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What Do Language Priors Contribute to Darcy-Flow Inversion? A Mechanistic Audit

arXiv:2606.24967v1 Announce Type: new Abstract: In ill-posed inverse problems, the recovered solution depends as much on the prior as on the data, yet much of the engineering knowledge that could serv

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What Does a Pathological Speech Assessment Model Know about Acoustic Features? A Case Study on Oral and Oropharyngeal Cancer Patients

DGX agent

arXiv:2606.24949v1 Announce Type: cross Abstract: This work investigates the interpretability of a Wav2Vec 2.0based speech intelligibility assessment model for oral and oropharyngeal cancer patients t

applicationsarxiv-cs-ai

25 Jun 2026

What Does It Mean to Break a Distillation Defense?

arXiv:2606.25059v1 Announce Type: cross Abstract: Black-box LLMs (accessible only via API) are vulnerable to distillation attacks, in which an attacker queries the model and trains a student on its ou

safetyarxiv-cs-ai

What Does the Brain See? Multiview Neural Representations to Demystify the Brain-Visual Alignment

arXiv:2606.25718v1 Announce Type: new Abstract: Zero-shot visual decoding from electroencephalography (EEG) aims to infer visual semantics from non-invasive neural recordings, but remains challenging

What Intermediate Layers Know: Detecting Jailbreaks from Entropy Dynamics

model-releasesarxiv-cs-cl

arXiv:2606.25182v1 Announce Type: new Abstract: Jailbreak attacks reveal a persistent weakness in aligned Large Language Models: carefully crafted prompts can elicit policy-violating responses despite

Tutorials

What's in an Earth Embedding? An Explainability Analysis of Location Encoders

arXiv:2606.24997v1 Announce Type: new Abstract: Geographic implicit neural representations (INRs) learn to map any coordinate on Earth to a location embedding, implicitly encoding geospatial data into

tutorialsarxiv-cs-lg

When Certainty Is an Artifact: Keyword Lexicon Blindness and the (Mis)Measurement of Rhetorical Stance

arXiv:2606.26062v1 Announce Type: new Abstract: Can a statistically significant, large-effect-size finding in computational social science be entirely an artifact of the measurement instrument? We pre

researcharxiv-cs-cl

When Do Conservation Laws Survive Learned Representations? Certified Horizons for Latent World Models

arXiv:2606.24945v1 Announce Type: new Abstract: We ask a representation-learning question about physical world models: when does a conservation law remain certifiable after a model learns a latent rep

When Does Synthetic Data Augmentation Improve Score-Based Imbalanced Classification?

arXiv:2606.26053v1 Announce Type: cross Abstract: Synthetic data augmentation is widely used to mitigate class imbalance, but its theoretical effects on score-based classification remain poorly unders

When Multi-Sensor Fusion Fails to Generalize: Cattle Posture Classification Under Animal-Level and Temporal Distribution Shift

arXiv:2606.24986v1 Announce Type: new Abstract: Automated cattle posture-classification systems frequently report near-perfect accuracy, yet their robustness under realistic deployment conditions rema

Why Do Accumulated Transformations Extrapolate?

arXiv:2606.24975v1 Announce Type: cross Abstract: PaTH Attention showed that replacing RoPE's position-indexed rotations with accumulated data-dependent Householder reflections yields strong length ex

researcharxiv-cs-cl

Why Multi-Step Tool-Use Reinforcement Learning Collapses and How Supervisory Signals Fix It

arXiv:2606.26027v1 Announce Type: new Abstract: Tool use enables large language models (LLMs) to perform complex tasks, and recent agentic reinforcement learning (RL) methods show promise for enhancin

safetyarxiv-cs-cl

Why Pool When You Can Flow? Active Learning with GFlowNets

arXiv:2509.00704v2 Announce Type: replace Abstract: The scalability of pool-based active learning is limited by the computational cost of evaluating large unlabeled datasets, a challenge that is parti

researcharxiv-cs-lg

WinDOM: Self-Family Distillation for Small-Model GUI Grounding

arXiv:2606.25964v1 Announce Type: cross Abstract: Small (sim2B) GUI-grounding agents are attractive for on-device deployment, accessibility tooling, and low-cost iteration, but at this scale they face

local-aiarxiv-cs-lg

WOLF-VLA: Whole-Body Humanoid Optimal Locomotion Framework for Vision-Language-Action Learning

