Search: “framework”

DynSHAP: Towards Explainable Dynamic Survival Analysis

arXiv:2609.13042v1 Announce Type: new Abstract: Deep learning models for dynamic survival analysis (DSA) achieve strong predictive performance by incorporating longitudinal patient data, but their bla

applicationsarxiv-cs-lg

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Fundamental Dynamical Units for Physics-Informed Structural Inference from Perturbation Time-Series in Networked Systems

DGX agent

arXiv:2609.11934v1 Announce Type: new Abstract: In networked dynamical systems, the parameter of primary mechanistic interest is signed interaction structure. Recovering this structure from perturbati

model-releasesarxiv-cs-lg

14 Sept 2026

GLaMoR: Consistency Checking of OWL Ontologies using Graph Language Models

arXiv:2504.19023v2 Announce Type: replace-cross Abstract: Semantic reasoning aims to infer new knowledge from existing knowledge, with OWL ontologies serving as a standardized framework for organizing

researcharxiv-cs-lg

Independent Learning of Nash Equilibria in Partially Observable Markov Potential Games with Decoupled Dynamics

arXiv:2605.06377v2 Announce Type: replace-cross Abstract: We study Nash equilibrium learning in partially observable Markov games (POMGs), a multi-agent reinforcement learning framework in which agent

agentsarxiv-cs-lg

Layered Safety: Enhancing Autonomous Collision Avoidance via Multistage CBF Safety Filters

arXiv:2603.00338v2 Announce Type: replace Abstract: This paper presents a general end-to-end framework for constructing robust and reliable layered safety filters that can be leveraged to perform dyna

safetyarxiv-cs-ro

Not All Speech Is Intent: Adaptive Self-Correcting Inference Layer for Post-ASR False Wake-Up

model-releasesarxiv-cs-cl

arXiv:2609.12469v1 Announce Type: new Abstract: False wake-up activations remain a persistent challenge in conversational AI. Speech phonetically similar to a device's wake word can produce a syntacti

NOVA-GS: Noise-Aware View-Consistent Gaussian Splatting for Low-Light Novel View Synthesis

arXiv:2609.12682v1 Announce Type: new Abstract: Reconstructing 3D scenes under real-world low-light conditions remains challenging due to severe sensor noise, low signal-to-noise ratios, and degraded

applicationsarxiv-cs-cv

Optimization-Based Robust Permissive Synthesis for Interval MDPs

model-releasesarxiv-cs-ro

arXiv:2510.03481v3 Announce Type: replace Abstract: We present an optimization-based framework for robust permissive synthesis for Interval Markov Decision Processes (IMDPs). While robust IMDP control

RA-SOD: Reliability-Aware RGB-T Salient Object Detection under Modality Degradation

arXiv:2609.12622v1 Announce Type: new Abstract: RGB-Thermal (RGB-T) salient object detection leverages complementary cues from visible and thermal modalities to improve robustness in challenging envir

applicationsarxiv-cs-cv

RodForesight: A World Model Enhanced Diffusion Policy for Slender and Material Agnostic Rod Insertion

arXiv:2609.12103v1 Announce Type: new Abstract: Slender rod insertion arises in precision manufacturing, where millimetre scale diameter and tight clearances demand accurate perception and control. Co

safetyarxiv-cs-ro

Self-Verifying Anomaly Detection using Explainable AI for Cybersecurity of DER Networks

arXiv:2609.12305v1 Announce Type: cross Abstract: The rapid growth of Distributed Energy Resources (DERs) has significantly expanded the cyber attack surface of modern power grids. Furthermore, increa

researcharxiv-cs-lg

Trajectory Tracking Control Design for Autonomous Helicopters with Guaranteed Error Bounds

model-releasesarxiv-cs-ro

arXiv:2603.08045v2 Announce Type: replace-cross Abstract: This paper presents a systematic framework for computing formally guaranteed trajectory tracking error bounds for autonomous helicopters based

UFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation

model-releasesarxiv-cs-cv

arXiv:2609.12397v1 Announce Type: new Abstract: Multi-modal image generation, particularly subject-driven customization, has garnered growing attention in recent years. Despite the rapid advancement o

