Search: “framework”

MILAAP: Mobile Link Allocation via Attention-based Prediction

arXiv:2506.19947v2 Announce Type: replace-cross Abstract: Channel hopping (CS) communication systems must adapt to interference changes in the wireless network and to node mobility for maintaining thr

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Mind the Gap: Navigating Inference with Optimal Transport Maps

DGX agent

arXiv:2507.08867v3 Announce Type: replace-cross Abstract: Machine learning (ML) techniques have recently enabled enormous gains in sensitivity to new phenomena across the sciences. In particle physics

researcharxiv-cs-lg

9 Sept 2026

Mind-to-Face: Neural-Driven Photorealistic Avatar Synthesis via EEG Decoding

arXiv:2512.04313v2 Announce Type: replace Abstract: Current expressive avatar systems rely heavily on visual cues, failing when faces are occluded or when emotions remain internal. We present Mind-to-

MLIP Detective: Active Failure Mode Discovery Beyond Benchmark Scores for Machine-Learning Interatomic Potentials

arXiv:2609.08399v1 Announce Type: new Abstract: Universal machine-learning interatomic potentials (u-MLIPs) aim to generalize across diverse configurations. Benchmarks enable reproducible evaluation b

Model-Adaptive and Risk-Constrained Frequency Hopping Against Predictive Jammers

arXiv:2609.06514v1 Announce Type: new Abstract: Adaptive frequency hopping against predictive jamming must address both model uncertainty and policy exposure: the context-loss relationship may vary ac

local-aiarxiv-cs-lg

MolParser-Mobile: Ultrafast OCSR System for Large-Scale Chemical Literature Mining

arXiv:2609.05807v1 Announce Type: new Abstract: Optical Chemical Structure Recognition (OCSR) is a fundamental component of chemical literature mining, enabling molecular database construction, reacti

hardwarearxiv-cs-cv

MR-STORM: Scalable Multi-Arm Control By Distributed MPC

arXiv:2602.10114v2 Announce Type: replace Abstract: Centralized motion planning algorithms struggle to scale in multi-arm manipulation, where inter-arm coupling and tight workspaces amplify complexity

hardwarearxiv-cs-ro

MRI-Guided Reslice-Refined Cross-Slice SDF Reconstruction of the Left Ventricle from Cardiac MRI with Sparse Axial Supervision

arXiv:2609.08148v1 Announce Type: new Abstract: Reconstructing a three-dimensional left-ventricular (LV) endocardial surface from cardiac magnetic resonance (CMR) data is challenging when supervision

MSCA-UNet: Multi-Scale Context and Attention U-Net for Image Segmentation

arXiv:2609.06356v1 Announce Type: new Abstract: U-Net remains a practical baseline for image segmentation because of its simple encoder-decoder structure and skip connections. However, the bottleneck

Applications

MSSP: Multi-Scale Spatially-Constrained Partition for Unsupervised Semantic Segmentation of 3D Point Clouds

arXiv:2609.06959v1 Announce Type: new Abstract: 3D point cloud semantic segmentation is essential for real-world spatial understanding, yet the prohibitive cost of human annotations motivates unsuperv

applicationsarxiv-cs-cv

Multi-granularity Adaptive Hypergraph Representation Learning via Granular-ball

arXiv:2609.05574v1 Announce Type: new Abstract: Hypergraph representation learning aims to capture high-order information in graphs by constructing hyperedges that simultaneously connect multiple node

Multi-History-Step SDE Inversion for Image Editing with Superior Regional Awareness

arXiv:2609.06602v1 Announce Type: new Abstract: In recent years, diffusion stochastic differential equation (SDE) inversion and inversion-free methods have become prevalent for training-free image edi

Multi-robot Learning-based Informative Path Planning Using Spatio-Temporal Gaussian Process Kalman Filter

arXiv:2609.05515v1 Announce Type: new Abstract: Multi-robot informative path planning (IPP) for persistent target monitoring requires robots to reason about spatial uncertainty, temporal evolution, an

safetyarxiv-cs-ro

Multimodal Resource-Exhaustion Attacks on Vision-Language Models via Joint Pixel-Prompt Optimization

arXiv:2609.05889v1 Announce Type: cross Abstract: Resource-exhaustion attacks against autoregressive vision-language models (VLMs) typically assume unimodal threat models, treating the image branch as

Multiple Myeloma Lesion Segmentation on Whole-Body Diffusion-Weighted Imaging via Efficient Anatomical Anticipation and Multimodal Confirmation

arXiv:2609.06165v1 Announce Type: new Abstract: Whole-body diffusion-weighted imaging (WB-DWI) is widely used for multiple myeloma (MM) assessment, yet automated lesion segmentation remains challengin

