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arXiv:2607.22035v1 Announce Type: new Abstract: Currently, most foundation models can reproduce or strongly depend on copyrighted training content, but output similarity alone is insufficient for infr

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Industrial Tokenization for LLM-Based Health Intelligence: A Federated Architecture for Industrial Evidence Integration

DGX agent

arXiv:2607.22153v1 Announce Type: cross Abstract: Industrial health management increasingly relies on heterogeneous information sources, including condition monitoring systems, supervisory control and

agentsarxiv-cs-lg

27 Jul 2026

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks

arXiv:2607.21941v1 Announce Type: new Abstract: Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and

Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos

arXiv:2607.21805v1 Announce Type: cross Abstract: We study the long-term behavior of the Multiplicative Weights Update (MWU) algorithm in game settings where learning dynamics frequently fail to conve

The Lift Spectrum: How Measurement-to-Space Adaptivity Shapes Robustness in Image-Free Single-Pixel Sensing

arXiv:2607.22077v1 Announce Type: cross Abstract: Single-pixel sensing encodes a scene as a short sequence of coded measurements, and image-free methods infer the task directly from that sequence. Rem

Time-Reversed Imaging: A Multimodal Benchmark and Framework for Reconstructing Past Human-Environment Interactions

arXiv:2607.22352v1 Announce Type: new Abstract: We introduce time-reversed imaging, a new paradigm that infers what just happened in a scene from fading multimodal traces. Instead of extrapolating or

A Comparative Evaluation of Embeddings and LLMs in a Greek Book Publisher Setting - The CUP Dataset

arXiv:2607.21274v1 Announce Type: cross Abstract: We present CUP, a Greek book retrieval benchmark consisting of 868 catalog records and 104 expert-annotated queries with graded relevance judgments. W

Compact Latent Coordination for Autonomous Vehicles at Unsignalized Intersections

arXiv:2607.21488v1 Announce Type: cross Abstract: Coordinating autonomous vehicles at unsignalized intersections remains a critical challenge for multi-agent reinforcement learning (MARL) systems, whi

Differentiable Logic Programming to Mitigate Reasoning Shortcuts in Neurosymbolic Systems

arXiv:2607.21185v1 Announce Type: new Abstract: Neurosymbolic (NeSy) systems integrate neural networks with logical reasoning to achieve both generalization and interpretability, but recent work has s

Fitting Generalized Power Diagrams to 3D Image Data: A Prerequisite for Virtual Materials Testing

arXiv:2507.14268v2 Announce Type: replace Abstract: This paper reviews algorithmic and modeling approaches for fitting generalized power diagrams to three-dimensional image data, a key step in virtual

Hilbert Operator for Progressive Encoding (HOPE): A Mathematical Framework for Deconstructing Learned Representations in Deep Networks

arXiv:2607.21366v1 Announce Type: cross Abstract: Deep neural networks encode complex representations, but deconstructing this internal knowledge remains a challenge. Given the link between learning a

Is Your Safe Controller Actually Safe? A Critical Review of CBF Tautologies and Hidden Assumptions

arXiv:2603.06954v2 Announce Type: replace Abstract: This tutorial provides a critical review of the practical application of Control Barrier Functions (CBFs) in robotic safety. While the theoretical f

safetyarxiv-cs-ro

Scalable Low-Cost Laboratory Automation: A Digital Twin-Integrated Robotic Platform for Autonomous Liquid Handling (RAINBOTTM)

arXiv:2607.20662v1 Announce Type: new Abstract: Laboratory automation accelerates discovery, yet its adoption is constrained by the high cost, proprietary design, and limited remote supervisability of

agentsarxiv-cs-ro

Tutorials

SCoPE: Shift-Aware Speaker-Conditioned Priors for Emotion Recognition in Conversations

arXiv:2607.20445v1 Announce Type: new Abstract: In conversations, human emotions are transient; however, they tend to persist across multiple utterances. For example, we rarely switch instantly betwee

tutorialsarxiv-cs-cl

When RLVR Shrinks the Reasoning Boundary: Diagnosing Pass@k Inversion

arXiv:2607.20543v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) can improve one-sample accuracy while making a model worse under repeated sampling. We study thi

