Search: “models”

Rethinking Irregular Time Series Forecasting from the Perspective of Basis Functions

arXiv:2608.17284v1 Announce Type: cross Abstract: Irregular time series forecasting is crucial in many domains, such as healthcare and meteorological observation. However, due to the inherent characte

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Runtime Governance for Agentic AI: Action-Boundary Control with Trusted Provenance and Fail-Closed Execution

DGX agent

arXiv:2608.16891v1 Announce Type: new Abstract: Agentic AI systems request tool actions that can modify files, send messages, launch jobs, or change workflow state. This shifts the safety problem from

safetyarxiv-cs-ai

19 Aug 2026

Salesforce expands Headless Data 360 for MCP so developers can bring insights to agents

Agentic artificial intelligence runs on data, so Salesforce Inc. today announced it’s launching Headless Data 360 for Model Context Protocol to provide that data directly to agents, allowing them acce

agentssiliconangle

SEE: Structure-aware Exploring & Exploiting for Long-horizon GUI Agent Trajectory Synthesis

arXiv:2607.18046v2 Announce Type: replace Abstract: Graphical User Interface (GUI) agents powered by vision-language models hold promise for automating real-world mobile tasks. However, progress is li

safetyarxiv-cs-lg

Task Specialization Fine-Tuning for Contextual Reinforcement Learning

arXiv:2608.17180v1 Announce Type: cross Abstract: Contextual Reinforcement Learning (CRL) seeks to generalize classical RL by maximizing task coverage across a context space of related tasks. While pr

To Remove or Not to Remove Clouds: A Comparative Analysis and Fusion of Raw SAR and Synthetic NDWI for Overcast Water Segmentation

arXiv:2608.17398v1 Announce Type: new Abstract: Persistent clouds blind optical satellites during floods. While Synthetic Aperture Radar (SAR) penetrates clouds, its raw data is noisy and lacks clear

v0.32.15

**Release Summary – v0.32.15 (GitHub Release)** Version 0.32.15 was published on **19 Aug**, adding a *model metadata cache* to reduce per‑request overhead in Ollama. The release builds on the previou

local-aiollama-releases

Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images

arXiv:2506.14934v2 Announce Type: replace Abstract: Distinguishing between quark- and gluon-initiated jets is a critical and challenging task in high-energy physics, pivotal for improving new physics

A Highly Efficient Diversity-based Input Selection for DNN Improvement Using VLMs

arXiv:2601.08024v2 Announce Type: replace Abstract: Maintaining or improving the performance of Deep Neural Networks (DNNs) through fine-tuning requires labeling newly collected inputs, a process that

A Low-Cost IoT Device for Environmental Monitoring and Embedded Solar Forecasting with On-Device Incremental Learning

arXiv:2608.14698v1 Announce Type: cross Abstract: Hyperlocal meteorological sensing is essential for accurate solar photovoltaic forecasting, yet professional-grade meteorological stations require inv

local-aiarxiv-cs-lg

A Pilot Study of Autocompleting Tokenizers

arXiv:2608.15080v1 Announce Type: new Abstract: Modern input methods routinely rely on autocomplete to omit information that can be recovered from local context. Inspired by these autocomplete-assiste

local-aiarxiv-cs-cl

A Privacy Study of Sparse Collaborative Inference

arXiv:2608.16236v1 Announce Type: new Abstract: Collaborative inference (CI) splits a model between an edge device and a server, whereby the client computes an intermediate activation, transmits it, a

researcharxiv-cs-lg

A Survey of Body and Face Motion: Datasets, Performance Evaluation Metrics and Generative Techniques

arXiv:2512.09005v2 Announce Type: replace Abstract: Body and face motion play an integral role in communication. They convey crucial information on the participants. Advances in generative modeling an

A Tree-Structured Approach for Phishing Template and Attacker Attribution Analysis

arXiv:2608.16158v1 Announce Type: cross Abstract: Phishing remains a persistent and evolving cybersecurity threat, with attack volumes reaching record levels. This growth is driven by the industrializ

A Unified Backbone--Expert Framework with Relation-Token and Residual--Classifier Interfaces for Automatic Modulation Recognition

arXiv:2608.15160v1 Announce Type: cross Abstract: Automatic modulation recognition (AMR) faces distinct representation bottlenecks under varying observation lengths, where a single model architecture

