All entries

A Bitter Lesson for Data Filtering

arXiv:2605.19407v1 Announce Type: cross Abstract: We investigate data filtering for large model pretraining via new scaling studies that target the high compute, data-scarce regime. In spite of an app

A Case for Agentic Tuning: From Documentation to Action in PostgreSQL

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Clear filters

arXiv:2605.19988v1 Announce Type: cross Abstract: Documentation has long guided computer system tuning by distilling expert knowledge into per-parameter recommendations. Yet such guides capture only w

model-releasesarxiv-cs-ai

20 May 2026

A Closed-loop, State-centric, Multi-agent Framework for Passenger Load Estimation from Heterogeneous Data Streams

arXiv:2605.19834v1 Announce Type: cross Abstract: To support operations and passenger-facing services, transit agencies need reliable passenger load trajectories. Currently, load estimates are typical

A Cloud-Based Tool for Meteorite Recovery Using Drones and Machine Learning

arXiv:2605.19179v1 Announce Type: cross Abstract: We present a cloud-based tool that uses drones and machine learning to help recover instrumentally observed meteorite falls. We showcase a collection

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

researcharxiv-cs-cl

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A Family of Divergence Measures for Evaluating the Reconstruction Quality of Explainable Ensemble Trees

arXiv:2605.19618v1 Announce Type: new Abstract: Validating interpretable surrogate models for ensemble learners requires measuring agreement between the ensemble's internal representation and its surr

a few months back, it become clear to us that a large part of technical work would be driven by agents in the future. coding agents were bec…

a few months back, it become clear to us that a large part of technical work would be driven by agents in the future. coding agents were becoming ubiquitous and highly capable. since we build a platfo

agentsharrison-chase--x

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition

arXiv:2507.01932v2 Announce Type: replace-cross Abstract: We study a class of nonconvex-nonconcave minimax problems in which the inner maximization problem satisfies a local Kurdyka-Lojasiewicz (KL) c

A Framework for Evaluating Zero-Shot Image Generation in Concept-based Explainability

arXiv:2605.19855v1 Announce Type: cross Abstract: Concept-based Explainable Artificial Intelligence (XAI) interprets deep learning models using human-understandable visual features (e.g., textures or

Industry

a general-purpose model solved a major open problem in mathematics. we'll be saying this a lot over the coming years, but this is a kinda bi…

a general-purpose model solved a major open problem in mathematics. we'll be saying this a lot over the coming years, but this is a kinda big milestone. i'm very excited for AI to greatly extend our u

industrysam-altman--x

A Geometric Analysis of Sign-Magnitude Asymmetry in a ReLU + RMSNorm Block under Ternary Quantization

arXiv:2605.18933v1 Announce Type: new Abstract: Pre-norm Transformers with RMSNorm tolerate ternary {-1,0,+1} weight quantization with surprisingly small loss (Ma et al., 2024). We give a geometric ex

A Geometric Analysis of Small-sized Language Model Hallucinations

arXiv:2602.14778v3 Announce Type: replace-cross Abstract: Hallucinations -- plausible but factually incorrect responses -- pose a major challenge to the reliability of Large Language Models (LLMs), es

Local Ai

A glimpse into the fleet: Deep space patrol (4K Sci-Fi) [OC]

local-air-stablediffusion

A user-generated AI image creation showcasing a deep space patrol scene rendered in 4K quality using Stable Diffusion, a popular text-to-image generation model. The post was shared on the r/StableDiff

A Grid-Based Framework for E-Scooter Demand Representation and Temporal Input Design for Deep Learning: Evidence from Austin, Texas

arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str

researcharxiv-cs-cv

A Heuristic Approach for Performance Tuning in RL-based Quadrotor Control via Reward Design and Termination Conditions

arXiv:2605.19166v1 Announce Type: cross Abstract: Reinforcement learning (RL)-based quadrotor control policies have achieved impressive performance in tasks such as fast navigation in cluttered enviro

A Hybrid Modeling Framework for Crop Prediction Tasks via Dynamic Parameter Calibration and Multi-Task Learning

arXiv:2603.15411v2 Announce Type: replace Abstract: Accurate prediction of crop states (e.g., phenology stages and cold hardiness) is essential for timely farm management decisions such as irrigation,