Unified CT and MRI Pancreas Segmentation for Label-Efficient Cross-Modality Subregion Transfer

arXiv:2609.13043v1 Announce Type: new Abstract: Robust medical image segmentation across imaging modalities is challenging because of large differences in appearance and intensity distributions. Model

safetyarxiv-cs-cv

When Connected Does Not Mean Similar: Charting the Homophily Boundary of SNAP-KG for Streaming Entity Integration

arXiv:2609.12356v1 Announce Type: new Abstract: SNAP-KG is a framework for assigning newly arriving entities to semantic communities in a growing knowledge graph (KG) using only their raw features, wi

researcharxiv-cs-lg

Tapes Together Strong: The Co-evolution of Computation and Cooperation

arXiv:2609.10817v1 Announce Type: cross Abstract: How does cooperation evolve in complex agentic systems? Prior work in evolutionary game theory studies why individuals are incentivized to cooperate b

agentsarxiv-cs-ai

12 Sept 2026

Beyond Surface Imitation: Contrastive Modeling for Reasoning Path Alignment in Multimodal In-Context Learning

arXiv:2609.10177v1 Announce Type: new Abstract: In-context learning (ICL) is widely used in multimodal large language models (MLLMs) and achieves strong performance across a wide range of multimodal t

safetyarxiv-cs-ai

City Editing: Hierarchical Agentic Execution for Dependency-Aware Urban Geospatial Modification

arXiv:2602.19326v3 Announce Type: replace-cross Abstract: Urban renewal requires incremental modifications to existing geospatial plans, yet manually updating complex layouts under spatial constraints

agentsarxiv-cs-ai

Differentially Private EEG Feature Anonymization: A Privacy-Utility Case Study in Clinical Neurophysiology

arXiv:2609.11777v1 Announce Type: cross Abstract: Clinical electroencephalography (EEG) data are valuable for healthcare research and for developing artificial intelligence (AI)-based clinical decisio

applicationsarxiv-cs-lg

Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)

model-releasesarxiv-cs-lg

arXiv:2609.11569v1 Announce Type: cross Abstract: We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale.

Local Ai

Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection

arXiv:2609.10988v1 Announce Type: cross Abstract: The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswing in fatalities due to the novel coronavirus, unde

local-aiarxiv-cs-cv

From State Synchronization to Cognitive Self-Evolution: An Operational Architecture for Cognitive Digital Twins

arXiv:2609.09625v1 Announce Type: new Abstract: As Digital Twin (DT) systems evolve beyond state synchronization toward task-oriented and knowledge-driven operation, Cognitive Digital Twins (CDTs) hav

Improving the Sensitivity of Gravitational Wave Detection with Weighted Conformal Prediction

arXiv:2609.11401v1 Announce Type: cross Abstract: In the last decade, kilometre-scale interferometric gravitational-wave detectors have observed hundreds of compact binary mergers, the majority of whi

safetyarxiv-cs-lg

Local Ai

M3-Former: Multimodal Transformer with Mixture-of-Experts for Long-Term Vessel Trajectory Prediction

arXiv:2609.10559v1 Announce Type: cross Abstract: To address the challenges of behavioral multimodality, limited semantic utilization, and long-term error accumulation in vessel trajectory prediction,

local-aiarxiv-cs-cv

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

model-releasesarxiv-cs-cl

arXiv:2604.04036v2 Announce Type: replace-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challengin

Numbat: Building and Verifying a Self-Contained Machine-Learning Stack

model-releasesarxiv-cs-lg

arXiv:2609.10632v1 Announce Type: cross Abstract: Machine-learning systems are built almost exclusively on a few large Python-orchestrated frameworks, and they inherit those stacks' engineering costs:

Optimizing AI Inference Across the Deployment Stack

model-releasesarxiv-cs-lg

arXiv:2609.10550v1 Announce Type: cross Abstract: AI deployment performance is shaped not by model architecture alone, but by interactions among compression, compiler transformations, and serving poli

Reflex-Informed Neuromuscular Reinforcement Learning for Muscle-Driven Locomotion

arXiv:2609.11733v1 Announce Type: cross Abstract: Muscle-driven locomotion provides a physically grounded approach to generating realistic human movement. However, achieving both physiological plausib

safetyarxiv-cs-lg

RiVaT-Fuse: Reliability-Calibrated Variational Tensor Fusion for Multimodal Prediction under Modality Uncertainty

model-releasesarxiv-cs-cv

arXiv:2609.10798v1 Announce Type: cross Abstract: Image-metadata prediction requires fusing heterogeneous evidence whose reliability can vary across samples and latent factors. Existing representation

The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoption

arXiv:2609.09560v1 Announce Type: cross Abstract: This study evaluates Vibe Coding, an emerging AI-led conversational programming paradigm that enables developers to generate software through natural-

TransClean: A Benchmark for Detecting and Extracting Clean Translations from Large Language Model Outputs

model-releasesarxiv-cs-cl

arXiv:2609.11399v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for machine translation, yet their outputs often contain additional text beyond the translation itsel

Two-Parameter Flow Map Learning for Continuous-Time Diffeomorphic Image Registration

model-releasesarxiv-cs-cv

arXiv:2609.10789v1 Announce Type: new Abstract: Diffeomorphic image registration is central to medical image analysis, enabling anatomically consistent alignment across subjects. Most learning-based d

