Search: “papers”

Long-Term PM2.5 Forecasting Using a DTW-Enhanced CNN-GRU Model

arXiv:2510.22863v2 Announce Type: replace-cross Abstract: Reliable long-term forecasting of PM2.5 concentrations is critical for public health early-warning systems, yet existing deep learning approac

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MARS: Multi-Agent Re-ranking for Repeat-Order Food Delivery Recommendation

DGX agent

arXiv:2607.25420v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in recommender systems, but it is often unclear how much performance can be obtained from strong pr

local-aiarxiv-cs-ai

29 Jul 2026

Matrix-Free Photoacoustic Image Reconstruction via Sensor-Token Self-Attention

arXiv:2607.25576v1 Announce Type: new Abstract: Photoacoustic tomography (PAT) combines the optical absorption contrast of biological tissue with the spatial resolution of ultrasound, yet recovering t

Local Ai

Mind the Missing Split: Resolving Feature Heterogeneity in Swarm Learning with Random Forests

arXiv:2607.25538v1 Announce Type: new Abstract: Swarm Learning is a decentralized collaborative learning mechanism that allows multiple organizations to train a shared model without central coordinati

local-aiarxiv-cs-lg

Multimodal Hybrid Retrieval-Augmented Generation for Scientific Document Understanding using Open-Source SLMs

arXiv:2607.24799v1 Announce Type: cross Abstract: Large Language Models tend to hallucinate when answering domain-specific ques tions from scientific documents without prior fine-tuning. Currently, me

Noise-Free One-Step LoRA for Task-Driven Image Restoration with Diffusion Priors

arXiv:2607.25390v1 Announce Type: new Abstract: Degraded images not only reduce visual quality but also impair downstream high-level vision tasks. Task-driven image restoration (TDIR) addresses this i

applicationsarxiv-cs-cv

ODYSSE: Episode-wise Policy Optimization for Personalized Agentic Reasoning

arXiv:2607.25369v1 Announce Type: new Abstract: Agentic systems have rapidly advanced in their ability to interact with real-world environments, leverage external tools, and provide services for users

Tutorials

On the Design and Evaluation of Human-centered Explainable AI Systems: A Systematic Review and Taxonomy

arXiv:2510.12201v2 Announce Type: replace Abstract: As AI becomes more common in everyday living, there is an increasing demand for intelligent systems that are both performant and understandable. Exp

tutorialsarxiv-cs-ai

Operational evaluation of data-driven forest fire forecasting models

arXiv:2603.25469v2 Announce Type: replace Abstract: A growing body of literature has focused on predicting wildfire occurrence using machine learning methods, capitalizing on high-resolution data and

applicationsarxiv-cs-lg

Parallel Decoding Distillation for Fast Image and Video Generation

model-releasesarxiv-cs-cv

arXiv:2607.26004v1 Announce Type: new Abstract: Generation in video diffusion or flow models is computationally expensive due to the slow and iterative sampling process. Current state-of-the-art (SOTA

Physics-Aware End-to-End Deep Reinforcement Learning for Quadcopter Control with Actuator Dynamics

arXiv:2607.25985v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs), particularly quadcopters, present unique challenges for autonomous control due to their underactuated dynamics: only

PLATO: Pointer Learner for Agent and Task Openness

arXiv:2607.25082v1 Announce Type: new Abstract: Open agent systems (OASYS) are increasingly prevalent in real-world domains where the sets of agents and tasks change unpredictably over time. Such open

Predictive Control for Driving under Uncertain Road Geometry Estimated from Onboard Vision

arXiv:2508.02494v2 Announce Type: replace-cross Abstract: Autonomous vehicles driving on unknown roads must estimate the road geometry from onboard sensors and follow the resulting reference while res

safetyarxiv-cs-ro

Reading Legends on Ancient Coins: An Object Detection Approach for Character Recognition on a Novel Roman Republican Dataset

arXiv:2607.25455v1 Announce Type: new Abstract: When it comes to the proper classification of ancient coins with respect to their time and issuer, the textual inscriptions on these coins, also known a

Reasoning with Memory: A Temporal Granularity-Adaptive Framework for Training-Free Long Video Understanding

arXiv:2607.24794v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) demonstrate superior generalization in fundamental video tasks, restricted context windows limit their lo

