Search: “concepts”

A Computational Tropical Geometry Framework for Neural Networks

arXiv:2405.20174v3 Announce Type: replace Abstract: We propose a computational tropical geometry framework for the symbolic analysis of neural networks with tropical activations. The number of linear

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

AI Smart Glasses for Wearable Intelligence: From Egocentric Sensing to Agentic Personalization

DGX agent

arXiv:2609.19793v1 Announce Type: new Abstract: Recent advances in artificial intelligence (AI) are reshaping smart glasses from egocentric capture and display devices into platforms for wearable inte

agentsarxiv-cs-cv

18 Sept 2026

Applications

Detecting Deceptive Recruitment: A Signal-theoretic Machine Learning Framework for Early Identification of Labour Exploitation

arXiv:2609.20336v1 Announce Type: cross Abstract: Deceptive online job advertisements have emerged as a primary pathway into forced labour, yet systematic detection methods remain underdeveloped due t

applicationsarxiv-cs-lg

Digital Twins for Opinion Dynamics: A Generative LLM Framework for Social Networks

arXiv:2609.19913v1 Announce Type: new Abstract: The study of opinion dynamics in social networks is one of the key challenges in computational social science with direct relevance to understanding pol

Finding Common Ground: Graded Communal Knowledge in Bluesky Starter Packs

arXiv:2609.19549v1 Announce Type: cross Abstract: Communication is made possible by common ground---the unspoken knowledge that people share and presuppose of one another, whether that be online or of

researcharxiv-cs-cl

Inference-Engine Fingerprinting Attacks are Practical: Exploring Model-Driven Environmental Discovery, Exploitation, and Escape

arXiv:2609.20614v1 Announce Type: cross Abstract: Frontier AI models are rapidly gaining the ability to exploit vulnerabilities in complex pieces of software. The risk is not theoretical, as evidenced

Local Sparsity Enables Unsupervised LLM Safety Detection

arXiv:2609.20129v1 Announce Type: cross Abstract: Deployment-time safety methods for large language models (LLMs) are predominantly supervised and assume access to unsafe training data. Nevertheless,

Mechanical Precision Weeding with a Quadruped Robot

arXiv:2609.20048v1 Announce Type: new Abstract: Herbicide-based weed control is increasingly unsustainable due to rising weed resistance and the adverse environmental impacts of chemical use. While me

agentsarxiv-cs-ro

Open ultrasound foundation model for robust segmentation and clinical measurement across heterogeneous settings

arXiv:2609.19230v1 Announce Type: new Abstract: Ultrasound is the most widely deployed imaging modality worldwide, yet clinical AI remains fragmented into narrow single-task models that fail when devi

researcharxiv-cs-cv

Redact or Keep? A Fully Local AI Cascade for Educational Dialogue De-Identification

arXiv:2606.18372v2 Announce Type: replace-cross Abstract: Educational dialogue is a valuable but sensitive resource for research: the same transcripts that capture authentic learning often capture per

Subliminal Prompting Beyond Static Geometry: Causal Depth and Multi-Token Confounds

model-releasesarxiv-cs-cl

arXiv:2609.19149v1 Announce Type: new Abstract: Subliminal learning shows that language models can transmit a hidden trait through outputs that appear unrelated to it. One proposed explanation, token

Tele-Traversability: Rethinking Traversability for Teleoperated Ground Robots in Terrain Navigation

arXiv:2609.19577v1 Announce Type: new Abstract: Teleoperation, a human-in-the-loop control scheme, allows a human operator to remotely command and guide a mobile robot to navigate in off-road environm

safetyarxiv-cs-ro

The syntax and semantics of goals

arXiv:2609.19448v1 Announce Type: new Abstract: In both cognitive science and computer science, goals are conceptualized as cognitive states that flexibly combine with world knowledge to organize and

Approximation of the Basset force in the Maxey-Riley-Gatignol equations via universal differential equations

arXiv:2604.08194v2 Announce Type: replace Abstract: The Maxey-Riley-Gatignol equations (MaRGE) model the motion of spherical inertial particles in a fluid. They contain the Basset force, an integral t

Benchmarking Large Language Models for Biomedical Relation Extraction

model-releasesarxiv-cs-cl

arXiv:2609.19071v1 Announce Type: new Abstract: Extracting SNP-phenotype associations from biomedical literature is vital but challenging. We benchmarked diverse NLP models, including MLMs, hybrid arc

