Search: “framework”

Information-Theoretic Foundations for Machine Learning

arXiv:2407.12288v5 Announce Type: replace-cross Abstract: The progress of machine learning over the past decade is undeniable. In retrospect, it is both remarkable and unsettling that this progress wa

tutorialsarxiv-cs-lg

4 Aug 2026

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What Transfers from Text to Vision? Capability Scaling Laws and Transfer Dynamics for VLMs

DGX agent

arXiv:2608.00013v1 Announce Type: new Abstract: Choosing the right large language model (LLM) backbone is the most consequential decision when building a vision-language model (VLM), yet it remains fu

model-releasesarxiv-cs-cl

4 Aug 2026

Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases

arXiv:2502.19135v2 Announce Type: replace Abstract: We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted kno

Agents

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603.11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI sy

agentsarxiv-cs-ai

JoVA: Unified Multimodal Learning for Joint Video-Audio Generation and Editing

arXiv:2512.13677v2 Announce Type: replace Abstract: In this paper, we present JoVA, a streamlined framework that unifies joint video-audio generation and editing. While existing methods often rely on

safetyarxiv-cs-cv

Learning Lookahead Lemmas for Neural Network Verification

arXiv:2607.29051v1 Announce Type: cross Abstract: State-of-the-art neural network verifiers use the branch-and-bound procedure as their core solving mechanism. We introduce an inprocessing framework f

Safe Vision Language Action Models via Barrier Enhanced Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.29569v1 Announce Type: new Abstract: This article presents a modular inference framework that integrates Flow Matching generative models with formal Control Barrier Function (CBF) safety gu

Hardware

AgenticCANN: Automated Ascend C Operator Generation via Knowledge-Augmented Agentic Evolution

arXiv:2607.26661v1 Announce Type: new Abstract: Ascend C operator optimization is critical for NPU (Neural Processing Unit) inference performance but requires deep hardware expertise.While large langu

hardwarearxiv-cs-ai

Agents

(EC)2: Event-Centric Explainability for Cybersecurity Through Multi-Agent LLM Investigations

arXiv:2607.26201v1 Announce Type: cross Abstract: Security operations centers rely on anomaly detection systems to flag suspicious events. Feature-level explanations for anomaly detectors offer limite

agentsarxiv-cs-ai

It's All Just Vectorization: einx, a Universal Notation for Tensor Operations

arXiv:2607.27987v1 Announce Type: new Abstract: Tensor operations represent a cornerstone of modern scientific computing. However, the Numpy-like notation adopted by predominant tensor frameworks is o

MagicSelector: Joint Optimization for Agent Tool Selection via Counterfactual Decomposition and Progressive Reranking

model-releasesarxiv-cs-cl

arXiv:2607.17751v2 Announce Type: cross Abstract: We present MagicSelector, a joint optimization framework integrating Counterfactual task decomposition, Progressive reranking, and Dynamic Top-K, desi

Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective

arXiv:2607.27660v1 Announce Type: cross Abstract: Submodular Information Measures (SIMs) have recently emerged as a powerful framework for representation learning and multimodal learning. In particula

Do Methods Support the Claims? Intra-Paper Verification for Peer Review

arXiv:2607.26066v1 Announce Type: new Abstract: The growing volume of scientific submissions has motivated interest in using large language models (LLMs) to assist peer review. Existing automated nove

safetyarxiv-cs-cl

30 Jul 2026

Large-Scale ChatBot Validation Through Customer Digital Twin Simulations

arXiv:2607.26060v1 Announce Type: new Abstract: LLM-based chatbots are transforming customer service in regulated domains such as banking, but scalable and cost-effective validation remains a critical

safetyarxiv-cs-cl

30 Jul 2026

Physics-Informed Graph Neural Networks for Robust AC-Optimal Power Flow

arXiv:2410.04818v2 Announce Type: replace-cross Abstract: We present PINCO, an unsupervised learning framework that integrates Graph Neural Networks with physics-informed neural networks for AC optima

30 Jul 2026

Simulation-based parameter estimation via a combination of embedded normalizing flows and implied empirical probabilities under moment restrictions

arXiv:2607.25026v1 Announce Type: cross Abstract: In this work, we present a simulation-based parameter estimation framework for a model defined by a computational simulation of a physical system. We

