Search: “models”

Physics-Guided Generative AI for Property-Targeted 3D Porous Media Design

arXiv:2607.24274v1 Announce Type: cross Abstract: Inverse design of three-dimensional porous media is central to applications in filtration, catalysis, energy storage, fuel cells, thermal management,

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Predicting the Outcome of rTMS Depression Therapy using EEG Signals and CNN

DGX agent

arXiv:2607.22776v1 Announce Type: new Abstract: Repetitive transcranial magnetic stimulation (rTMS) is a non invasive therapy for Major Depressive Disorder (MDD). In this study, we generate images usi

safetyarxiv-cs-lg

28 Jul 2026

Progress-conditioned Group Policy Optimization for Long-Horizon Agentic Tasks

arXiv:2607.22724v1 Announce Type: cross Abstract: Group-based policy optimization has been increasingly used to train large language model (LLM) agents from sparse outcome rewards by comparing traject

safetyarxiv-cs-ai

PTStore (Prefix Tensor Store): Distributed Prefix Caching and Replication for High Throughput Inference Serving

arXiv:2607.22648v1 Announce Type: new Abstract: Inspired by the design of client caching in Content Delivery Networks (CDNs), PTStore distributes and replicates popular tensors that form reusable KV c

Quality Action Assurance: Multimodal Verification of Examiner Claims in VR OSCEs

arXiv:2607.19063v2 Announce Type: replace Abstract: Objective Structured Clinical Examinations (OSCEs) are the gold standard for assessing clinical competence, yet scoring remains vulnerable to examin

local-aiarxiv-cs-ai

Quantum-Inspired Evolutionary Neighborhood Search for Arrival-Departure Track Utilization Adjustment under Short-Term Disturbances

arXiv:2607.24049v1 Announce Type: new Abstract: Short-term disturbances at major passenger railway stations alter train arrival and departure times as well as the release sequence of station resources

Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts

arXiv:2509.03530v2 Announce Type: replace Abstract: Suicide is a leading cause of death, yet predicting it remains a significant challenge. Risk factors such as depression or substance use are commonl

ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System

arXiv:2607.14178v2 Announce Type: replace Abstract: Recent advances in Large Language Models have fueled autonomous AI agents capable of tackling complex scientific tasks, yet existing automated resea

agentsarxiv-cs-ai

Reasoning to Regulate: Chain-of-Thought for Traffic Rule Understanding

arXiv:2607.24199v1 Announce Type: new Abstract: Understanding and complying with traffic regulations is a safety-critical requirement for autonomous driving, yet remains challenging due to the diversi

safetyarxiv-cs-cv

SechKAN: Kolmogorov-Arnold Networks with Hyperbolic Secant Functions

arXiv:2607.18290v2 Announce Type: replace-cross Abstract: In recent years, Kolmogorov-Arnold Networks (KANs) have attracted increasing attention due to their effectiveness in machine learning and scie

local-aiarxiv-cs-ai

Hardware

Small-Pollinator Detection in Cluttered Field Video

arXiv:2607.22913v1 Announce Type: new Abstract: Detecting pollinators in field video is challenging: targets are small, visually similar, and observed against cluttered vegetation under blur and occlu

hardwarearxiv-cs-cv

Stabilizing Deep Reconstruction Operators with Contractive Anchoring

arXiv:2607.23341v1 Announce Type: cross Abstract: Pretrained deep denoisers can be used to solve a wide range of model-based image reconstruction tasks via Plug-and-Play (PnP) and Regularization-by-De

Structural Loss Metrics for Tensor Approximation via Matrix Low-Rank Approximation

arXiv:2607.24009v1 Announce Type: new Abstract: Matricized low-rank approximation via SVD is a standard surrogate for tensor decompositions, but entry-wise reconstruction error fails to capture multiw

TaoMate: Anchor-Guided Memory Bridging Evolving and Reference States for Real-Time Audio-Video Digital Human Generation

arXiv:2607.24359v1 Announce Type: new Abstract: Real-time long-form digital-human generation relies on causal models to extend audio-visual content while preserving subject appearance and audio-video

local-aiarxiv-cs-cv

Task-Conditional Faithfulness Auditing of Multimodal LLMs for Grid Diagnosis

arXiv:2607.24539v1 Announce Type: new Abstract: Multimodal large language models (LLMs) can combine topology, measurements, and incident text for grid diagnosis, yet answer accuracy does not establish

