Search: “framework”

Conformal risk control for model-form uncertainty in parametric non-intrusive reduced-order models

arXiv:2608.03360v1 Announce Type: cross Abstract: Non-intrusive reduced-order models (NIROMs) have become a standard tool for approximating parametric partial differential equations from computer desi

applicationsarxiv-cs-lg

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Enactive Artificial Intelligence: A Decision-Centric Architecture for Complex Systems

DGX agent

arXiv:2608.03413v1 Announce Type: new Abstract: As artificial intelligence (AI) continues to evolve and mature, recent AI practices have moved beyond large language models (LLMs) and text or image gen

applicationsarxiv-cs-ai

5 Aug 2026

Evaluating LLM Trade-offs for Enterprise Automation: Lessons from Workflow Generation in a Production Enterprise Platform

model-releasesarxiv-cs-ai

arXiv:2608.03311v1 Announce Type: cross Abstract: Enterprise compliance management requires rapid adaptation to evolving regulatory frameworks (e.g., DORA, AI RMF, FedRAMP) and tight remediation SLAs.

FedCritic-MIMO: Communication-Efficient Serverless Federated Critic Learning for Massive-MIMO Resource Control in Open and Disaggregated 6G RANs

arXiv:2608.03852v1 Announce Type: new Abstract: This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource c

Heteroscedasticity of Denoising Score Matching with Generalised Smooth Noise

arXiv:2508.01597v2 Announce Type: replace Abstract: Score Matching (SM) is a powerful framework for estimating the log-density derivatives of a distribution without calculating its normalizing constan

researcharxiv-cs-lg

Human Centric Embodied Intelligence for Soft Wearable Robotics

arXiv:2608.03556v1 Announce Type: new Abstract: Soft wearable robots have evolved rapidly from proof-of-concept devices into promising platforms for rehabilitation, occupational assistance, and human

tutorialsarxiv-cs-ro

MuEvo: LLM-Driven Evolution of Multi-Heuristic Ensemble

arXiv:2608.03636v1 Announce Type: cross Abstract: Large language model-based automated heuristic design (LLM-AHD) has shown strong potential in discovering effective heuristics for combinatorial optim

researcharxiv-cs-ai

Multimodal Plant Root Phenotyping with Integration of 3D Skeleton Extraction and Language Analysis

arXiv:2608.03109v1 Announce Type: new Abstract: Plant root phenotyping is fundamental to understanding below-ground structures, optimizing crop management, and improving agricultural sustainability. T

researcharxiv-cs-cv

Operationally Feasible Synthetic Power-Grid Scenarios via Learning the AC-Operable Joint Distribution

arXiv:2608.03878v1 Announce Type: new Abstract: Synthetic power-grid scenarios are essential for planning, resilience assessment, contingency analysis, and data-driven power-system applications. Recen

Robust General Utility for Reinforcement Learning

arXiv:2608.03562v1 Announce Type: new Abstract: Reinforcement learning (RL) with general utility extends classic RL by optimizing an arbitrary utility functional of the policy-induced occupancy measur

Simulation-free and finite-time diffusion model

arXiv:2608.03117v1 Announce Type: new Abstract: The performance of generative diffusion models is determined by the choice of the reference diffusion process connecting the empirical and prior distrib

researcharxiv-cs-lg

UniWorld-Design: From Pixel Generation to Layer-Native Design

model-releasesarxiv-cs-cv

arXiv:2608.03971v1 Announce Type: new Abstract: We introduce UniWorld-Design, a framework that redefines image generation from flat pixel synthesis to structured visual composition, with semantic RGBA

Agents

Verified Tool Calls Improve LLM Agent Reliability Under Non-Atomic Failures

arXiv:2608.02645v1 Announce Type: cross Abstract: Large Language Model (LLM) agents rely on external tools to perform multistage tasks. Existing agent frameworks typically assume that tool calls are a

agentsarxiv-cs-ai

WeClawArena: An Auditable Sandbox and Benchmark for Cross-User Agents Collaboration and Security in Human-Centered Agent Networks

model-releasesarxiv-cs-ai

arXiv:2608.03499v1 Announce Type: new Abstract: Recent advances in persistent personal-agent frameworks are making human-centered agent networks realistic deployment targets: each user can be served b

A Few Neurons Reveal When LLMs Misuse Tools: Sparse Detection and Selective Steering for Reliable Tool Use

arXiv:2608.00218v1 Announce Type: new Abstract: Agentic LLMs exhibit three consequential tool-use failures: invalid arguments (validity), unnecessary calls (over-calling), and omitted calls when tools

