Search: “applications”

Neural Operator based Multi-Field Reconstruction of Inner Solar Boundary State

arXiv:2608.22782v1 Announce Type: cross Abstract: The Solar wind is a continuous flow of charged particles emanating from the solar surface and governed by complex, interacting magnetohydrodynamic pro

researcharxiv-cs-cv

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NeuroPrefetcher: Storage-Aware Sparse LLM Inference via Delta Prefetching

DGX agent

arXiv:2608.22643v1 Announce Type: cross Abstract: Deploying large language models on edge devices is increasingly limited by a widening gap between model size and available memory. Existing approaches

model-releasesarxiv-cs-lg

25 Aug 2026

Hardware

On the Choice of Tensor Estimation for Corner Detection, Optical Flow and Denoising

arXiv:2608.22314v1 Announce Type: new Abstract: Many image processing methods such as corner detection, optical flow and iterative enhancement make use of image tensors. Generally, these tensors are e

hardwarearxiv-cs-cv

One Request, Multiple Experts: LLM Orchestrates Domain Specific Models via Adaptive Task Routing

arXiv:2511.12484v2 Announce Type: replace-cross Abstract: With the integration of massive distributed energy resources and the widespread participation of novel market entities, the operation of activ

agentsarxiv-cs-ai

Opportunities and Challenges of Natural Language Processing for Low-Resource Senegalese Languages in Social Science Research

arXiv:2601.09716v2 Announce Type: replace Abstract: Natural Language Processing (NLP) is rapidly transforming research methodologies across disciplines, yet African languages remain largely underrepre

researcharxiv-cs-cl

Power-Performance Characterization of TinyML Systems

arXiv:2608.21646v1 Announce Type: cross Abstract: TinyML systems are enabling machine learning (ML) inference at the edge. However, there is little quantitative analysis of such systems. This paper pr

researcharxiv-cs-ai

Primal--Dual Alternating Neural Learning for Timely Classification with Performance Guarantees

arXiv:2608.23480v1 Announce Type: cross Abstract: Timely risk classification is essential in many clinical monitoring settings, where decisions must balance the benefit of classifying patients early f

QuantFormer: Learning to Quantize for Neural Activity Forecasting in Mouse Visual Cortex

arXiv:2412.07264v2 Announce Type: replace-cross Abstract: Understanding complex animal behaviors hinges on deciphering the neural activity patterns within brain circuits, making the ability to forecas

Random Hazard Forests

arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times

Rank Reversal in Multilingual LLM Judges: A Label-Free Double-Centering Calibrator

arXiv:2608.22432v1 Announce Type: cross Abstract: Multilingual LLM judges produce different evaluator-backbone rankings depending on the prompt language: on an eight-language Agent-as-a-Judge benchmar

Rethinking Communication Metrics: How Should We Measure Meaning?

arXiv:2608.21626v1 Announce Type: new Abstract: Semantic communication shifts the objective of communication systems from accurate symbol reconstruction toward meaning preservation, task accomplishmen

RIACT: A Responsible AI System for Personalized Study Habit Tracking and Early Burnout Signal Detection in University Students

arXiv:2608.21379v1 Announce Type: new Abstract: Student burnout is highly prevalent in higher education, with reported rates ranging from 12% to over 70% and consistently exceeding those of the workin

safetyarxiv-cs-ai

Sa2VA: Marrying SAM2 with MLLM for Dense Grounded Understanding of Images and Videos

arXiv:2501.04001v4 Announce Type: replace Abstract: This work presents Sa2VA, the first comprehensive, unified model for dense grounded understanding of both images and videos. Unlike existing multi-m

SelFusion: Self-distillation for Diffusion Language Models

arXiv:2608.22898v1 Announce Type: new Abstract: Diffusion language models (DLMs) alleviate the inherent latency bottleneck of autoregressive (AR) large language models (LLMs), but their degraded gener

researcharxiv-cs-cl

Semantic Reasoning Denoising: Correcting Language Model Reasoning with Semantic Operators

arXiv:2608.22090v1 Announce Type: cross Abstract: Large language models can produce fluent reasoning traces whose local semantic errors propagate to an incorrect conclusion, while unconstrained self-c

Spectrum-Aware Bounds on Invertibility for Privacy-Enhancing Instance Encoding

arXiv:2608.23382v1 Announce Type: new Abstract: Instance encoding is a popular empirical technique for privacy enhancement when sharing data to an untrusted server. It transforms sensitive data throug

