Search: “framework”

SPK: Eliciting Structured Prior Knowledge for Interpretable Out-of-Distribution Detection in Real-Time Object Detection

arXiv:2608.19080v1 Announce Type: new Abstract: Object detectors often produce over-confident predictions for objects outside their training categories, leading to so-called out-of-distribution (OoD)

safetyarxiv-cs-cv

20 Aug 2026

Human

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Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents

DGX agent

arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve.

safetyarxiv-cs-lg

20 Aug 2026

Hardware

Tuning the Stochastic Machine: A Systems Engineer's Operating Model for Human-AI Engineering

arXiv:2608.19125v1 Announce Type: new Abstract: When an expert corrects an LLM assistant's error, the correction usually dies with the session, and the error class returns. I argue this is an operatio

hardwarearxiv-cs-ai

20 Aug 2026

VERAGMIL: Virtual Environment for Scooping Granular Foods with Imitation Learning Models

arXiv:2608.18258v1 Announce Type: new Abstract: Robot-Assisted Feeding (RAF) systems are essential for assisting individuals with disabilities or motor impairments in eating tasks. Manipulating granul

researcharxiv-cs-ro

20 Aug 2026

A Constant-Competitive Algorithm for Dynamic Mixture-of-Experts Serving

arXiv:2608.16947v1 Announce Type: cross Abstract: Huang, Lou, and Xiao introduced Dynamic Mixture-of-Experts Serving and gave an O(sqrt(log k))-competitive randomized algorithm for its integral primal

researcharxiv-cs-lg

Action-Effect Memory Pretraining for Robot Manipulation

arXiv:2606.12499v2 Announce Type: replace Abstract: We present AEM, an Action-Effect Memory pretraining framework for robot manipulation that learns compact temporal representations from vision-action

safetyarxiv-cs-ro

Asynchronous Message Passing for Addressing Oversquashing in Graph Neural Networks

arXiv:2509.06777v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) suffer from oversquashing, where structural bottlenecks limit message propagation between distant nodes, hindering task

safetyarxiv-cs-lg

Audio Physical Dynamics Inspired Deepfake Detection for Voice Authentication Systems

arXiv:2512.06040v2 Announce Type: replace-cross Abstract: Voice authentication systems deployed at the network edge face dual threats: a) sophisticated deepfake synthesis attacks and b) control-plane

Can Large Language Models Explain Flight Safety Events? A Prior-Guided Semantic LLM-based Approach

arXiv:2608.18017v1 Announce Type: new Abstract: Improving flight safety with flight data requires not only accurate detection of risk events, but more importantly, clear interpretation of their underl

Cluster Aggregated GAN (CAG): A Cluster-Based Hybrid Model for Appliance Pattern Generation

arXiv:2512.22287v4 Announce Type: replace-cross Abstract: Synthetic appliance data are essential for developing non-intrusive load monitoring algorithms and enabling privacy preserving energy research

Conformal Prediction for Molecular Properties under Label Shift

arXiv:2608.17678v1 Announce Type: new Abstract: Drug discovery and development underpins healthcare but remains costly and failure-prone. A critical bottleneck lies in predicting molecular properties

applicationsarxiv-cs-lg

Agents

DeAR: Decentralized Agentic Reasoning via Capability Grounding and Collaborative Thought Navigation

arXiv:2608.17282v1 Announce Type: new Abstract: Existing agentic reasoning systems typically rely on centralized protocols. This design introduces routing bottlenecks and static role allocations that

agentsarxiv-cs-ai

Deep Learning for Cross-Border Electricity Price Forecasting: A Comparative Study

model-releasesarxiv-cs-lg

arXiv:2608.17091v1 Announce Type: new Abstract: While publicly available electricity market data presents a valuable resource for forecasting research, the field lacks established benchmark datasets f

Delta2Gamma: Band-Wise Adaptive Contrastive Learning of EEG for Alzheimer's Disease Detection

arXiv:2608.17231v1 Announce Type: cross Abstract: Low-cost, scalable screening for dementia remains an open problem. Imaging-based diagnosis is costly and hard to deploy widely. Electroencephalography

applicationsarxiv-cs-ai

Local Ai

Education-centered critical policy analysis of AI: Ghana's AI strategy as a case

arXiv:2608.16910v1 Announce Type: cross Abstract: National AI strategies increasingly guide governance, workforce development, innovation, and competitiveness, but less is known about how they frame e

local-aiarxiv-cs-ai

Effector-Centric NMPC of Tiltable-Multirotors for Offset-Free Omnidirectional Aerial Manipulation

