Search: “framework”

Similarity Gates Approve Reversals: A Validity Audit of Embedding-Cosine Thresholds in Agent Systems

arXiv:2608.10216v1 Announce Type: cross Abstract: Agent frameworks ship quality gates that compare text blocks by embedding-cosine similarity and decide at a fixed cutoff. Deduplication filters, seman

12 Aug 2026

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Research

Stochastic Emulation of a Fully Coupled Preindustrial E3SMv3 Simulation

DGX agent

arXiv:2608.10277v1 Announce Type: cross Abstract: We present a stochastic coupled emulator of E3SM version 3, built on the SamudrACE framework, which couples an atmosphere emulator (ACE2) with a full-

researcharxiv-cs-lg

12 Aug 2026

Templated or fully Synthetic? Prompt construction as a confound in measuring LLM political stance beyond writing assistance

arXiv:2608.11008v1 Announce Type: new Abstract: Political stance detection in LLMs has long been dominated by closed-ended, multiple-choice political survey questions---originally designed for humans,

safetyarxiv-cs-cl

12 Aug 2026

Not an A11y: How Android Accessibility Exposes Mobile AI Agents to Indirect Prompt Injection

arXiv:2608.08939v1 Announce Type: new Abstract: The rise of autonomous AI agents represents a major paradigm shift in how users interact with mobile devices. Frameworks such as MobileRun and Mobile-Us

11 Aug 2026

Progressive Alignment of Recommender Foundation Model through Multi-Phase Post-Training

arXiv:2608.06792v1 Announce Type: cross Abstract: Foundation model(FM) for recommendation has shown strong ability to model long-horizon sequential user behavior. In practice, a single pretrained foun

10 Aug 2026

Robot Learning from Human Demonstrations: Handwritten Alphabet Trajectories and Human-Likeness Evaluation

model-releasesarxiv-cs-lg

arXiv:2608.06221v1 Announce Type: cross Abstract: Learning from demonstration (LfD) provides a developmental framework through which robots can develop motor skills by observing and imitating human dy

7 Aug 2026

Schema-Guided Hierarchical Information Extraction and Semantic Evaluation Using Generative AI

model-releasesarxiv-cs-ai

arXiv:2608.06167v1 Announce Type: new Abstract: We present a schema-based framework for extracting complex, structured information from unstructured text documents using generative AI, followed by aut

7 Aug 2026

Surv-IPTB: An Attention-Based Model for Estimating Individual Probability of Treatment Benefit with Survival Data

arXiv:2608.06288v1 Announce Type: new Abstract: This work presents a novel attention-based framework for estimating the Individual Probability of Treatment Benefit (IPTB) in survival analysis contexts

researcharxiv-cs-lg

7 Aug 2026

An entropic explanation of insistence on sameness in autism

arXiv:2608.04616v1 Announce Type: new Abstract: An information theory-based framework is proposed in attempt to explain insistence on sameness in autism as an instance of a general behavior pattern in

tutorialsarxiv-cs-lg

6 Aug 2026

Leveraging Interpretable Tsetlin Machine for PDF Malware Detection

arXiv:2607.09290v2 Announce Type: replace-cross Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents du

local-aiarxiv-cs-lg

6 Aug 2026

What We Observe as LLM Behavior Can Be a Side-effect of Inference Backend

model-releasesarxiv-cs-ai

arXiv:2608.04714v1 Announce Type: cross Abstract: Benchmark scores are reported as properties of a model, yet the inference framework used to produce them, such as HuggingFace, vLLM, or Ollama, are co

6 Aug 2026

A Security-Oriented Lifecycle Model for Large Language Model Systems

arXiv:2608.03626v1 Announce Type: cross Abstract: Large language models are being integrated into critical infrastructure and enterprise workflows at unprecedented scale,yet the lifecycle frameworks g

CLIP-EBC: CLIP Can Count Accurately through Enhanced Blockwise Classification

arXiv:2403.09281v3 Announce Type: cross Abstract: We propose CLIP-EBC, the first fully CLIP-based model for accurate crowd density estimation. While the CLIP model has demonstrated remarkable success

Deep Frequency-Aware Functional Maps for Robust Shape Matching

arXiv:2402.03904v3 Announce Type: replace Abstract: Deep functional map frameworks are widely employed for 3D shape matching. However, most existing deep functional map methods cannot adaptively captu

researcharxiv-cs-cv

Information-Geometric Forward Policy Training in GFlowNets

arXiv:2608.03967v1 Announce Type: cross Abstract: Generative Flow Networks (GFlowNets) have emerged as a flexible framework for amortised inference over discrete and mixed discrete-continuous objects,

local-aiarxiv-cs-lg

Resume Means Resume: A Machine-Checked Conformance Contract for Checkpoint, Interrupt, and Resume Semantics in Workflow Persistence Layers

arXiv:2608.03836v1 Announce Type: new Abstract: A framework that persists execution state so a run can be interrupted, survive a crash, and continue must decide what a resume means for effects that al

agentsarxiv-cs-lg

The Google Bug Hunters Team admitted to me that they cannot fundamentally patch prompt engineering bypasses in Gemini

Hello everyone Yesterday I gave a report on Gemini bugs and the techniques I learned on Gemini so far with the Engineering Prompt and interestingly today I got a very interesting and controversial ans

model-releasesr-chatgpt

Dense Language Generation Made Simple: Deterministic, Randomized, and Multi-Order Algorithms

arXiv:2608.01320v1 Announce Type: cross Abstract: Language generation in the limit is a theoretical framework for studying how a generator can learn to produce new valid strings from a stream of posit

tutorialsarxiv-cs-cl

Applications

Global-Scale Self-Supervised Spatiotemporal Learning for NDVI Time-Series Reconstruction

arXiv:2608.02322v1 Announce Type: new Abstract: Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning pr

applicationsarxiv-cs-cv

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

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

model-releasesarxiv-cs-cl

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

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

model-releasesarxiv-cs-ai

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

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

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

(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

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

researcharxiv-cs-lg

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

researcharxiv-cs-cv

Batten Down Your Packages: Mitigation Guidance for Supply Chain Compromise

model-releasesgoogle-cloud-ai

Written by: Kelli Vanderlee, Stuart Carrera For years, the cybersecurity industry's understanding of software supply chain compromise has been anchored by a few watershed events, including Russian cyb

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

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

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

researcharxiv-cs-lg

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

model-releasesarxiv-cs-lg

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

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

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

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

model-releasesarxiv-cs-lg

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

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