Search: “tools”

A Short and Unified Convergence Analysis of the SAG, SAGA, and IAG Algorithms

arXiv:2602.05304v2 Announce Type: replace Abstract: Stochastic variance-reduced algorithms such as Stochastic Average Gradient (SAG) and SAGA, and their deterministic counterparts like the Incremental

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An entropy formula for the Deep Linear Network

DGX agent

arXiv:2509.09088v3 Announce Type: replace Abstract: We study the Riemannian geometry of the Deep Linear Network (DLN) as a foundation for a thermodynamic description of the learning process. The main

model-releasesarxiv-cs-lg

23 May 2026

Can Breath Biomarkers Causally Influence Blood Glucose? Investigating VOC-Mediated Modulation in Diabetes

arXiv:2605.22075v1 Announce Type: new Abstract: Diabetes is a global health burden, and early detection is critical for timely intervention. This study explores a non-invasive, data-driven framework t

Community-Aware Vertex Ordering for Reference-Based Graph Compression: A Cross-Encoder Empirical Study

arXiv:2605.21510v1 Announce Type: cross Abstract: Reference-based graph compression encodes each vertex's neighbor list relative to a recent vertex, exploiting locality to compress large directed grap

Local Ai

Detecting Atypical Clients in Federated Learning via Representation-Level Divergence

arXiv:2605.22266v1 Announce Type: new Abstract: Federated learning enables collaborative training across distributed clients with heterogeneous data, but such heterogeneity often leads to unstable upd

local-aiarxiv-cs-lg

Efficient Higher-order Subgraph Attribution via Message Passing

arXiv:2605.22385v1 Announce Type: new Abstract: Explaining graph neural networks (GNNs) has become more and more important recently. Higher-order interpretation schemes, such as GNN-LRP (layer-wise re

Interpreting and Steering State-Space Models via Activation Subspace Bottlenecks

arXiv:2602.22719v2 Announce Type: replace Abstract: State-space models (SSMs) have emerged as an efficient strategy for building powerful language models, avoiding the quadratic complexity of computin

MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Scaling of Diffusion Language Models

arXiv:2603.16077v3 Announce Type: replace Abstract: Masked diffusion models (MDM) exhibit superior generalization when learned using a Partial masking scheme (Prime). This approach converts tokens int

tutorialsarxiv-cs-lg

Position: The Time for Sampling Is Now! Charting a New Course for Bayesian Deep Learning

arXiv:2605.21765v1 Announce Type: new Abstract: The practical adoption of sampling-based inference (SAI) in Bayesian neural networks (BNNs) remains limited, partly due to persistent misconceptions abo

tutorialsarxiv-cs-lg

Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs

model-releasesarxiv-cs-lg

arXiv:2605.21975v1 Announce Type: new Abstract: Financial markets are characterized by extreme non-stationarity, low signal-to-noise ratios, and strong dependence on external information such as news,

Reinforcement learning for ion shuttling on trapped-ion quantum computers

arXiv:2605.22463v1 Announce Type: cross Abstract: Scalable trapped-ion quantum computing is commonly realized with modular chips that feature distinct zones with specific functionalities, such as stor

Stabilising Explainability Fragility in Cybersecurity AI: The Impact and Mitigation of Multicollinearity in Public Benchmark Datasets

model-releasesarxiv-cs-lg

arXiv:2605.22529v1 Announce Type: new Abstract: This paper investigates a unexplored yet impactful vulnerability in AI explainability used in intrusion detection (IDS): multicollinearity-induced insta

The Attribution Impossibility: No Feature Ranking Is Faithful, Stable, and Complete Under Collinearity

arXiv:2605.21492v1 Announce Type: new Abstract: No feature ranking can be simultaneously faithful, stable, and complete when features are collinear. For collinear pairs, ranking reduces to a coin flip

safetyarxiv-cs-lg

Agentic CLEAR: Automating Multi-Level Evaluation of LLM Agents

arXiv:2605.22608v1 Announce Type: new Abstract: Agentic systems are becoming more capable: agents define strategies, take actions, and interact with different environments. This autonomy poses serious

Agents

An Entity Linking Agent for Question Answering

arXiv:2508.03865v4 Announce Type: replace Abstract: Some Question Answering (QA) systems rely on knowledge bases (KBs) to provide accurate answers. Entity Linking (EL) plays a critical role in linking

agentsarxiv-cs-cl

Boiling the Frog: A Multi-Turn Benchmark for Agentic Safety

model-releasesarxiv-cs-cl

arXiv:2605.22643v1 Announce Type: new Abstract: Background. Traditional safety benchmarks for language models evaluate generated text: whether a model outputs toxic language, reproduces bias, or follo

