All entries

arXiv:2605.04856v1 Announce Type: new Abstract: Computed tomography (CT) is indispensable for clinical diagnosis and image-guided interventions but exposes patients to ionizing radiation, motivating t

local-aiarxiv-cs-cv

Tutorials

9 themes defining the future of AI-driven customer engagement: Insights from Twilio’s Signal event

DGX agent

Customer engagement is shifting from disconnected interactions to continuous, AI-driven experiences that span channels and adapt in real time — and unified data, orchestration and AI agents are rapidl

tutorialssiliconangle

7 May 2026

A Bayesian Approach for Task-Specific Next-Best-View Selection with Uncertain Geometry

arXiv:2605.05095v1 Announce Type: cross Abstract: We develop a framework for task-specific active next-best-view selection in 3D reconstruction from point clouds, by casting the problem in the languag

A Biased Nonnegative Block Term Tensor Decomposition Model for Dynamic QoS Prediction

arXiv:2605.04813v1 Announce Type: new Abstract: With the rapid development of cloud computing and Web services, Quality of Service (QoS) has become a key criterion for service selection and recommenda

A Closed-Form Dual-Barrier CBF Safety Filter for Holonomic Robots on Incrementally Built Occupancy Grid Maps

arXiv:2605.05182v1 Announce Type: new Abstract: We present a dual-barrier control barrier function (CBF) safety filter for real-time, safety-critical velocity control of holonomic robots operating in

safetyarxiv-cs-ro

A Comparative Analysis of Machine Learning and Deep Learning Models for Tweet Sentiment Classification: A Case Study on the Sentiment140 Dataset

arXiv:2605.04888v1 Announce Type: new Abstract: The exponential growth of social media has created an urgent need for automated systems to analyze unstructured public sentiment in real time. This stud

applicationsarxiv-cs-cl

A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter

model-releasesarxiv-cs-cl

arXiv:2605.04885v1 Announce Type: new Abstract: This paper compares a PyCaret AutoML branch and a CNN-BiLSTM branch for binary hate speech detection on Indonesian Twitter using the HS label from the c

A Consistency-Centric Approach to Set-Based Optimization with Multiple Models of Unranked Fidelity

arXiv:2605.04051v1 Announce Type: cross Abstract: In complex real-world settings, optimization is challenged by the presence of diverse models of differing fidelity. In many optimization problems, a s

applicationsarxiv-cs-lg

A cross-modal network for facial expression recognition

arXiv:2605.04439v1 Announce Type: new Abstract: Deep neural networks enriched with structural information have been widely employed for facial expression recognition tasks. However, these methods ofte

safetyarxiv-cs-cv

A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers

arXiv:2605.03391v1 Announce Type: cross Abstract: Weighted first-order model counting (WFOMC) is a central task in lifted probabilistic inference: It asks for the weighted sum of all models of a first

researcharxiv-cs-ai

Agents

A few major use cases for agentic coding for me: 1. Adhoc data visualizations. Anytime I have a question that can be answered quantitatively…

agentsfrancois-chollet--x

A few major use cases for agentic coding for me: 1. Adhoc data visualizations. Anytime I have a question that can be answered quantitatively, I generate some code to make a plot. 2. Adhoc data annotat

A few weeks ago @simonw got Claude to port LiteParse to the browser. Today, we are launching that work as a complete guide in our docs! http…

model-releasesjerry-liu--x

A few weeks ago @simonw got Claude to port LiteParse to the browser. Today, we are launching that work as a complete guide in our docs! https://developers.llamaindex.ai/liteparse/guides/browser-usage/

A Foundation Model for Zero-Shot Logical Rule Induction

arXiv:2605.04916v1 Announce Type: cross Abstract: Inductive Logic Programming (ILP) learns interpretable logical rules from data. Existing methods are transductive: their learned parameters are bound

applicationsarxiv-cs-lg

A foundation model of vision, audition, and language for in-silico neuroscience

arXiv:2605.04326v1 Announce Type: cross Abstract: Cognitive neuroscience is fragmented into specialized models, each tailored to specific experimental paradigms, hence preventing a unified model of co

A geometric relation of the error introduced by sampling a language model's output distribution to its internal state

arXiv:2605.04899v1 Announce Type: new Abstract: GPT-style language models are sensitive to single-token changes at generation points where the predicted probability distribution is spread across multi

a good grid system is key

A good grid system is foundational to effective design and layout work, providing structure and alignment for visual elements. This Nous Research post likely discusses how grid systems improve consist

researchnous-research--x

A Harmonic Mean Formulation of Average Reward Reinforcement Learning in SMDPs

arXiv:2605.04880v1 Announce Type: new Abstract: Recent research has revived and amplified interest in algorithms for undiscounted average reward reinforcement learning in infinite-horizon, non-episodi

