Search: “framework”

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

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Research

Type-Balanced Federated Learning for Visual Analog Meter Reading

DGX agent

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

researcharxiv-cs-cv

29 Sept 2026

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

Applications

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

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

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

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

Applications

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

HyperErase: Scale-Calibrated Hypernetwork for Multi-Concept Erasure in Text-to-Image Models

model-releasesarxiv-cs-cv

arXiv:2609.31154v1 Announce Type: new Abstract: Recent advances in text-to-image (T2I) generation have substantially improved visual synthesis, but have also raised increasing safety concerns due to t

InternW0-Delta: A World Action Model Bridging Predictive Dynamics and Actions with 20K+ Hours of Open Data

arXiv:2609.31394v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly model visual dynamics and action generation for generalist robot manipulation. A central challenge is to integrate

KneePreM: Towards 3D Knee MRI Foundation Models via Large-Scale Unlabeled Pretraining and Label-Efficient Fine-Tuning

arXiv:2609.31461v1 Announce Type: new Abstract: Background: Large volumes of unlabeled knee MRI scans are available across repositories but remain insufficiently leveraged. We developed KneePreM, a kn

LandscapeSHAP: Which Persistent Homology Class Gets the Credit?

arXiv:2609.31469v1 Announce Type: cross Abstract: Shapley values, a solution concept from cooperative game theory, have recently become a standard tool for feature credit allocation in machine learnin

Latent Generative Solvers for Generalizable Long-Term Physics Simulation

arXiv:2602.11229v3 Announce Type: replace Abstract: Reliable physics simulation demands two capabilities that today's neural PDE solvers do not deliver together: generalization across heterogeneous PD

LEAD: An EEG Foundation Model for Alzheimer's Disease Detection

arXiv:2502.01678v5 Announce Type: replace-cross Abstract: Electroencephalography (EEG) provides a non-invasive, highly accessible, and cost-effective approach for detecting Alzheimer's disease (AD). H

Learning to Bias: Machine Learning-Enhanced Particle Filters

arXiv:2609.30498v1 Announce Type: new Abstract: Sequential inference estimates latent states from noisy and incomplete observations. Particle Filters (PFs), a class of Monte Carlo methods based on imp

Tutorials

LLPR: Location-aware learning and physics-based reconstruction for raindrop removal from a single image

arXiv:2609.30758v1 Announce Type: new Abstract: Raindrops can cause occlusion and distortion in the background scenes due to their adherence to windows or camera lenses. Existing raindrop removal meth

tutorialsarxiv-cs-cv

Low-Rank Friction for Memory-Efficient Transformer Pretraining

arXiv:2609.30342v1 Announce Type: cross Abstract: iKFAD is a recently proposed optimiser that replaces adaptive learning rates with adaptive friction in the momentum dynamics, yet performs as well as

Memory-Aware Multi-Sensor Perception for Efficient and Safe Navigation in Dynamic Environments

arXiv:2609.30495v1 Announce Type: new Abstract: Autonomous navigation in previously unseen environments requires effective perception, persistent environmental representation, and collision avoidance

safetyarxiv-cs-ro

More Sensors Only One Field: Rethinking Continual Spatio-Temporal Forecasting

arXiv:2609.31325v1 Announce Type: new Abstract: Continual spatio-temporal forecasting supports traffic management and environmental monitoring under evolving dynamics and expanding sensor networks. Ho

Applications

Motion Style Slider: Endpoint-Supervised Continuous Style Control for Human Motion Diffusion

arXiv:2609.30795v1 Announce Type: new Abstract: Existing human motion diffusion methods provide strong motion generation quality, and recent style transfer models can inject target style cues, but fin

applicationsarxiv-cs-cv