Search: “framework”

Robust Average-Reward Markov Decision Processes: Minimax-Optimal Learning via Plug-in Reductions

arXiv:2608.06545v1 Announce Type: new Abstract: Distributionally robust Markov decision processes provide a principled framework for sequential decision making under model uncertainty. We study how ma

safetyarxiv-cs-lg

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Same Attention, Different Truths: Put Logit-Lens over Visual Attention to Detect and Mitigate LVLM Object Hallucination

DGX agent

arXiv:2608.07302v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) often suffer from object hallucination, generating objects that are absent from the image. Prior work largely att

researcharxiv-cs-ai

10 Aug 2026

Hardware

Scalable High-Fidelity Macromolecular Docking for GPU-Accelerated Supercomputers

arXiv:2608.07078v1 Announce Type: cross Abstract: Flexible macromolecular docking offers high-fidelity predictions of biomolecular interactions, but remains prohibitively expensive at scale. Among exi

hardwarearxiv-cs-ai

Scalable Long-Horizon Planning with Staggered Updates for Lifelong MAPF

arXiv:2608.06702v1 Announce Type: cross Abstract: Lifelong Multi-Agent Path Finding (LMAPF) requires generating collision-free paths for large agent fleets under strict real-time constraints. Reactive

Synthetic LiDAR Data Generation and Deterministic Downsampling for Point Cloud Classification on the Edge

arXiv:2608.07106v1 Announce Type: new Abstract: Deploying three-dimensional deep learning frameworks to low-power embedded processors is bottlenecked by the unstructured nature of spatial data and the

applicationsarxiv-cs-lg

Understanding Differentiable Embeddings Through Differential and Integral Geometry

arXiv:2608.06809v1 Announce Type: new Abstract: How can an analyst decide whether a nonlinear dimensionality reduction embedding can be trusted? Existing diagnostics provide only partial answers: proj

UniCycleFlow: Bidirectional Unpaired Image Translation with a Shared Rectified Flow

arXiv:2608.06784v1 Announce Type: new Abstract: Bidirectional unpaired image translation must preserve source-specific structure while learning coherent transformations in both directions without pair

UniJEPA: A Unified Joint-Embedding Predictive Architecture for Task-Agnostic Visual World Modeling

arXiv:2608.07409v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) have emerged as a principled framework for self-supervised learning of world models in compact latent s

tutorialsarxiv-cs-cv

Unsupervised Adaptation of PDE Foundation Models

arXiv:2608.07053v1 Announce Type: new Abstract: Pretrained partial differential equation (PDE) foundation models can generalize across different equations, but adapting them to unseen PDE systems typi

Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination

arXiv:2608.05391v1 Announce Type: new Abstract: Care plan coordination demands synthesizing heterogeneous clinical, functional, and psychosocial information across multiple professional disciplines, w

safetyarxiv-cs-ai

Bayesian adaptively-weighted ensembles for few-shot abdominal segmentation

arXiv:2608.05815v1 Announce Type: new Abstract: Few-shot learning has emerged as a promising approach for anatomical segmentation when labelled data are scarce. However, different few-shot learning al

Beyond Relevance: Bayesian Evidence Acquisition for Agentic Whole-Slide Image Reasoning

arXiv:2608.05757v1 Announce Type: new Abstract: Whole-slide image (WSI) reasoning requires an agent to sequentially acquire visual evidence before answering a diagnostic question. Existing training-fr

agentsarxiv-cs-cv

BioKD: Selective Physiology-to-Video Knowledge Distillation via Reliability Gate for Emotion Recognition

arXiv:2608.06023v1 Announce Type: new Abstract: To address the limitations of video-based emotion recognition under ambiguous or socially masked behavioral cues, as well as the poor deployability of p

tutorialsarxiv-cs-lg

D-CLOT: Double Closed Loop Optimal Transport for Unsupervised Action Segmentation

model-releasesarxiv-cs-ai

arXiv:2608.05877v1 Announce Type: cross Abstract: Optimal transport (OT) has emerged as an effective framework for unsupervised action segmentation. Yet, in existing OT-based methods, the latent actio

Dual-Output Multi-Exposure HDR Reconstruction via SDR Fusion and Gain Map Inverse Tone Mapping

arXiv:2608.05626v1 Announce Type: new Abstract: We propose DOME-HDR, a dual-output multi-exposure HDR reconstruction framework that jointly produces a perceptually balanced SDR image and a consistent