arXiv:2608.17819v1 Announce Type: new Abstract: Aerial manipulation extends robotic operations to previously inaccessible aerial environments. Unlike arm-equipped aerial systems, tiltable-multirotors

applicationsarxiv-cs-ro

Hardware

Evaluating AI Agent Skill Performance with NVIDIA SkillEvaluator

NVIDIA SkillEvaluator is an open‑source framework that measures how pre‑verified “skills” improve AI agent performance through static checks, distinctiveness analysis, and live task runs in isolated e

hardwarenvidia-developer

G-ReAct: Graph-Guided Deep Search via Structure-State Co-Evolution

arXiv:2608.01324v2 Announce Type: replace Abstract: Deep search has become a fundamental capability of large language models (LLMs) for solving open-domain complex tasks. However, existing approaches

LLM Enhancement with Domain Expert Mental Model to Reduce LLM Hallucination with Causal Prompt Engineering

arXiv:2509.10818v2 Announce Type: replace Abstract: When consequential decisions depend on knowledge that exists nowhere in writing, LLMs hallucinate not from retrieval failure but from model absence.

Local Ai

MotoSafety: Edge-AI with Learned Temporal Importance for Two-Wheeler Collision Risk Assessment Under Time Pressure

arXiv:2608.17823v1 Announce Type: cross Abstract: Powered two-wheeler riders face critical safety challenges in low- and middle-income countries, yet limited studies exist on how cognitive stressors s

local-aiarxiv-cs-ai

Serverless Apache Spark on Google Cloud: Architecture Choices & AI Troubleshooting

model-releasesgoogle-cloud-ai

In modern enterprise data engineering, Apache Spark remains a cornerstone framework for processing massive datasets at scale. However, managing infrastructure such as provisioning clusters, tuning YAR

Solving nonconvex Hamilton--Jacobi--Isaacs equations with PINN-based policy iteration

arXiv:2507.15455v3 Announce Type: replace-cross Abstract: We propose a mesh-free policy iteration framework that combines classical dynamic programming with physics-informed neural networks (PINNs) to

SW-ProxyCE: Zero-Query Adversarial Transfer from Public EEG Encoders to Private Downstream Models

model-releasesarxiv-cs-lg

arXiv:2608.16931v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have recently emerged as a promising paradigm for EEG decoding by learning reusable representations from

The Curious Case of Exploding DecPOMDPs: Containing the Fire through Policy Counting

arXiv:2608.17749v1 Announce Type: new Abstract: Decentralised partially observable Markov decision processes (DecPOMDPs) provide a general framework for modelling multi-agent decision making under unc

Too Sure to Be Safe: Model Calibration for Reliable Log Anomaly Detection

arXiv:2608.17965v1 Announce Type: cross Abstract: Online log anomaly detection is critical for maintaining the reliability of large-scale computing systems. Although recent language model-based log an

When to Review: Spaced Repetition for Continual Pre-Training of Language Models

arXiv:2608.17530v1 Announce Type: new Abstract: Continual pre-training of large language models must acquire new information without erasing old knowledge. Existing replay methods often choose a globa

A cross-modal generative model for incomplete and degraded prostate MRI with multicentre clinical validation

arXiv:2608.16233v1 Announce Type: cross Abstract: Missing or degraded sequences can limit prostate multiparametric MRI. We developed MSCNet, a sequence-conditioned cross-modal generative framework for

A Policy Algebra for Trust-Preserving Agentic AI Execution

arXiv:2608.16402v1 Announce Type: new Abstract: Large language model-based agentic frameworks primarily optimize capability: whether an agent can reason, retrieve information, call tools, delegate wor

ACTS-SQL: Agentic and Critic-Oriented Tree-Structured SQL Correctness with Large Language Models

arXiv:2608.15145v1 Announce Type: new Abstract: Large Language Models (LLMs) have been increasingly adopted in Text-to-SQL systems, yet SQL errors remain a major obstacle in real-world Text-to-SQL inf

Argumentation for Common Ground: Finding Zones of Possible Agreement between Individuals in Conflict

arXiv:2608.15634v1 Announce Type: new Abstract: How can common ground between societies in conflict be identified when citizens' acceptability of peace agreements is shaped by contested narratives? Su

BDIP-Net: Dual-Interaction Graph Learning for Property Prediction of Bilayer Materials

arXiv:2608.14640v1 Announce Type: cross Abstract: Stacked bilayer materials exhibit rich stacking-dependent properties driven by the interplay between strong intra-layer bonding and weak inter-layer v

ClawGym II: Exploring Black-Box RL on Agent Harness

arXiv:2608.16798v1 Announce Type: cross Abstract: Agent harnesses have substantially improved performance on long-horizon tasks by coordinating agent interactions with the environment. However, reinfo

