Search: “models”

Low-Latency Video Anonymization for Crowd Anomaly Detection: Privacy Versus Performance

arXiv:2410.18717v2 Announce Type: replace Abstract: Recent advancements in artificial intelligence hold ample potential for monitoring applications using surveillance cameras. However, concerns about

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Mixture Prototype Flow Matching for Open-Set Supervised Anomaly Detection

DGX agent

arXiv:2605.02438v1 Announce Type: new Abstract: Open-set supervised anomaly detection (OSAD) aims to identify unseen anomalies using limited anomalous supervision. However, existing prototype-based me

researcharxiv-cs-cv

5 May 2026

Multi-Dataset Cross-Domain Knowledge Distillation for Unified Medical Image Segmentation, Classification, and Detection

arXiv:2605.01563v1 Announce Type: new Abstract: We propose a unified cross-domain transfer learning framework that leverages knowledge from multiple heterogeneous medical imaging datasets to improve p

Multi-Scale Gaussian-Language Map for Zero-shot Embodied Navigation and Reasoning

arXiv:2605.01736v1 Announce Type: new Abstract: Understanding the geometric and semantic structure of environments is essential for embodied navigation and reasoning. Existing semantic mapping methods

Multimodal Data Curation Through Ranked Retrieval

arXiv:2605.01163v1 Announce Type: cross Abstract: Shared embedding spaces are widely used for multimodal search and data curation. In practice, two problems often limit how well this works. First, emb

safetyarxiv-cs-lg

Local Ai

Neural Cellular Automata: From Cells to Pixels

arXiv:2506.22899v3 Announce Type: replace Abstract: Neural Cellular Automata (NCAs) are bio-inspired dynamical systems in which identical cells iteratively apply a learned local update rule to self-or

local-aiarxiv-cs-cv

Tutorials

On the Characterization and Limits of 4D Radar for Aided Inertial Navigation

arXiv:2605.01773v1 Announce Type: new Abstract: Frequency Modulated Continuous Wave (FMCW) radar is a promising sensor for aided inertial navigation, due to its robustness in environments that challen

tutorialsarxiv-cs-ro

Agents

Outbidding and Outbluffing Elite Humans: Mastering Liar's Poker via Self-Play and Reinforcement Learning

arXiv:2511.03724v3 Announce Type: replace Abstract: AI researchers have long focused on poker-like games as a testbed for environments characterized by multi-player dynamics, imperfect information, an

agentsarxiv-cs-ai

Parking Assistance for Trailer-Truck Transport Vehicles Using Sensor Fusion and Motion Planning

arXiv:2605.02716v1 Announce Type: new Abstract: Autonomous driving technology has rapidly evolved over the past decade, offering significant improvements in transportation efficiency, safety, and cost

safetyarxiv-cs-ro

Patient-Specific Optimization for Mandibular Reconstruction Planning with Enhanced Bone Union

arXiv:2605.01084v1 Announce Type: new Abstract: Mandibular reconstruction with vascularized bone grafts is complicated by donor-host nonunion, and current virtual surgical planning produces a geometri

Pedagogical Promise and Peril of AI: A Text Mining Analysis of ChatGPT Research Discussions in Programming Education

arXiv:2605.00361v1 Announce Type: cross Abstract: GenAI systems such as ChatGPT are increasingly discussed in programming education, but the ways in which the research literature conceptualizes and fr

applicationsarxiv-cs-ai

Principles and Guidelines for Randomized Controlled Trials in AI Evaluation

arXiv:2605.02050v1 Announce Type: cross Abstract: This work establishes a foundational framework for standardizing AI evaluation RCTs (sometimes called human uplift studies). Drawing on established ex

Profile-Specific 3DMM Regression from a Single Lateral Face Image

arXiv:2605.01746v1 Announce Type: new Abstract: Single-image 3D face reconstruction is a core problem in computer vision, with important clinical applications such as cephalometric landmark analysis i

ProPACT: A Proactive AI-Driven Adaptive Collaborative Tutor for Pair Programming

arXiv:2605.02703v1 Announce Type: cross Abstract: Effective pair programming depends on coordination of attention, cognitive effort, and joint regulation over time, yet most adaptive learning systems

safetyarxiv-cs-lg

Provable Benefit of Curriculum in Transformer Tree-Reasoning Post-Training

arXiv:2511.07372v3 Announce Type: replace Abstract: Recent curriculum techniques in the post-training stage of LLMs have been empirically observed to outperform non-curriculum approaches in improving