Equipment-centric workpiece localization in near real-time using deep learning-based vision and event-driven finite state machines

arXiv:2608.05744v1 Announce Type: new Abstract: Continuous workpiece localization is essential for traceability and process coordination in hot forging, but direct tracking is unreliable because of ex

Estimating time spent on work tasks

arXiv:2608.05172v1 Announce Type: cross Abstract: The task-based framework in economics models occupations as bundles of tasks. It is the standard lens for understanding how technology affects work: a

safetyarxiv-cs-ai

FashionPose: Unified Text-Driven Fashion Synthesis with Joint Geometric and Photometric Control

arXiv:2507.13311v2 Announce Type: replace Abstract: Realistic and controllable garment synthesis is essential for fashion e-commerce, yet it demands precise coordination between human pose geometry an

safetyarxiv-cs-cv

Integrating Implicit and Explicit Relational Biases through Graph-Based Multiple Instance Learning: A Case Study in Skin Lesion Diagnosis

arXiv:2608.06037v1 Announce Type: new Abstract: Relational inductive biases are essential for capturing structural dependencies among data. This study investigates a dual-level relational framework fo

tutorialsarxiv-cs-ai

OPERA: Operator-residual feedback for reliable autonomous optical experiments with language-model agents

arXiv:2608.05990v1 Announce Type: new Abstract: Autonomous agents choose actions using scores that may not reflect experimental success. We developed OPERA, an operator-residual framework for optical

OrchestraBench: Evaluating Multi-Agent Orchestration Failure Modes, Recovery, and Decomposition Quality

model-releasesarxiv-cs-ai

arXiv:2608.05263v1 Announce Type: new Abstract: Multi-agent orchestration frameworks are moving from demos to production, yet benchmarks typically report task accuracy without diagnosing why a pipelin

Poli-Bias: Understanding and Measuring Large Language Model Biases in International Political Conflicts

arXiv:2608.06123v1 Announce Type: new Abstract: Measuring political bias in large language models (LLMs) remains challenging as it can manifest through subtle differences in framing, argumentation, an

safetyarxiv-cs-ai

Positive-Unlabeled Preference Optimization For Chest X-ray Report Generation

arXiv:2608.05341v1 Announce Type: new Abstract: Vision-Language Models (VLMs) for radiology report generation are typically trained on retrospective clinical reports, which suffer from omission noise:

applicationsarxiv-cs-cv

Potential Matching Optimal Transport: Continuous Normalizing Flows for Exact p-Wasserstein Dynamics

arXiv:2608.05666v1 Announce Type: new Abstract: We introduce Potential Matching Optimal Transport (PMOT), a potential-flow framework for general p-cost optimal transport with c_p(x,y)=|x-y|^p. PMOT pa

TriQua: Reconciling Granularity and Context in Factuality Evaluation

arXiv:2608.05228v1 Announce Type: new Abstract: The 'decompose-then-verify' paradigm for LLM factuality evaluation faces a fundamental trade-off: atomic facts, i.e., one sentence conveying one unit of

A geometry-based deep equilibrium model for image restoration under multiplicative Gamma noise

arXiv:2608.04944v1 Announce Type: cross Abstract: We propose a deep learning framework for image restoration from images degraded by both multiplicative Gamma noise and blur. Unlike conventional deep

A Long-Run Persistence Theory for AI Systems under the Redundancy-Adjusted Artificial Age Score (AAS)

arXiv:2608.04012v1 Announce Type: new Abstract: Artificial intelligence systems are increasingly expected to operate over repeated cycles of interaction, adaptation, and update rather than through iso

AI Literacy for Legal Translation: Developing Digital Resilience

arXiv:2608.04641v1 Announce Type: new Abstract: Generative AI is transforming legal translation by introducing opportunities alongside linguistic, technical, legal, ethical and cognitive risks. This c

applicationsarxiv-cs-ai

ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation

arXiv:2608.05026v1 Announce Type: cross Abstract: High-quality annotation of artworks is essential for computational art research, yet extracting implicit semantics remains challenging due to the reli

Data-Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles

arXiv:2602.07453v2 Announce Type: replace Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study

safetyarxiv-cs-lg

Enhancing Low Back Pain Assessment with Diffusion Models for Lumbar Spine MRI Segmentation

arXiv:2608.04906v1 Announce Type: new Abstract: This study introduces a diffusion-based framework for robust and accurate semantic segmentation of lumbar spine MRI scans from patients with low back pa