Comprehensive Benchmarking of Deep Learning Architectures for Lung Cancer Histopathology

arXiv:2608.15915v1 Announce Type: cross Abstract: Lung cancer remains the leading cause of cancer-related mortality worldwide, while histopathological diagnosis is often affected by inter-observer var

Decentralized Federated Learning for Heterogeneous Multi-Task Semantic Communication

arXiv:2608.15256v1 Announce Type: new Abstract: Collaborative training in distributed semantic communication (DSC) networks typically relies on decentralized federated learning (DFL). However, pushing

Demand-Driven Vertiport Siting and Discrete-Event Fleet Simulation for On-Demand Urban Air Mobility Network Design

arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and d

applicationsarxiv-cs-ai

Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density

arXiv:2608.16506v1 Announce Type: cross Abstract: Dataset alignment is a central step in data analysis across science and engineering, where the goal is to match observations between datasets. Entropi

safetyarxiv-cs-lg

DuplexGen: Decoupling Content, Timing, and Acoustics for Synthetic Dialogue Speech

arXiv:2608.16053v1 Announce Type: new Abstract: Synthetic conversational speech has become an important resource for developing and evaluating conversational speech systems. However, existing dialogue

researcharxiv-cs-cl

Dynamic Pricing and Advertising with Demand Learning

arXiv:2304.14385v4 Announce Type: replace-cross Abstract: We consider a novel pricing and advertising framework in which a seller not only sets the product price but also designs flexible advertising

safetyarxiv-cs-lg

Evolving Executable Pipeline Programs for AutoML with Language Models

model-releasesarxiv-cs-lg

arXiv:2608.16416v1 Announce Type: new Abstract: Automated machine learning (AutoML) systems search for pipelines within a space of preprocessing operators, learners, and hyper-parameters specified in

Explainable Heterogeneous Anomaly Detection in Financial Networks via Adaptive Expert Routing

arXiv:2510.17088v3 Announce Type: replace-cross Abstract: Financial anomalies arise from heterogeneous mechanisms - price shocks, liquidity freezes, contagion cascades, and momentum reversals - yet ex

Local Ai

Global Federated Learning Strategies for Building Efficient Personalized Models

arXiv:2608.15107v1 Announce Type: new Abstract: Federated learning (FL) is a practical framework that can train models on distributed user data while guaranteeing data privacy; however, due to heterog

local-aiarxiv-cs-lg

GUIDER: Evaluating Goal-Free Human Intent Inference for Teleoperated Manipulation on Real-Robot Data

arXiv:2608.15446v1 Announce Type: new Abstract: This paper presents an evaluation of a goal-free probabilistic framework for human intent inference during robotic manipulation. We deploy the Global Us

applicationsarxiv-cs-ro

Agents

Hierarchical Agentic Incident Response with Digital-Twin-Validated Attack Inference

arXiv:2608.15016v1 Announce Type: cross Abstract: Network incident response remains slow and labor-intensive as the defender must infer multi-stage attacks from partial observations and translate reco

agentsarxiv-cs-ai

Iterative Self-Learning for Expressive Text-to-Speech Synthesis

arXiv:2608.15910v1 Announce Type: cross Abstract: Expressive text-to-speech (TTS) systems that use explicit conditioning labels provide direct and interpretable control over expressive attributes, in

researcharxiv-cs-cl

LaGSplat: Inferring Physics-Governed Interactive Simulation from Monocular Video Using Latent Lagrangian Gaussian Splatting

arXiv:2608.16324v1 Announce Type: new Abstract: We present LaGSplat (Latent Lagrangian Gaussian Splatting), a framework that infers interactive, physics-governed dynamics from one or a few monocular v

safetyarxiv-cs-cv

Large Language Model Assisted Operational Monitoring for Battery Energy Storage System Integrated Power Distribution Networks

arXiv:2608.15396v1 Announce Type: new Abstract: Battery energy storage systems (BESS) are increasingly used in distribution networks for voltage regulation and demand response, which increases the vol

Lipschitz Bandits with Arbitrary Feedback Delays

arXiv:2608.15036v1 Announce Type: new Abstract: The Lipschitz bandit problem extends the traditional multi-armed bandit framework to continuous action spaces by assuming that the reward functions sati

researcharxiv-cs-lg

Logical Embeddings for Argument Analysis

arXiv:2608.15325v1 Announce Type: cross Abstract: We propose a new framework for machine-learning-oriented argument analysis tasks. Our proposal involves replacing traditional contextualized word embe