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AI Evaluation Should Measure Verification Cost, Not Correctness Alone

arXiv:2608.08709v1 Announce Type: new Abstract: The reliability of AI generative models is typically measured by output correctness, yet in practice it depends on the effort required to verify those o

Applications

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AirFlow: Context Preserving and Multi-Rate State Modeling for Air Quality Forecasting

DGX agent

arXiv:2608.09775v1 Announce Type: new Abstract: Accurate air quality forecasting is essential for public health and urban environmental management, but remains challenging because pollutant channels d

applicationsarxiv-cs-ai

11 Aug 2026

Agents

AIVV: Neuro-Symbolic LLM Agent-Integrated Verification and Validation for Trustworthy Autonomous Systems

arXiv:2604.02478v2 Announce Type: replace Abstract: Deep learning models excel at detecting anomaly patterns in normal data. However, they do not provide a direct solution for anomaly classification a

agentsarxiv-cs-ai

AkasicDB: Demonstrating Omni RAG with a Unified Vector-Graph-Relational DBMS

arXiv:2608.09214v1 Announce Type: cross Abstract: Recent Retrieval-Augmented Generation (RAG) systems increasingly combine vector retrieval with structured knowledge, such as Graph RAG and Filtered ve

Alpha as an Efficiency Signal: Visibility-Routed RGBA Image-to-Video Generation

arXiv:2608.09355v1 Announce Type: new Abstract: RGBA videos combine RGB appearance with an alpha channel, enabling animated assets to be applied across arbitrary backgrounds, which are heavily used in

researcharxiv-cs-cv

AMD:Anatomical Motion Diffusion with Interpretable Motion Decomposition and Fusion

arXiv:2312.12763v3 Announce Type: replace Abstract: Generating realistic human motion sequences from text descriptions is a challenging task that requires capturing the rich expressiveness of both nat

researcharxiv-cs-cv

An Agentic AI Framework Overcomes Fundamental Limitations of Large Language Models for Glaucoma Detection from Fundus Photography

arXiv:2608.07651v1 Announce Type: new Abstract: Large language models (LLMs) show promise in medical image interpretation but suffer from hallucination, limited accuracy, and run-to-run inconsistency.

An Agentic Generative Large Language Model for Treatment Planning of Colorectal Cancer

arXiv:2608.09142v1 Announce Type: new Abstract: Treatment planning in precision oncology requires synthesizing heterogeneous patient information with rapidly evolving clinical guidelines to ensure gui

safetyarxiv-cs-cl

Local Ai

An AI Scientist that Doesn't Drift: Taste, Structure, and Falsifiable Findings in a Quadruped Navigation Research Loop

arXiv:2608.07542v1 Announce Type: new Abstract: Autonomous research loops driven by large language models can run machine-learning experiments at scale but tend to drift toward local refinements of wh

local-aiarxiv-cs-ai

An Auto-Scaling Approach for Serverless Environments Based on a Multi-Expert Consensus Mechanism

arXiv:2607.15511v2 Announce Type: replace-cross Abstract: Serverless computing provides automatic resource management and pay-per-use execution, but effective autoscaling remains challenging because o

An evolutionary model of animats with VLM-based subjective evaluation

arXiv:2608.07537v1 Announce Type: cross Abstract: In this study, we propose a framework that incorporates subjective evaluations provided by a Vision-Language Model (VLM) into the fitness evaluation a

An Expectation-Maximization Perspective on Reinforcement Learning for LLM Reasoning

arXiv:2504.18587v2 Announce Type: replace-cross Abstract: Reinforcement learning has emerged as a powerful approach for improving the reasoning capabilities of large language models, as demonstrated b

An Explainable GNN Framework for Component-Level Anomaly Diagnosis

arXiv:2608.09246v1 Announce Type: new Abstract: Industrial processes are complex systems composed of multiple interacting sensors that generate multivariate time series (MTS). Detecting anomalies in s

An Information-Theoretic Framework for Feature Construction in Out-of-Distribution Detection

arXiv:2506.14194v2 Announce Type: replace Abstract: We present a theory for the construction of out-of-distribution (OOD) detection features for neural networks. We introduce random features for OOD t

An invertible generative model for forward and inverse problems

arXiv:2509.03910v2 Announce Type: replace-cross Abstract: We formulate inverse problems in a Bayesian framework and aim to train an invertible generative model that is capable of simulation (i.e., sam

Applications

Analogical Learning for Cross-Scenario Generalization: Framework and Application to Intelligent Localization

arXiv:2504.08811v3 Announce Type: replace Abstract: Modern learning systems often struggle with joint learning across diverse scenarios and immediate adaptation to new ones, because they rely heavily

applicationsarxiv-cs-lg

Analysis and experiments of the dissipative Twistcar: direction reversal and asymptotic approximations

model-releasesarxiv-cs-ro

arXiv:2506.19112v3 Announce Type: replace Abstract: Underactuated wheeled vehicles are commonly studied as nonholonomic systems with periodic actuation. Twistcar is a classical example inspired by a r