ReLATE: Reliability-Guided Evidence Fusion for Robust UAV--Satellite cross-view Geo-Localization

arXiv:2607.25524v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-satellite cross-view geo-localization matches UAV images against satellite imagery and has achieved impressive accuracy

Retrieval-Augmented Generation in LLMs for Mental Health: Quantifying the Incremental Contribution of Retrieval Within a Layered Safety Architecture

arXiv:2607.24817v1 Announce Type: cross Abstract: Digital mental health interventions (DMHIs) offer scalable support, but ensuring they accurately detect users' intent during volatile situations can b

SAFAARI: Schema-Aware Framework for Accelerated Advertiser Response Intelligence

arXiv:2607.25042v1 Announce Type: new Abstract: The evolution of customer support systems is rapidly advancing with agentic chatbots, yet these systems face significant limitations when accessing ente

agentsarxiv-cs-ai

SAM-MI: A Mask-Injected Framework for Enhancing Open-Vocabulary Semantic Segmentation with SAM

model-releasesarxiv-cs-cv

arXiv:2511.20027v2 Announce Type: replace Abstract: Open-vocabulary semantic segmentation (OVSS) aims to segment and recognize objects universally. Trained on extensive high-quality segmentation data,

ScaleResfusion: Residual Rectified Flow based on Residual Vector Field

arXiv:2607.25275v1 Announce Type: cross Abstract: Real-world Image Restoration (Real-IR) aims to recover high-quality (HQ) images from complex and unknown degradations. Although recent diffusion-based

SciClaimSeekers at CheckThat! 2026: Retrieving Scientific Sources for Social Media Claims with LLM Reranking

arXiv:2607.24803v1 Announce Type: cross Abstract: Scientific claims often spread on social media faster than they can be verified, while posts rarely link to the original scholarly sources. To tackle

researcharxiv-cs-cl

SPARC Segmentation to Prediction via Affine Regression and Counterfactuals

arXiv:2607.25413v1 Announce Type: new Abstract: Transaction propensity prediction in B2B e commerce presents unique challenges distinct from B2C contexts, primarily due to the heterogeneous procuremen

applicationsarxiv-cs-lg

Speculate While You Reason: Teaching Agents to Predict Their Next Tool Call via Joint Agent-Speculator RL

arXiv:2607.25816v1 Announce Type: new Abstract: Large language model agents often spend substantial wall-clock time waiting for tool call results. Tool-call speculation can hide this latency by predic

agentsarxiv-cs-ai

SpeechLLM Meets Federated Learning for End-to-End ASR: English and Italian Case Studies

model-releasesarxiv-cs-cl

arXiv:2607.25716v1 Announce Type: new Abstract: Federated learning (FL) enables privacy-preserving training of automatic speech recognition (ASR) systems across distributed data sources, yet its appli

Standard Transformers Achieve the Minimax Rate in Nonparametric Regression with C^{s,lambda} Targets

arXiv:2602.20555v2 Announce Type: replace-cross Abstract: The tremendous success of Transformer models in fields such as large language models and computer vision necessitates a rigorous theoretical i

researcharxiv-cs-lg

Steeringless Drifting: Differential-Torque Control of a Four-Wheel Independently Driven Vehicle

arXiv:2607.24863v1 Announce Type: new Abstract: Control methods for emerging vehicle chassis architectures are important for autonomous driving near handling limits. Unlike conventional drift control,

agentsarxiv-cs-ro

The Disruptive Impact of Large Language Models on Capture the Flag Competitions and the Path Toward Fair Play

arXiv:2607.25425v1 Announce Type: new Abstract: Capture the Flag (CTF) competitions are among cybersecurity's most effective training grounds, developing practical skill across cryptography, web explo

The Effect of Text Chunk Size on Retrieval-Augmented Generation Performance

arXiv:2607.24767v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems have emerged as a powerful process for allowing large language models (LLMs) to retrieve relevant informa

