Search: “framework”

AgentPatch: Coarse-to-Fine Weak-Task Repair for Merging Agentic Multimodal Large Language Models

arXiv:2608.06699v1 Announce Type: new Abstract: Agentic multimodal large language models (MLLMs) extend multimodal perception and reasoning with planning, tool use, and interaction in dynamic environm

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An Agentic Hybrid Top-Down and Bottom-Up Approach to Knowledge Graph Generation

DGX agent

arXiv:2608.07023v1 Announce Type: cross Abstract: Organizing thousands of unstandardized, multilingual expertise declarations is a persistent challenge for Human Resources (HR) platforms, directly imp

agentsarxiv-cs-ai

10 Aug 2026

An Exploratory Evaluation of LLM-Assisted Rewriting of Moderate-Complexity Financial Sentences for DisCoCat-Based Sentiment Analysis

model-releasesarxiv-cs-cl

arXiv:2608.07439v1 Announce Type: new Abstract: Quantum natural language processing (QNLP) provides a grammar-aware framework for text modeling, and Distributional Compositional Categorical (DisCoCat)

AnyTrack: Unifying Visual Object Tracking with Any Modalities

arXiv:2608.06773v1 Announce Type: new Abstract: Visual object tracking aims to continuously locate specific targets within sequential frames, evolving from single-modal methods to multi-modal ones. Ho

Autonomous discovery of accelerator commissioning algorithms

arXiv:2608.07138v1 Announce Type: cross Abstract: Simulated commissioning has become essential for de-risking modern light-source design and commissioning, but the procedures being simulated are still

Beyond Fluency: A Clinical Benchmark and Anomaly-Enhanced Baseline for Spine MRI Report Generation

model-releasesarxiv-cs-cv

arXiv:2608.07117v1 Announce Type: new Abstract: Radiology reporting is time-consuming and subject to inter-rater variability, making automated report generation an attractive clinical application for

bioMoR: Biology-Guided Mixture-of-Recursions for Effective Genomic Learning

arXiv:2608.06727v1 Announce Type: new Abstract: Transformer models for high-dimensional omics analysis process thousands of genes or pathways, although only a subset requires deep computation. Mixture

Bootstrap-Conditioned Action Selection with Tabular Foundation Models

arXiv:2608.06559v1 Announce Type: new Abstract: Contextual bandits offer a natural framework for sample-efficient personalization, but practical deployment remains difficult under sparse, biased inter

safetyarxiv-cs-lg

Degradation-Aware Prompt Learning with Cross-Modal Compensation for Adverse Weather Removal

arXiv:2608.06939v1 Announce Type: new Abstract: Adverse weather causes diverse and complex image degradations, severely compromising the reliability of computer vision systems. Existing all-in-one res

Dual-Space Modality Consistency Learning for Universal Cross-Modal Re-Identification

arXiv:2608.06943v1 Announce Type: new Abstract: Cross-modal Re-Identification (ReID) aims to retrieve the same identity across heterogeneous imaging modalities and has been widely studied in visible-i

Local Ai

Evolving Parallel Algorithm Portfolios via Potential-Aware Instance Generation with LLMs

arXiv:2608.06808v1 Announce Type: new Abstract: The Automatic Construction of Portfolios via Large Language Models (LLM-ACP) suffers from poor generalization in practical few-shot scenarios when solvi

local-aiarxiv-cs-ai

Free Denoising Diffusion Models

arXiv:2510.22778v3 Announce Type: replace-cross Abstract: We develop a free-probabilistic framework for denoising diffusion, in which the data is a self-adjoint operator and its law a spectral distrib

Local Ai

Geometry-Aware Camera Localization for Bronchoscopy

arXiv:2608.07116v1 Announce Type: cross Abstract: Camera localization in bronchoscopy remains a challenging problem due to stringent accuracy requirements, real-time constraints, and limited training

local-aiarxiv-cs-ai

GOPI: Generation-Oriented 3D Pose Inference for Furniture Insertion from Single-View RGB-D Indoor Scenes

arXiv:2608.06836v1 Announce Type: new Abstract: We study the problem of inserting new furniture into indoor scene images. Under masked single-view 2D image-plane conditioning, however, the physical sc

H2AL: Hyperbolic Hierarchy-aware Aggregative Learning for Registration-based Few-shot Medical Image Segmentation

arXiv:2608.07340v1 Announce Type: cross Abstract: Registration-based Few-shot medical image segmentation (RFMIS) aims to generate pseudo-labels for unlabeled images by warping a labeled image through

tutorialsarxiv-cs-ai

LyEvO: Lyapunov-Guided Evolutionary Optimization for Safe and Robust Sim-to-Real Policy Learning

arXiv:2608.06481v1 Announce Type: cross Abstract: Training controllers that are safe and robust in simulation, and systematically assessing their readiness for real-world deployment, remain key challe

Multimodal Drivers' Emotion Recognition and Safety-Oriented Intervention for Intelligent Transportation Systems

arXiv:2608.06378v1 Announce Type: cross Abstract: Driver emotions can affect risk perception, decision-making, and vehicle control under complex road conditions. Existing studies mainly focus on drive

MuST-VAD: Mutual Structured Learning for Video Anomaly Detection

arXiv:2608.06913v1 Announce Type: new Abstract: In this paper, we propose MuST-VAD, a mutual structured learning framework for weakly supervised video anomaly detection (VAD) in which an anomaly detec

tutorialsarxiv-cs-cv

NiyamAI - An Intent-Bound AI Agent with Cryptographically Verifiable Guardrails using Zero-Knowledge Proofs

model-releasesarxiv-cs-ai

arXiv:2608.07167v1 Announce Type: new Abstract: Giving an AI agent the ability to send emails, query databases, or execute commands is useful--until the agent is tricked into doing something it should

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

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

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

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

Applications

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

After evaluating one of our upcoming models, Astra, we're treating it as our first 'critical' model for cybersecurity under our Preparedness…

After evaluating one of our upcoming models, Astra, we're treating it as our first 'critical' model for cybersecurity under our Preparedness Framework. This is a scenario we've planned for, and we're

model-releasesopenai--x

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

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

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

Applications

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

Local Ai

Wan-Animate-2: Pushing the Application Boundaries of Character Animation Models

📝 Introduction We present Wan-Animate-2, a novel end-to-end character animation framework that directly consumes driving videos in a redesigned Diffusion Transformer, which achieves high-fidelity moti

local-air-localllama

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

6 Aug 2026

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