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AutoEval Done Right: Using Synthetic Data for Model Evaluation

arXiv:2403.07008v3 Announce Type: replace-cross Abstract: The evaluation of machine learning models using human-labeled validation data can be expensive and time-consuming. AI-labeled synthetic data c

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AutoFFS: Adversarial Deformations for Facial Feminization Surgery Planning

DGX agent

arXiv:2603.02288v2 Announce Type: replace Abstract: Facial feminization surgery (FFS) is a key component of gender affirmation for transgender and gender diverse patients, aiming to reshape craniofaci

safetyarxiv-cs-cv

2 Jun 2026

Applications

AutoForest: Automatically Generating Forest Plots from Biomedical Studies with End-to-End Evidence Extraction and Synthesis

arXiv:2606.02403v1 Announce Type: cross Abstract: Systematic reviews rely on forest plots to synthesise quantitative evidence across biomedical studies, but generating them remains a fragmented and la

applicationsarxiv-cs-ai

Local Ai

AutoIQ: An Ensemble Framework for Automatic Assessment of Geometric Distortion in Prostate Diffusion-Weighted Imaging

arXiv:2606.00393v1 Announce Type: cross Abstract: Geometric distortion in prostate diffusion-weighted imaging (DWI) can impair lesion localization and reduce the reliability of MRI-based clinical asse

local-aiarxiv-cs-cv

Agents

Automated Conjecture Resolution with Formal Verification

arXiv:2604.03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementar

agentsarxiv-cs-ai

Automated Erythrocyte Detection and Tracking for Retinal Blood Flow Quantification in Erythrocyte-Mediated Angiography

arXiv:2606.01006v1 Announce Type: new Abstract: Capillary-level retinal blood flow (RBF) has strong potential as a biomarker for various ocular diseases. However, modalities for measuring capillary-le

researcharxiv-cs-cv

Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French

arXiv:2606.02009v1 Announce Type: new Abstract: In Automated Essay Scoring (AES), benchmarking practices have fostered minimalist evaluation practices, in contrast with the broader-view recommendation

safetyarxiv-cs-cl

Automatically Differentiable Nonlinear Tensor Networks (ADNTNs) for Exponential Compression of Deep Neural Networks

arXiv:2606.00130v1 Announce Type: cross Abstract: We study Automatically Differentiable Nonlinear Tensor Networks (ADNTNs), a family of structured weight generators whose compact core tensors are trai

AutoMedBench: Towards Medical AutoResearch with Agentic AI Models

arXiv:2606.01961v1 Announce Type: new Abstract: Autonomous agents are increasingly expected to support end-to-end medical-AI research workflows, moving beyond isolated prediction tasks or short-form c

Autopilot-Preserving Residual Q-Learning with HJB-Inspired Finite-Action Risk Filtering for Fixed-Wing UAV Command Supervision

arXiv:2606.01397v1 Announce Type: cross Abstract: A fixed-wing UAV must hold airspeed, altitude, and heading references under wind, gusts, and turbulence, channels coupled so that correcting one can d

Avatar Forcing: Real-Time Interactive Head Avatar Generation for Natural Conversation

arXiv:2601.00664v2 Announce Type: replace-cross Abstract: Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models

AXIOM: A Trust-First Neuro-Symbolic Execution Architecture for Verifiable Mathematical Reasoning

arXiv:2606.00671v1 Announce Type: new Abstract: We present AXIOM, a trust-first neuro-symbolic execution architecture for natural-language mathematical reasoning. In AXIOM, the language model function

Back to the Feature: Explaining Video Classifiers with Video Counterfactual Explanations

arXiv:2511.20295v2 Announce Type: replace Abstract: Counterfactual explanations (CFEs) are minimal and semantically meaningful modifications of the input of a model that alter the model predictions. T

researcharxiv-cs-cv

BADGER: Bridging Agentic and Deterministic Evaluation for Generative Enterprise Reasoning

arXiv:2606.02109v1 Announce Type: new Abstract: Enterprise AI systems that translate natural language into SQL queries and orchestrate multi-step agentic reasoning pipelines require evaluation approac

Agents

BAGEN: Are LLM Agents Budget-Aware?

