Search: “local-ai”

CMAMBADEPTH: Self-supervised Monocular Depth Estimation with Channel Mamba and Hybrid Attention

arXiv:2609.24494v1 Announce Type: new Abstract: Accurate monocular depth estimation serves as a core enabler for single camera scene understanding. However, existing self-supervised monocular depth es

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Contrastive World Models

DGX agent

arXiv:2609.22175v1 Announce Type: cross Abstract: World models trained via pixel reconstruction can struggle in visually complex environments, where irrelevant information dominates the objective and

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22 Sept 2026

Corrective Forcing: Unified Post-Training for Diffusions and Flows in Generative Speech Enhancement

arXiv:2609.24651v1 Announce Type: new Abstract: Diffusion and flow models, as promising generative paradigms for speech enhancement, face a training--inference mismatch: training uses analytical path

D-JEPA: A Decision-Aligned Latent World Model

arXiv:2609.24749v1 Announce Type: cross Abstract: Latent world models predict the consequences of actions, but accurate prediction does not guarantee that latent distance reflects which candidate will

Dissecting Agentic Forensics: The Role of Triage, Prompting, and Evidence Arbitration in Open-World Fake Image Detection

arXiv:2609.24359v1 Announce Type: new Abstract: Image forensics is increasingly an open-world problem: manipulations range from fully synthetic images to localized edits, splicing and swapping, while

FedMust: Semi-supervised Multi-task Student-Teacher Federated Learning for Multi-organ CT Segmentation

arXiv:2609.24627v1 Announce Type: new Abstract: Multi-organ segmentation using deep learning requires large amounts of annotated patient data; however, institutions often lack sufficiently large and d

HDMamba-YOLO: Efficient State-Space Perception and Local Spatial Reconstruction for UAV Small Object

arXiv:2609.23061v1 Announce Type: new Abstract: Small-object detection in UAV imagery is challenged by weak visual evidence, ambiguous boundaries, dense object distributions, and complex backgrounds.

If You Hear It, Help Find It: Orthogonal Knowledge Distillation for Open-Vocabulary Audio-Visual Event Localization

arXiv:2609.23376v1 Announce Type: cross Abstract: Open-vocabulary audio-visual event localization (OV-AVEL) grounds a text-queried event in time from video, audio, and language. The supervision source

Joint Domain-Class Modeling for Federated Learning Under Feature Skew

arXiv:2609.22932v1 Announce Type: new Abstract: Federated learning (FL) enables collaborative model training without centralizing private data, but performance often degrades under feature skew: clien

Knowledge Graph-Augmented Ambient AI for Clinical Note Generation

arXiv:2609.22239v1 Announce Type: new Abstract: Ambient AI is increasingly adopted in healthcare to automatically generate clinical notes from patient-clinician conversations, with the potential to su

Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

arXiv:2609.24882v1 Announce Type: new Abstract: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from hig

LiAuto-MindViT: A Hybrid Vision Backbone with Adaptive Bidirectional Mamba

arXiv:2609.24337v1 Announce Type: new Abstract: While Mamba-based models have shown strong potential for long sequence modeling, adapting them to vision is challenging due to the requirement of local

Look Where It Counts: A Free, Label-Free Visual Evidence Signal for Fine-Grained Vision-Language Reasoning

arXiv:2609.24244v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) fail at fine-grained visual questions less because they cannot reason than because they never see the evidence:

LoopCD: Loop-wise Contrastive Decoding for Improving Reasoning in Looped Language Models

arXiv:2609.24196v1 Announce Type: new Abstract: Looped Language Models (LoopLMs) perform 'latent reasoning' by recursively refining internal latent representations with shared weights, offering a more

MarsRecon: Self-Supervised and Multimodal Surface Representations for Mars

arXiv:2609.22379v1 Announce Type: new Abstract: High-resolution orbital imagery offers a rich record of the Martian surface, but sparse geological labels limit supervised representation learning. We p

ME-Brain-1.0: Memory, Cognition and Action for Evolving Embodied Intelligence

arXiv:2609.24271v1 Announce Type: new Abstract: Current embodied systems largely rely on pretrained capabilities that remain fixed after deployment, limiting their ability to learn from physical inter

