A Framework to Measure Affective
Polarization via Contentious Online Discussions | [
"cs.SI",
"cs.CL",
"cs.CY"
] | Affective polarization, the emotional divide between ideological groups marked by in-group love and out-group hate, has intensified in the United States, driving contentious issues like masking and lockdowns during the COVID-19 pandemic. Despite its societal impact, existing models of opinion change fail to account for... | {
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2412.14415 | DriveGPT: Scaling Autoregressive Behavior Models for Driving | [
"cs.LG",
"cs.AI",
"cs.CV",
"cs.RO"
] | We present DriveGPT, a scalable behavior model for autonomous driving. We model driving as a sequential decision-making task, and learn a transformer model to predict future agent states as tokens in an autoregressive fashion. We scale up our model parameters and training data by multiple orders of magnitude, enabling ... | {
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2412.14417 | Cutting Sequence Diffuser: Sim-to-Real Transferable Planning for Object
Shaping by Grinding | [
"cs.RO"
] | Automating object shaping by grinding with a robot is a crucial industrial process that involves removing material with a rotating grinding belt. This process generates removal resistance depending on such process conditions as material type, removal volume, and robot grinding posture, all of which complicate the analy... | {
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2412.14418 | An Immersive Multi-Elevation Multi-Seasonal Dataset for 3D
Reconstruction and Visualization | [
"cs.CV",
"cs.LG"
] | Significant progress has been made in photo-realistic scene reconstruction over recent years. Various disparate efforts have enabled capabilities such as multi-appearance or large-scale modeling; however, there lacks a welldesigned dataset that can evaluate the holistic progress of scene reconstruction. We introduce a ... | {
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2412.14422 | Enhancing Diffusion Models for High-Quality Image Generation | [
"cs.CV",
"cs.AI",
"cs.LG"
] | This report presents the comprehensive implementation, evaluation, and optimization of Denoising Diffusion Probabilistic Models (DDPMs) and Denoising Diffusion Implicit Models (DDIMs), which are state-of-the-art generative models. During inference, these models take random noise as input and iteratively generate high-q... | {
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} |
2412.14424 | FedPIA -- Permuting and Integrating Adapters leveraging Wasserstein
Barycenters for Finetuning Foundation Models in Multi-Modal Federated
Learning | [
"cs.CV",
"cs.AI",
"cs.LG"
] | Large Vision-Language Models typically require large text and image datasets for effective fine-tuning. However, collecting data from various sites, especially in healthcare, is challenging due to strict privacy regulations. An alternative is to fine-tune these models on end-user devices, such as in medical clinics, wi... | {
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} |
2412.14426 | All-in-One Tuning and Structural Pruning for Domain-Specific LLMs | [
"cs.CL",
"cs.AI"
] | Existing pruning techniques for large language models (LLMs) targeting domain-specific applications typically follow a two-stage process: pruning the pretrained general-purpose LLMs and then fine-tuning the pruned LLMs on specific domains. However, the pruning decisions, derived from the pretrained weights, remain unch... | {
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} |
2412.14428 | WildSAT: Learning Satellite Image Representations from Wildlife
Observations | [
"cs.CV",
"cs.LG",
"q-bio.QM"
] | What does the presence of a species reveal about a geographic location? We posit that habitat, climate, and environmental preferences reflected in species distributions provide a rich source of supervision for learning satellite image representations. We introduce WildSAT, which pairs satellite images with millions of ... | {
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} |
2412.14430 | Balanced Gradient Sample Retrieval for Enhanced Knowledge Retention in
Proxy-based Continual Learning | [
"cs.LG"
] | Continual learning in deep neural networks often suffers from catastrophic forgetting, where representations for previous tasks are overwritten during subsequent training. We propose a novel sample retrieval strategy from the memory buffer that leverages both gradient-conflicting and gradient-aligned samples to effecti... | {
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} |
2412.14432 | IntroStyle: Training-Free Introspective Style Attribution using
Diffusion Features | [
"cs.CV",
"eess.IV"
] | Text-to-image (T2I) models have gained widespread adoption among content creators and the general public. However, this has sparked significant concerns regarding data privacy and copyright infringement among artists. Consequently, there is an increasing demand for T2I models to incorporate mechanisms that prevent the ... | {
"Other": 0,
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} |
2412.14435 | Cherry-Picking in Time Series Forecasting: How to Select Datasets to
Make Your Model Shine | [
"cs.LG",
"cs.AI"
] | The importance of time series forecasting drives continuous research and the development of new approaches to tackle this problem. Typically, these methods are introduced through empirical studies that frequently claim superior accuracy for the proposed approaches. Nevertheless, concerns are rising about the reliabilit... | {
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} |
2412.14436 | ORBIT: Cost-Effective Dataset Curation for Large Language Model Domain
Adaptation with an Astronomy Case Study | [
"cs.CL",
"cs.AI"
] | Recent advances in language modeling demonstrate the need for high-quality domain-specific training data, especially for tasks that require specialized knowledge. General-purpose models, while versatile, often lack the depth needed for expert-level tasks because of limited domain-specific information. Domain adaptation... | {
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} |
2412.14442 | EPN: An Ego Vehicle Planning-Informed Network for Target Trajectory
Prediction | [
"cs.RO"
] | Trajectory prediction plays a crucial role in improving the safety of autonomous vehicles. However, due to the highly dynamic and multimodal nature of the task, accurately predicting the future trajectory of a target vehicle remains a significant challenge. To address this challenge, we propose an Ego vehicle Planning-... | {
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} |
2412.14444 | GenHMR: Generative Human Mesh Recovery | [
"cs.CV",
"cs.AI",
"cs.GR",
"cs.LG"
] | Human mesh recovery (HMR) is crucial in many computer vision applications; from health to arts and entertainment. HMR from monocular images has predominantly been addressed by deterministic methods that output a single prediction for a given 2D image. However, HMR from a single image is an ill-posed problem due to dept... | {
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} |
2412.14446 | VLM-AD: End-to-End Autonomous Driving through Vision-Language Model
Supervision | [
"cs.CV",
"cs.LG"
] | Human drivers rely on commonsense reasoning to navigate diverse and dynamic real-world scenarios. Existing end-to-end (E2E) autonomous driving (AD) models are typically optimized to mimic driving patterns observed in data, without capturing the underlying reasoning processes. This limitation constrains their ability to... | {
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} |
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