Search: “framework”

StegGNN: Learning Graphical Representation for Image Steganography

model-releasesarxiv-cs-cv

arXiv:2609.32362v1 Announce Type: new Abstract: Image steganography refers to embedding secret messages within cover images while maintaining imperceptibility. Recent advances in deep learning - prima

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Structured Latent Modeling for Supervised Multimodal Information Decomposition

DGX agent

arXiv:2609.35502v1 Announce Type: new Abstract: Multimodal prediction relies on diverse forms of evidence: information repeated across modalities, cues specific to a single source, and complex cross-m

researcharxiv-cs-lg

29 Sept 2026

Tutorials

Style-Driven Data Synthesis and Degradation-Aware Enhancement for Ultrasound Image Restoration

arXiv:2609.35120v1 Announce Type: new Abstract: Low-cost handheld ultrasound devices can be widely deployed compared to professional hospital ultrasound machines. However, their images suffer from com

tutorialsarxiv-cs-cv

SurgGMF: Fully Causal Gaussian Motion Forecasting for Anticipatory Surgical Scene Rendering

arXiv:2609.34733v1 Announce Type: new Abstract: Dynamic surgical scene modeling is essential for robotic perception, simulation, and decision support. Although existing neural rendering methods enable

SyncEdit: Rethinking Lip Synchronization as Editing with Audio-Driven Diffusion Models

arXiv:2603.09084v2 Announce Type: replace Abstract: Lip synchronization refers to the task of modifying facial lip movements such that they are temporally aligned with a given audio signal. It is a fu

safetyarxiv-cs-cv

SynCo: Learning Cross-Modal Synergy by Contrasting Interaction Residuals

model-releasesarxiv-cs-cv

arXiv:2609.32846v1 Announce Type: new Abstract: Multimodal contrastive learning is a dominant paradigm for learning transferable representations from unlabeled data, but standard objectives primarily

Task-Oriented Communications for Edge-Assisted Multi-View Localization

arXiv:2609.35173v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) often lose satellite positioning in urban canyons, indoor facilities, and jammed o

applicationsarxiv-cs-ro

TemporalGraphLLM: Temporal Graph Neural Networks with Large Language Models for Dynamic Text-Attributed Graphs

arXiv:2609.31881v1 Announce Type: new Abstract: Dynamic text-attributed graphs (DTAGs), where nodes, edges, and textual attributes evolve over time, are crucial in applications such as social networks

applicationsarxiv-cs-lg

The Platonic Universe: Do Foundation Models See the Same Sky?

arXiv:2509.19453v2 Announce Type: replace-cross Abstract: We investigate when foundation models converge towards shared representations, and how this convergence depends on model capacity, training re

Theory Guided and Interpretable Neural Operator Design for Partial Differential Equation Learning

model-releasesarxiv-cs-lg

arXiv:2609.33715v1 Announce Type: new Abstract: Accurate numerical solutions of partial differential equations (PDEs) are crucial in numerous science and engineering applications. In this work, we int

ThinkNet: Compact Architecture Selection and Validation-Gated Ensembles for Subject-Independent MI-EEG Decoding

model-releasesarxiv-cs-lg

arXiv:2609.33967v1 Announce Type: cross Abstract: Practical assistive and rehabilitative brain--computer interfaces require subject-independent motor-imagery EEG (MI-EEG) decoders that generalize to n

TopoMamba: A Load-Support Relation-Guided Multi-Directional State-Space Model for Topology Optimization

arXiv:2609.33688v1 Announce Type: cross Abstract: Deep learning has emerged as an efficient alternative for predicting high-performance material distributions in topology optimization. Existing method

Type-Balanced Federated Learning for Visual Analog Meter Reading

arXiv:2609.31998v1 Announce Type: new Abstract: Analog dial meters are widely deployed in industrial applications and utility sites, where environments and meter types vary and inspection data may be

Unified Trajectory Matching Policy Optimization: Diverse T2I Generation and VLA Generalization

arXiv:2609.34688v1 Announce Type: new Abstract: Reward-maximizing reinforcement learning (RL) is widely used to post-train stochastic diffusion and flow policies for text-to-image (T2I) generation. Ho

safetyarxiv-cs-cv

VCRE-Fib: View-Conditioned Regional Evidence for Fine-Grained Ultrasound Grading of Schistosoma japonicum-Associated Liver Fibrosis

arXiv:2609.32840v1 Announce Type: new Abstract: Accurate assessment of Schistosoma japonicum-associated liver fibrosis is essential for disease management and long-term follow-up in endemic regions. U

local-aiarxiv-cs-cv

Verifying Neural Networks with Reinforcement Learning

arXiv:2609.34553v1 Announce Type: new Abstract: Formal verification can play a key role in ensuring the reliability of Deep Neural Networks (DNNs) deployed in safety-critical systems. Modern DNN verif