Attributes Should Come from Images, Not Class Names: Distribution-Conditioned Attribute Selection for Vision-Language Models

arXiv:2607.18695v1 Announce Type: new Abstract: A popular route to interpretable zero-shot classification asks a large language model (LLM) to describe each class name and prompts CLIP with the result

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models

arXiv:2607.19618v1 Announce Type: cross Abstract: Genomic language models achieve strong performance across regulatory-genomics tasks, yet what these models internally represent remains opaque, and th

D2VBench: Benchmarking Large Language Models with Value Dilemmas in Daily Scenarios

model-releasesarxiv-cs-cl

arXiv:2607.19834v1 Announce Type: new Abstract: With the wide application of large language models (LLMs) in real-world scenarios, the value implication of their outputs is crucial. However, existing

Local Ai

Did Alice Do Wrong? Cross-Cultural Differences in Student Perceptions of Generative AI Use in University Computing Education

arXiv:2607.19699v1 Announce Type: cross Abstract: The rise of generative AI (GenAI) in higher education has prompted urgent debates surrounding academic integrity and ethical use. This study examines

local-aiarxiv-cs-ai

HOMIE: Human-object Centric Video Personalization via Multimodal Intelligent Enhancement

arXiv:2607.18217v2 Announce Type: replace Abstract: Human-object centric video personalization (HOCVP) is a core task within subject-driven video generation. However, existing methods suffer from two

safetyarxiv-cs-cv

Learning About Learning: A Path from Spin Glasses to Artificial Intelligence

arXiv:2601.07635v3 Announce Type: replace-cross Abstract: The Hopfield model, originally inspired by spin glasses, occupies a central place at the intersection of statistical mechanics, neural network

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review

arXiv:2507.10142v2 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) has achieved strong performance in simulated benchmarks, yet real deployments often violate the assumption

Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentation

arXiv:2602.07643v2 Announce Type: replace Abstract: Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse

Disentangling Knowledge States with Ability and Proficiency Modeling for Knowledge Tracing

arXiv:2607.13103v1 Announce Type: cross Abstract: Knowledge tracing (KT) aims to predict students' future performance by modeling their evolving knowledge states from historical interactions. Existing

Fine-grained CLIP fine-tuning with self-annotated region alignment

arXiv:2607.13661v1 Announce Type: new Abstract: Contrastive Language-Image Pre-training (CLIP) has been shown to have limitations in its fine-grained dense feature representation, due to its pre-train

Probabilistic Extension of Neuro-Symbolic AGI Robots based on Belnap's Typed Intensional FOL

arXiv:2607.13073v1 Announce Type: new Abstract: Neuro-symbolic AI based on IFOL_B is a way to combine neural learning and symbolic reasoning to overcome limitations of purely neural systems (like lack

Self-Improving is Often Sudden: Enlightenment-style Finetuning for Large-Scale Models

arXiv:2607.13395v1 Announce Type: new Abstract: The pursuit of autonomously self-improving models has attracted growing interest in the era of large-scale foundation models. Drawing inspiration from t

Video to All-in-focus Image Reconstruction Algorithm for Automated Microscopic Urinalysis

arXiv:2607.13601v1 Announce Type: cross Abstract: Microscopic urinalysis is a routine diagnostic test at hospitals. Recent studies have demonstrated the effectiveness of deep learning methods to autom

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

arXiv:2409.10094v3 Announce Type: replace Abstract: Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e

Bulkhead: Automated Semantic Detection and Remediation of Container Escape Vulnerabilities

arXiv:2607.12723v1 Announce Type: cross Abstract: Filesystem isolation in container ecosystems is often weakened by cross-boundary path misresolution, causing path traversal (PaTra) vulnerabilities. T

Calibrated Selective Prediction Using Deep Ensembles for ROI-Based Thyroid Nodule Ultrasound Classification Under Dataset Shift: A Retrospective Evaluation

arXiv:2607.12075v1 Announce Type: cross Abstract: Background: Deep learning models can classify thyroid nodules on ultrasound, but reliable clinical decision support also requires calibrated probabili