ME-VLM:A Unified VLM for Embodied Cognition and Agent Coordination

arXiv:2609.24526v1 Announce Type: new Abstract: Physical AI requires models to ground visual and linguistic understanding in real-world environments while accounting for environmental constraints and

Measuring the Assistant's Harmlessness Preferences on the User Turn

arXiv:2609.23935v1 Announce Type: new Abstract: Post-training turns a general next-token predictor into a chat model with a persistent assistant persona. If that persona is a character the model plays

Neural Residual Modeling for Scientific Data Compression under Guaranteed Error Bounds

arXiv:2609.23185v1 Announce Type: new Abstract: Lossy compression of scientific simulation data increasingly relies on learned, latent-space architectures such as Residual Vector Quantization (RVQ), w

ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation

arXiv:2609.23950v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition,

Pharmacokinetic State Space Models for Unbiased Prediction of Haemodynamic Collapse

arXiv:2609.24338v1 Announce Type: new Abstract: An Intraoperative Hypotension (IOH) event is a frequent complication during administration of general anaesthesia with serious downstream consequences,

PileBelief: Persistent Physical State for Interaction-Driven World Modeling

arXiv:2609.22858v1 Announce Type: new Abstract: World models allow robots to anticipate action consequences before execution. This capability is especially valuable in excavation, where each scoop res

PosEviLoc: Position-Conditioned Spatial Evidence for Language-Based 3D Localization

arXiv:2609.23534v1 Announce Type: new Abstract: Language-based 3D localization retrieves the point-cloud submap containing a target position from descriptions of nearby objects and their spatial relat

Provably Efficient Reinforcement Learning in Continuous-Time Episodic MDPs with Poisson Decision Epochs

arXiv:2609.23127v1 Announce Type: new Abstract: Many real-world reinforcement learning (RL) problems evolve in continuous time, where decisions occur at irregular, event-driven intervals rather than a

Reconstructed holograms and explanation-aware evaluation for low-cost computational pollen analysis in veterinary cytology

arXiv:2609.23017v1 Announce Type: new Abstract: Automated pollen analysis supports veterinary cytology, but brightfield microscopy is costlier and more complex than lens-less digital in-line holograph

Risk-Aware Motion Planning and Control under Unknown Dynamics with Hybrid Observations

arXiv:2609.23792v1 Announce Type: new Abstract: We consider robotic motion planning and control under unknown dynamics with hybrid state observations, where state measurements are available only in pa

RoboTalk: Learning Multi-Robot Communication and Coordination from Multimodal Demonstrations

arXiv:2609.23997v1 Announce Type: new Abstract: Multi-robot collaboration could enable more efficient and scalable solutions to complex robotic tasks, but collaboration under partial observability rem

SAGE: Optimal-Stopping Peer Selection for Decentralised Federated Learning

arXiv:2609.23773v1 Announce Type: cross Abstract: Decentralised federated learning replaces server aggregation with peer-to-peer model exchange, making collaborator selection a local decision under un

SCALE: Simulation-Calibrated Amortized Learning for Energy Materials (A hybrid architecture connecting deterministic modeling, real-world data, and transformer-scale inference for accelerated energy-materials discovery)

arXiv:2609.22233v1 Announce Type: new Abstract: Energy systems face converging pressures for security, affordability, resilience, and sustainability, creating a need for faster discovery of deployable

ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving

arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This m

SparkDiffusion: Mitigating the High-Sparsity Trap --- A Unified Framework for up to 265imes Single-GPU Acceleration of Visual Generation

arXiv:2609.23153v1 Announce Type: new Abstract: Video diffusion transformers are expensive because attention dominates long spatiotemporal token sequences. We identify the high-sparsity trap: at extre

Spatial-Interactor: Learning Spatial Reasoning through Interaction with the Observable Physical World

arXiv:2609.23038v1 Announce Type: cross Abstract: Spatial reasoning is essential for vision-language models (VLMs) to understand and act in the physical world. Reasoning in dynamic environments requir

Stability-Aligned Residual Adaptation for Rapid Recovery from Dynamics Shifts

arXiv:2603.07775v2 Announce Type: replace Abstract: Robotic systems deployed beyond controlled environments encounter abrupt and unobserved dynamics shifts that induce substantial transient performanc