The Cross-Domain Generalization Cost of Offensive Language Detection

arXiv:2607.23512v1 Announce Type: new Abstract: Offensive language detection models generally suffer performance degradation when deployed across datasets and across languages, yet most existing studi

The JEPA Paradox in Language: The Geometry of Linguistic Alternatives

arXiv:2607.23531v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) are effective for images, video, and audio, yet deterministic JEPA-style latent prediction has not beco

Applications

The SpiNNaker2 chip: a many-core platform for flexible and scalable brain-inspired computing

arXiv:2607.24396v1 Announce Type: cross Abstract: In deep learning, efficiency gets more and more important to compensate for the ongoing growth in model sizes and applications. Neuromorphic hardware

applicationsarxiv-cs-ai

Too much evidence, too little time: From text to actionable recommendations through multi-objective evidence reasoning

arXiv:2607.22574v1 Announce Type: new Abstract: Evidence-based clinical decision making requires specialists to identify, evaluate and synthesize relevant scientific literature. However, PubMed search

What Can Be Enforced? A Theory of Certified Runtime Safety for Tool-Using Agents

arXiv:2607.22868v1 Announce Type: new Abstract: Runtime guardrails act before irreversible tool calls, but their guarantees depend on what policy state is representable, what a judge observes, and whe

safetyarxiv-cs-ai

When Can You Correct Distribution Drift in Temporal Graph Generation? A Sharpening--Drift Tension and an Impossibility for Observation-Based Correction

arXiv:2607.24662v1 Announce Type: new Abstract: Generative models of temporal graphs are trained on one stretch of an evolving network and deployed on the next, and they degrade badly in the gap. We s

A Drift Stable Quantum Federated Learning for Intelligent Services

arXiv:2607.21647v1 Announce Type: new Abstract: Quantum federated learning enables distributed clients to train quantum neural networks without sharing local data, making it promising for privacy-awar

local-aiarxiv-cs-lg

Active few-shot segmentation by reinforcing data selection

arXiv:2607.22371v1 Announce Type: new Abstract: Few-shot learning enables medical image segmentation models to adapt to new tasks using only a small number of labelled examples. However, adaptation pe

agentsarxiv-cs-cv

Adaptive Learned State Estimation based on KalmanNet

arXiv:2604.02441v2 Announce Type: replace Abstract: Hybrid state estimators that combine model-based Kalman filtering with learned components have shown promise on simulated data, yet their performanc

agentsarxiv-cs-ro

Beyond Binary Rooftop Mapping: A Four-Class Deep Learning Framework for Green Roof Potential Assessment from Open Swiss Geospatial Data

arXiv:2607.22342v1 Announce Type: new Abstract: The development of effective urban climate adaptation strategies requires comprehensive spatial information on rooftops and buildings, since such inform

CARA: Concept-Aware Risk Attention for Interpretable Collision Anticipation

arXiv:2607.22494v1 Announce Type: cross Abstract: Collision anticipation in autonomous driving requires not only accurate early warnings but also interpretable reasoning about what risk factors are be

agentsarxiv-cs-cv

CorVS+: Correspondence-Driven Association of Video Trajectories and Sensors for Identity-Aware Person Localization in Warehouses

arXiv:2510.26369v2 Announce Type: replace-cross Abstract: Logistics warehouses have struggled with labor shortages, but the inbound processes remain particularly human-powered. Worker location data is

local-aiarxiv-cs-cv

Distributional Determinantal Point Process for Repulsive Clustering of Distributions

arXiv:2607.21847v1 Announce Type: cross Abstract: We introduce the distributional determinantal point process (dDPP) as a novel repulsive point process whose atoms are probability distributions rather

dRAE: Representation Autoencoder with Hyper-Spherical Codes

arXiv:2607.22148v1 Announce Type: new Abstract: In this work, we aim to discretize the high-dimensional visual representations to bridge the gap with language models - a non-trivial challenge, as exis

Dysphagia Risk Stratification in Head and Neck Cancer via Two-Stage PRO-Clinical Stacking

arXiv:2607.22514v1 Announce Type: new Abstract: Dysphagia is a debilitating late effect of head and neck cancer (HNC) treatment, yet timely identification of at-risk patients remains challenging in su

Efficient Online LLM Watermark Detection via Rao-Blackwellized E-Processes

arXiv:2607.21958v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed, reliable and efficient mechanisms for distinguishing AI-generated text from human-written c