Hardware

A Fortran General-Purpose Transpiler: Proof of Concept

arXiv:2608.00130v1 Announce Type: cross Abstract: Fortran has been the cornerstone of high-performance computing for decades and remains unmatched in many domains. Yet the language faces an expertise

hardwarearxiv-cs-cl

AdaThink-Med: Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification

arXiv:2509.24560v2 Announce Type: replace Abstract: Extended Chain-of-Thought (CoT) reasoning has significantly bolstered the capabilities of medical large language models (LLMs). However, current mod

Assessing the Benefits of Combining Advanced Deep Learning Techniques for Post-Disaster Building Damage Assessment from UAV Imagery

arXiv:2608.01906v1 Announce Type: new Abstract: Rapid and accurate post-disaster building damage assessment is essential, yet remains a challenging task. Unmanned Aerial Vehicle (UAV) imagery offers a

applicationsarxiv-cs-cv

Local Ai

Assessing the Impacts of Imperfect Datasets on Client Selections in Federated Learning

arXiv:2608.02250v1 Announce Type: new Abstract: Federated learning (FL) is a popular distributed learning framework where multiple clients perform local training and a server aggregates the locally up

local-aiarxiv-cs-lg

Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization

arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical findi

researcharxiv-cs-cl

Averaging Bias: Human Faithfulness Annotations are not Locally Faithful

arXiv:2608.00205v1 Announce Type: new Abstract: Evaluation of faithfulness of text summarization treats a model generated summary as faithful only if every of its sentences is supported by the source

Complete Motion Planning using Workspace-Fibered Decomposition for nR-Planar Manipulator

arXiv:2608.01172v1 Announce Type: new Abstract: We propose a workspace-fibered decomposition framework for motion planning in nR planar redundant manipulators operating in cluttered environments. Rath

researcharxiv-cs-ro

Computational and Statistical Guarantees of the extit{c}-Rectified flow

arXiv:2608.02487v1 Announce Type: cross Abstract: Recently, rectified flow has emerged as a fundamental framework for large-scale image generation, powering state-of-the-art systems such as FLUX.1 and

applicationsarxiv-cs-lg

Conformalized Large Language Models under Configuration Shift

arXiv:2608.01460v1 Announce Type: new Abstract: Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs)

researcharxiv-cs-lg

CoT-Edit: Let CoT Guide Instruction Video Editing

arXiv:2608.01113v1 Announce Type: new Abstract: Text-driven instruction-based video editing in complex scenes remains challenging: purely textual prompts often fail to capture precise spatial relation

tutorialsarxiv-cs-cv

CRISP: Critical Step Perception for Training Efficient Deep Search Agents

arXiv:2608.01867v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly extended into deep search agents that solve complex questions through multi-step interaction with external

Deep Research Pretraining via Predictive Navigation

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

Domain-Generalized Adaptive Semantic Communication for Collaborative Perception

arXiv:2608.00056v1 Announce Type: cross Abstract: We propose RSTA, a domain-generalized semantic communication framework enabling source-free V2X collaborative perception under both observation-domain

Domain-Specific Evaluation of Text-to-Speech Systems: A Multi-Metric Benchmarking Study

arXiv:2608.02235v1 Announce Type: new Abstract: Recent advances in neural text-to-speech (TTS) systems have substantially improved speech naturalness and intelligibility across many languages. However

Exploiting Intrinsic Duality for Multi-Hop Question Generation

arXiv:2608.00712v1 Announce Type: new Abstract: Multi hop question generation (MQG) aims to generate questions from multiple given documents and target answers, whereas question answering (QA) focuses

Extended Field of View Analysis for VideoGAN-based Trajectory Generation

arXiv:2608.02289v1 Announce Type: new Abstract: Realistic and diverse trajectory generation is central to enabling higher levels of vehicle automation. While rule-based and classical learning-based me

researcharxiv-cs-cv

Feed-Forward Steering in Transformer Residual Dynamics

arXiv:2608.02071v1 Announce Type: new Abstract: Attention-only dynamical theories model Transformer residual directions as particles aggregating on a sphere. We extend this framework by incorporating

Geometric Analysis of Token Selection in Multi-Head Attention

arXiv:2602.01893v2 Announce Type: replace-cross Abstract: We present a geometric framework for analysing multi-head attention in large language models (LLMs). Without altering the mechanism, we view s