What masking geometry works best for EEG foundation models?

model-releasesarxiv-cs-lg

arXiv:2609.33487v1 Announce Type: new Abstract: EEG foundation models hold promise for scalable brain-signal decoding across clinical and cognitive neuroscience applications, yet their pre-training pi

When Noise Meets Long-Tail: Feature-Threshold Dual Calibration for Robust Pseudo-Labeling

arXiv:2609.33668v1 Announce Type: new Abstract: Pseudo-labeling has become a cornerstone of learning from unlabeled data in semantic segmentation. Yet its effectiveness drops sharply in real-world sce

safetyarxiv-cs-cv

Which Self-Improvements Should We Trust? Reliable Self-Improvement When Agents Reuse Their Benchmarks

arXiv:2609.33180v1 Announce Type: cross Abstract: As recursive self-improvement (RSI) rapidly advances, reliable evaluation becomes critical for guiding adaptive search. RSI typically relies on finite

ZeroCode: On-demand Error-Correcting Code Construction from the Zero Matrix via Reinforcement Learning

arXiv:2609.34265v1 Announce Type: new Abstract: Error-correcting codes (ECCs) are essential across diverse applications, from wireless communications and storage to quantum computing, yet each applica

A Survey on Fake Review Detection: From Pre-trained Language Models to Large Language Models

model-releasesarxiv-cs-ai

arXiv:2609.30292v1 Announce Type: cross Abstract: Online reviews shape consumer decisions, platform governance, and corporate reputation.Fake reviews compromise this information channel by injecting d

Adapting Visualization Techniques for Time-Series Anomaly Detection: From Convolutional Neural Networks to Convolutional-Recurrent Neural Networks

arXiv:2411.04707v4 Announce Type: replace Abstract: Deep neural networks achieve strong performance on complex tasks but are often regarded as 'black boxes,' which limits their adoption in domains whe

applicationsarxiv-cs-cv

Adaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices

arXiv:2609.30348v1 Announce Type: cross Abstract: Gaussian processes constitute a cornerstone of probabilistic machine learning, yet scaling them to large datasets typically forces a trade-off between

researcharxiv-cs-ai

Adaptive Pilot Selection for Unified Semantic Communication and Semantic Sensing in ISAC

arXiv:2609.30891v1 Announce Type: cross Abstract: Semantic communication (SemCom) and integrated sensing and communication (ISAC) are promising technologies for future 6G wireless networks. Existing s

researcharxiv-cs-ai

Aerial Manipulation in the Wild with Onboard Perception, Policy Learning, and Whole-Body Control

arXiv:2609.30521v1 Announce Type: new Abstract: Aerial manipulation in outdoor environments remains challenging due to the simultaneous requirements of reliable state estimation, stable aerial motion,

safetyarxiv-cs-ro

AFA-Net: A Differential Attention Approach for Auditory Attention Detection

arXiv:2609.31402v1 Announce Type: cross Abstract: Auditory Attention Detection (AAD) utilizes electroencephalographic (EEG) signals to identify a target speaker in a multi-speaker environment. Despite

Agents

Agentic AI security pushes vendors toward shared safeguards

Agentic AI security is becoming a cross-industry challenge as autonomous systems move among products and platforms. Okta Inc. argues that building trust will require coordinated safeguards rather than

agentssiliconangle

Air-Ground Collaborative Robots for Fire and Rescue Missions: A Survey from the Mapping and Navigation Perspective

arXiv:2412.20699v3 Announce Type: replace Abstract: Air-ground collaborative robots have shown great potential in the field of fire and rescue. Mapping and navigation, as the key foundation for air-gr

researcharxiv-cs-ro

AlphaEarth distinguishes cities but compresses urban variation

arXiv:2609.30356v1 Announce Type: new Abstract: Cities differ in built form, land cover and development history, complicating comparison across places and time. Satellite foundation models map Earth's

Atelier: Learning Local Self-Supervised Features for CryoEM Volumes via Hypernetworks

arXiv:2609.30569v1 Announce Type: new Abstract: CryoEM map interpretation requires features that are spatially localized, consistent across samples, and informative across spatial scales. Most deep le

local-aiarxiv-cs-ai

BabelCoder: Agentic Code Translation with Specification Alignment

model-releasesarxiv-cs-ai

arXiv:2512.06902v2 Announce Type: replace-cross Abstract: As software systems evolve, developers increasingly work across multiple programming languages and often face the need to migrate code from on