29 Jul 2026

Actuator-Aware Spatiotemporal Tube Synthesis for Temporal Reach-Avoid-Stay Tasks

arXiv:2607.23040v1 Announce Type: cross Abstract: This work proposes an actuator-aware spatiotemporal tube (STT) synthesis framework to accomplish temporal reach-avoid-stay (T-RAS) tasks for an unknow

researcharxiv-cs-ro

Agents

Agent-UCT: Upper Confidence Bounds Applied to Trees for Agentic Workflow Optimization with Cost-Awareness

arXiv:2607.24162v1 Announce Type: new Abstract: Optimizing agentic workflows, such as retrieval-augmented generation (RAG) pipelines, requires navigating a combinatorial space of discrete component ch

agentsarxiv-cs-ai

DomainPilot: Domain-Level Loss-Guided Two-Stage Data Mixture Optimization for Efficient Language Model Fine-Tuning

arXiv:2607.22769v1 Announce Type: cross Abstract: The training efficacy of large language models (LLMs) is fundamentally constrained by the quality and composition of training data. Existing dynamic d

MEMOIR: Temporal Behavioral Memory for Recommendation Across the Preference-Drift Spectrum

arXiv:2607.23986v1 Announce Type: cross Abstract: We propose MEMOIR, a framework that segments user interaction histories into temporal windows, generates semantic behavioral memory for each period us

researcharxiv-cs-cl

MicroZoom: Structure-Preserving Detail Synthesis at Extreme Scale

arXiv:2607.24729v1 Announce Type: new Abstract: We introduce MicroZoom, a generative framework for gigapixel image synthesis at the microscopic scale. Given a standard photograph and a sparse set of c

tutorialsarxiv-cs-cv

MiSS: A Logic-Driven Explanation of Minimal Sufficient Coalitions for Point Cloud Classifiers

arXiv:2607.24074v1 Announce Type: new Abstract: We present MiSS, a black-box, query-based framework for explaining 3D point cloud classifiers through perturbation-relative sufficiency reasoning. MiSS

Local Ai

Neonatal Hypoxic-ischaemic Encephalopathy Classification from the EEG and HRV Signals Using a Conformer based Masked Autoencoder

arXiv:2607.23554v1 Announce Type: cross Abstract: In this paper, we propose the MAEConformer, a novel self-supervised learning framework that combines the Conformer architecture with the Masked Autoen

local-aiarxiv-cs-ai

Sparse Gaussian-Mixture-Model Q-Functions via Hadamard Overparametrization for Online Reinforcement Learning

arXiv:2607.23474v1 Announce Type: new Abstract: This paper develops an online, off-policy policy-iteration framework for reinforcement learning (RL), based on sparse Gaussian-mixture-model Q-functions

TopoFE: topology-aware LLM-guided Automated Feature Engineering

arXiv:2607.23286v1 Announce Type: new Abstract: Automatic feature engineering (AutoFE) for tabular learning can be naturally formulated as a program synthesis problem, where the objective is to discov

TRACE-CTI: Auditable Post-Extraction Governance of TTP Claims with Knowledge Graphs

arXiv:2607.24563v1 Announce Type: new Abstract: Security Operations Centers increasingly rely on automated mapping of Cyber Threat Intelligence reports to MITRE ATT&CK, yet extractor outputs remain fa

safetyarxiv-cs-ai

Local Ai

Bowel Obstruction Detection and Localization on Abdominal CT with Deep Learning

arXiv:2607.22173v1 Announce Type: new Abstract: Bowel obstruction is a common and potentially life-threatening gastrointestinal condition. In the face of rising diagnostic workloads, the automated dia

local-aiarxiv-cs-cv

27 Jul 2026

Applications

Explaining Weather Bulletins via ILP

arXiv:2607.21184v1 Announce Type: new Abstract: Inductive Logic Programming (ILP) originated within the Logic Programming community in the Nineties as a framework for combining symbolic learning with

applicationsarxiv-cs-ai

24 Jul 2026

The Geometry of Personality: Activation Steering with Jungian Cognitive Functions

arXiv:2607.20803v1 Announce Type: cross Abstract: Activation steering enables control and interpretation of LLMs, yet existing work primarily models personality through static trait frameworks such as

24 Jul 2026

Generalized Kalman filter based temporal difference reinforcement learning

arXiv:2607.20010v1 Announce Type: new Abstract: In this paper, we present a generalized temporal-difference (TD) reinforcement learning framework based on the theory of conditional expectations. The v

HypEMBER: Hypernetwork-based Ensemble for Robust Policy Learning of Parametrized Dynamical Systems

arXiv:2607.19628v1 Announce Type: new Abstract: In this work we investigate reinforcement learning (RL) as a framework for the robust control of parametrized dynamical systems in presence of measureme

Pushing the Frontier of Full-Song Generation: Hierarchical Autoregressive Planning Meets Flow-Matching Rendering

arXiv:2607.20253v1 Announce Type: cross Abstract: In this report, we present a unified song generation framework capable of producing high-quality full-length music from lyrics, text descriptions, and