Hardware

SweepLSD: A One-Pass, O(width)-Memory Line Segment Detector with an Integer-Only Streaming Core and a Real-Time FPGA Realization

arXiv:2608.22086v1 Announce Type: cross Abstract: We present SweepLSD, a line segment detector that reads the image exactly once and emits each segment within a few rows of its last pixel passing the

hardwarearxiv-cs-cv

Sycophants in the Courtroom: Are LLMs Fragile to Juridical Authority and Evolving Legal Standards?

arXiv:2608.21409v1 Announce Type: cross Abstract: In medicine, claims remain valid when supported by empirical evidence grounded in stable biological reality. In law, by contrast, truth is contingent,

Tutorials

Teaching LLMs How ICU Physicians Approach Clinical Reasoning Through OMOP-Aligned Retrieval Improves Reasoning Across Clinical Domains

arXiv:2608.22622v1 Announce Type: cross Abstract: Clinical decision-making relies on identifying relevant patient information to guide diagnosis and treatment, a challenge that is especially difficult

tutorialsarxiv-cs-ai

Training Proactive and Personalized LLM Agents

arXiv:2511.02208v2 Announce Type: replace Abstract: Despite rapid progress, current AI agents are primarily optimized for isolated task completion. We argue for a paradigm shift toward training agents

Vibe Coding on Trial: Operating Characteristics of Unanimous LLM Juries

arXiv:2602.18492v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are now good enough at coding that developers can describe intent in plain language and let the tool produce the

ViTexSZ: Heterogeneous Vision-Text Knowledge Distillation for EEG Seizure Detection

arXiv:2608.21445v1 Announce Type: new Abstract: Automated seizure detection from electroencephalography (EEG) is essential for continuous neurological monitoring, particularly for subclinical epilepti

safetyarxiv-cs-cv

When More Modalities Hurt: Modality Dropout for Heavy-Duty Vehicle Engine Diagnostics

arXiv:2608.23161v1 Announce Type: new Abstract: Heavy-duty vehicle diagnostics generate three disconnected data modalities: unstructured multi- lingual service complaints, high-dimensional sensor tele

When Not to Imitate: Boundary-Aware Skill Memory for Reliable Tool-Use LLM Agents

arXiv:2608.22339v1 Announce Type: new Abstract: Extracting skills from past successes is critical for the efficient evolution of Large Language Model (LLM) agents. Prevailing agent self-evolution para

agentsarxiv-cs-cl

XIT: Exploration and Exploitation Informed Trees for Active Gas Distribution Mapping in Unknown Environments

arXiv:2602.13739v2 Announce Type: replace Abstract: Mobile robotic gas distribution mapping (GDM) provides critical situational awareness during emergency responses to hazardous gas releases. However,

agentsarxiv-cs-ro

ZOTTA: Test-Time Adaptation with Gradient-Free Zeroth-Order Optimization

arXiv:2603.14254v2 Announce Type: replace Abstract: Test-time adaptation (TTA) aims to improve model robustness under distribution shifts by adapting to unlabeled test data, but most existing methods

Actively Learning Joint Contours of Multiple Computer Experiments

arXiv:2512.13530v2 Announce Type: replace-cross Abstract: Contour location---the process of sequentially training a surrogate model to identify the design inputs that result in a pre-specified respons

AEGIS: Preventing Cross-Domain Resource Abuse in MCP

arXiv:2608.20481v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an open source JSON-RPC protocol that standardizes how large language models (LLMs) interact with external systems

safetyarxiv-cs-ai

Anchored Regularized Direct Least Squares (ARDLS): Integrating Established Prioritization Operators for Priority Elicitation in the Analytic Hierarchy Process

arXiv:2608.21187v1 Announce Type: cross Abstract: Pairwise reciprocal matrices are fundamental to the Analytic Hierarchy Process (AHP), a decision-making model. While the Direct Least Squares (DLS) me

researcharxiv-cs-ai

Benchmarking noisy label detection methods

model-releasesarxiv-cs-lg

arXiv:2510.16211v2 Announce Type: replace Abstract: Label noise is a common problem in real-world datasets, affecting both model training and validation. Clean data are essential for achieving strong

BIPPO: Budget-Aware Independent PPO for Energy-Efficient Federated Learning Services

arXiv:2511.08142v2 Announce Type: replace Abstract: Federated Learning (FL) is a promising machine learning solution in large-scale IoT systems, guaranteeing load distribution and privacy. However, FL

safetyarxiv-cs-lg

EditPPT: Faithful Long-Deck Slide Editing via Structured Tool-Using Multi-Agent with Dual-Modal Validators

arXiv:2608.20381v1 Announce Type: cross Abstract: Automating slide editing requires simultaneously satisfying modification accuracy, preservation fidelity, and robustness to deck length. Existing LLM-