Galaxy Phase-Space and Field-Level Cosmology: The Strength of Semi-Analytic Models

model-releasesarxiv-cs-lg

arXiv:2512.10222v2 Announce Type: replace-cross Abstract: Semi-analytic models are a widely used approach to simulate galaxy properties within a cosmological framework, relying on simplified yet physi

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds

arXiv:2608.04827v1 Announce Type: cross Abstract: We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with ge

tutorialsarxiv-cs-lg

Learning to Resolve Neutron Resonances with Fully Convolutional Neural Networks

arXiv:2608.04027v1 Announce Type: new Abstract: This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neu

safetyarxiv-cs-lg

Monte Carlo Tree Search for Table-to-Multimodal Report Generation

model-releasesarxiv-cs-ai

arXiv:2608.04071v1 Announce Type: new Abstract: Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical c

Physics-informed reduced-order modelling with equivariant spectral submanifolds

model-releasesarxiv-cs-lg

arXiv:2608.04239v1 Announce Type: new Abstract: Spectral submanifold (SSM) reduction has emerged as a mathematically principled route to reliable nonlinear reduced-order models, capturing dynamics bey

Rethinking Reservoir Pruning: A Dynamical Perspective for Echo State Networks

arXiv:2608.04593v1 Announce Type: cross Abstract: Echo State Networks (ESNs) offer an efficient framework for temporal prediction, but their randomly initialized reservoirs are often over-parameterize

applicationsarxiv-cs-ai

Static Timing Orchestration for Tree-Structured Robot Control Firmware

arXiv:2608.04600v1 Announce Type: new Abstract: As robotic systems become increasingly complex, generating control firmware from structural description files has emerged as a promising paradigm for re

researcharxiv-cs-ro

Stochastic Emulation using Generalized Stratified Sampling for Performance-Based Risk Optimization of Structures

arXiv:2608.05006v1 Announce Type: new Abstract: Metamodels are instrumental in reducing the computational burden associated with nested reliability analyses and optimization loops in Performance-Based

The Cost of Binarizing Survival Outcomes in Clinical Prognostic Modeling

arXiv:2608.04046v1 Announce Type: cross Abstract: Survival analysis is an established framework for analyzing time-to-event data, yet many clinical machine learning studies still binarize the outcome

Towards a New Grammar of Reasoning for Artificial Legal Intelligence and the Mecelle as Its Semantic Protocol

arXiv:2608.04011v1 Announce Type: cross Abstract: This article examines the enduring epistemic and methodological crisis of traditional legal practice in light of the opportunities and constraints int

Towards End-to-End Multilingual Metaphor Processing: Integrating Detection, Translation, and Evaluation

arXiv:2608.04260v1 Announce Type: new Abstract: Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require r

researcharxiv-cs-cl

UBLLIE: Unified Backlight and Low-Light Image Enhancement

arXiv:2608.04429v1 Announce Type: new Abstract: Backlit and low-light images often suffer from severe exposure imbalance or global underexposure, presenting significant challenges for both visual perc

applicationsarxiv-cs-cv

Accelerating Human-Aware Robot Trajectory Generation via Diffusion and Consistency Distillation

arXiv:2608.03159v1 Announce Type: new Abstract: This research proposes a constrained motion planning framework for robot manipulators in human-robot interaction (HRI). For a non-redundant manipulator

safetyarxiv-cs-ro

Activation-Guided Neuron Intervention to Induce Alzheimer's-Related Computational Language Phenotypes in a Large Language Model

arXiv:2608.03067v1 Announce Type: new Abstract: Changes in spontaneous speech provide an early signal of cognitive dysfunction in Alzheimer's disease (AD) that large language models (LLMs) can detect.

researcharxiv-cs-cl

AS-FedBridge: Pseudo-Spike Bridge Distillation for Heterogeneous ANN-SNN Federated Learning

model-releasesarxiv-cs-lg

arXiv:2608.03324v1 Announce Type: new Abstract: Federated learning enables collaborative model training across distributed edge devices while strictly preserving data privacy. To facilitate practical

Autoreflection: How Agentic Strange Loops Turn Human Culture into AI Infrastructure

arXiv:2608.03800v1 Announce Type: cross Abstract: An LLM-based agent is a loop that reads itself. Agentic frameworks externalize identity, memory, and disposition into editable files. The agent loads

Behaviorally Adaptive Visual Diversion for Inclusive and Resilient Digital Assessment Delivery

arXiv:2608.03531v1 Announce Type: new Abstract: Institutions increasingly rely on browser lockdown, webcam monitoring, and behavioral analytics to secure high-stakes digital assessments, yet these mec