model-releasesarxiv-cs-ro

arXiv:2606.25591v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, con

Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety

arXiv:2606.25034v1 Announce Type: new Abstract: General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversaria

safetyarxiv-cs-cv

3D Masked Autoencoders are Robust Learners of Volumetric and Multimodal Cellular Representations for Microscopy

arXiv:2606.23964v1 Announce Type: cross Abstract: Self-supervised learning in fluorescence microscopy often relies on 2D projections, despite the inherently three-dimensional nature of cells. We prese

local-aiarxiv-cs-cv

3DCarGen: Scalable 3D Car Generation via 3D-consistent Multi-view Synthesis

arXiv:2606.24257v1 Announce Type: new Abstract: High-quality 3D vehicle assets are essential for autonomous driving simulation. Although multi-view diffusion-based paradigms enable controllable single

A Benchmark for Hallucination Detection in VLMs for Gastrointestinal Endoscopy

arXiv:2606.24115v1 Announce Type: cross Abstract: Vision-language models (VLMs) are prone to hallucination, which remains a major barrier to their safe deployment in clinical practice. To date, most h

A Benchmark of State-Space Models vs. Transformers and BiLSTM-based Models for Historical Newspaper OCR

arXiv:2604.00725v2 Announce Type: replace Abstract: End-to-end OCR for historical newspapers remains challenging, as models must handle long text sequences, degraded print quality, and complex layouts

A Comparative Study of Bayesian Contextual Bandits for Real-Time Warehouse Sorter Optimization

arXiv:2606.23977v1 Announce Type: new Abstract: Efficient sorter diversion control of automated material handling systems (MHS) is critical for optimizing operational efficiency in large-scale warehou

Applications

A Differentially Private Weighted Empirical Risk Minimization Procedure and its Application to Outcome Weighted Learning

arXiv:2307.13127v3 Announce Type: replace-cross Abstract: Data used to train predictive models via empirical risk minimization (ERM) often contain sensitive personal information. While differential pr

applicationsarxiv-cs-lg

A Dual Edge Spatial Jacobian Image Graph for Interpretable Diabetic Retinopathy Grading

arXiv:2606.24168v1 Announce Type: cross Abstract: Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requ

Applications

A Fair Evaluation of Graph Foundation Models for Node Property Prediction

arXiv:2606.24509v1 Announce Type: cross Abstract: Due to the wide use of graph-structured data in different fields of industry and science, the development of Graph Foundation Models (GFMs) has recent

applicationsarxiv-cs-ai

A Fast and Effective Method for Euclidean Anticlustering: The Assignment-Based-Anticlustering Algorithm

arXiv:2601.06351v2 Announce Type: replace Abstract: Anticlustering is an NP-hard combinatorial optimization problem that consists of partitioning a set of objects into equal-sized groups called anticl

researcharxiv-cs-lg

A Geometry-Informed Computer Vision Method for Detecting and Examining Overtaking Vehicles From A Bicycle

arXiv:2606.23699v1 Announce Type: new Abstract: Instrumented bicycle studies have produced direct field evidence on vehicle passing behavior, but extracting overtaking events from continuous rear-faci

safetyarxiv-cs-cv

A global log for medical AI

arXiv:2510.04033v2 Announce Type: replace Abstract: Modern computer systems rely on syslog, a universal protocol that records critical events across heterogeneous infrastructure. Medicine's rapidly gr

safetyarxiv-cs-ai

A Hybrid Quantum-Classical Approach for Melt Pool Prediction in Laser Powder Bed Fusion

arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools fro

A novel Framework for Open-Vocabulary Multi-Object Recognition using CLIP

arXiv:2603.05962v2 Announce Type: replace Abstract: To address the limitations of existing open-vocabulary object recognition methods, including high system complexity, substantial training costs, and

A Pairwise Human-Human Interaction Detection and Recognition Framework for Mobile Service Robots

model-releasesarxiv-cs-ro

arXiv:2602.22346v2 Announce Type: replace Abstract: Autonomous mobile service robots, such as lawnmowers or cleaning robots, operating in human-populated environments need to reason about human-human

A Paninian Foundation for Indic Language Processing

arXiv:2606.24172v1 Announce Type: cross Abstract: More than a billion people communicate in Indic languages, yet the natural language processing infrastructure serving them remains fragmented and unde

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling

arXiv:2606.24696v1 Announce Type: cross Abstract: Physics-informed surrogate models can accelerate computational fluid dynamics simulations. However, many existing methods reproduce global flow patter