HPC-Enabled Video-based Coastal Wave Parameter Estimation Using V-JEPA and Deep Spatiotemporal Learning

arXiv:2607.11998v1 Announce Type: cross Abstract: High deployment cost, poor spatial coverage and susceptibility to storm conditions are all challenges faced by traditional in-situ methods. This paper

Mitigating The Effect of Class Imbalance in Data with Hierarchical and Dependable Structure

arXiv:2607.11994v1 Announce Type: cross Abstract: Classifying cybersecurity vulnerabilities using the Common Weakness Enumeration (CWE) taxonomy is challenging due to extreme class imbalance and stron

RippleBench: Capturing Ripple Effects Using Existing Knowledge Repositories

arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat

Silent Alarm: A J-Space Protocol for Comparing Danger Recognition Across Models and Quantization Levels

arXiv:2607.12792v1 Announce Type: cross Abstract: Jailbreak-robustness research typically evaluates safety through generated responses using an LLM-as-judge approach. Such evaluations, however, are se

Solution of the Hempel's statistical ambiguity problem and Causal AI

arXiv:2607.12826v1 Announce Type: new Abstract: This paper addresses Carl Hempel's longstanding problem of statistical ambiguity in inductive-statistical inference, in which contradictory predictions

The Sound of Absence: Audio-Language Embedding Models Struggle with Negation

arXiv:2607.12290v1 Announce Type: cross Abstract: Audio-language embedding models such as CLAP are widely evaluated on matching present sound events, but rarely on negation. We show this affirmation-o

ArtMine: Discovering and Formalizing Artistic Processes

arXiv:2607.08331v1 Announce Type: cross Abstract: Understanding how artworks are created requires reasoning about the iterative decisions, material operations, and contextual influences that shape art

ASMR: Agentic Schema Generation for Ship Maintenance Report Writing

arXiv:2607.08177v1 Announce Type: new Abstract: In this paper, we study the automatic schema generation problem: given a collection of historical ship maintenance and operational reports across multip

Drift-Aware Temporal Graph Rewiring (DATGR) for Adaptive Semantic Modeling in Biomedical Text

arXiv:2607.08490v1 Announce Type: new Abstract: Biomedical language evolves rapidly as new discoveries emerge, causing traditional text models to lose semantic fidelity over time. Static embeddings an

Leveraging Color Naming for Image Enhancement

arXiv:2607.08185v1 Announce Type: cross Abstract: Enhancing images to make them visually appealing is a persistent challenge in computer vision. Many deep-learning methods train models on paired datas

LightCrafter: PBR-Conditioned Video Diffusion Refinement for Controllable and Consistent Relighting

arXiv:2607.08016v1 Announce Type: new Abstract: Video relighting requires balancing long-form temporal consistency with a physically grounded understanding of light transport, which depends on accurat

Persistent Multiscale Density-based Clustering

model-releasesarxiv-cs-lg

arXiv:2512.16558v3 Announce Type: replace Abstract: Clustering is a cornerstone of modern data analysis. Detecting clusters in exploratory data analyses (EDA) requires algorithms that make few assumpt

Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles

arXiv:2607.08373v1 Announce Type: cross Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to detect deviations from norm

SPHINX: First Explain, Then Explore

arXiv:2606.17482v2 Announce Type: replace Abstract: Generating adversarial driving scenarios is critical for evaluating and improving autonomous vehicle decision-making systems in simulation. Recent a

safetyarxiv-cs-cv

Statistical inverse learning problems with random observations

arXiv:2312.15341v1 Announce Type: cross Abstract: We provide an overview of recent progress in statistical inverse problems with random experimental design, covering both linear and nonlinear inverse

Validating LLMs in social science: Epistemic threats and emerging norms

arXiv:2607.07915v1 Announce Type: cross Abstract: Large language models (LLMs) are reshaping social science methodology. Researchers increasingly prompt language models to generate quantitative measur

safetyarxiv-cs-cl