Exact and general decoupled solutions of the LMC Multitask Gaussian Process model

arXiv:2310.12032v4 Announce Type: replace Abstract: The Linear Model of Co-regionalization (LMC) is a very general multitask gaussian process model for regression or classification. While its expressi

Federated and differentially private estimation of KL divergence

model-releasesarxiv-cs-lg

arXiv:2411.16478v3 Announce Type: replace Abstract: Measuring distribution drifts is a key task in managing distributed, sensitive data, as it underpins a wide range of federated learning and analytic

Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence

arXiv:2608.21156v1 Announce Type: cross Abstract: LLMs have evolved from language generators to autonomous agents capable of complex, long-horizon tasks. This evolution has produced paradigms includin

agentsarxiv-cs-ai

Hardware

How to Train a Real-World Silicon Concierge? Internalizing Complex Business Workflow to Only OneModel

arXiv:2608.20350v1 Announce Type: cross Abstract: Traditional industrial agents rely on modular pipelines, including Router, Retriever, Planner, Executor, Responder, Reviewer, and other components. Th

hardwarearxiv-cs-ai

ImmigrationReason: A Structured Dataset of U.S. Immigration Appeals for Legal Reasoning Research

model-releasesarxiv-cs-cl

arXiv:2608.20391v1 Announce Type: new Abstract: Most legal NLP resources draw from federal case law and focus on coarse classification, leaving administrative adjudication, where the vast majority of

Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles

arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and

researcharxiv-cs-ai

Is Multimodal Speculative Decoding Ready for Diffusion-Based Parallel Drafting? A Survey and Empirical Diagnosis

arXiv:2608.20743v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them

safetyarxiv-cs-ai

Is Vibe Coding Safe? Benchmarking Vulnerability of Agent-Generated Code in Real-World Tasks

model-releasesarxiv-cs-cl

arXiv:2512.03262v3 Announce Type: replace-cross Abstract: Vibe coding is a new software development paradigm in which human engineers prompt a large language model (LLM) agent to complete complex codi

No Judgment Without a Reason: Counterfactual Receipts for Versioned AI Evaluators

arXiv:2608.20938v1 Announce Type: new Abstract: Evaluators often produce correct labels via flawed reasoning, a critical failure for agentic systems gating actions, routing reviews, or supplying train

Pneumatic Units for Logic-based Sequential Excitation (PULSE) in Wearable Haptic Devices

arXiv:2608.20626v1 Announce Type: cross Abstract: Soft, wearable robotic devices can deliver haptic feedback to support a wide range of tasks, such as extended reality, training various skills, and re

researcharxiv-cs-ro

Radiometric fingerprinting of object surfaces using mobile laser scanning and semantic 3D road space models

arXiv:2603.11252v2 Announce Type: replace Abstract: Although semantic 3D city models are internationally available and becoming increasingly detailed, the incorporation of material information remains

RARE: Decoupling Representation Steering from Expert Routing in Mixture-of-Experts Language Models

arXiv:2608.21236v1 Announce Type: new Abstract: Representation engineering offers a lightweight means of controlling language-model behavior by modifying intermediate hidden states, but its direct app

researcharxiv-cs-cl

Local Ai

ReFrame: Evidence-Guided Test-Time Safety Alignment in Multimodal Large Language Models

arXiv:2608.21100v1 Announce Type: new Abstract: While multimodal large language models (MLLMs) extend model capabilities beyond text, they also make safety alignment increasingly challenging. Multimod

local-aiarxiv-cs-ai

RODE: A Radial-Orthogonal Decoupled Engine for Optimization

model-releasesarxiv-cs-lg

arXiv:2608.21024v1 Announce Type: new Abstract: Modern neural network training increasingly uses matrix-aware optimizers, yet their conditioned matrix step is typically added directly to the weight, j

Self-Speculation for Faster Reasoning Models

model-releasesarxiv-cs-cl

arXiv:2608.20359v1 Announce Type: new Abstract: Large language models (LLMs) are deployed for increasingly complex tasks involving planning and multi-step decision making, but high-quality performance

Spatially Aware Dictionary-Free Koopman Eigenfunction Identification for Modeling and Control

arXiv:2511.22648v2 Announce Type: replace Abstract: A spatially aware dictionary-free eigenfunction discovery (SADFED) framework is proposed for identification of low-rank Koopman models from data wit