arXiv:2606.00198v1 Announce Type: cross Abstract: While agents are increasingly spending more resources, today agent cost is mostly measured only after execution. A Budget-Aware Agent (BAGEN) should t

agentsarxiv-cs-ai

Balancing Accuracy and Efficiency: Adaptive Dynamics Orchestration for Model Predictive Control

arXiv:2606.00085v1 Announce Type: new Abstract: Model Predictive Control (MPC) for autonomous navigation faces a fundamental trade-off between model accuracy and real-time efficiency. High-fidelity dy

safetyarxiv-cs-ro

Tutorials

Balancing Learning Rates Across Layers: Exact Two-Step Dynamics and Optimal Scaling in Linear Neural Networks

arXiv:2606.00340v1 Announce Type: new Abstract: We study optimal learning-rate selection in two-layer and three-layer linear neural networks trained to learn linear target functions. In particular, we

tutorialsarxiv-cs-lg

Bandit Simulation for Average Reward Inference

arXiv:2606.00913v1 Announce Type: cross Abstract: Multi-arm bandit algorithms are increasingly used in online platforms, clinical trials, and social science experiments, but valid statistical inferenc

safetyarxiv-cs-lg

Baton: Explicit Semantic Blueprints for Joint Video-Audio Generation

arXiv:2605.25195v2 Announce Type: replace Abstract: Current open-source diffusion models struggle to generate stable and synchronized audio-visual content, particularly in scenarios demanding complex

safetyarxiv-cs-cv

Bayesian Inference of Nonlinear Malaria Dynamics in Ghana via an Ensemble Markov Chain Monte Carlo Sampler

arXiv:2606.00783v1 Announce Type: cross Abstract: Reliable quantification of malaria dynamics in sub-Saharan Africa is hindered by short, noisy, and spatially heterogeneous surveillance records. In Gh

Applications

Bayesian meta-learning for modeling Alzheimer's disease progression

arXiv:2606.02228v1 Announce Type: cross Abstract: Predicting whether an individual with Alzheimer's disease will experience mild or severe disease progression is essential for personalized treatment.

applicationsarxiv-cs-cv

Bayesian Spectral Emotion Transition Discovery from Multi-Annotator Disagreement

arXiv:2606.01906v1 Announce Type: new Abstract: Emotions evolve through the dynamics of conversation, and understanding their transition structure is foundational to applications ranging from mental-h

Before and After Temperature: A Distributional View of Creative LLM Generation

arXiv:2606.01451v1 Announce Type: new Abstract: Reference-free evaluation of large language model (LLM) creativity relies on perplexity, entropy, and top-1 margin. We show that a much stronger signal

Tutorials

Before the Model Learns the Bug:Fuzzing RLVR Verifiers

arXiv:2606.01066v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) replaces human preference labels with executable reward functions such as math answer checkers, JS

tutorialsarxiv-cs-ai

Behavior Cloning of MPC for 3-DOF Robotic Manipulators

arXiv:2606.00383v1 Announce Type: cross Abstract: While Model Predictive Control (MPC) provides strong stability and robustness, it imposes a significant computational burden on real-time systems. Thi

safetyarxiv-cs-lg

Behavior-Invariant Task Representation Learning with Transformer-based World Models for Offline Meta-Reinforcement Learning

arXiv:2606.00780v1 Announce Type: cross Abstract: Offline meta-reinforcement learning leverages static datasets to enable agents to generalize to unseen environments by combining offline efficiency wi

Agents

Belief Consistency Between Foundation-Model Evidence and Geometric Perception in Persistent Robotic Maps

arXiv:2606.00318v1 Announce Type: cross Abstract: Persistent maps used by autonomous robots increasingly fuse a geometric perception stack whose assertions are well-characterized with a foundation-mod

agentsarxiv-cs-cv

BenchEvolver: Frontier Task Synthesis via Solution-Centric Evolution

arXiv:2606.01286v1 Announce Type: cross Abstract: The rapid progress of frontier large language models has led to widespread benchmark saturation, limiting the ability of existing datasets to differen

Benchmark Dataset for Catalysis on 2D MXenes

arXiv:2606.00794v1 Announce Type: cross Abstract: Merging first-principles calculations with machine learning (ML), we aim to accelerate the exploration of catalytic behaviour in novel materials. We f

Benchmarking Large Language Models for Cryptanalysis and Side-Channel Vulnerabilities

arXiv:2505.24621v3 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have transformed natural language understanding and generation, leading to extensive benchmarkin

Benchmarking LLM-as-a-Judge for Long-Form Output Evaluation

arXiv:2606.01629v1 Announce Type: new Abstract: As large language models (LLMs) are increasingly used for long-form generation, reliably evaluating long-form outputs has become a critical challenge. L

Benchmarking Local LLMs for Natural-Language-to-SQL Querying in Biopharmaceutical Manufacturing: An Empirical Benchmark on Consumer-Grade Hardware

arXiv:2606.01338v1 Announce Type: new Abstract: Biopharmaceutical manufacturing organizations operate under regulatory frameworks such as FDA guidance, EU Good Manufacturing Practice (GMP), and the EU