Understanding In-Context Multimodal Jailbreaks via Posterior Reweighting

arXiv:2609.10613v1 Announce Type: cross Abstract: In-context learning (ICL) jailbreaks reveal a critical vulnerability in multimodal large language models (MLLMs): harmful demonstrations in the prompt

safetyarxiv-cs-lg

A Decade of Bayesian Optimization for Controller Tuning and Robot Learning: Tutorial, Review, and Future Prospects

model-releasesarxiv-cs-ro

arXiv:2609.09403v1 Announce Type: new Abstract: In the past decade, Bayesian optimization (BO) has emerged as a powerful and adaptable framework for automatic controller tuning and robot learning. Thi

A Translational Note on AI Safety Evaluation

arXiv:2609.06573v1 Announce Type: new Abstract: Recent studies report that automated red-teaming finds more vulnerabilities, at lower cost, than human red-teaming on standard AI safety benchmarks, and

Aegix Pulse: A Traceable Three-Stage Architecture for Personalized Content Generation and Context-Preserving Revision

arXiv:2609.07672v1 Announce Type: new Abstract: Production content-generation systems must integrate a user's immediate task, long-term brand identity, historical evidence, and revision feedback. We p

applicationsarxiv-cs-ai

Auditable Emergency Triage for Maternal and Newborn Care in India

arXiv:2609.09356v1 Announce Type: new Abstract: At Noora Health, our nurses answer more than 50,000 medical queries per month on our WhatsApp-based service that provides caregivers with on-demand supp

researcharxiv-cs-cl

Automated Design of Inventory Policy with Large Language Models: An Exploratory Study

arXiv:2609.08071v1 Announce Type: new Abstract: Firms making inventory decisions have access to operational data, optimization tools, and large language models (LLMs). Typically, data characterize the

Beyond One-Shot Expansion: Contrastive Evidence Exploration for Multi-Hop Retrieval

arXiv:2609.07050v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) critically depends on retrieving the evidence necessary for effective reasoning. However, this remains particularly

Beyond Right and Wrong: Evaluating Second-order Social Reasoning in Large Language Models

arXiv:2609.05437v1 Announce Type: new Abstract: Previous AI alignment efforts have focused primarily on first-order social norms -- teaching models what is socially acceptable or unacceptable (e.g., `

safetyarxiv-cs-ai

Bridging the Semantic-Utility Gap in Multimodal RAG via Generator-in-the-Loop Alignment

arXiv:2609.08188v1 Announce Type: new Abstract: Vision-language models (VLMs) augmented with retrieval-augmented generation (RAG) benefit from access to external evidence. However, standard retrievers

safetyarxiv-cs-ai

Building Trustworthy Graph-Agentic RAG for Social Good: Architectures, Failure Propagation, and Assurance by Construction

arXiv:2609.06391v1 Announce Type: new Abstract: Graph-agentic retrieval-augmented generation combines structured evidence with adaptive controllers that can plan retrieval, traverse relations, verify

agentsarxiv-cs-ai

Data-Driven Risk Fields for Safer End-to-End Autonomous Driving

arXiv:2609.10377v1 Announce Type: cross Abstract: Safety is a fundamental requirement for autonomous driving, yet existing end-to-end driving models still lack explicit risk-aware learning capacities.

safetyarxiv-cs-cv

Local Ai

Elastoformer: Enabling Dynamic Adaptivity via Elastic Model Transformation

arXiv:2609.10018v1 Announce Type: new Abstract: EdgeAI systems are increasingly employing computer vision applications to enable intelligent, on-device decision-making in real-time. However, these dep

local-aiarxiv-cs-cv

EmoMed: An Emotionally-Aware Agent for Multimodal Medical Support with Real-Time Information Retrieval

arXiv:2609.07194v1 Announce Type: new Abstract: We present EmoMed - a multimodal medical consultation agent that adapts its responses based on users' emotional states while maintaining clinical accura

EvolveScaler: Synthesizing Information-Evolution Contexts via Executable State Machines and Natural-Language Rendering

arXiv:2609.08435v2 Announce Type: new Abstract: In persistent interactions, long contexts may encode an evolving process rather than a fixed record: later events can revise or revoke earlier informati

ExpertLens: Visualizing Embedding Spaces for Post-Hoc Explainability in MoE Enhanced Retrievers

arXiv:2609.06155v1 Announce Type: cross Abstract: Neural models, including dense retrievers, have been widely adopted in Information Retrieval (IR), often delivering state-of-the-art performance. Desp

Feyospace-v1: How the Cyber Mercury Seven Trained Frontier Cyber Models

arXiv:2609.08418v1 Announce Type: new Abstract: Training capable cyber agents is often treated primarily as a problem of model scale, yet open-weight post-training is constrained more directly by the