Recovering Clinical Utility Under Differential Privacy: Empirical Validation of Adaptive Federated Aggregation on Heterogeneous Cardiovascular Datasets

arXiv:2607.19403v1 Announce Type: cross Abstract: Validating federated learning frameworks on real clinical data is an essential step between proof-of-concept demonstrations in controlled synthetic en

TreeSRNF: Square-Root Normal Fields for Generative Modelling of the Geometric and Structural Variability in Tree-like 3D Objects

arXiv:2607.13456v1 Announce Type: new Abstract: We introduce a novel mathematical framework for analyzing and generating complex tree-shaped 3D objects, such as botanical trees and plants, which defor

tutorialsarxiv-cs-cv

16 Jul 2026

Applications

Atomic Units of X: The Compression Layer of Intelligence

arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog

applicationsarxiv-cs-ai

15 Jul 2026

Self-Evolving In-Context Learning for Direct Pilot-to-Beamformer Design in MU-MISO Systems

arXiv:2607.11970v1 Announce Type: cross Abstract: We develop an enhanced in-context learning (ICL) framework to improve the performance of pilot-based beamforming in multi-user multiple-input single-o

15 Jul 2026

UMSS: Towards Unsupervised Multi-modal Semantic Segmentation

arXiv:2607.12372v1 Announce Type: new Abstract: Multimodal semantic segmentation (MSS) is essential for robust perception in complex environments, yet its potential remains largely untapped because of

tutorialsarxiv-cs-cv

15 Jul 2026

Collective Intelligence with Foundation Models

arXiv:2607.07729v1 Announce Type: cross Abstract: As foundation models grow in scale and diversity, coordinating multiple models into cooperative reasoning systems offers a path toward safer, more rel

10 Jul 2026

Effective Gaussian Management for High-fidelity Scene Reconstruction

arXiv:2509.12742v4 Announce Type: replace Abstract: This paper proposes an effective Gaussian management framework for high-fidelity scene reconstruction of both appearance and geometry. Unlike recent

10 Jul 2026

CoFINN: Conservation Flux Informed Neural Networks for Physics Problems Governed by Conservation Laws

arXiv:2607.06587v1 Announce Type: new Abstract: We present CoFINN (Conservation Flux Informed Neural Networks), a physics-informed deep learning framework for predicting compressible flow fields gover

D2PO: Optimizing Diffusion Samplers via Dynamic Preference

arXiv:2607.06609v1 Announce Type: cross Abstract: We propose D2PO (Dynamic Direct Preference Optimization), a principled framework for optimizing diffusion sampling policies with respect to timestep s

safetyarxiv-cs-ai

EdgeCompress: Coupling Multidimensional Model Compression and Dynamic Inference for EdgeAI

arXiv:2607.06982v1 Announce Type: new Abstract: Convolutional neural networks (CNNs) have demonstrated encouraging results in image classification tasks. However, the prohibitive computational cost of

Physics-guided spatiotemporal neural models for fuel density prediction

arXiv:2607.06999v1 Announce Type: cross Abstract: This paper presents a physics-guided machine learning (PGML) framework for fuel density prediction, integrating physics constraints and domain knowled

Applications

DIVO: Continuous-time DVL-Inertial-Visual Odometry for Unmanned Underwater Vehicles

arXiv:2607.04615v1 Announce Type: new Abstract: This paper presents a novel acoustic-visual-inertial odometry solution leveraging a continuous-time trajectory estimation framework for unmanned underwa

applicationsarxiv-cs-ro

Granger Causality in Extremes

arXiv:2407.09632v3 Announce Type: replace-cross Abstract: We introduce a rigorous mathematical framework for Granger causality in extremes, designed to identify causal links from extreme events in tim

Mixture-of-Gaussians-Guided Schedule Design for Brownian Bridge Diffusion Models

arXiv:2607.03517v1 Announce Type: cross Abstract: Brownian Bridge Diffusion Models (BBDM) offer an appealing framework for image restoration and inverse problems by constructing a stochastic bridge fr

safetyarxiv-cs-cv

Nonparametric Control Koopman Operators

arXiv:2405.07312v5 Announce Type: replace-cross Abstract: This paper presents a novel Koopman composition operator representation framework for control systems in reproducing kernel Hilbert spaces (RK

Property-Constrained 3D Porous Media Reconstruction from 2D Images via Conditional Generative Adversarial Networks

arXiv:2607.02693v1 Announce Type: new Abstract: This study presents a conditional Generative Adversarial Network (cGAN) framework for generating 3D porous media volumes with controlled porosity, train