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

arXiv:2602.02958v4 Announce Type: replace Abstract: Despite rapid progress in autoregressive video diffusion, an emerging system algorithm bottleneck limits both deployability and generation capabilit

hardwarearxiv-cs-lg

Quantifying Multimodal Capabilities: Formal Generalization Guarantees in Pairwise Metric Learning

arXiv:2605.01424v1 Announce Type: new Abstract: Multimodal learning leverages the integration of diverse data modalities to enhance performance in complex tasks. Yet, it frequently encounters incomple

applicationsarxiv-cs-lg

RA-CMF: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction

arXiv:2605.00901v1 Announce Type: new Abstract: The use of CT imaging is important for screening, diagnosis, therapy planning, and prognosis of lung cancers. Unfortunately, due to differences in imagi

ReFRAME or Remain: Unsupervised Lexical Semantic Change Detection with Frame Semantics

arXiv:2602.04514v3 Announce Type: replace Abstract: The majority of contemporary computational methods for lexical semantic change (LSC) detection are based on neural embedding distributional represen

researcharxiv-cs-cl

ReMedi: Reasoner for Medical Clinical Prediction

arXiv:2605.01474v1 Announce Type: new Abstract: Predicting future clinical outcomes from electronic health records (EHR) remains challenging due to the complexity and heterogeneity of patient data. LL

applicationsarxiv-cs-cl

Robo3R: Enhancing Robotic Manipulation with Accurate Feed-Forward 3D Reconstruction

arXiv:2602.10101v2 Announce Type: replace Abstract: 3D spatial perception is fundamental to generalizable robotic manipulation, yet obtaining reliable, high-quality 3D geometry remains challenging. De

safetyarxiv-cs-ro

Robotic Affection -- Opportunities of AI-based haptic interactions to improve social robotic touch through a multi-deep-learning approach

arXiv:2605.02538v1 Announce Type: cross Abstract: Despite the advancement in robotic grasping and dexterity through haptic information, affective social touch, such as handshaking or reassuring stroki

researcharxiv-cs-ro

Self-Supervised Spatial And Zero-Shot Angular Super-Resolution by Spatial-Angular Implicit Representation For Rotating-View SNR-Efficient Diffusion MRI

arXiv:2605.02575v1 Announce Type: new Abstract: Rotating-view thick-slice acquisition is highly SNR-efficient for mesoscale diffusion MRI (dMRI) but requires numerous rotating views to satisfy Nyquist

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts

arXiv:2510.22628v2 Announce Type: replace-cross Abstract: This paper presents a real-time modular defense system named Sentra-Guard. The system detects and mitigates jailbreak and prompt injection att

safetyarxiv-cs-ai

Short window attention enables long-term memorization

arXiv:2509.24552v3 Announce Type: replace Abstract: Recent works show that hybrid architectures combining local sliding window attention layers and global attention layers outperform either of these a

SIFT-VTON: Geometric Correspondence Supervision on Cross-Attention for Virtual Try-On

arXiv:2605.01296v1 Announce Type: new Abstract: Diffusion-based virtual try-on methods achieve photorealistic synthesis through cross-attention mechanisms that transfer garment features to target body

Agents

Sim-to-Real Transfer and Robustness Evaluation of Reinforcement Learning Control with Integrated Perception on an ASV for Floating Waste Capture

arXiv:2605.02529v1 Announce Type: new Abstract: Autonomous surface vessels for floating-waste removal operate under varying hydrodynamics, external disturbances, and challenging water-surface percepti

agentsarxiv-cs-ro

Skeleton-Based Posture Classification to Promote Safer Walker-Assisted Gait in Older Adults

arXiv:2605.00890v1 Announce Type: new Abstract: Falls among older adults are a significant public health concern, leading to severe injuries, loss of independence, and increased healthcare costs. This

applicationsarxiv-cs-cv

Sparse Representation Learning for Vessels

arXiv:2605.01382v1 Announce Type: new Abstract: Analyzing human vasculature and vessel-like, tubular structures, such as airways, is crucial for disease diagnosis and treatment. Current methods often

STABLEVAL: Disagreement-Aware and Stable Evaluation of AI Systems

arXiv:2605.02122v1 Announce Type: new Abstract: Human evaluation remains the primary standard for assessing modern AI systems, yet annotator disagreement, bias, and variability make system rankings fr

safetyarxiv-cs-lg

SurgTEMP: Temporal-Aware Surgical Video Question Answering with Text-guided Visual Memory for Laparoscopic Cholecystectomy

arXiv:2603.29962v3 Announce Type: replace Abstract: Surgical procedures are inherently complex and risky, requiring extensive expertise and constant focus to navigate evolving intraoperative scenes. C

SynPAIN: A Synthetic Dataset of Pain and Non-Pain Facial Expressions

arXiv:2507.19673v3 Announce Type: replace Abstract: Accurate pain assessment in patients with limited ability to communicate, such as older adults with severe dementia, represents a critical healthcar