Tools Are Not Islands: Set-Level Tool Retrieval for LLM Agents via Query-Conditioned Hyperedge Prediction

arXiv:2607.25718v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly rely on invoking external tools to complete real-world tasks. Tool retrieval, which selects a small tas

agentsarxiv-cs-ai

Toward a systematic method for identifying language areas

arXiv:2607.25305v1 Announce Type: new Abstract: Macroareas are geographical areas used in typological research for grouping variables of interest. In linguistic typology, languages in a given macroare

researcharxiv-cs-cl

Towards Real-World RUL Prediction for Aircraft Compressors Under Variable Conditions with Physics-Guided Domain Adaptation

arXiv:2607.24809v1 Announce Type: cross Abstract: Remaining useful life prediction for aircraft centrifugal air compressors in real commercial operations poses challenges that controlled benchmark dat

Towards Robust Reinforcement Learning for Small-Scale Language Model Agents

arXiv:2607.25091v1 Announce Type: new Abstract: The alignment of Small Language Models (SLMs) in the 70--500M parameter range using reinforcement learning is often considered unstable, though the unde

Two Views, One Voice: Evidence-Grounded Conversational Music Recommendation

arXiv:2607.24846v1 Announce Type: cross Abstract: Traditional conversational recommenders entangle retrieval and response generation within a single text interface, so exact entity cues fade as the di

Unified Semantic Modeling Framework for Large-Scale Job Understanding at LinkedIn

arXiv:2607.24783v1 Announce Type: new Abstract: Job understanding is critical to LinkedIn's mission of connecting talent with opportunity. This task involves transforming unstructured and noisy job po

A Case Study on the Acceptance of a Humanoid Robotic Head Employed in Three Public Spaces

arXiv:2607.24113v1 Announce Type: cross Abstract: Previous research has shown that a human-like robot's acceptance heavily depends on the setting in which it operates and its ability to perform releva

applicationsarxiv-cs-ai

A Computational Ethical Framework for Financial Digital Phenotyping for Mental Health

arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r

Hardware

A didactical-driven teacher assistant for a dimensional modeling course

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

hardwarearxiv-cs-ai

A General Deep Learning Framework for Wireless Resource Allocation under Discrete Constraints

arXiv:2603.19322v2 Announce Type: replace-cross Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for pr

Hardware

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference

arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy

hardwarearxiv-cs-ai

A note on the motion representation and configuration update in time stepping schemes for the constrained rigid body

arXiv:2607.24317v1 Announce Type: new Abstract: The dynamics of a holonomically constrained rigid body can be modeled by Newton-Euler equations subjected to geometric constraints. This is frequently f

researcharxiv-cs-ro

A Reconstruction-Based Framework for Caption Evaluation Beyond Reference Captions

arXiv:2607.23235v1 Announce Type: new Abstract: Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on ref

A scalable online machine learning approach for Stock Recommendation

arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e

applicationsarxiv-cs-ai

A Simple, Optimal and Efficient Algorithm for Online Exp-Concave Optimization

arXiv:2512.23190v3 Announce Type: replace Abstract: Online eXp-concave Optimization (OXO) is a fundamental problem in online learning, where the goal is to minimize regret when loss functions are expo

A Statistical Difference between Single-Layer Learning and Hierarchical Learning in Wide Neural Networks

arXiv:2607.23397v1 Announce Type: new Abstract: Hierarchical neural networks are widely used in artificial intelligence, yet their mathematical properties remain incompletely understood. In the infini

A Unified Stereo Geometry Estimation Framework for Disparity and Surface Normal

arXiv:2607.24024v1 Announce Type: new Abstract: Stereo matching and surface normal estimation are fundamental tasks in 3D vision. However, existing feed-forward stereo methods still struggle to produc

AdaKAN: A dual-branch adaptive Kolmogorov-Arnold network for medical image segmentation

arXiv:2607.22891v1 Announce Type: new Abstract: Medical image segmentation is a fundamental task in computer-aided diagnosis, yet it remains challenging due to the complexity of anatomical structures

AIFL: A Global Daily Streamflow Forecasting Model Using a Deterministic LSTM Pre-trained on ERA5-Land and Fine-tuned on IFS

arXiv:2602.16579v2 Announce Type: replace-cross Abstract: Reliable global streamflow forecasting is essential for flood preparedness and water resource management, yet data-driven models often suffer

An Interactive Vision Language Platform for Cognitive Remediation in Schizophrenia

arXiv:2607.22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning. For patients