Industry

A jury sided with Sam Altman and OpenAI in court. But Elon Musk won in the court of public opinion, writes Tim Higgins. https://on.wsj.com/4…

A court ruled in favor of Sam Altman and OpenAI in a legal dispute with Elon Musk, though Musk's public messaging resonated strongly with audiences. The case highlights the divergence between legal ou

industryelon-musk--x

A Logistic Regression Model to Predict Malaria Severity in Children

arXiv:2605.18900v1 Announce Type: cross Abstract: One of the main causes of death around the globe is malaria. Researchers have sought to develop predictive models for malaria outbreaks based on meteo

agentsarxiv-cs-lg

A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits

arXiv:2605.19944v1 Announce Type: cross Abstract: While empirical scaling laws for LLM reasoning are well-documented, the theoretical mechanisms governing out-of-distribution (OOD) generalization rema

A Methodology for Selecting and Composing Runtime Architecture Patterns for Production LLM Agents

arXiv:2605.20173v1 Announce Type: new Abstract: Production LLM agents combine stochastic model outputs with deterministic software systems, yet the boundary between the two is rarely treated as a firs

A Multi-Agent Framework for Feature-Constrained Difficulty Control in Reading Comprehension Item Generation

arXiv:2605.19316v1 Announce Type: new Abstract: Recent studies in difficulty-controlled reading comprehension item generation have leveraged large language models (LLMs) to produce items by adjusting

agentsarxiv-cs-cl

Tutorials

A Multi-Dimensional Clustering Approach for Identifying Inborn Errors of Immunity

arXiv:2605.18880v1 Announce Type: cross Abstract: Rare diseases such as inborn errors of immunity (IEI) require early diagnosis to prevent end organ damage and improve quality of life. Hurdles in acce

tutorialsarxiv-cs-cv

A Nash Equilibrium Framework For Training-Free Multimodal Step Verification

arXiv:2605.20033v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache

researcharxiv-cs-cv

A Nonlinear Complexity Index for Wearable PPG Cardiovascular Stability: Multiscale Validation, Systematic Evaluation Correction, and Bayesian Parameter Optimization

arXiv:2605.18802v1 Announce Type: cross Abstract: Cardiovascular stability estimation from wearable photoplethysmography (PPG) requires a principled nonlinear framework, yet major gaps persist in heur

A novel YOLO26-MoE optimized by an LLM agent for insulator fault detection considering UAV images

arXiv:2605.19595v1 Announce Type: cross Abstract: The inspection of electrical power line insulators is essential for ensuring grid reliability and preventing failures caused by damaged or degraded in

A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests

arXiv:2601.20529v3 Announce Type: replace Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods gi

researcharxiv-cs-ro

A Reproducibility Analysis of PO4ISR: Diagnosing and Mitigating Semantic Drift in LLM-Based Session Recommendation

arXiv:2605.18780v1 Announce Type: cross Abstract: Reasoning-based Large Language Models (LLMs) like PO4ISR have set new benchmarks in session-based recommendation. However, the reproducibility of thei

A Systematic Failure Analysis of Vision Foundation Models for Open Set Iris Presentation Attack Detection

model-releasesarxiv-cs-cv

arXiv:2605.19020v1 Announce Type: new Abstract: Vision foundation models have demonstrated strong transferability across diverse visual recognition tasks and are increasingly considered for biometric

A Two-Parameter Weibull Framework for Diagnosing Transformer Weight Distributions

arXiv:2605.18898v1 Announce Type: new Abstract: We apply the Weibull distribution -- a two-parameter family from extreme-value theory -- as a diagnostic framework for element-wise weight magnitude dis

A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions

arXiv:2605.19306v1 Announce Type: new Abstract: We address the open problem of training hypernetworks for Controllable Pareto Front Learning (CPFL) under split feasibility conditions with rigorous the

A Unified Framework for Structure-Aware Clustering and Heterogeneous Causal Graph Learning

arXiv:2605.19313v1 Announce Type: cross Abstract: In complex multivariate systems, interactions among variables are defined by dependency structures, often encoded as directed acyclic graphs (ext{DAGs