MV-STRIDE: Enabling MLLMs to Master Multi-View Spatial Reasoning via Hierarchical Capability Modeling

arXiv:2609.07258v1 Announce Type: new Abstract: Despite the rapid progress of Multimodal Large Language Models (MLLMs) in 2D vision-language tasks, robust multi-view spatial reasoning remains a fundam

Neither Adversarial Training Nor Purification: Emergent Adversarial Robustness from Oscillatory Predictive Learning

arXiv:2609.08683v1 Announce Type: new Abstract: Adversarial robustness in computer vision is still largely achieved through adversarial training or test-time adversarial purification, both of which in

NeuCME: Toward Dynamic Multimodal Continual Learning via Neural Combinatorics of Multiple Experts

arXiv:2609.07009v1 Announce Type: cross Abstract: Multimodal continual learning has recently shown great potential for developing agents with human-like intelligence by continuously learning new tasks

NOVA: Normal-Side Modeling for Training-Free Zero-Shot Video Anomaly Detection

arXiv:2609.06360v1 Announce Type: new Abstract: Training-free zero-shot video anomaly detection (ZS-VAD) leverages vision-language models (VLMs) to localize anomaly instances from a predefined anomaly

NSFlow: End-to-End Differentiable Neuro-Symbolic Optical Flow for Visual Odometry

arXiv:2609.06074v1 Announce Type: new Abstract: Sparse optical flow provides stable inter-frame correspondence, playing a key role in Visual Odometry (VO) and Visual-Inertial Odometry (VIO). Classical

Object-Aware Background-Controlled Editing via Weighted Velocity Guidance

arXiv:2609.06288v1 Announce Type: new Abstract: Training-free image editing steers diffusion or flow-matching generative models at inference time by modifying prompt-conditioned denoising velocities.

local-aiarxiv-cs-cv

Observe Before You Alert: Adaptive Driver Alerting with Vision-Language Models

arXiv:2609.08130v1 Announce Type: new Abstract: Driver alerting from dashcam video requires sequential decision-making under partial observability: a system must decide not only whether a scene is ris

Observing Health Outcomes Using Remote Sensing Imagery and Geo-Context Guided Visual Transformer

arXiv:2602.00110v2 Announce Type: replace Abstract: Visual transformers have driven major progress in remote sensing image analysis, particularly in object detection and segmentation. Recent vision-la

OCTN: Neural OCT Representations for Robot-Guided Precision Intervention

arXiv:2609.06810v1 Announce Type: new Abstract: Optical coherence tomography (OCT) offers compact, contactless, micron-scale imaging suitable for intraoperative guidance, but native OCT volumes are di

hardwarearxiv-cs-ro

OdysSim: Building Foundation Models for Human Behavior Simulation

arXiv:2606.14199v2 Announce Type: replace-cross Abstract: Large language models are increasingly deployed as human simulators for interactive evaluation and social simulation. Yet helpfulness-driven p

On-the-go Forgetting without Explicit Unlearning via ERASE

arXiv:2609.05966v1 Announce Type: new Abstract: Existing unlearning approaches typically rely on post hoc weight adaptation or distillation, leading to duplicated memory costs, degraded generalization

Agents

One MLLM, One Call: Efficient Zero-Shot Vision-and-Language Navigation via Spatial-Aware Waypoints

arXiv:2609.06476v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to navigate unseen environments by following natural langu

agentsarxiv-cs-cv

One Shared LoRA Weight for MRI Reconstruction across Acceleration Factors

arXiv:2609.06338v1 Announce Type: new Abstract: Accelerated MRI reconstruction recovers images from undersampled k-space. However, different acceleration factors produce distinct artifact patterns. Ex

Parameterized and Streaming Algorithms for Euclidean Fair k-Center Clustering

arXiv:2609.06384v1 Announce Type: new Abstract: Motivated by the growing importance of fairness in machine learning, fair k-center clustering has attracted considerable research attention as a fundame

safetyarxiv-cs-lg

PCFlow: Physics-Conditioned Flow Matching for GPR B-Scan Image Synthesis

arXiv:2609.07300v1 Announce Type: new Abstract: Ground-penetrating radar (GPR) B-scan image synthesis is important for data augmentation, algorithm validation, and simulation acceleration, yet generat