Tutorials

Anatomically Consistent Cross-Contrast Super-Resolution of Anisotropic Brain T2w MRI

arXiv:2608.08401v1 Announce Type: new Abstract: T2-weighted (T2w) brain MRI provides fluid-sensitive soft-tissue contrast that is important for neuro-oncology and radiotherapy planning. However, T2w s

tutorialsarxiv-cs-cv

Anchor-Based AI Approach for Pre-Crash Object Detection Utilizing Micro-Doppler Signatures in Automotive Radar

model-releasesarxiv-cs-ro

arXiv:2608.08701v1 Announce Type: new Abstract: Advanced automated driving presents significant potential to improve modern automotive safety systems, but it depends highly on the reliable activation

AnchorFold: A Focus-Then-Fold Framework via Recursive Attention Propagation for Efficient Multi-Vector Visual Document Retrieval

arXiv:2608.08732v1 Announce Type: cross Abstract: Multi-vector vision-language retrievers enable fine-grained Visual Document Retrieval (VDR) through late interaction, but storing and scoring hundreds

researcharxiv-cs-cl

AndroidReality: How Far Are Mobile Agents from the Real World?

arXiv:2608.07775v1 Announce Type: new Abstract: Mobile agents have achieved promising results on clean online benchmarks such as AndroidWorld, yet their performance often degrades sharply in real-worl

AnyCamVLA: Zero-Shot Camera Adaptation for Viewpoint Robust Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2603.05868v2 Announce Type: replace Abstract: Despite remarkable progress in Vision-Language-Action models (VLAs) for robot manipulation, these large pre-trained models require fine-tuning to be

APEX-VW: A Document-Level English-Spanish Post-Editing Dataset in the Healthcare Domain

model-releasesarxiv-cs-cl

arXiv:2608.08059v1 Announce Type: new Abstract: Post-Editing (PE) of Machine Translation (MT) output often involves repeating the same lexical and terminological corrections across many segments, espe

Application of Artificial Intelligence for Fraudulent Banking Operations Recognition

arXiv:2608.07471v1 Announce Type: cross Abstract: This study considers the task of applying artificial intelligence to recognize bank fraud. In recent years, due to the COVID19 pandemic, bank fraud ha

Approximation Rates for Metaplectic Neural Networks

arXiv:2608.08872v1 Announce Type: new Abstract: In this paper we develop quantitative approximation results for shallow neural networks constructed using a dictionary based on metaplectic operators. F

AQUA20: A Benchmark Dataset for Underwater Species Classification under Challenging Conditions

model-releasesarxiv-cs-cv

arXiv:2506.17455v3 Announce Type: replace Abstract: Robust visual recognition in underwater environments remains a significant challenge due to complex distortions such as turbidity, low illumination,

Local Ai

AquiLLM: An Architecture for Supporting Tacit Knowledge Capture in Research Groups

arXiv:2608.08883v1 Announce Type: new Abstract: Recent advances in retrieval-augmented generation (RAG) and large language models (LLMs) enable researchers to integrate AI into scientific workflows. H

local-aiarxiv-cs-ai

Hardware

AraSSM: A bidirectional state-space encoder for Arabic masked language modeling

arXiv:2608.08256v1 Announce Type: new Abstract: Pretrained Transformer encoders such as AraBERT, MARBERT, and CAMeLBERT have become the standard backbone for Arabic natural language understanding, but

hardwarearxiv-cs-cl

ARC: Augmented-Rank Conformalization for Changepoint Localization --- Finite-Sample Validity and Distribution-Robust Efficiency

model-releasesarxiv-cs-cv

arXiv:2608.08424v1 Announce Type: cross Abstract: Conformal changepoint localization turns any score into a confidence set for the changepoint with finite-sample coverage. Coverage is universal; effic

ArchAgent v2: A Case Study with the Data Prefetching Championship

arXiv:2608.09874v1 Announce Type: new Abstract: Agentic artificial intelligence has shown great promise in automating algorithm design, but scaling similar techniques to computer microarchitecture dis

Archer: Adaptive Reuse of Cached Hidden States for Efficient Rollback in Diffusion Language Models

arXiv:2608.08086v1 Announce Type: new Abstract: Diffusion language models (DLMs) iteratively refine a sequence, allowing earlier predictions to be revised as context evolves. This rollback capability

researcharxiv-cs-cl

Are Latent Reasoning Models Easily Interpretable?