Hardware

Accelerating Sparse Transformer Inference on GPU

arXiv:2506.06095v4 Announce Type: replace Abstract: Large language models (LLMs) are popular around the world due to their powerful understanding capabilities. As the core component of LLMs, accelerat

hardwarearxiv-cs-lg

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

arXiv:2605.19366v1 Announce Type: new Abstract: Environmental science plays a pivotal role in safeguarding ecosystems, a domain driven by large-scale, heterogeneous data. In the big data era, artifici

Accurate Evaluation of Quickest Changepoint Detectors via Non-parametric Survival Analysis

arXiv:2605.18798v1 Announce Type: new Abstract: We propose non-parametric estimators for the average run length (ARL) and average detection delay (ADD) in quickest changepoint detection (QCD) under fi

Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment

model-releasesarxiv-cs-cl

arXiv:2506.14148v2 Announce Type: replace-cross Abstract: This paper presents a novel non-invasive object classification approach using acoustic scattering, demonstrated through a case study on hair a

Tutorials

Activation Functions, Statistics and Learning of Higher-Order Interactions in Restricted Boltzmann Machines

arXiv:2605.19178v1 Announce Type: cross Abstract: The great success of neural networks in recognizing hidden patterns and correlations in complex data lies in the way they take advantage of the large

tutorialsarxiv-cs-lg

Applications

Active Context Selection Improves Simple Regret in Contextual Bandits

arXiv:2605.20040v1 Announce Type: new Abstract: We study the contextual multi-armed bandit problem with a finite context space (a.k.a. subpopulations), where the learner recommends a best action for e

applicationsarxiv-cs-lg

Active Graph really feels like the culmination of all of my BabyAGI and graph experiments. [fyi, technical history of babyagi: http://babyag…

Active Graph really feels like the culmination of all of my BabyAGI and graph experiments. [fyi, technical history of babyagi: http://babyagi.wiki] would love to hear thoughts if you try it out! the e

agentsyohei-nakajima--x

Active Learning of Fractional-Order Viscoelastic Model Parameters for Realistic Haptic Rendering

model-releasesarxiv-cs-ro

arXiv:2512.00667v2 Announce Type: replace-cross Abstract: Effective medical simulators necessitate realistic haptic rendering of biological tissues that exhibit viscoelastic material properties, such

Adapted Center and Scale Prediction: More Stable and More Accurate

model-releasesarxiv-cs-cv

arXiv:2002.09053v3 Announce Type: replace Abstract: Pedestrian detection benefits from deep learning technology and gains rapid development in recent years. Most of detectors follow general object det

Adaptive Multi-Scale Goodness Aggregation for Forward-Forward Learning

arXiv:2605.18804v1 Announce Type: cross Abstract: We propose Adaptive Multi-Scale Goodness Aggregation (AMSGA), a novel extension of the Forward-Forward (FF) algorithm designed to improve stability, r

Adaptive Power Iteration Method for Differentially Private PCA

arXiv:2602.11454v3 Announce Type: replace-cross Abstract: We study left(epsilon,eltaright)-differentially private algorithms for the problem of approximately computing the top singular vector of a mat

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models

arXiv:2511.10292v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) typically process visual inputs as a prefix to the language decoder. As the model autoregressively genera

Adaptive Threshold-Driven Continuous Greedy Method for Scalable Submodular Optimization

arXiv:2604.03419v2 Announce Type: replace Abstract: Submodular maximization under matroid constraints is a fundamental problem in combinatorial optimization with applications in sensing, data summariz

agentsarxiv-cs-lg

Add a Specialized Deep Research Skill to Agent Harnesses

model-releasesnvidia-developer

This article covers the NVIDIA AI-Q Blueprint for building specialized deep research agents that empower AI systems to gather context, synthesize information, and support complex decision-making acros

Addressing prior dependence in hierarchical Bayesian modeling for PTA data analysis II: Noise and SGWB inference through parameter decorrelation

arXiv:2511.01959v2 Announce Type: replace-cross Abstract: Pulsar Timing Arrays (PTA) provide a powerful framework to measure low-frequency gravitational waves, but accuracy and robustness of the resul

Adversarial Stress Testing of SPARK Humanoid Safety Filters

model-releasesarxiv-cs-ro

arXiv:2605.19009v1 Announce Type: new Abstract: Humanoid robots are difficult to deploy safely because they have high-dimensional bodies, many collision constraints, and must operate near people and o