Benchmarking Multimodal LLMs on Code Generation for Complex Interactive Webpages

arXiv:2606.00154v1 Announce Type: cross Abstract: Recent advancements in multimodal large language models (MLLMs) have achieved remarkable progress in multimodal reasoning and code generation, catalyz

Benchmarking Recursive-Collapse Warning Claims Under Matched False-Positive Control

arXiv:2606.00329v1 Announce Type: cross Abstract: Recursive systems can enter collapse-like regimes -- self-reinforcing amplification, persistent recursion, and narrowing diversity that mask accelerat

Benchmarking Security Risk Detection and Verification in Open Agentic Skill Ecosystems

arXiv:2606.00925v1 Announce Type: cross Abstract: Open agent platforms allow community contributors to publish reusable skills that agents can invoke at runtime. This extensibility also creates a supp

Benchmarking Waitlist Mortality Prediction in Heart Transplantation Through Time-to-Event Modeling using New Longitudinal UNOS Dataset

arXiv:2507.07339v2 Announce Type: replace-cross Abstract: Decisions about managing patients on the heart transplant waitlist are currently made by committees of doctors who consider multiple factors,

Benchmarks for Vision-Language Models in Urban Perception Should Be Reliability-Aware and Negotiated

arXiv:2606.00871v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used to generate structured descriptions of street-level imagery for tasks such as streetscape auditing

BERT4beam: Large AI Model Enabled Generalized Beamforming Optimization

arXiv:2509.11056v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is anticipated to emerge as a pivotal enabler for the forthcoming sixth-generation (6G) wireless communication sy

researcharxiv-cs-lg

Better Source, Better Flow: Learning Condition-Dependent Source Distribution for Flow Matching

arXiv:2602.05951v2 Announce Type: replace-cross Abstract: Flow matching has recently emerged as a promising alternative to diffusion-based generative models, particularly for text-to-image generation.

Better with Experience: Self-Evolving LLM Agents for Evidence-Grounded Health Community Notes

arXiv:2606.02215v1 Announce Type: new Abstract: Large Language Model (LLM)-augmented Community Notes offer a scalable path for timely, evidence-grounded correction of health misinformation on social p

BEVIO: Efficient Bird's-Eye-View based Sparse-Update Visual-Inertial Odometry for Lunar Day-Night Navigation

arXiv:2606.00709v1 Announce Type: new Abstract: Visual-Inertial Odometry (VIO) provides smooth, high-rate state estimates and has been widely used for robotic navigation in both terrestrial and planet

researcharxiv-cs-ro

Beware of the Batch Size: Hyperparameter Bias in Evaluating LoRA

arXiv:2602.09492v2 Announce Type: replace-cross Abstract: Low-rank adaptation (LoRA) is a standard approach for fine-tuning large language models, yet its many variants report conflicting empirical ga

Beyond Access: Guided LLM Scaffolding for Independent Learning in Undergraduate Statistics

arXiv:2606.01375v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly entering students' learning practices, but their educational value depends on whether they support reaso

Beyond Augmentation: Score-Guided Pathological Prior for EEG-based Depression Detection

arXiv:2606.00180v1 Announce Type: cross Abstract: Deep learning-based Major Depressive Disorder (MDD) detection using Electroencephalography (EEG) is fundamentally constrained by the 'small-sample dil

Beyond Categories of Caste: Examining Caste Bias and Morality in Text-to-Image AI Models

arXiv:2606.00039v1 Announce Type: cross Abstract: Text-to-Image (T2I) models have shown promising utility across various domains. However, such models are also amplifying harmful societal biases in th

Beyond Discreteness: Sample Complexity Analysis of Straight-Through Estimator for 1-bit Quantization

arXiv:2505.18113v2 Announce Type: replace Abstract: Training quantized neural networks requires addressing the non-differentiable and discrete nature of the underlying optimization problem. To tackle

researcharxiv-cs-lg

Beyond ell_2-norm and ell_infty-norm: A Curvature-Inspired ell_p-Norm Scheme for Deep Neural Networks

arXiv:2606.02078v1 Announce Type: new Abstract: The existing optimizers for deep neural networks (DNNs) typically rely on either the ell_2 norm or the ell_infty norm, resulting in optimizers that do n

Beyond End-to-End Video Models: An LLM-Based Multi-Agent System for Educational Video Generation

arXiv:2602.11790v2 Announce Type: replace Abstract: Although recent end-to-end video generation models demonstrate impressive performance in visually oriented content creation, they remain limited in