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation

arXiv:2511.20635v3 Announce Type: replace Abstract: Pre-trained video models learn powerful priors for generating high-quality, temporally coherent content. While these models excel at temporal cohere

tutorialsarxiv-cs-cv

Interaction Dynamics MPC for Knee Rehabilitation Exoskeletons: A Closed-Loop SEA Outer-Loop Study

arXiv:2606.13485v3 Announce Type: replace-cross Abstract: Safe rehabilitation is an interaction-dynamics problem: the controller must regulate a prescribed motion while absorbing involuntary spasm, vo

safetyarxiv-cs-ro

LEAP: Lean Environment-Feedback via Adaptive Pruning for Code RL in GPU Kernel Generation

arXiv:2608.01804v1 Announce Type: new Abstract: Post-training large language models (LLMs) via reinforcement learning (RL) has significantly advanced code generation capabilities. To bypass the heavy

Learning Smooth SE(3) Trajectories under Left-Invariant Riemannian Metrics

arXiv:2608.01562v1 Announce Type: new Abstract: Optimal trajectory generation for rigid-body motions on Lie groups can be formulated as a variational problem that minimizes energy functionals defined

tutorialsarxiv-cs-ro

LiveLight: Real-time Streaming Video Relighting with Interactive Control

arXiv:2608.01771v1 Announce Type: new Abstract: We present LiveLight, the first diffusion-based framework for real-time streaming video relighting with interactive 3D lighting control. Achieving this

applicationsarxiv-cs-cv

Localization in Spatiotemporal Fields via Environmental PDEs

arXiv:2608.00272v1 Announce Type: new Abstract: This paper proposes a localization framework that uses spatiotemporal fields governed by partial differential equations (PDEs) as localization signature

safetyarxiv-cs-ro

MAPLE: Metadata Augmented Private Language Evolution

arXiv:2603.19258v2 Announce Type: replace Abstract: Differentially private (DP) fine-tuning of large language models (LLMs) requires massive compute and full model access, which rules out state-of-the

Agents

MedTextWeaver: Procedural Knowledge Evolution in Agentic Medical Text Editing

arXiv:2602.00740v2 Announce Type: replace Abstract: Medical text editing is essential for improving communication among diverse stakeholders in clinical settings. However, adapting LLM agents to this

agentsarxiv-cs-cl

MedUPS: Towards Diagnostic Assistance in Uncommon Medical Cases with Large Language Models

arXiv:2608.01012v1 Announce Type: new Abstract: Uncommon and off-guideline cases are difficult for clinical decision support, because physicians must make a series of management decisions under diagno

Mitigating Visual Hallucinations in Multimodal Systems through Retrieval-Augmented Reliability-Aware Inference

arXiv:2606.15782v2 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-language understanding and natural-language response

safetyarxiv-cs-cv

Not All EEG Moments Are Equal: Position-Adaptive Time Scheduling for EEG Generation

arXiv:2608.00048v1 Announce Type: cross Abstract: Electroencephalography (EEG) generation is essential for alleviating data scarcity and enabling large scale neural modeling in brain computer interfac

Local Ai

Open-DiffLoco: Open-Source Differentiable Learning for Deployable Blind Quadruped Locomotion

arXiv:2608.02069v1 Announce Type: cross Abstract: Developing deployable locomotion policies through conventional reinforcement learning often requires complex reward engineering and expensive training

local-aiarxiv-cs-lg

Optimized Piecewise Affine Abstractions of Neural Networks with Learnable Activation Functions

arXiv:2602.06737v2 Announce Type: replace Abstract: We present a generalized framework for the range verification of neural networks featuring non-linear activation functions. Our approach first const

tutorialsarxiv-cs-lg

Policy Optimality Measurement for Multi-Vehicle Decision-Making: From Extrinsic Indicators to Intrinsic Quality

arXiv:2608.01133v1 Announce Type: new Abstract: Evaluating Multi-Agent Reinforcement Learning (MARL) policies in autonomous driving fundamentally relies on extrinsic statistical indicators (e.g., rewa

Practical Noise Modeling for SPAD Intensity Imaging

arXiv:2608.00489v1 Announce Type: new Abstract: Single-photon avalanche diode (SPAD) cameras are promising for low-light and high-dynamic-range intensity imaging, but their practical use is limited by

safetyarxiv-cs-cv