Search: “evaluation”

Study-Strategy Clusters from EdNet Logs Track Engagement, Not Mastery

arXiv:2608.16963v1 Announce Type: new Abstract: Learning analytics often treats unsupervised clusters of intelligent tutoring system (ITS) logs as learner types that should predict learning. We test t

researcharxiv-cs-lg

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TabularQGAN: A quantum generative model for tabular data synthesis

DGX agent

arXiv:2505.22533v2 Announce Type: replace-cross Abstract: In this paper, we introduce a novel quantum generative model for synthesizing tabular data. Synthetic data is valuable in scenarios where real

applicationsarxiv-cs-ai

19 Aug 2026

The 10th AI City Challenge

arXiv:2608.17044v1 Announce Type: cross Abstract: The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical A

Training-Free Human-in-the-Loop Anomaly Detection via Memory Bank Correction

arXiv:2608.17775v1 Announce Type: new Abstract: Anomaly detectors are hardest to deploy exactly where training data is scarcest: a newly commissioned production line has a handful of verified 'golden'

applicationsarxiv-cs-lg

Uncertainty-Aware Decision Making in Multimodal Large Language Models

arXiv:2608.17084v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) increasingly answer questions whose correctness depends on visual, textual, temporal, acoustic, document, chart

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Unsupervised Deep Generative Models for Anomaly Detection in Neuroimaging: A Systematic Scoping Review

arXiv:2510.14462v3 Announce Type: replace Abstract: Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly explored for identifying pathological brain abnormalit

researcharxiv-cs-cv

Vision-Language Models for Analog Gauge Reading: An Empirical Study of Specialization, Transfer and Reliability

arXiv:2608.17723v1 Announce Type: new Abstract: Analog gauges remain common in industrial environments where manual inspection is costly or hazardous. The engineering application addressed here is dir

When Personalization Becomes Bias: Structural and Discursive Religious Framing in AI-Generated Financial Advice

arXiv:2608.16909v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly integrated into financial advisory systems, yet their role in reproducing religious bias remains underex

When Writing Style Drifts: Benchmarking Authorship Verification under Distribution Shifts in Genre, Time and the AI-Era

model-releasesarxiv-cs-cl

arXiv:2608.17979v1 Announce Type: new Abstract: Authorship verification (AV) assumes that an author's writing style remains sufficiently stable to distinguish it from that of other writers. In practic

Which Source Wins? Task-Dependent Reliance in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2608.17205v1 Announce Type: new Abstract: Vision-language models (VLMs) combine images and text, but when the two conflict and one becomes harder to read, it is unclear how a model shifts its re

WIP: LLM Odyssey: A Game-Based Platform for Teaching LLM Engineering Concepts

arXiv:2608.16924v1 Announce Type: cross Abstract: This work-in-progress (WIP) innovative practice category paper presents LLM Odyssey, an open source, browser-based serious gaming platform comprising

applicationsarxiv-cs-ai

WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization

arXiv:2608.16955v1 Announce Type: cross Abstract: Post-disaster damage to terrestrial infrastructure can disrupt wireless coverage,while Uncrewed Aerial Vehicle (UAV) swarms provide a promising soluti

local-aiarxiv-cs-lg

A Plug-and-Play 2D Motion Interface for Real-World Motion Language Models

arXiv:2608.15984v1 Announce Type: new Abstract: Motion Language Models (MoLMs) typically understand human motions by tokenizing 3D motion and processing the resulting tokens using a language model. Ho

applicationsarxiv-cs-cv

A Temporal Reasoning Benchmarking Framework for LRMs via Difficulty-controlled and Dynamic Test Generation

arXiv:2607.04784v1 Announce Type: cross Abstract: Defining the reasoning boundaries and ensuring the reliability of Large Reasoning Models (LRMs) remains a critical challenge. Current benchmarks prima

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

applicationsarxiv-cs-ai

A Versatile Foundation Model for AI-enabled Mammogram Interpretation

arXiv:2509.20271v2 Announce Type: replace Abstract: Breast cancer is the most commonly diagnosed cancer and the leading cause of cancer-related mortality in women globally. Mammography is essential fo

AdROD: HyperNetwork-based Adversarially Robust Object Detection for Autonomous Driving

arXiv:2608.16031v1 Announce Type: cross Abstract: Camera-based object detectors are vulnerable to physical adversarial attacks designed to suppress detections. While adversarial training and input pur