Agents

TADI: Tool-Augmented Drilling Intelligence via Agentic LLM Orchestration over Heterogeneous Wellsite Data

arXiv:2605.00060v1 Announce Type: new Abstract: We present TADI (Tool-Augmented Drilling Intelligence), an agentic AI system that transforms drilling operational data into evidence-based analytical in

agentsarxiv-cs-ai

The (Marginal) Value of a Search Ad: An Online Causal Framework for Repeated Second-price Auctions

arXiv:2605.01756v1 Announce Type: cross Abstract: Existing auto-bidding algorithms in digital advertising often treat the value of an ad opportunity as the revenue obtained when an ad is shown and/or

The Quantization Trap: Breaking Linear Scaling Laws in Multi-Hop Reasoning

arXiv:2602.13595v2 Announce Type: replace Abstract: Neural scaling laws provide a predictable recipe for AI advancement: reducing numerical precision should linearly improve computational efficiency a

hardwarearxiv-cs-ai

Token-Efficient Change Detection in LLM APIs

arXiv:2602.11083v2 Announce Type: replace Abstract: Remote change detection in LLMs is a difficult problem. Existing methods are either too expensive for deployment at scale, or require initial white-

Unbox Responsible GeoAI: Navigating Climate Extreme and Disaster Mapping

arXiv:2605.00315v1 Announce Type: cross Abstract: As climate extreme and disaster events become more frequent and intense, Geospatial Artificial Intelligence (GeoAI) has emerged as a transformative ap

researcharxiv-cs-ai

Local Ai

UnGAP: Uncertainty-Guided Affine Prompting for Real-Time Crack Segmentation

arXiv:2605.02380v1 Announce Type: new Abstract: Real-time crack segmentation is vital for structural health monitoring but is plagued by aleatoric uncertainties arising from varying lighting, blur, an

local-aiarxiv-cs-cv

Unifying Deep Stochastic Processes for Image Enhancement

arXiv:2605.01568v1 Announce Type: new Abstract: Deep stochastic processes have recently become a central paradigm for image enhancement, with many methods explicitly conditioning the stochastic trajec

VoxAfford: Multi-Scale Voxel-Token Fusion for Open-Vocabulary 3D Affordance Detection

arXiv:2605.01365v1 Announce Type: new Abstract: Open-vocabulary 3D affordance detection requires localizing interaction regions on point clouds given novel affordance descriptions. Recent methods exte

Adaptive Node Feature Selection For Graph Neural Networks

arXiv:2510.03096v2 Announce Type: replace Abstract: We propose an adaptive node feature selection approach for graph neural networks (GNNs) that identifies and removes unnecessary features during trai

Adaptive Querying with AI Persona Priors

arXiv:2605.00696v1 Announce Type: cross Abstract: We study adaptive querying for learning user-dependent quantities of interest, such as responses to held-out items and psychometric indicators, within

researcharxiv-cs-cl

Agent Capsules: Quality-Gated Granularity Control for Multi-Agent LLM Pipelines

arXiv:2605.00410v1 Announce Type: new Abstract: A multi-agent pipeline with N agents typically issues N LLM calls per run. Merging agents into fewer calls (compound execution) promises token savings,

safetyarxiv-cs-cl

AIDA-ReID: Adaptive Intermediate Domain Adaptation for Generalizable and Source-Free Person Re-Identification

arXiv:2605.00111v1 Announce Type: new Abstract: Person re-identification (Re-ID) aims to match images of the same individual across non-overlapping camera views and remains challenging due to domain s

Boosting multimodal inference performance by >10% with a single Python dictionary

This Modal blog post describes a performance optimization technique for multimodal AI inference that achieves over 10% improvement through a simple Python dictionary-based approach. The article likely

hardwaremodal-blog

Local Ai

Cloud Is Closer Than It Appears: Revisiting the Tradeoffs of Distributed Real-Time Inference

arXiv:2605.00005v1 Announce Type: new Abstract: The increasing deployment of deep neural networks (DNNs) in cyber-physical systems (CPS) enhances perception fidelity, but imposes substantial computati

local-aiarxiv-cs-lg

Directed Social Regard: Surfacing Targeted Advocacy, Opposition, Aid, Harms, and Victimization in Online Media

arXiv:2605.00776v1 Announce Type: new Abstract: The language in online platforms, influence operations, and political rhetoric frequently directs a mix of pro-social sentiment (e.g., advocacy, helpful

researcharxiv-cs-cl

DPU or GPU for Accelerating Neural Networks Inference -- Why not both? Split CNN Inference

arXiv:2605.00174v1 Announce Type: cross Abstract: Video and image streaming on edge devices requires low latency. To address this, Neural Networks (NNs) are widely used, and prior work mainly focuses

hardwarearxiv-cs-cv