arXiv:2604.04902v2 Announce Type: replace Abstract: Latent reasoning models (LRMs) have attracted significant research interest due to their low inference cost (relative to explicit reasoning models)

Artificial Leviathan: Exploring Social Evolution of LLM Agents Through the Lens of Hobbesian Social Contract Theory

arXiv:2406.14373v3 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) and advancements in Artificial Intelligence (AI) offer an opportunity for computational social science

ASPaeroFlow: Decomposition Heuristics for Joint Air Traffic Flow & Capacity Management

arXiv:2608.09315v1 Announce Type: new Abstract: While mathematical models act as vital decision support systems for operational Air Traffic Flow and Capacity Management (ATFCM), existing approaches is

ATLAS: Agentic Taxonomy of Large-Scale Software Ecosystems

model-releasesarxiv-cs-cl

arXiv:2606.21597v2 Announce Type: replace-cross Abstract: The open-source ecosystem on GitHub lacks a systematic hierarchical taxonomy of software repositories. GitHub Topics, the dominant organizatio

ATLASFusion: Aggregation Tracking with Location-Aware Sparse Fusion for Robust Spatio-Temporal Multi-View Pedestrian Tracking

arXiv:2509.08421v2 Announce Type: replace-cross Abstract: For multimedia spatial intelligence through time, multi-view multi-object tracking (MVMOT) suffers from persistent challenges in maintaining c

Tutorials

Attention-Guided Perturbation Network for Industrial Anomaly Detection

arXiv:2408.07490v4 Announce Type: replace Abstract: In unsupervised image anomaly detection, reconstruction-based methods learn normal patterns for data reconstruction, but often undesirably reconstru

tutorialsarxiv-cs-cv

Attn-QAT: 4-Bit Attention With Quantization-Aware Training

arXiv:2603.00040v3 Announce Type: replace-cross Abstract: Achieving reliable 4-bit attention is a prerequisite for end-to-end FP4 computation on emerging FP4-capable GPUs, yet attention remains the ma

Auditing Instruction-Trajectory Mismatches in Multimodal Robot Demonstrations

arXiv:2608.07895v1 Announce Type: cross Abstract: Robot demonstration datasets used to train vision-language-action policies can contain a subtle but harmful failure mode: trajectories that are behavi

safetyarxiv-cs-lg

Local Ai

Auditing Medical Vision-Language Models on Chest Radiographs: Estimating Reference Agreement Across Institutions

arXiv:2608.07550v1 Announce Type: new Abstract: Vision-language models return structured chest-radiograph findings through interfaces exposing no confidence score, so a receiving institution cannot re

local-aiarxiv-cs-cv

Automated Generation of Complexity-Validated Decision Scenarios Using Large Language Models

arXiv:2608.08822v1 Announce Type: new Abstract: Cognitive decision-making research depends on diverse scenarios with carefully controlled complexity, yet manual production is slow, inconsistent, and b

Automating Deception: Scalable Multi-Turn LLM Jailbreaks

arXiv:2511.19517v3 Announce Type: replace-cross Abstract: Multi-turn conversational attacks, which leverage psychological principles like Foot-in-the-Door (FITD), where a small initial request paves t

Autonomous Driving with Priority-Ordered STL Specifications Under Multimodal Uncertainty

arXiv:2606.20336v2 Announce Type: replace Abstract: Autonomous vehicles must plan trajectories that satisfy multiple requirements, such as safety, traffic-rule compliance, and passenger comfort. Howev

safetyarxiv-cs-ro

Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents

arXiv:2510.04465v3 Announce Type: replace-cross Abstract: LLM agents require personal information for personalization in order to effectively act on users' behalf, but this raises privacy concerns tha

AutoRefine: Compiling Trajectories into Validated Typed Agent Artifacts

arXiv:2601.22758v2 Announce Type: replace Abstract: Large language model agents repeatedly encounter related tasks, yet systems that learn from trajectories commit every lesson to one predefined artif

Autorubric: A Unifying Framework for Rubric-Based LLM Evaluation on Non-Verifiable Tasks

arXiv:2603.00077v3 Announce Type: replace-cross Abstract: Rubric-based LLM judges have become indispensable for evaluating and optimizing systems on non-verifiable tasks, where success cannot be reduc

Avalon-ToM-Bench: Evaluating Fine-Grained Theory of Mind via Asymmetric Game Mechanics

arXiv:2608.09638v1 Announce Type: new Abstract: Theory of Mind (ToM) is essential for agent interactions, yet existing evaluations either rely on static scenarios that oversimplify mental-state reason

Back to the Future: A workbook time machine for spread sheet creation benchmarks

arXiv:2608.07873v1 Announce Type: new Abstract: We introduce the workbook time machine, a pipeline that automatically creates benchmarks evaluating the ability of language models to create derived obj