PCSDiff: Diffusion-Based Bias Correction and Super Resolution Toward Practical Operational Medium-Term Precipitation Forecast

arXiv:2609.06942v1 Announce Type: new Abstract: Medium-range precipitation forecasts are impaired by persistent systematic biases, lead-time-dependent error accumulation, and coarse spatial resolution

local-aiarxiv-cs-lg

PhysFlow: Physics-Aware Optical Flow for Motion Controllable Video Generation

arXiv:2609.08215v1 Announce Type: new Abstract: Video generation models have recently attracted substantial attention for their ability to generate visually compelling videos, yet ensuring physically

local-aiarxiv-cs-cv

PhysReal: Learning Real-World Deformable Object Physics via Hybrid Constitutive Modeling

arXiv:2609.07532v1 Announce Type: new Abstract: Learning physically plausible dynamics from visual observations is essential for interactive world models and embodied agents. However, modeling real-wo

local-aiarxiv-cs-ro

PhysSAE: Mechanistic Interpretability with Sparse Autoencoders

arXiv:2609.07061v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) embed PDE residuals into neural network training, but their internal representations remain opaque: it is unkno

PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusion

arXiv:2609.06436v1 Announce Type: new Abstract: High-resolution 3D asset generation is vital in various 3D applications. Existing state-of-the-art diffusion-based models remain constrained by fixed re

local-aiarxiv-cs-cv

PocketVE: Stable and Property-Guided Structure-Based Drug Design with Variance-Exploding Diffusion

arXiv:2609.08101v1 Announce Type: cross Abstract: Protein-conditioned 3D molecule generation is a central challenge in structure-based drug design, requiring a balance between pocket compatibility, mo

Tutorials

Polarity-Asymmetric Structural Calibration for Link Sign Prediction

arXiv:2609.05896v1 Announce Type: cross Abstract: Link sign prediction (LSP) aims to infer the positive or negative polarity of unobserved links in signed networks. Signed Graph Neural Networks (SGNNs

tutorialsarxiv-cs-lg

Agents

Predictive-Coding-Based Autonomous Regulation of Internally Generated and Externally Coupled Processing in Human-Robot Interaction

arXiv:2609.06888v1 Announce Type: new Abstract: Predictive coding characterizes adaptive behavior as a dynamic balance between internally generated predictions and external sensory evidence, yet how a

agentsarxiv-cs-ro

PRG-Fusion: Orchestrating Generative Priors with Reconstruction Evidence for Driving View Synthesis

arXiv:2609.06948v1 Announce Type: new Abstract: Synthesizing photorealistic driving videos along specified trajectories is essential for scalable closed-loop simulation. Reconstruction-based methods l

Applications

Privacy Leakage from a Thousand Words: Millipixel Location Recovery from Dot Maps

arXiv:2609.07623v1 Announce Type: cross Abstract: Dot maps, which visualize individual data points as dots over a geographic region, are widely used across diverse domains to represent spatial pattern

applicationsarxiv-cs-cv

Proactive Context-Forecasted Safety Constraints for Nonstationary Reinforcement Learning

arXiv:2609.08080v1 Announce Type: new Abstract: Ensuring safety in reinforcement learning under nonstationarity requires anticipating changes in risk before they lead to unsafe behavior. Existing appr

safetyarxiv-cs-lg

Proper Dataset Valuation by Pointwise Mutual Information

arXiv:2405.18253v4 Announce Type: replace Abstract: Data plays a central role in advancements in modern artificial intelligence, with high-quality data emerging as a key driver of model performance. T

hardwarearxiv-cs-lg

Provable Pluralistic Alignment: Multi-Party RLHF under Offline Human Feedback

arXiv:2403.05006v2 Announce Type: replace Abstract: Pluralistic alignment requires learning from feedback that reflects persistent and potentially conflicting stakeholder preferences while ultimately

safetyarxiv-cs-lg

Proximity-CLIP: Text-Guided Semantic Proximity Learning for Zero-Shot Anomaly Detection

arXiv:2609.07229v1 Announce Type: new Abstract: Vision-language models offer a promising approach for zero-shot anomaly detection (ZSAD). However, due to object-centric bias, normal and anomalous text

RAPTOR: Role-Aware Private Training for Mixture-of-Experts

arXiv:2609.05770v1 Announce Type: new Abstract: Differentially private (DP) fine-tuning methods treat sparse Mixture-of-Experts (MoE) models as a single dense block, ignoring that shared layers see al

Re-engineering SORT-based algorithms for low-cost small object tracking from omnidirectional footage

arXiv:2609.07547v1 Announce Type: new Abstract: Multi-object tracking (MOT) has advanced rapidly in urban surveillance and autonomous driving, yet many trackers rely on ReID- and transformer-based app

Reactive Flux Matching: Mechanism Discovery and Adaptive Sampling of Rare Events

arXiv:2606.06295v2 Announce Type: replace Abstract: Path sampling methods generate ensembles of reactive trajectories connecting metastable states, but extracting mechanistic insight from these data r

Reading Decoder Trajectories: Training-Free Counterfactual Query-Trajectory Reliability for Small-Object Detection

arXiv:2609.06581v1 Announce Type: new Abstract: Small-object detection remains challenging because limited pixels cause information loss and suppress the scale knowledge encoded in pretrained detector