Local Ai

Broadening Access to Transportation Safety Data with Generative AI: A Schema-Grounded Framework for Spatial Natural Language Queries

arXiv:2605.21712v1 Announce Type: new Abstract: Transportation safety analysis requires integrating crash records, roadway attributes, and geospatial data through GIS-based workflows, but access remai

local-aiarxiv-cs-cl

Chain-of-thought obfuscation learned from output supervision can generalise to unseen tasks

arXiv:2601.23086v2 Announce Type: replace Abstract: Chain-of-thought (CoT) reasoning provides a significant performance uplift to LLMs by enabling planning, exploration, and deliberation of their acti

tutorialsarxiv-cs-ai

Diagnosis Is Not Prescription: Linguistic Co-Adaptation Explains Patching Hazards in LLM Pipelines

arXiv:2605.21958v1 Announce Type: new Abstract: When a multi-module LLM agent fails, the module most responsible for the failure is not necessarily the best place to intervene. We demonstrate this Dia

Discovering Implicit Large Language Model Alignment Objectives

arXiv:2602.15338v2 Announce Type: replace-cross Abstract: Large language model (LLM) alignment relies on complex reward signals that often obscure the specific behaviors being incentivized, creating c

Dissecting Embodied Abilities in Multimodal Language Models through Skill-level Evaluation and Diagnosis

model-releasesarxiv-cs-cv

arXiv:2510.08759v2 Announce Type: replace Abstract: Understanding the capability bottlenecks of embodied multimodal large language models (MLLMs) is crucial for improving embodied agents. However, exi

FRED: A Multi-Modal Autonomous Driving Dataset for Flooded Road Environments

model-releasesarxiv-cs-cv

arXiv:2605.22018v1 Announce Type: new Abstract: The Flooded Road Environments Dataset (FRED) is, to our knowledge, the first multi-modal autonomous driving dataset specifically targeting the collectio

From TF-IDF to Transformers: A Comparative and Ensemble Approach to Sentiment Classification

arXiv:2605.22003v1 Announce Type: new Abstract: Sentiment analysis, also referred to as opinion mining, primarily tries to extract opinion from any text-based data. In the context of movie reviews and

Geometry-Adaptive Explainer for Faithful Dictionary-Based Interpretability under Distribution Shift

arXiv:2605.21849v1 Announce Type: cross Abstract: Mechanistic interpretability aims to explain a model's behavior by identifying causally responsible internal structures. Dictionary-based explainers s

Harder to Defend: Towards Chinese Toxicity Attacks via Implicit Enhancement and Obfuscation Rewriting

arXiv:2605.22258v1 Announce Type: new Abstract: Large language models (LLMs) require robust toxicity evaluation beyond explicit wording. This setting remains underexplored in Chinese, where toxicity m

OSS: Open Suturing Skills Vision-Based Assessment Challenge 2024-2025

model-releasesarxiv-cs-cv

arXiv:2605.22200v1 Announce Type: new Abstract: Achieving high levels of surgical skill through effective training is essential for optimal patient outcomes. Automated, data-driven skill assessment ho

PrivacyAkinator: Articulating Key Privacy Design Decisions by Answering LLM-Generated Multiple-choice Questions

arXiv:2605.20206v1 Announce Type: cross Abstract: NIST's Privacy Risk Assessment Methodology (PRAM) provides a structured framework for privacy experts to assess privacy risks. However, its complexity

applicationsarxiv-cs-ai

SE3Kit: A Lightweight Python Library for Specialized Geometric Primitives in Robotics

arXiv:2605.22633v1 Announce Type: new Abstract: The Python robotics ecosystem faces a challenge: while many libraries exist for rigid body transformations, few are both lightweight and mathematically

applicationsarxiv-cs-ro

Security Document Classification with a Fine-Tuned Local Large Language Model: Benchmark Data and an Open-Source System

model-releasesarxiv-cs-ai

arXiv:2605.20368v1 Announce Type: cross Abstract: Organizations that scan documents for sensitive information face a practical problem. Cloud services require data to be sent to external infrastructur

stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation

arXiv:2605.21800v1 Announce Type: cross Abstract: World models are central to building agents that can reason, plan, and generalize beyond their training data. However, research on world models is cur

researcharxiv-cs-ro

Synthetic Data Alone is Enough? Rethinking Data Scarcity in Pediatric Rare Disease Recognition

arXiv:2605.22767v1 Announce Type: new Abstract: Children with rare genetic diseases often exhibit distinctive facial phenotypes, yet developing computer vision systems for early diagnosis remains chal

applicationsarxiv-cs-cv

Tokenisation via Convex Relaxations

arXiv:2605.22821v1 Announce Type: new Abstract: Tokenisation is an integral part of the current NLP pipeline. Current tokenisation algorithms such as BPE and Unigram are greedy algorithms -- they make