Steerable and Reactive Grasping Through Modular Design with a Three-Point Interface

arXiv:2609.24896v1 Announce Type: new Abstract: Dexterous grasping requires deciding where to grasp, reaching the target, and maintaining stable contact. We connect these stages through a compact thre

Steering Vector Fields for Context-Aware Inference-Time Control in Large Language Models

arXiv:2602.01654v2 Announce Type: replace Abstract: Steering vectors (SVs) offer a lightweight way to control large language models (LLMs) at inference time by shifting hidden activations, providing a

Stochastic Flow Map for Count Data

arXiv:2609.23290v1 Announce Type: cross Abstract: High-dimensional count data are common in scientific applications, but most diffusion and flow models are designed for continuous or categorical data,

Tackling Feature-Classifier Mismatch in Federated Learning via Prompt-Driven Feature Transformation

arXiv:2407.16139v2 Announce Type: replace Abstract: Federated Learning (FL) faces challenges due to data heterogeneity, which limits the global model's performance across diverse client distributions.

Tail-Weight Control and Localized Generalization in Nearly Low-Rank Adversarial Classification

arXiv:2609.23688v1 Announce Type: new Abstract: We study norm-constrained linear classification under Eu clidean adversarial perturbations in a Gaussian model with a low-dimen sional informative subsp

Toward Personalized Sleep Guidance from Wearable Data Using Language Models

arXiv:2609.22463v1 Announce Type: new Abstract: Sleep monitoring using wearable data has shown promise for personal health, yet large language model (LLM)-based summarization and question answering re

Transferring Visual Explanations: How Cross-Architecture Knowledge Distillation Affects Model Interpretability

arXiv:2609.23561v1 Announce Type: new Abstract: Deploying efficient neural networks is essential in resource-constrained environments, yet compact models often sacrifice interpretability - a critical

UniGIO: Unified Generative Global In-situ Weather Modeling from Spatiotemporal Incomplete Observations

arXiv:2609.22217v1 Announce Type: new Abstract: Global In-situ Observation (GIO) provides fine-scale, direct records of the global weather system from sparse point stations, making it an indispensable

Unsupervised Brain Anomaly Detection as a Bayesian Inverse Problem with Diffusion Prior

arXiv:2609.24265v1 Announce Type: cross Abstract: Unsupervised anomaly detection (UAD) aims to localize abnormal regions in medical scans without pixel-level annotations. A typical strategy seeks to r

Vision-Wireless Fusion for Multi-User Localization: A Cross-Modal Transformer Approach

arXiv:2609.23372v1 Announce Type: new Abstract: Accurate multi-user localization is challenging in complex urban environments, where wireless measurements can become ambiguous under noise, blockage, a

WOLF: World Model Guided LiDAR Exploration with Predictive Frontiers

arXiv:2609.23656v1 Announce Type: new Abstract: LiDAR-based unmanned aerial vehicle (UAV) exploration builds maps by continually selecting where to observe next. However, decisions based on the measur

XSQ-AST: An Explainable Audio Spectrogram Transformer Framework for Localising Synthetic Speech Artifacts

arXiv:2609.24770v1 Announce Type: cross Abstract: Localising artifacts in synthetic speech remains challenging, as most evaluation methods yield only global quality scores. This paper presents XSQ-AST

Adapting Rigid-Body Dynamics Derivatives for Constraint Embedding Closed-Chain Models

arXiv:2609.21024v1 Announce Type: new Abstract: This paper extends an existing algorithm for the first-order derivatives of rigid-body dynamics to the case of closed-chain kinematic systems modeled us

21 Sept 2026

Adaptive World Memory 3D Foundation Model for Scalable 3D Mapping, Localization, and Rendering

arXiv:2609.21502v1 Announce Type: new Abstract: Recent 3D foundation models enable generalizable geometric reasoning from RGB images but remain limited in persistent memory, scalability, and renderabl

21 Sept 2026

Assessment of Machine Learning-Based Critical Heat Flux Models in the CTF Subchannel Code for Square Rod Bundle Prediction

arXiv:2609.21995v1 Announce Type: new Abstract: The prediction of critical heat flux (CHF), a key safety-related quantity in nuclear thermal hydraulics, remains an important challenge due to its direc