Curvature-aware Expected Free Energy as an Acquisition Function for Bayesian Optimization

arXiv:2603.26339v2 Announce Type: replace Abstract: We propose an Expected Free Energy-based acquisition function for Bayesian optimization to solve the joint learning and optimization problem, i.e.,

Disentangling Long-Term Memory via Latent Neuro-Symbolic Reasoning

arXiv:2609.18461v1 Announce Type: new Abstract: Personalized agents are required to reason over long-term history interactions to infer both explicit preferences and implicit behavioral evidence. Whil

DPG loss functions for learning parameter-to-solution maps by neural networks

arXiv:2506.18773v2 Announce Type: replace-cross Abstract: We develop, analyze, and experimentally explore residual-based loss functions for machine learning of parameter-to-solution maps in the contex

EDCT-Bench: Uncovering Faithfulness Gaps in VLMs via Explanation-Driven Counterfactual Testing

arXiv:2609.17953v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) can produce Natural Language Explanations (NLEs) that sound plausible yet remain inconsistent with the visual evidence t

Hardware

Lecture notes on Physics Informed Neural Networks, Neural Operators, and their applications

arXiv:2609.17638v1 Announce Type: cross Abstract: This is the set of lecture notes for the PhD course href{https://www.unibz.it/en/faculties/engineering/phd-computer-science/study-course-offering/2025

hardwarearxiv-cs-ai

Reflections on Trusting Trust, Revisited: Contaminating Self-Modifying AI Coding Agents with Poisoned Benchmarks

arXiv:2609.17817v1 Announce Type: cross Abstract: Thompson's 'Reflections on Trusting Trust' showed that a compiler can be poisoned to reinsert its own backdoor, so that even recompiling clean source

Social Laws for Multi-agent Coordination in Stochastic Environments

arXiv:2609.18929v1 Announce Type: cross Abstract: In multi-agent environments, coordinating agents to prevent interference and ensure robust individual performance is a critical challenge. Previous re

Solving Conic Programs over Sparse Graphs using a Variational Quantum Approach: The Case of the AC Optimal Power Flow

arXiv:2509.00341v3 Announce Type: replace-cross Abstract: Conic programs arising in physics, quantum information, machine learning, and engineering are often defined over sparse graphs. Although such

Teaching AI, Robotics, & Community: A Hubs-Based K-12 Education Framework for Reaching Rural Schools

arXiv:2609.18072v1 Announce Type: new Abstract: K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship. Programs like FIRST provi

The Limits of BPE Tokenization in Polish: Segmentation-Flexional Forms, Grammatical Anchoring, and First-Person Stability in Inflectional Language Models

arXiv:2609.17553v1 Announce Type: new Abstract: This article analyzes BPE tokenization in Polish as a test case for the limits of statistical segmentation in an inflectional language. It asks whether

researcharxiv-cs-cl

Think Before You Move: Latent Motion Reasoning for Text-to-Motion Generation

arXiv:2512.24100v2 Announce Type: replace Abstract: Current state-of-the-art paradigms predominantly treat Text-to-Motion (T2M) generation as a direct translation problem, mapping symbolic language di

safetyarxiv-cs-cv

Using OCR Heads to Verbalize Image Semantics

arXiv:2609.18823v1 Announce Type: cross Abstract: How do VLMs map from pixels to semantics? To understand this general question, we focus on a narrow one: studying how VLMs perform optical character r

Visual Input and Its Framing Affect Attribute-based Descriptions Produced by Large Vision-Language Models

arXiv:2609.18345v1 Announce Type: new Abstract: Large vision-language models (LVLMs) are commonly used with only a single text prompt as the input, or plus an image. In this paper, we demonstrate that

researcharxiv-cs-cv

Tutorials

Vocabulary-Guided Gait Recognition

arXiv:2609.18413v1 Announce Type: new Abstract: What is a gait? Appearance-based gait networks consider a gait as the human shape and motion information from images. Model-based gait networks treat a

tutorialsarxiv-cs-cv

Who Audits Whom, on What Substrate, with What Evidence? An Independence-Graded Audit Protocol for Agentic AI

arXiv:2609.18272v1 Announce Type: new Abstract: Agentic AI systems plan, invoke tools and act with limited supervision; they are now both the subject of audits and, increasingly, the auditor. Independ