A Comprehensive Comparison of Deep Learning Architectures for COVID-19 Classification on CT & X-ray Imagery

arXiv:2605.20445v1 Announce Type: new Abstract: COVID-19 was a significant challenge that led to the loss of numerous lives daily. Not only a certain country was involved in this outbreak, but even th

researcharxiv-cs-cv

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation

arXiv:2605.21058v1 Announce Type: new Abstract: Causal representation learning (CRL) and traditional representation learning have largely developed along different trajectories. Traditional representa

AI-Assisted Competency Assessment from Egocentric Video in Simulation-Based Nursing Education

arXiv:2605.20233v1 Announce Type: new Abstract: Assessing learner competency in clinical simulation requires expert observation that is time-intensive, difficult to scale, and subject to inter-rater v

safetyarxiv-cs-cv

Local Ai

AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing

arXiv:2605.21421v1 Announce Type: new Abstract: Motion capture is the gold standard for measuring human movement, but clinical use remains limited by cost, technical complexity, and privacy concerns.

local-aiarxiv-cs-cv

AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation

arXiv:2605.20303v1 Announce Type: new Abstract: Airfoil shape design is a fundamental task in aerospace engineering, with a direct impact on flight stability and fuel consumption. Deep learning has re

ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarization

arXiv:2605.20967v1 Announce Type: new Abstract: Memes have become a prominent medium of political communication in the Arab world, reflecting how humor, imagery, and text interact to express ideologic

Agents

Auto-Dreamer: Learning Offline Memory Consolidation for Language Agents

arXiv:2605.20616v1 Announce Type: new Abstract: Language agents increasingly operate over streams of related tasks, yet existing memory systems struggle to convert accumulated experience into reusable

agentsarxiv-cs-cl

Beyond Routing: Characterising Expert Tuning and Representation in Vision Mixture-of-Experts

arXiv:2605.20610v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are often interpreted by analysing which categories are routed to which experts. However, routing alone does not reveal

researcharxiv-cs-cv

Beyond Text-to-SQL: An Agentic LLM System for Governed Enterprise Analytics APIs

arXiv:2605.21027v1 Announce Type: new Abstract: Enterprise analytics aims to make organizational data accessible for decision-making, yet non-technical users still face barriers when using traditional

Building a Custom Taxonomy of AI Skills and Tasks from the Ground Up with Job Postings

arXiv:2605.21029v1 Announce Type: new Abstract: Utilizing LLMs for automated taxonomy construction presents a clear opportunity for the comprehensive, yet efficient mapping of potentially complex doma

tutorialsarxiv-cs-cl

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

arXiv:2605.20782v1 Announce Type: new Abstract: Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurre

CoarseSoundNet: Building a reliable model for ecological soundscape analysis

arXiv:2605.21143v1 Announce Type: cross Abstract: A soundscape is composed of three types of sound: biophony (sounds made by animals), geophony (natural abiotic sounds) and anthropophony (sounds made

applicationsarxiv-cs-lg

Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features

arXiv:2407.08976v2 Announce Type: replace-cross Abstract: Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effect

CRANE: Correcting Errors in Raw Nanopore Signals Using Hidden Markov Models

arXiv:2603.20420v2 Announce Type: replace-cross Abstract: Nanopore sequencing can read substantially longer sequences of nucleic acid molecules, called reads, than other sequencing methods, which has

Efficient numeracy in language models through single-token number embeddings

arXiv:2510.06824v2 Announce Type: replace Abstract: To drive progress in science and engineering, large language models (LLMs) must be able to process large amounts of numerical data and solve long ca

tutorialsarxiv-cs-lg

FineVision: Open Data Is All You Need

arXiv:2510.17269v2 Announce Type: replace Abstract: The advancement of vision-language models (VLMs) is hampered by a fragmented landscape of inconsistent and contaminated public datasets. We introduc

safetyarxiv-cs-cv