Advancing Open and Reproducible Relational Learning: RelArena-alpha, TabPFN-Rel and RPI

arXiv:2608.16319v1 Announce Type: new Abstract: This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we

applicationsarxiv-cs-lg

Agent Gym: A Framework for Continuous Evaluation and Evolution of LLM Agents Through Human-in-the-Loop Feedback

arXiv:2608.15591v1 Announce Type: new Abstract: Large Language Model (LLM) agents deployed in production environments face a fundamental tension: the agent's behavior is frozen at deployment time, whi

Agentic Test-Time Scaling for WebAgents

arXiv:2602.12276v2 Announce Type: replace Abstract: Test-time scaling has become a standard way to improve performance and boost reliability of neural network models. However, its behavior on agentic,

Ask to Be Sure: Informative Interactions for Confident Multi-Turn LLM Recommendation

arXiv:2608.15949v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have enabled their use as conversational recommender systems (CRS), demonstrating strong recommendatio

Tutorials

Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering

arXiv:2608.15757v1 Announce Type: new Abstract: Incomplete multi-view clustering (IMVC) aims to uncover shared cluster structures from data with partially observed views. Although recent imputation-fr

tutorialsarxiv-cs-cv

Beyond the pale: Assessing prevalence and contents of extremist speech in LLM training data

arXiv:2608.14813v1 Announce Type: new Abstract: Despite a strong interest on the part of the research community in the topic of trustworthy and safe AI, the composition of the text corpora that large

researcharxiv-cs-cl

Budget-Aware Tool Use Enables Effective Agent Scaling

arXiv:2511.17006v2 Announce Type: replace Abstract: Scaling test-time computation has been extended from language model reasoning to tool-augmented agents, where scaling involves not only thinking in

Cross-View Urban Sensing: Mapping Subjective Streetscape Perception via AlphaEarth Embeddings and Urban Context

arXiv:2608.16310v1 Announce Type: new Abstract: Residents' perception of the urban streetscape is an important factor in public health, active mobility, and social wellbeing. Street view imagery (SVI)

CUBICS: Situation-aware performance estimation for safety-relevant ML components

arXiv:2608.16564v1 Announce Type: new Abstract: Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A

Decomposing Staleness in Recommender Systems: A Dual-Filter Framework for Supersession and Decay

arXiv:2608.15780v1 Announce Type: cross Abstract: Stale recommendations are a pervasive challenge and a leading source of user complaints on large-scale content platforms. Items lose relevance through

Decomposing Whole Slide Image Report Generation with Graph-Constrained Multiple Instance Learning Workflows

arXiv:2608.15353v1 Announce Type: new Abstract: Whole-slide image (WSI) report generation requires recognizing spatially distributed pathological features and organizing them into a coherent diagnosti

Deep Probabilistic Indoor Gas Source Localization via Physical Dependency-Guided Sequential Inference

arXiv:2608.16221v1 Announce Type: new Abstract: Reliable gas source localization (GSL) is critical to safety in industrial and urban environments, yet remains challenging indoors because walls and obs

local-aiarxiv-cs-ro

Demystifying Oversmoothing in Sheaf Neural Networks: An Index-Theoretic Criterion

arXiv:2608.16180v1 Announce Type: new Abstract: To combat oversmoothing in Graph Convolutional Networks, Sheaf Neural Networks (SNNs) were proposed as a generalization by equipping the graph with a sh

researcharxiv-cs-lg

Divergent-Convergent Reasoning: Scaling Test-Time Compute through Structured Solution Synthesis

arXiv:2608.15303v1 Announce Type: new Abstract: Test-time compute can substantially improve Large Language Model (LLM) reasoning performance, yet how and when additional compute helps remains poorly u

Do Assessment Instruments Measure the Same Thing for Humans and LLMs? A Latent Structure Analysis

arXiv:2608.15630v1 Announce Type: cross Abstract: The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A c

Tutorials

Emergence of Transfer Learning towards Specific Identification of Alzheimer's Disease A Prospective Approach

arXiv:2608.14731v1 Announce Type: new Abstract: Worldwide, millions of senior citizens are suffering from Alzheimer disease abbreviated as AD, a well- versed form of dementia. AD is featured by amnesi

tutorialsarxiv-cs-cv

ETHOS: Towards a Modular Ethics Framework for Clinical Multi-Agent Systems

arXiv:2608.15424v1 Announce Type: cross Abstract: The rapid adoption of large language models has enabled the development of clinical multi-agent systems (MAS) capable of integrating multimodal patien