AlignJEPA: Predictive Vision-Language Alignment for Remote Sensing Foundation Models

arXiv:2608.15456v1 Announce Type: new Abstract: Remote sensing (RS) foundation models provide transferable Earth observation representations across sensors, resolutions, and geographies, yet most rema

ALPS: Measuring Valid Creativity in Large Language Models with Mathematical Construction

arXiv:2608.15979v1 Announce Type: new Abstract: Large language models produce outputs presented as discoveries - new proofs, conjectures, or molecules. Whether such an output that appears creative is

Tutorials

An Analytical-Prior Framework for Data-Efficient Prediction of Sound-Reduction Frequencies in Rectangular Side-Branch Helmholtz Resonators

arXiv:2608.16873v1 Announce Type: new Abstract: High-fidelity finite-element simulations can provide accurate numerical predictions for side-branch resonators, but large simulation datasets are expens

tutorialsarxiv-cs-lg

Anatomy of a Quantized Agent: VRAM Stability and Forecasting in Code-Synthesis Agentic Workloads

arXiv:2608.15117v1 Announce Type: new Abstract: Analytical models of peak VRAM consumption for LLM inference decompose memory into weight-storage, KV-cache, and activation terms parameterized by step

ARGUS: Attention-Guided Transformers for Scalable Person Identification Using Wi-Fi Telemetry

arXiv:2608.14670v1 Announce Type: cross Abstract: Passive, device-free person identification offers an alternative to camera- and wearable-based biometrics, yet existing wireless approaches rely large

ARISE: An adaptive residual-informed stability ensemble for feature selection in small-sample biomedical omics

arXiv:2608.14866v1 Announce Type: cross Abstract: Objective: Small-sample molecular classification requires feature selectors that identify predictive, stable, and nonredundant subsets for binary and

researcharxiv-cs-lg

As models become more capable, the risks associated with developing and testing them internally also grow. We temporarily paused reinforceme…

As models become more capable, the risks associated with developing and testing them internally also grow. We temporarily paused reinforcement learning (RL) training on our latest models intended for

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Automated Fetal Brain MRI Biometry in Healthy and Pathological Cases

arXiv:2608.15692v1 Announce Type: new Abstract: Automated biometric analysis of fetal brain MRI enables reproducible, observer-independent quantitative assessment, yet existing methods are often restr

local-aiarxiv-cs-cv

Automatic Cephalometric Landmark Localization on CBCT-Derived Digitally Reconstructed Radiographs for Skeletal Malocclusion Classification

arXiv:2608.16535v1 Announce Type: new Abstract: Manual cephalometric landmark annotation is important for craniofacial assessment but is labor-intensive and difficult to scale. We introduce CephViT, a

local-aiarxiv-cs-cv

BabelSteering: Multilingual Safety Alignment via English Steering Vectors

model-releasesarxiv-cs-cl

arXiv:2608.16577v1 Announce Type: new Abstract: Large language models (LLMs) are deployed globally in high-stakes settings, yet most safety research and alignment efforts remain concentrated on Englis

Bactrainus: Optimizing Large Language Models for Multi-hop Complex Question Answering Tasks

arXiv:2501.06286v2 Announce Type: replace-cross Abstract: Multi-hop question answering requires a system to identify and integrate evidence distributed across documents, yet large language models rema

Baseline-Relative Counterfactual Refinement for Bit-Aware Visual Token Communication

arXiv:2608.16192v1 Announce Type: new Abstract: Generative visual-token communication reduces transmission load by sending only selected discrete tokens and reconstructing missing content at the recei

researcharxiv-cs-ai

BaT: Towards Self-Evolving Medical Research Agent with Stage Rubrics

arXiv:2608.16211v1 Announce Type: new Abstract: Long-horizon agents are beginning to automate complete workflows that produce code, reports, and research artifacts. Medical imaging workflows are multi

Beam-Wise Statistical Background Subtraction for Static Roadside LiDAR: A Cross-Sensor Benchmark Study

arXiv:2608.14868v1 Announce Type: new Abstract: Background subtraction is a key preprocessing step for infrastructure-based LiDAR perception, enabling efficient isolation of dynamic traffic participan

Behaviour Is an Incomplete Measure of Reasoning Development: Cross-surface pre-arrival accessibility and the limits of developmental inference in a recurrent-depth reasoner

arXiv:2608.16085v1 Announce Type: cross Abstract: Capability development is routinely inferred from behavioural thresholds, from final checkpoints, or from what a decoder can read out of a hidden stat

Benchmarking Identity-Sensitive LLM Outputs for Surveillance and Security Robots

model-releasesarxiv-cs-ro

arXiv:2608.16030v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate textual robot design specifications, interaction policies, and risk assessments during ea