Whom Do AI Agents Work For? Role Assignment Induces Sponsorship Bias in LLM Recommenders

arXiv:2609.17989v1 Announce Type: cross Abstract: Large language models (LLMs) now serve as conversational shopping assistants on platforms that also sell advertising. These AI agents face a conflict

Applications

A Vision-Language Foundation Model for Precise and Comprehensive Brain Tumor Diagnosis from Preoperative Multimodal Data

arXiv:2609.16597v1 Announce Type: cross Abstract: Background Non-invasive presurgical diagnosis of brain tumor types from Magnetic Resonance Imaging (MRI) is essential but challenging due to overlappi

applicationsarxiv-cs-ai

Continuous-Time Machine Learning: A Unified Mathematical Perspective

arXiv:2609.16710v1 Announce Type: cross Abstract: Continuous-time (CT) machine learning has emerged as a principled framework for modeling temporal dynamics as a continuous process, particularly when

DoubleAgents: Human-Agent Alignment in a Socially Embedded Workflow

arXiv:2509.12626v4 Announce Type: replace-cross Abstract: Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evo

From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling

arXiv:2609.16493v1 Announce Type: new Abstract: Traditional catastrophe (CAT) risk models rely on costly manual construction to generate extreme weather scenarios, an approach largely unchanged since

Geospatial Metadata Improves Discoverability by Connecting Datasets Across Scientific Disciplines

arXiv:2609.16498v1 Announce Type: cross Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inter

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning

arXiv:2509.23616v2 Announce Type: replace-cross Abstract: The class imbalance problem refers to the disproportionate distribution of samples across different classes within a dataset, where the minori

High-Fidelity Digital Twin Data Models by Randomized Dynamic Mode Decomposition and Deep Learning with Applications in Fluid Dynamics

arXiv:2609.17101v1 Announce Type: new Abstract: The purpose of this paper is the identification of high-fidelity digital twin data models from numerical code outputs by non-intrusive techniques (i.e.,

Multi-Agent Learning with Cooperation-Driven Optimization Dynamics

arXiv:2609.16917v1 Announce Type: cross Abstract: Multilayer Artificial Neural Networks trained via backpropagation are the basic blocks of many, more complex, classification algorithms. Their strengt

agentsarxiv-cs-lg

QALPA: Property-guided diffusion modeling for efficient exploration of chemical spaces of flexible molecules

arXiv:2609.16527v1 Announce Type: cross Abstract: Exploring the chemical space of flexible molecules remains challenging because the vast number of possible compounds and conformations, together with

Risk-Calibrated Bayesian Streaming Intrusion Detection with SRE-Aligned Decisions

arXiv:2510.09619v2 Announce Type: replace-cross Abstract: [Corrected v2: an audit found that the score, threshold, and latency descriptions below are not what the shared codebase implements, and that

A Personalized Dynamic Balance Evaluation Paradigm for Hip Exoskeleton-Assisted Walking under Unexpected Ground Perturbations

arXiv:2609.14765v1 Announce Type: cross Abstract: Hip exoskeletons may improve recovery from unexpected gait perturbations, yet personalizing assistance remains difficult because balance is multidimen

A primer on evaluation methods for large language models in healthcare

arXiv:2609.14819v1 Announce Type: cross Abstract: Large language models (LLMs) have a growing range of applications in medicine, and their evaluation is critical for ensuring they provide benefit and

agentsarxiv-cs-ai

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

arXiv:2609.15297v1 Announce Type: new Abstract: In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. I

Another Blueprint In The Wall: How to Ask Frontier AI Like a Kid?

arXiv:2609.14803v1 Announce Type: new Abstract: This paper reports experiments across six frontier model types from OpenAI, Anthropic, xAI, and Google DeepMind. Ten independent sessions per model type

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

Can Interpretation Predict Behavior on Unseen Data?

arXiv:2507.06445v4 Announce Type: replace-cross Abstract: Interpretability research often predicts model responses to targeted mechanistic interventions. But can we predict responses to unseen input d

CoMem: Collective-Individual Memory Synergy for Evolutionary Multi-Agent Systems

arXiv:2609.15009v1 Announce Type: new Abstract: Designing effective memory mechanisms is crucial for advancing LLM-driven Multi-Agent Systems (MAS), helping agents learn together and perform better ov

agentsarxiv-cs-ai