Evaluating Multimodal LLMs across Text and Audio Modalities for Accessible Disaster Assistance

arXiv:2608.14651v1 Announce Type: new Abstract: Effective disaster risk communication is a foundational humanitarian challenge, yet current emergency infrastructure fails to meet the needs of individu

Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents

arXiv:2608.15071v1 Announce Type: new Abstract: Learning from experience is critical for developing capable, self-improving large language model (LLM) agents. Existing methods typically extract knowle

FedPA-LoRA: Product-Aligned Framework for Mitigating Aggregation and Initialization Errors in Heterogeneous Federated LoRA

arXiv:2608.15381v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) enables efficient federated fine-tuning of large language models, but its factorized parameterization creates a tension betwe

FLOPs vs Real Work: The Importance of Replication in AI Efficiency Assessment

arXiv:2608.14550v1 Announce Type: new Abstract: AI efficiency has recently taken the spotlight in both academy and industry due to massive model scales, high energy demands, and environmental costs. W

From Dense Prediction to Visual Editing: Structured Supervision for Unified Image and Video Creation

arXiv:2608.14740v1 Announce Type: new Abstract: Unified image and video creation requires a model to follow diverse instructions while preserving identity, geometry, and temporal structure from visual

GenRouter: Unified Workflow Routing for Agentic Image Generation

arXiv:2608.16721v1 Announce Type: new Abstract: The rapid evolution of text-to-image (T2I) generation models has effectively solved the foundational challenge of raw pixel synthesis, shifting the comm

safetyarxiv-cs-cv

Geometrically Constrained and Token-Based Probabilistic Spatial Transformers

arXiv:2509.11218v2 Announce Type: replace-cross Abstract: Spatial transformations such as rotation and scale obscure the morphological cues needed for accurate image classification. Careful considerat

HistReNeRF: Historic Image Relocalisation within Contemporary Neural Radiance Field Reconstructions

arXiv:2608.15420v1 Announce Type: new Abstract: Relocalising archival photographs within a contemporary scene model is challenging because historic and modern views can differ in photographic appearan

I would like to publicly commend @sama and @OpenAI for this taking it at face value. It is very clear that strange and perhaps dangerous thi…

I would like to publicly commend @sama and @OpenAI for this taking it at face value. It is very clear that strange and perhaps dangerous things are happening and our systems are not ready for this. Mo

safetyemad-mostaque--x

Identifying Confusion Trends in Concept-based XAI for Multi-Label Classification

arXiv:2608.15731v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) deployed in high-risk domains, such as healthcare and autonomous driving, must be not only accurate but also understandabl

Tutorials

Identifying Harm in Personalized, Generative AI Systems Requires User-Centered Auditing at the Interaction Level

arXiv:2608.14692v1 Announce Type: cross Abstract: Personalized, generative AI systems increasingly adapt their behavior to individual users over time, fundamentally changing model behavior. While exis

tutorialsarxiv-cs-ai

Implementation of a Metacognition Framework for Self-Awareness and Self-Regulation in Ensembles of LLMs

arXiv:2608.15400v1 Announce Type: new Abstract: Large Language Models (LLMs) are notorious for struggling with assessing their own uncertainty, detecting knowledge conflicts, or recognizing when probl

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

JoLT: Joint Latent Trajectories for Context-Guided High-Resolution Tiled Generation

arXiv:2608.15395v1 Announce Type: new Abstract: Although text-to-image generative models produce impressive results, they struggle to generate densely detailed, high-resolution (HR) images. Current li

KHiM-Mamba: Injecting Pathology Knowledge into Mamba via Hidden-State Modulation for Whole Slide Image Analysis

arXiv:2608.14757v1 Announce Type: cross Abstract: Whole slide image analysis is commonly formulated as multiple instance learning (MIL), where instance features are contextually updated and aggregated

Language-Guided Generation for Personalized Inspection Planning

arXiv:2506.02917v2 Announce Type: replace Abstract: We propose a training-free, Vision-Language Model (VLM)-guided approach for efficiently generating trajectories to facilitate target inspection plan

applicationsarxiv-cs-ro