Search: “framework”

arXiv:2508.06990v2 Announce Type: replace Abstract: Semantic navigation requires an agent to navigate toward a specified target in an unseen environment. Employing an imaginative navigation strategy t

agentsarxiv-cs-ro

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Improving Federated Graph Recommendation with Semantic Guidance

DGX agent

arXiv:2606.15277v2 Announce Type: replace-cross Abstract: Graph-based recommendation models effectively capture high-order collaborative signals from user--item interaction graphs. Federated learning

model-releasesarxiv-cs-lg

9 Sept 2026

Inferring Urban Mobility Interactions from Aggregated Dynamics

arXiv:2609.07349v1 Announce Type: new Abstract: Real-time urban governance depends not only on knowing where people are, but on how they move between places, directional flows that could be convention

Interpretable and Fair Generalized Additive Neural Networks via Multi-objective Learning

arXiv:2609.05946v1 Announce Type: new Abstract: Interpretability and fairness are two of the most emphasized dimensions in trustworthy artificial intelligence (AI). Various explainable AI methods have

Introductory Notes on Learning^2

arXiv:2609.06546v1 Announce Type: cross Abstract: Although machine learning can be used to predict the evolution of physical systems from data, a formulation that learns only the system state at each

IPM-FM: A Foundation Model with Consensus Feature Selection for Industrial Process Monitoring

arXiv:2609.08375v1 Announce Type: new Abstract: Industrial process monitoring is fundamental to the safety and economic performance of modern process plants. Current practice remains a one-task-one-mo

IXPLORE: Bounded Ideal Point Estimation with Grid-Based Uncertainty Quantification

arXiv:2609.06018v1 Announce Type: new Abstract: Ideal point estimation is widely used to analyze and visualize political data. However, selecting the corresponding spatial model involves various trade

JEDI: JEPA-to-Edge Distillation for Efficient Cropland Segmentation from Satellite Imagery

arXiv:2609.07915v1 Announce Type: new Abstract: Large vision models provide useful representations for remote-sensing segmentation but are often too expensive for deployment at the satellite or field

LAMP: Language-Assisted Motion Planning for Controllable Video Generation

arXiv:2512.03619v4 Announce Type: replace Abstract: Video generation has achieved remarkable progress in visual fidelity and controllability, enabling conditioning on text, layout, or motion. Among th

Large Discrete Policy: Advancing Explicit Behavior Modeling with Stochastic Iterative Scoring

arXiv:2609.07049v1 Announce Type: cross Abstract: Behavior policies are often formulated as continuous generative models, whose iterative denoising processes are expressive but difficult to interpret

Latent-to-Latent Flow for Volumetric Stochastic Segmentation

arXiv:2609.07460v1 Announce Type: new Abstract: Uncertainty arising from inter-observer variability in medical image segmentation plays an important role in developing treatment plans. Research in thi

LatentFM: A Latent Flow Matching Approach for Generative Medical Image Segmentation

arXiv:2512.04821v4 Announce Type: replace Abstract: Generative models have achieved remarkable progress with the emergence of flow matching (FM). It has demonstrated strong generative capabilities and

LATS: Levy Adaptive Tree Sampling for Feedback-Driven Diverse Target Discovery

arXiv:2609.06761v1 Announce Type: new Abstract: While diffusion models excel at capturing complex data distributions, scientific discovery often requires steering generation toward specific, uncharact

Learning Acrobatic Flight from Preferences

arXiv:2508.18817v3 Announce Type: replace-cross Abstract: Preference-based reinforcement learning (PbRL) enables agents to learn control policies without requiring manually designed reward functions,

Learning Quantum Data Distribution via Chaotic Quantum Diffusion Model

arXiv:2602.22061v3 Announce Type: replace-cross Abstract: Generative models for quantum data pose significant challenges but hold immense potential in fields such as chemoinformatics and quantum physi

Learning Subgroup Relations Using Siamese Graph Neural Networks

arXiv:2607.11140v2 Announce Type: replace Abstract: Determining whether one finite group is isomorphic to a subgroup of another is a fundamental problem in computational group theory. In this work, we

Learning to Price and Stock Under Contextual and Censored Demand

arXiv:2609.06083v1 Announce Type: new Abstract: To make optimal joint pricing and inventory control decisions is a critical challenge for modern retailers. In practice, retailers face changing market

Applications

LightSplat: Real-Time High-Fidelity 3D Gaussian SLAM with Loop Closure

arXiv:2609.07274v1 Announce Type: cross Abstract: SLAM systems based on 3D Gaussian Splatting (3DGS) have recently demonstrated promising reconstruction accuracy for dense 3D scene representations. Ho

applicationsarxiv-cs-cv

LLM-Aided Design for Manufacturing: A Multi-Agent System for Intent-Preserving Redesign of CAD for Improved Manufacturability

arXiv:2609.05559v1 Announce Type: cross Abstract: We introduce autonomous, intent-preserving Design for Manufacturing (DFM) redesign of CAD parts: given an engineer's CAD model, the method returns a v

LLM Layers Immediately Correct Each Other

arXiv:2609.07876v1 Announce Type: cross Abstract: Recent methods in language model interpretability employ techniques such as sparse autoencoders to decompose residual stream contributions into linear

Local Ai

Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation

arXiv:2609.05841v1 Announce Type: new Abstract: Language-goal aerial navigation requires an agent to local- ize a potentially unobserved target from relational instruc- tions and partial observations,

local-aiarxiv-cs-cv

Agents

MARBO: Relational Belief Grounding for LLM Agents in Social Deduction Games

arXiv:2609.06563v1 Announce Type: cross Abstract: Social deduction games (SDGs) require agents to reason under partial observability by maintaining relational beliefs about hidden roles and team align

agentsarxiv-cs-lg

MARR: Decoupling Policy, Execution, and Calibration for All-in-One Medical Image Restoration

arXiv:2609.06645v1 Announce Type: new Abstract: All-in-one medical image restoration seeks to recover heterogeneous clinical images with a single model, but PET, CT, and MRI differ substantially in de

MetaKV: Adaptive KV Cache Compression for Constrained LLM Inference

arXiv:2609.07966v1 Announce Type: new Abstract: Key--value (KV) cache compression is an effective way to reduce the memory overhead of large language model (LLM) inference, particularly for long-conte

MetaRSI / RSI2: A Meta-Recursive Self-Improving System for Recursive Self-Improving Systems Themselves

arXiv:2609.06396v1 Announce Type: new Abstract: Recursive self-improvement (RSI) lets a system improve the model-building machinery from its own failures, so every later model inherits the gain. Yet R

MGD: Moment Guided Diffusion for Maximum Entropy Generation

arXiv:2602.17211v2 Announce Type: replace-cross Abstract: Generating samples from limited information is a fundamental problem across scientific domains. Classical maximum entropy methods provide prin

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

Mind the Gap: Navigating Inference with Optimal Transport Maps

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

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

Local Ai

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

Hardware

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

Hardware

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

Local Ai

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