A Hybrid Method for Low-Resource Named Entity Recognition

arXiv:2605.04489v1 Announce Type: cross Abstract: Named Entity Recognition (NER) is a critical component of Natural Language Processing with diverse applications in information extraction and conversa

applicationsarxiv-cs-cl

Tutorials

A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines

arXiv:2603.09789v2 Announce Type: replace Abstract: Accurate financial volatility forecasting is crucial but challenged by the non-linear, highly correlated nature of market data. Recently, quantum co

tutorialsarxiv-cs-lg

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning

arXiv:2506.14432v3 Announce Type: replace-cross Abstract: We present FOMO260K, a large-scale, heterogeneous dataset of 260,927 brain Magnetic Resonance Imaging (MRI) scans from 77,589 MRI sessions and

A Mean Curvature Approach to Boundary Detection: Geometric Insights for Unsupervised Learning

arXiv:2605.04274v1 Announce Type: new Abstract: Accurate boundary detection in high-dimensional data remains a central challenge in unsupervised learning, particularly in the presence of non-linear st

applicationsarxiv-cs-lg

Tools

A new PR review experience is now available in Cursor 3. Take PRs from creation to merge, all in one place. You can see comments, diffs, com…

A new PR review experience is now available in Cursor 3. Take PRs from creation to merge, all in one place. You can see comments, diffs, commits, and review status to understand what changed and next

toolscursor--x

Hardware

A Physics-Aware Framework for Short-Term GPU Power Forecasting of AI Data Centers

arXiv:2605.04074v1 Announce Type: new Abstract: AI data centers experience rapid fluctuations in power demand due to the heterogeneity of computational tasks that they have to support. For example, th

hardwarearxiv-cs-lg

A Provably Convergent and Practical Algorithm for Gromov--Wasserstein Optimal Transport

arXiv:2605.04175v1 Announce Type: new Abstract: Gromov--Wasserstein optimal transport (GWOT) aligns metric measure spaces by matching their within-domain relational structures, but large-scale GWOT re

Hardware

A Queueing-Theoretic Framework for Stability Analysis of LLM Inference with KV Cache Memory Constraints

arXiv:2605.04595v1 Announce Type: new Abstract: The rapid adoption of large language models (LLMs) has created significant challenges for efficient inference at scale. Unlike traditional workloads, LL

hardwarearxiv-cs-lg

A Reconstruction System for Industrial Pipeline Inner Walls Using Panoramic Image Stitching with Endoscopic Imaging

arXiv:2603.00714v2 Announce Type: replace Abstract: Visual analysis and reconstruction of pipeline inner walls remain challenging in industrial inspection scenarios. This paper presents a dedicated re

A Regulatory Governance Framework for AI-Driven Financial Fraud Detection in U.S. Banking: Integrating OCC, SR 11-7, CFPB, and FinCEN Compliance Requirements for Model Development, Validation, and Monitoring Lifecycles

arXiv:2605.04076v1 Announce Type: new Abstract: U.S. financial institutions deploying AI-based fraud detection face a fragmented compliance landscape spanning four regulatory frameworks -- OCC Bulleti

A Scalable Multi-Task Model for Virtual Sensors

arXiv:2601.20634v2 Announce Type: replace Abstract: Virtual sensors replace expensive physical sensors in critical applications through machine learning by predicting target signals from available mea

A Self-Attentive Meta-Optimizer with Group-Adaptive Learning Rates and Weight Decay

arXiv:2605.04055v1 Announce Type: new Abstract: Adaptive optimizers like AdamW apply uniform hyperparameters across all parameter groups, ignoring heterogeneous optimization dynamics across layers and

A semicontinuous relaxation of Saito's criterion and freeness as angular minimization

arXiv:2604.02995v2 Announce Type: replace-cross Abstract: We introduce a nonnegative functional mathfrak{S} on the space of line arrangements in P^2 that vanishes precisely on free arrangements, obtai

A Skill-Based AI Agentic Pipeline for Library of Congress Subject Indexing

arXiv:2605.03537v1 Announce Type: cross Abstract: This paper presents a modular AI agentic skill pipeline for automating subject indexing with Library of Congress Subject Headings (LCSH). Subject inde

safetyarxiv-cs-ai

A unified Benchmark for Multi-Frame Image Restoration under Severe Refractive Warping

model-releasesarxiv-cs-cv

arXiv:2605.05079v1 Announce Type: new Abstract: Video sequence capturing through refractive dynamic media, such as a turbulent air or water surface, often suffer from severe geometric distortions and