Backbone-Adaptive Evidence Routing for Robust Pairwise LLM Judging

model-releasesarxiv-cs-ai

arXiv:2609.30751v1 Announce Type: new Abstract: Pairwise language-model judges can gather evidence through direct comparison, reasoning, or reference-based verification, but no single protocol is best

Beyond Empirical Support: Structured Outlier Generation via Sinkhorn Optimal Transport

arXiv:2609.31470v1 Announce Type: cross Abstract: Outliers are essential for evaluating and improving the robustness of machine learning systems, especially when future distributions may differ signif

Budgeted Quotient-Residual Guidance for Frozen Pocket-Conditioned Molecular Diffusion

arXiv:2609.31222v1 Announce Type: new Abstract: Pocket-conditioned molecular diffusion updates ambient atom coordinates, but many lead-optimization objectives are expressed on quotient features such a

local-aiarxiv-cs-lg

Can You Check That? The Checkability Boundary for Local LLM Network Automation

arXiv:2609.31540v1 Announce Type: cross Abstract: Sending every network-automation input to a third-party frontier LLM exports sensitive artifacts such as production configurations, topologies, and lo

local-aiarxiv-cs-ai

CCRV-Bench: Constraint-Based Evaluation of Causal Reasoning in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.30979v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated excellent performance in visual tasks, but their visual causal reasoning capabilities still lack reliabl

Tutorials

Combining General and Domain-Specific Pretext Tasks for Brain MR Image Segmentation

arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models r

tutorialsarxiv-cs-ai

Containing Behavioral Cascades from Manipulated Claims in LLM-Powered Multi-Robot Systems

arXiv:2609.30523v1 Announce Type: new Abstract: Large language model (LLM)-powered multi-robot systems are vulnerable to semantic manipulation: an accepted false world-state claim can trigger a fleet-

researcharxiv-cs-ro

Agents

CRC-Router: Risk-Constrained Routing for Medical Agentic AI Systems

arXiv:2609.30714v1 Announce Type: new Abstract: Agentic AI systems are increasingly being explored in medical imaging to improve throughput and reduce clinician workload; however, safe deployment rema

agentsarxiv-cs-ai

Agents

DAPEVO: Deep Adaptive Patch Frame-Event Visual Odometry

arXiv:2609.30947v1 Announce Type: new Abstract: Visual odometry is essential for autonomous navigation in GPS-denied environments, yet RGB-based methods remain vulnerable to motion blur, challenging i

agentsarxiv-cs-cv

Do Neural Networks Preserve Case Structure? Case-Based Decomposition, Interpretation, and Decision Consistency

arXiv:2607.11347v2 Announce Type: replace Abstract: Neural networks increasingly inform consequential decisions, making their reliability increasingly important. Yet their internal mechanisms provide

applicationsarxiv-cs-ai

Hardware

EAServe: Encode-Aware Disaggregated Serving for Multimodal Large Language Models

arXiv:2609.31551v1 Announce Type: cross Abstract: Disaggregating the two stages, Prefill and Decode, onto separate GPU pools is now a standard optimization for (text-only) LLM serving. However, multim

hardwarearxiv-cs-lg

Electric Vehicle Charging Station Location Selection using Geospatial Artificial Intelligence (GeoAI)

arXiv:2609.30417v1 Announce Type: new Abstract: As electric vehicle (EV) adoption increases, ensuring efficient and well-distributed charging infrastructure has become a critical challenge. While many

Evolutionary Safety of Recursive Self-Improving AI: Taxonomy, Risk Discovery, and Evaluation

arXiv:2609.31186v1 Announce Type: new Abstract: Artificial intelligence is advancing rapidly, with increasingly capable systems taking larger roles in reasoning, decision-making, scientific discovery,

safetyarxiv-cs-ai

Forensic Twins: Self-Supervised Residual Learning for AI-Generated Image Forensics

arXiv:2609.31514v1 Announce Type: new Abstract: Detectors of AI-generated images are typically trained using samples from all Generative AI architectures they must catch, and struggle as soon as a new

Frame the adversary: a structure-aware attack methodology

arXiv:2609.31128v1 Announce Type: new Abstract: Frequency-based adversarial attacks have recently grown popular by exploiting spectral sensitivities shared across neural architectures. Unlike spatial

From ASR to ASP: Evaluating Prompt Attack Vulnerabilities Against Open-Source LLMs

model-releasesarxiv-cs-cl

arXiv:2505.14368v3 Announce Type: replace-cross Abstract: Recent studies demonstrate that Large Language Models (LLMs) are vulnerable to attacks that generate harmful or sensitive outputs. As open-sou

Game Arena: Strategic LLM Evaluation in Competitive Environments

arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from s

researcharxiv-cs-ai