From Seasonality to Semantics: Benchmarking a Hybrid Probabilistic Forecasting System for Roadblocks in Bolivia

arXiv:2607.21785v1 Announce Type: cross Abstract: Roadblocks in Bolivia are a social conflict phenomenon with devastating economic impacts, estimated at losses equivalent to 4% of the national Gross D

local-aiarxiv-cs-cl

Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning

arXiv:2408.02295v4 Announce Type: replace Abstract: Conventional uncertainty-aware temporal difference (TD) learning often models TD errors as zero-mean Gaussian. This assumption can miss the heavy-ta

Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection

arXiv:2412.01101v2 Announce Type: replace Abstract: Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate

HiKV: Hierarchical Importance-Aware KV Cache with Hardware Acceleration for LLM Decoding

arXiv:2607.22389v1 Announce Type: cross Abstract: With the rapid adoption of long-context large language models (LLMs), the continuously growing KV cache during decoding has become the critical memory

How Do AI Coding Agents Contribute to Software Development? an Empirical Study of Agentic Pull Requests

arXiv:2607.21832v1 Announce Type: cross Abstract: Recent advances in large language models and their rapid adoption across software engineering tasks have made Artificial Intelligence (AI) coding agen

agentsarxiv-cs-lg

Industrial Tokenization for LLM-Based Health Intelligence: A Federated Architecture for Industrial Evidence Integration

arXiv:2607.22153v1 Announce Type: cross Abstract: Industrial health management increasingly relies on heterogeneous information sources, including condition monitoring systems, supervisory control and

agentsarxiv-cs-lg

IQ-JEPA: A Joint-Embedding Predictive Architecture with a Hermitian Vision Transformer for Sound Speed and Attenuation Estimation from Ultrasound IQ Data

arXiv:2607.22351v1 Announce Type: new Abstract: The speed of sound in tissue is a prerequisite for well-focused imaging and has diagnostic value, but recovering it from raw pulse-echo channel data is

Minimum Norm Interpolation via the Local Theory of Banach Spaces: The Role of 2-Uniform Convexity

arXiv:2603.28956v2 Announce Type: replace-cross Abstract: The minimum-norm interpolator (MNI) framework has recently attracted considerable attention as a tool for understanding generalization in over

safetyarxiv-cs-lg

MissHyper: Restoring Clinical Synchronicity in Missingness-Guided Hypergraph Forecasting

arXiv:2607.21922v1 Announce Type: new Abstract: Clinical irregular multivariate time series are shaped not only by physiological dynamics but also by the measurement process that determines when and w

local-aiarxiv-cs-lg

Optimal generalisation and learning transition in extensive-width shallow neural networks near interpolation

arXiv:2501.18530v3 Announce Type: replace-cross Abstract: We consider a teacher-student model of supervised learning with a fully-trained two-layer neural network whose width k and input dimension d a

safetyarxiv-cs-lg

RED-PIM: Reducing Data Movement for Transformers using Processing-in-Memory

arXiv:2607.21731v1 Announce Type: new Abstract: Transformers are widely used across many domains, including natural language processing, computer vision, web search, and DNA sequence analysis. Given t

local-aiarxiv-cs-lg

Robot Learning to Communicate through Projected Visual Abstractions

arXiv:2607.22434v1 Announce Type: new Abstract: Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Yet robots remain largely confined t

researcharxiv-cs-ro

Self-Poisoning in Adaptive Out-of-Distribution Detection: A Sharp-Threshold Theory and Certified Label-Free Calibration

arXiv:2607.21673v1 Announce Type: cross Abstract: Test-time adaptive out-of-distribution (OOD) detectors update a memory bank from the unlabelled stream. We show this adaptation obeys a provable dynam

Applications

SM4RT: Learning Structured Motion Geometry for 4D Reconstruction

arXiv:2607.22534v1 Announce Type: new Abstract: Geometry Foundation Models (GFMs) have substantially advanced monocular 3D reconstruction, yet extending this capability to 4D dynamic understanding rem

applicationsarxiv-cs-cv

Smart predict-then-robustly-optimize

arXiv:2607.21773v1 Announce Type: new Abstract: In this paper, we propose and study a robust variant of the smart predict-then-optimize approach that accounts for prediction shifts due to disturbance

TDiR: Transformer based Diffusion for Image Restoration Tasks

arXiv:2506.20302v2 Announce Type: replace Abstract: Images captured in challenging environments often experience various types of degradation, such as noise, color cast, blur, and light scattering. Th

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning

arXiv:2607.21971v1 Announce Type: cross Abstract: Test-time scaling through iterative self-evolution with environment feedback, as demonstrated by AlphaEvolve, shows remarkable performance gains. We h