Beyond Accuracy: Assessing Calibration of Geospatial Foundation Models and Their Sensitivity to Distribution Shifts

arXiv:2608.16614v1 Announce Type: new Abstract: Geospatial Foundation Models (GeoFMs) are most commonly ranked and selected by accuracy on standard benchmark conditions via averaged ranks. We show tha

Beyond Asking: A Pipeline for Personalized Game Generation that Reads Players from Behavior

arXiv:2608.16196v1 Announce Type: new Abstract: Personalized game generation requires inferring a player's abilities and behavioral style from how they play. Large language models have made this infer

Beyond Boundary Noise: Aggregated Aleatoric Uncertainty Fails to Capture Presence Ambiguity in 3D Lung Nodule Segmentation

arXiv:2608.14766v1 Announce Type: new Abstract: Uncertainty estimation is critical for the safe clinical deployment of deep learning in medical image segmentation, with aleatoric uncertainty theoretic

safetyarxiv-cs-cv

Beyond Direct Access: Resource Hijacking in LLM Agents

arXiv:2608.15108v1 Announce Type: cross Abstract: Large language model agents are increasingly connected to high-value resources such as computing infrastructure, credentials, usage budgets, identitie

local-aiarxiv-cs-ai

Beyond Uncertainty: Generalizable Failure Monitoring for Surgical Segmentation under Acquisition Degradation

arXiv:2608.16748v1 Announce Type: new Abstract: Surgical segmentation networks can fail silently under acquisition degradation: predicted masks may be wrong even when model confidence remains high. Ex

researcharxiv-cs-cv

Catching Hallucinated Citations in Video-LLM Question Answering: A Self-Verification Pipeline and Verifier Ablation Study

arXiv:2608.15574v1 Announce Type: cross Abstract: Video question answering systems built on vision-language models often produce timestamped claims with high confidence even when unsupported by the ci

local-aiarxiv-cs-ai

CBX-Bench: A Human-Aligned MLLM Council for Benchmarking Concept Bottleneck Model Explanations

arXiv:2608.15404v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) are designed to make visual classification interpretable by expressing predictions through human-understandable concept

CEDAR-GRPO: Process-Aware Reinforcement Learning for General Abductive Reasoning in LLMs

arXiv:2608.14791v1 Announce Type: new Abstract: Abductive reasoning, often characterized as inference to the best explanation, is central to explanation under uncertainty, from everyday sense-making a

Certifying Compressed Language Models: An Audit and a Statistical Toolkit

model-releasesarxiv-cs-lg

arXiv:2608.15046v1 Announce Type: new Abstract: A fraction of a point of benchmark accuracy is the usual evidence that a compressed model is equivalent to its original. That quantity is least informat

Coded Hankel Polynomial Chaos: Spectral Identification of Dominant Polynomial-Chaos Modes

arXiv:2608.16126v1 Announce Type: cross Abstract: Identification of dominant polynomial-chaos modes is usually formulated as a sparse-regression problem on a sampled multivariate polynomial dictionary

researcharxiv-cs-lg

Comprehension of Multilingual Expressions Referring to Target Objects in Visual Inputs

arXiv:2511.11427v2 Announce Type: replace Abstract: Referring Expression Comprehension (REC) requires models to localize objects in images based on different types of natural language descriptions. Ev

local-aiarxiv-cs-cv

Comprehensive Benchmarking of Deep Learning Architectures for Lung Cancer Histopathology

arXiv:2608.15915v1 Announce Type: cross Abstract: Lung cancer remains the leading cause of cancer-related mortality worldwide, while histopathological diagnosis is often affected by inter-observer var

Cross-Domain Industrial Fault Detection by Causal Mechanism Monitoring

arXiv:2608.14666v1 Announce Type: new Abstract: Unsupervised fault detection in industrial systems is dominated by reconstruction based methods that monitor individual sensor marginal distributions. T

safetyarxiv-cs-ai

Decentralized Federated Learning for Heterogeneous Multi-Task Semantic Communication

arXiv:2608.15256v1 Announce Type: new Abstract: Collaborative training in distributed semantic communication (DSC) networks typically relies on decentralized federated learning (DFL). However, pushing

Depth-guided Multi-view Exposure Bracketing for HDR Robot Vision

arXiv:2608.16014v1 Announce Type: new Abstract: Achieving reliable single-shot high dynamic range (HDR) imaging under extreme illumination conditions remains a long-standing challenge, yet no comprehe