Tutorials

A Private Approximation of the 2nd-Moment Matrix of Any Subsamplable Input

arXiv:2505.14251v2 Announce Type: replace Abstract: We study the problem of differentially private second moment estimation and present a new algorithm that achieve strong privacy-utility trade-offs e

tutorialsarxiv-cs-lg

A Robust Model-Based Approach for Continuous-Time Policy Evaluation with Unknown Levy Process Dynamics

arXiv:2504.01482v3 Announce Type: replace-cross Abstract: This paper develops a model-based framework for continuous-time policy evaluation (CTPE) in reinforcement learning, incorporating both Brownia

A specialized reasoning large language model for accelerating rare disease diagnosis: a randomized AI physician assistance trial

arXiv:2606.24510v1 Announce Type: new Abstract: Rare diseases affect millions of individuals worldwide, yet timely diagnosis remains a major public health challenge due to scarcity of specialized clin

A Survey on Federated Causal Discovery and Inference

arXiv:2606.23741v1 Announce Type: cross Abstract: Causal reasoning, which encompasses the discovery of causal structures and the inference of causal effects, is fundamental to data-driven decision mak

researcharxiv-cs-ai

A Synthetic Reliability-Aware PINN Benchmark for Offshore Wind Turbine Support-Structure Monitoring with Bayesian Inverse Identification

model-releasesarxiv-cs-cl

arXiv:2606.24176v1 Announce Type: new Abstract: Reliable structural health monitoring (SHM) of offshore wind turbine (OWT) support structures requires fast state estimation from sparse measurements. R

A Time-Reparameterized Cumulative Intensity Extrapolation Sampler for Discrete Flow Matching

arXiv:2606.24140v1 Announce Type: new Abstract: Discrete flow matching (DFM) provides a principled framework for generative modeling on discrete state spaces via continuous-time Markov chain dynamics.

local-aiarxiv-cs-lg

A Unified Framework for Runtime Verification and Model-Based Diagnosis in LOLA

arXiv:2606.23720v1 Announce Type: cross Abstract: We present an integrated framework that unifies runtime verification and model-based diagnosis within the stream specification language LOLA. By encod

researcharxiv-cs-ai

ABACUS: Adapting Unified Foundation Model for Bridging Image Count Understanding and Generation

arXiv:2606.23835v1 Announce Type: new Abstract: ABACUS is a unified vision-language model that handles object counting, crowd counting, referring-expression counting, and count-faithful image generati

Abstractions of Queries in Ontology-Based Data Access

arXiv:2606.24618v1 Announce Type: new Abstract: In ontology-based data access (OBDA), multiple data sources are integrated via mappings to an ontology. We consider an OBDA setting based on existential

safetyarxiv-cs-ai

Accelerated Stochastic Min-Max Optimization Based on Bias-corrected Momentum

arXiv:2406.13041v3 Announce Type: replace Abstract: Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least

Hardware

Accelerating Disaggregated RL for Visual Generative LLMs with Diffusion-Based Parallelism and Trainer-Assisted Generation

arXiv:2606.24369v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregr

hardwarearxiv-cs-ai

Accelerating Multimodal Large Language Models with Prior-Corrected Token Reduction

arXiv:2606.24156v1 Announce Type: new Abstract: Visual token reduction has emerged as an effective strategy for accelerating Multimodal Large Language Models (MLLMs). Many existing methods prune token

Accuracy and Satisfaction in Multi-Turn LLM Dialogues for NFR Assessment

arXiv:2606.24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional co

local-aiarxiv-cs-ai

Acquisition state behaves as a structured, measurable variable governing lung-nodule AI: kernel-driven measurement instability and noise-driven detection fragility, invisible to DICOM metadata

arXiv:2606.12824v2 Announce Type: replace-cross Abstract: AI governance for medical imaging is formalizing: the 2026 ACR-SIIM Practice Parameter recommends local acceptance testing and ongoing drift m

ActiveScope: Actively Seeking and Correcting Perception for MLLMs

arXiv:2606.24292v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive vision-language understanding, yet still struggle with fine-grained perception in

local-aiarxiv-cs-cv

Adaptive Hebbian Memory Routing in Vision Transformers for Few-Shot Learning

arXiv:2606.24756v1 Announce Type: new Abstract: Few-shot image recognition requires models to adapt to new classes from a small labeled support set. Hebbian fast-weight memory can provide temporary as