A Universal Large Language Model -- Drone Command and Control Interface

model-releasesarxiv-cs-ro

arXiv:2601.15486v2 Announce Type: replace Abstract: The use of artificial intelligence (AI) for drone control can have a transformative impact on drone capabilities, especially when real world informa

A Universal Space of Brain Dynamics for Unveiling Cognitive Transitions and Individual Differences

arXiv:2605.02936v1 Announce Type: cross Abstract: Representing dynamical systems through data-driven universal spaces has proven effective; however, achieving this universality for human brain activit

researcharxiv-cs-ai

Local Ai

A Workflow-Oriented Framework for Asynchronous Human-AI Collaboration in Hybrid and Compute-Intensive HPC Environments

arXiv:2605.03743v1 Announce Type: cross Abstract: Human involvement is critical in training and deploying AI systems in high-stakes defence and security contexts. However, real-time interaction is imp

local-aiarxiv-cs-ai

Hardware

Achieving Peak System and Workload Efficiency on NVIDIA GB200 NVL72 with Slurm Block Scheduling

This article discusses optimization techniques for maximizing efficiency on NVIDIA's GB200 NVL72 system using Slurm block scheduling, a job scheduling approach designed to improve resource utilization

hardwarenvidia-developer

Actionable Real-Time Modeling of Surgical Team Dynamics via Time-Expanded Interaction Graphs

arXiv:2605.04169v1 Announce Type: cross Abstract: Surgical team performance arises from complex interactions between technical execution and non-technical skills, including communication and coordinat

Active Contact Sensing for Robust Robot-to-Human Object Handover

arXiv:2605.04610v1 Announce Type: new Abstract: Robot-to-human object handover is an essential skill for robot assistants, from serving drinks at home to passing surgical tools in the operating room.

researcharxiv-cs-ro

AdapShot: Adaptive Many-Shot In-Context Learning with Semantic-Aware KV Cache Reuse

arXiv:2605.03644v1 Announce Type: new Abstract: Many-Shot In-Context Learning (ICL) has emerged as a promising paradigm, leveraging extensive examples to unlock the reasoning potential of Large Langua

researcharxiv-cs-ai

Adapt or Forget: Provable Tradeoffs Between Adam and SGD in Nonstationary Optimization

arXiv:2605.04269v1 Announce Type: cross Abstract: We provide a theoretical analysis of Adam under non-stationary stochastic objectives, separating two regimes: Euclidean tracking under adaptive strong

Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning

arXiv:2605.04066v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is an essential paradigm that enhances the reasoning capabilities of Large Language Models (LLMs).

safetyarxiv-cs-cl

Adapting Large Language Models to a Low-Resource Agglutinative Language: A Comparative Study of LoRA and QLoRA for Bashkir

model-releasesarxiv-cs-cl

arXiv:2605.04948v1 Announce Type: new Abstract: This paper presents a comparative study of parameter-efficient fine-tuning (PEFT) methods, including LoRA and QLoRA, applied to the task of adapting lar

Adapting Medical Vision Foundation Models for Volumetric Medical Image Segmentation via Active Learning and Selective Semi-supervised Fine-tuning

arXiv:2509.10784v3 Announce Type: replace-cross Abstract: Medical vision foundation models remain limited in downstream tasks, particularly volumetric medical image segmentation. While fine-tuning on

Adaptive Consensus in LLM Ensembles via Sequential Evidence Accumulation: Automatic Budget Identification and Calibrated Commit Signals

arXiv:2605.04236v1 Announce Type: new Abstract: Large Language Model ensembles improve reasoning accuracy up to a performance boundary; beyond it, additional deliberation degrades accuracy. Static-bud

Adaptive Dual-Path Framework for Covert Semantic Communication

arXiv:2605.03423v1 Announce Type: new Abstract: This paper proposes a novel adaptive dual-path framework for covert semantic communication (SemCom), which integrates covert information transmission wi

safetyarxiv-cs-ai

Adaptive Ensemble Aggregation for Actor-Critics

arXiv:2507.23501v2 Announce Type: replace Abstract: Ensembles are ubiquitous in off-policy actor-critic learning, yet their efficacy depends critically on how they are aggregated. Current methods typi

Adaptive Inverted-Index Routing for Granular Mixtures-of-Experts

arXiv:2605.04952v1 Announce Type: new Abstract: Mixture-of-experts (MoE) models enable scalable transformer architectures by activating only a subset of experts per token. Recent evidence suggests tha

Local Ai

Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Framework

arXiv:2605.05055v1 Announce Type: new Abstract: Localization in 5G and 6G networks is essential for important use cases such as intelligent transportation, smart factories, and smart cities. Although

local-aiarxiv-cs-lg